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Intercropping wheat and barley with nitrogen fixing legume species in low input organic systems Chapagain, Tejendra 2014

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INTERCROPPING WHEAT AND BARLEY WITH NITROGEN FIXING LEGUME SPECIES IN LOW INPUT ORGANIC SYSTEMS  by TEJENDRA CHAPAGAIN MSc Agriculture, Tribhuvan University, 2005   A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY  in  THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Plant Science)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   September 2014   © Tejendra Chapagain, 2014 ii  Abstract Declining land productivity associated with decreasing soil organic carbon (SOC) and nitrogen (N) is an issue for conventional production of small grains. Intercropping grains with legumes may provide a sustainable solution. I grew wheat (Triticum aestivum cv. ‘Scarlet’) as a monoculture and intercropped with either common bean (Phaseolus vulgaris cv. ‘Red Kidney’, or cv. ‘Black Turtle’), or fava bean (Vicia faba cv. ‘Bell’) in rows of wheat:bean 1:1 and 2:1 as well as broadcast arrangements to assess the effects of genotype and spatial arrangements on crop agronomy, land productivity, biological nitrogen fixation and transfer, N and carbon (C) accumulation in aboveground biomass, soil N balance, gross ecosystem photosynthesis (GEP), net ecosystem productivity (NEP), and water use efficiency (WUE). Barley (Hordeum vulgare cv. ‘Oxbridge’) and pea (Pisum sativum cv. ‘Reward’) were also included based on synchronized maturity, yield potential, protein content, and root architecture. Stable isotope methods (13C and 15N) coupled with field CO2 exchange measurements were used to determine C and N transformations. Intercrop plots had higher land productivity, improved grain and biomass quality, increased legume nodulation and percent N derived from symbiotic N2 fixation. Wheat-fava bean in the 1:1 arrangement displayed a 50% increase in land productivity. Barley-pea in the 2:1 arrangement also had the highest total land outputs (5.9 t ha-1) and land equivalent ratio (1.32). Wheat-fava bean in the 1:1 arrangement fixed the highest amount of N (74 kg N ha-1), transferred the most N (13% of N in wheat), and accumulated more C (26% higher than wheat monoculture) in shoot biomass. WUE of wheat was improved when grown with fava bean. Pea in intercrop plots also displayed increased nodulation (27-45%) and iii  symbiotic N2 fixation (9-17%) leading to the addition of 60-78 kg N ha-1. The GEP and NEP were highest in the 2:1 arrangement and led to the highest daytime C sequestration (229 mg C m-2 hr-1). I demonstrated that intercropping small grains with legumes, in specific spatial arrangements and under low input organic conditions, can counter conventional monoculture-associated SOC and N losses through higher land and ecosystem productivity, and greater organic N-fixation and transfer.   iv  Preface This thesis entitled ‘Intercropping Wheat and Barley with Nitrogen Fixing Legume Species in Low Input Organic Systems’ is a product of field and lab research carried out at the University of British Columbia - Vancouver.  The author is responsible for designing and implementing research activities, data collection, analysis and interpretation of the results, and writing manuscripts presented in this thesis.  The findings presented in Chapters 2-5 have been published or accepted as the following publications.  Chapagain, T. and A. Riseman (2012). Evaluation of Heirloom and Commercial Cultivars of Small Grains under Low Input Organic Systems. American Journal of Plant Sciences 3 (5): 655-669.  Chapagain, T., L. Super and A. Riseman (2014). Root Architecture Variation in Wheat and Barley Cultivars. American Journal of Experimental Agriculture 4 (7): 849-856.  Chapagain, T. and A. Riseman (2014). Intercropping Wheat and Beans: Effects on Agronomic Performance and Land Productivity. Crop Science 54 (5): 2285-2293.  Chapagain, T. and A. Riseman (2014). Barley-Pea Intercropping: Effects on Land Productivity, Carbon and Nitrogen Transformations. Field Crops Research 166: 18-25.  Chapagain, T. and A. Riseman, Nitrogen Transformation, Water Use Efficiency and Ecosystem Productivity in Monoculture and Wheat-Bean Intercropping Systems (Manuscript accepted for publication in Nutrient Cycling in Agroecosystems).   v  Table of Contents Abstract....... .............................................................................................................................................................. ii Preface…….. ............................................................................................................................................................. iv Table of Contents .................................................................................................................................................. v List of Tables ........................................................................................................................................................... x List of Figures ...................................................................................................................................................... xiv List of Acronyms and Abbreviations ........................................................................................................... xv Acknowledgements ......................................................................................................................................... xvii Dedication………… ................................................................................................................................................ xx CHAPTER 1: BACKGROUND INFORMATION AND OBJECTIVES ......................................................... 1 1.1 Small Grain Production: Opportunities and Challenges ............................................................. 1 1.1.1 Soil degradation: An emerging issue in small grain production ................................. 3 1.2 Intercropping: An Alternative to Conventional Small Grain Production ............................. 4 1.3 Nitrogen Transfer between Legumes and Associated Non-legume Plants ......................... 6 1.4 Estimating Nitrogen Fixation and Transfer using 15N Isotope Methods.............................. 8 1.4.1 15N natural abundance method ............................................................................................. 10 1.5 Understanding Wheat and Barley Root Architecture .............................................................. 13 1.6 CO2 Uptake, Respiration and Carbon Sequestration ................................................................. 15 1.7 Water Use Efficiency ............................................................................................................................. 17 vi  1.8 Research Goal and Specific Objectives ........................................................................................... 18 CHAPTER 2: CULTIVAR EVALUATION TRIAL ........................................................................................ 20 2.1 Materials and Methods ......................................................................................................................... 20 2.1.1 Climate description of the study area ................................................................................. 20 2.1.2 Soil and site description ........................................................................................................... 21 2.1.3 Experimental details .................................................................................................................. 21 2.1.4 Data collection and analysis .................................................................................................... 22 2.2 Results and Discussion ......................................................................................................................... 24 2.2.1 Plant-based parameters ........................................................................................................... 24 2.2.2 Management-based parameters ............................................................................................ 30 2.2.3 Protein content ............................................................................................................................ 33 2.3 Conclusions ............................................................................................................................................... 34 CHAPTER 3: WHEAT AND BARLEY ROOT ARCHITECTURE ............................................................. 57 3.1 Materials and Methods ......................................................................................................................... 57 3.1.1 Cultivar selection ......................................................................................................................... 57 3.1.2 Seed treatment ............................................................................................................................. 57 3.1.3 Study design and set-up ........................................................................................................... 58 3.1.4 Root architecture data analysis ............................................................................................. 58 3.2 Results and Discussion ......................................................................................................................... 59 3.2.1 Wheat root architecture ........................................................................................................... 59 vii  3.2.2 Barley root architecture ........................................................................................................... 60 3.2.3 Root architecture association with field performance ................................................. 60 3.3 Conclusions ............................................................................................................................................... 62 CHAPTER 4: WHEAT-BEANS INTERCROPPING ..................................................................................... 67 4.1 Materials and Methods ......................................................................................................................... 68 4.1.1 Climate description of the study area ................................................................................. 68 4.1.2 Soil and field description .......................................................................................................... 68 4.1.3 Experimental details .................................................................................................................. 69 4.1.4 Data collection and analysis .................................................................................................... 71 4.2 Results ........................................................................................................................................................ 77 4.2.1 Soil mineral nitrogen and δ15N content .............................................................................. 77 4.2.2 Plant performance indices ....................................................................................................... 78 4.2.3 Biological N2 fixation and transfer ....................................................................................... 80 4.2.4 N and C accumulation in biomass ......................................................................................... 81 4.2.5 Net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem photosynthesis and net ecosystem productivity ............................................................ 83 4.2.6 Water use efficiency ................................................................................................................... 84 4.2.7 Crop competition, weed and disease pressure ................................................................ 85 4.3 Discussion ................................................................................................................................................. 86 4.4 Conclusions ............................................................................................................................................... 91 viii  CHAPTER 5: BARLEY-PEA INTERCROPPING ........................................................................................ 117 5.1 Materials and Methods ....................................................................................................................... 117 5.1.1 Climate description of the study area .............................................................................. 117 5.1.2 Soil and site description ........................................................................................................ 117 5.1.3 Experimental details ............................................................................................................... 118 5.1.4 Data collection and analysis ................................................................................................. 119 5.2 Results ...................................................................................................................................................... 126 5.2.1 Soil mineral nitrogen and δ15N content ........................................................................... 126 5.2.2 Plant performance indices .................................................................................................... 126 5.2.3 Biological N2 fixation and transfer .................................................................................... 128 5.2.4 Biomass N and C accumulation ........................................................................................... 128 5.2.5 Net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem photosynthesis and net ecosystem productivity ......................................................... 129 5.2.6 Crop competition, weed and disease pressure ............................................................. 130 5.3 Discussion ............................................................................................................................................... 131 5.4 Conclusions ............................................................................................................................................. 134 CHAPTER 6: CONCLUSIONS AND FUTURE NEEDS ............................................................................. 147 LITERATURE CITED ........................................................................................................................................ 156 Appendix A Protocol adopted for N-determination in small grains using the       Kjeldahl method. ..................................................................................................................... 173 ix  Appendix B Performance of wheat and bean components in monocultures and   wheat-bean intercrop combinations. .............................................................................. 177 Appendix C Performance of barley and pea components in monocultures and      barley-pea intercrop combinations. ................................................................................. 179 Appendix D Coefficients of determination (r2) between bean performance metrics      in wheat-bean intercrop combinations. ......................................................................... 180 Appendix E Coefficients of determination (r2) between wheat performance metrics    in wheat-bean intercrop combinations. ......................................................................... 181 Appendix F Coefficients of determination (r2) between performance metrics in  wheat-fava bean intercrop combinations. ..................................................................... 182 Appendix G Coefficients of determination (r2) between pea performance metrics        in barley-pea intercrop combinations............................................................................. 183 Appendix H Coefficients of determination (r2) between barley performance metrics   in barley-pea intercrop combinations. ........................................................................... 184 Appendix I Performance of cereals and legumes in monocultures and intercropping systems. ........................................................................................................................................ 185 Appendix J CO2 flux, leaf area and chlorophyll concentration index measurements in cereal-legume intercropping systems. ............................................................................. 190 Appendix K Root growth and nodulation in cereal and legume genotypes. ............................. 191 Appendix L Types of cultivars based on the arrangement of spike-lets and seed characteristics. .......................................................................................................................... 192 x  List of Tables Table 2.1 Meteorological data during 2010 cropping season at UBC Farm, Vancouver, Canada. ............................................................................................................................................... 37 Table 2.2 Soil properties at site (prior to sowing i.e., spring 2010) at UBC Farm,   Vancouver, Canada. ....................................................................................................................... 38 Table 2.3 Small grain cultivars used for performance evaluation during 2010 spring   season at UBC Farm, Vancouver, Canada. ............................................................................. 39 Table 2.4 Legume crops and cultivars used for evaluation during 2010 cropping          season at UBC Farm, Vancouver, Canada. ............................................................................. 41 Table 2.5 Disease assessment key adopted during 2010 spring trial at UBC Farm, Vancouver, Canada. ....................................................................................................................... 43 Table 2.6 Rating key for nodule assessment (after Corbin et al., 1977) in legume           during 2010 cropping season at UBC Farm, Vancouver, Canada. ............................... 44 Table 2.7 Response of commercial wheat cultivars to organic production systems        during 2010 cropping season at UBC Farm, Vancouver, Canada. ............................... 45 Table 2.8 Performance of commercial and heirloom barley cultivars to organic     production during 2010 cropping season at UBC Farm, Vancouver, Canada. ........ 47 Table 2.9 Performance of legume cultivars to the organic production during 2010   cropping season at UBC Farm, Vancouver, Canada. .......................................................... 49 Table 2.10 Performance of commercial and heirloom wheat cultivars during 2010  cropping season at UBC Farm, Vancouver, Canada. ....................................................... 51 Table 2.11 Performance of commercial and heirloom barley cultivars during 2010  cropping season at UBC Farm, Vancouver. ........................................................................ 53 xi  Table 2.12 Protein content of wheat and barley cultivars grown under organic     production systems during 2010 cropping season at UBC Farm,            Vancouver, Canada. ..................................................................................................................... 54 Table 3.1 Root architecture metrics for heirloom and commercial wheat cultivars. .............. 63 Table 3.2 Root architecture metrics for heirloom and commercial barley cultivars. ............. 64 Table 3.3 Field performance of small grain cultivars grown under low input organic conditions during 2010 spring season at UBC Farm, Vancouver, Canada. .............. 65 Table 4.1 Climate data during the cropping seasons of 2011 and 2012 at UBC Farm, Vancouver, Canada. ....................................................................................................................... 93 Table 4.2 Soil mineral nitrogen (NH4+ and NO3-, mg kg -1 dry soil) at 0-15 cm depth      before planting (Spring-2011) and after final harvest (Fall-2012) in  monocultures and wheat-bean intercrop combinations. ............................................... 94 Table 4.3 Grain yields, land equivalency ratios and total land output values from monocultures and wheat-bean intercrop combinations. ............................................... 96 Table 4.4 Total biomass (grain plus shoot biomass) yields, land equivalency ratios            and total land output values from monocultures and wheat-bean intercrop combinations. ................................................................................................................................... 98 Table 4.5 1000 seed weights, biomass C:N and grain protein content of wheat and           bean components in monocultures and wheat-bean intercrop combinations. ... 100 Table 4.6 Nodule numbers, total N yield, biological nitrogen fixation and transfer by  legume in wheat-bean intercrop combinations during 2011-12 at UBC             Farm, Vancouver, Canada. ......................................................................................................... 102 xii  Table 4.7 Organic carbon and nitrogen yield from grain and shoot biomass in  monocultures and wheat-bean intercrop combinations during 2011-12                  at UBC Farm, Vancouver, Canada. .......................................................................................... 105 Table 4.8 Daytime averages of net ecosystem CO2 exchange, ecosystem respiration,       gross ecosystem photosynthesis and net ecosystem productivity in   monocultures and intercrop plots during 2011-12 at UBC Farm,              Vancouver, Canada. ..................................................................................................................... 107 Table 4.9 δ13C values in plant shoot tissue in monocultures and wheat-bean              intercrop combinations during 2011-12 at UBC Farm, Vancouver, Canada. ........ 110 Table 4.10 Crop on crop and crop on weed competition in wheat-bean intercrop combinations. .............................................................................................................................. 112 Table 5.1 Soil mineral nitrogen (NH4+ and NO3-; mg kg -1 dry soil) before planting      (Spring-2011) and after final harvest (Fall-2012) in monocultures and     intercrop plots. .............................................................................................................................. 136 Table 5.2 Grain yields, land productivity, biomass C:N and grain protein from    monoculture and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. ............................................................................................................................................. 137 Table 5.3 Total biomass (grain plus shoot biomass) yields, land equivalency ratios            and total land output values from monocultures and intercrop plots               during 2011-12 at UBC Farm, Vancouver, Canada. ......................................................... 138 Table 5.4 Harvest index, biomass C:N, chlorophyll concentration, and grain protein   content in monocultures and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. ..................................................................................................................... 139 xiii  Table 5.5 Nodule numbers, total N yield, biological nitrogen fixation and transfer                 by pea in monoculture and intercrop plots during 2011-12 at UBC Farm,   Vancouver, Canada. ..................................................................................................................... 140 Table 5.6 Average nitrogen yield from grain and shoot biomass in monocultures                and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. ................. 141 Table 5.7 Average carbon yield from grain and shoot biomass in monocultures                   and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. ................. 142 Table 5.8 Daytime averages of net ecosystem CO2 exchange, ecosystem respiration,       gross ecosystem photosynthesis and net ecosystem productivity in   monocultures and intercrop plots during 2011-12 at UBC Farm,              Vancouver, Canada. ..................................................................................................................... 143 Table 5.9 Crop on crop and crop on weed competition in barley-pea intercrop combinations during 2011-12 at UBC Farm, Vancouver, Canada. ............................ 144 Table 6.1 Summary of the effects of genotypes and spatial configurations on           agronomic and ecosystem metrics over monocultured plots. .................................... 149    xiv  List of Figures Figure 2.1 Disease assessment score and severity of leaf damage in wheat and barley. ....... 56 Figure 3.1 Root length (cm) distribution in diameter classes (mm) in wheat cultivars. ....... 66 Figure 3.2 Root length (cm) distribution in diameter classes (mm) in barley cultivars. ....... 66 Figure 4.1 Field layout and treatment composition in completely randomized block    design. ............................................................................................................................................. 113 Figure 4.2 Grain yield of wheat and bean components in monocultures and intercrop combinations. .............................................................................................................................. 114 Figure 4.3 Daytime average gross ecosystem photosynthesis (µmol CO2 m-2 s-1) in monocultures and wheat-bean intercrop combinations during 25, 50 and          75 days after sowing. ................................................................................................................ 115 Figure 4.4 Daytime average net ecosystem productivity (µmol CO2 m-2 s-1) in   monocultures and wheat-bean intercrop combinations during 25, 50                 and 75 days after sowing. ....................................................................................................... 116 Figure 5.1 Field layout and treatment composition in completely randomized block    design. ............................................................................................................................................. 145 Figure 5.2 Daytime average gross ecosystem photosynthesis (µmol CO2 m-2 s-1) in monocultures and barley-pea intercrop plots during 25, 50 and 75 days         after sowing. ................................................................................................................................. 146 Figure 5.3 Daytime average net ecosystem productivity (µmol CO2 m-2 s-1) in   monocultures and barley-pea intercrop plots during 25, 50 and 75 days         after sowing. ................................................................................................................................. 146   xv  List of Acronyms and Abbreviations AAFC  Agriculture and Agri-Food Canada ANOVA Analysis of Variance ARS  Agricultural Research Stations CCI  Chlorophyll Concentration Index CGC  Canada Grains Council cm  Centimeter DAS  Days after Sowing FAO  Food and Agriculture Organization g  Gram GEP  Gross Ecosystem Photosynthesis ha  Hectare HI  Harvest Index kg  Kilogram LER  Land Equivalent Ratio LSD  Least Significant Difference masl  Meter above sea level ml  Millilitre NEP  Net Ecosystem Productivity xvi  NS  Non-significant PLP  Plant Lodging Percentage pp.  Page RCBD  Randomized Complete Block Design Re  Ecosystem Respiration RH  Relative Humidity SEM  Standard Error of Mean SPSS  Statistical Package for Social Sciences t  Ton TGW  Thousand Grain Weight TLO  Total Land Outputs UBC  University of British Columbia USDA  United States Department of Agriculture WUE  Water Use Efficiency   xvii  Acknowledgements The author feels immense pleasure to express his deep sense of gratitude and appreciation to Dr. Andrew Riseman, Associate Professor in the Faculty of Land and Food Systems-LFS, and the Chairman of the Supervising Committee, for his constant supervision, friendly support, constructive comments, and invaluable counsel during the course of this investigation and writing of the thesis. I feel greatly fortunate to have Dr. Riseman as my mentor who helped me in every difficult time with his exceptional knowledge and experience. This work wouldn’t have been accomplished without his academic supervision and moral support in all phases of this research. The author is indebted to Dr. Art Bomke, Professor Emeritus and a member of supervising committee for his deep insight and interest in the subject of this thesis, and for his constant encouragement to move towards the results. The author also wishes to express heartfelt thanks to Dr. Murray Isman, Professor and Dean of the Faculty of Land and Food Systems, and a committee member for his tremendous inspiration and guidance throughout this project. The author would like to offer sincere thanks to Dr. Mahesh Upadhyaya, Professor and committee member for his precious suggestions and creative comments during field experimentation and manuscript preparation. The author is extremely grateful to the Graduate and Post-doctoral Studies (formerly known as the Faculty of Graduate Studies) of the University of British Columbia for offering the Four Year Doctoral Fellowship (4YF) with full tuition coverage during the first four years of his doctoral research. He is also thankful to the Faculty of Land and Food Systems (LFS) for offering the May L. Barnett Memorial Scholarship in Plant Science along with xviii  other departmental fellowships throughout his time at UBC. This financial support meant a lot for the author to study, research and spend a meaningful life in this multicultural community on campus at UBC - Vancouver. The author wishes to thank Ms. Shelley Small, the LFS Program Manager; Ms. Allison Barnes, the former LFS Manager; and Ms. Lia Maria, a graduate Secretary, for their moral support and necessary suggestion during his tenure at LFS. The author greatly acknowledges the entire team at the Centre for Sustainable Food Systems at UBC Farm for providing organically managed land for this research. Sincere thanks are due to the collaborating farmers in BC, Canada, and various states throughout the USA (i.e., Alaska, California, Colorado, Connecticut, Idaho, Maine, Oregon, Vermont, Wisconsin, and Washington), and institutions (Agriculture and Agri-Food Canada- AAFC, and Agricultural Research Service- ARS/USDA, Pullman, USA) who provided us with the seed of commercial and heirloom cultivars. The author has been quite fortunate to be surrounded by good people while at UBC. He wants to extend his deepest sense of thanks and appreciation to Ms. Laura Super and Mr. Greg Rekken, Plant Science lab members, for their friendly assistance in setting up and conduction of lab experiments, and for their contribution in implementing the lab protocols. Dr. Bishnu Pandey, Dr. Umesh Phuyal, Dr. Madhav Nepal, and Mr. Kapil Dev Regmi, and their families deserve special thanks for their familial coordination, encouragement, sharing of ideas, and other help from each possible corner. Words fail to express his emotional feelings towards his parent Mr. Prem Kumar Chapagain and Mrs. Kamala Chapagain, sister Mrs. Rama Neupane, brother-in-law Mr. Gyanu Neupane, xix  nephew Mr. Ayush Neupane, and beloved brothers Bikash and Prakash and their families, for their love, affection, endless patience, constant sacrifices as well as moral support extended to him during the study period. He has no words to express his deepest sense of love and emotions for his ever-loving wife Sarita, lovely son Sujal and daughter Shilu for care, love, understanding, encouragement and patience throughout the entire period of this study. Author (Tejendra Chapagain)   xx  Dedication         In Loving Memory of My Mother HARIMAYA CHAPAGAIN   1  CHAPTER 1: BACKGROUND INFORMATION AND OBJECTIVES 1.1 Small Grain Production: Opportunities and Challenges Wheat (Triticum spp.) is the third most produced cereal grain in the world after maize, (Zea mays L.; 875 million tons) and rice, (Oryza sativa L.; 718 million tons) with a production of over 674 million tons on over 216 million ha, or 3.1 t ha-1 (FAO, 2013). In Canada, it is the principal cereal grain grown as monoculture in Saskatchewan, Manitoba, Alberta and British Columbia (CGC, 2014), with a total production of 33 million tons on over 10 million ha, or 3.3 t ha-1 (AAFC, 2014). Barley (Hordeum vulgare L.) is also a major cereal grain grown worldwide with production of over 132 million tons on over 49 million hectares, or 2.7 t ha-1 (FAO, 2013). Like wheat, it is grown as monoculture in the prairies of Canada with a total national production of 9.4 million tons on over 2.8 million ha, or 3.7 t ha-1 (AAFC, 2014). The majority of wheat grown in Canada is spring wheat (including durum wheat), accounting for 94% of total production (Oleson, 2010); the remaining 6% is mostly winter wheat. The normal planting time of spring wheat and barley across Canada is from April to June with harvest from August to October. The cropping season for winter wheat, on the other hand, is from September through August. Spring non-durum wheat is planted on 75 percent of the harvested area (CGC, 2014) and is the largest category of wheat grown in Canada. However, in recent decades, crops such as canola (Brassica napus L.), dry pea (Pisum sativum L.), soybean (Glycine max L.), lentil (Lens culinaris Medik.) and broad beans (e.g., kidney beans- Phaseolus vulgaris L., and fava bean- Vicia faba L., etc.) have witnessed increased production in areas with sufficient precipitation (Statistics Canada, 2014). In 2  areas with insufficient precipitation, wheat production typically follows a summer-fallow monoculture system. On Vancouver Island, cereal grains were first grown during the early years of European colonization. However, wheat and barley gained economic importance after World War II when railways connected the prairies to the west coast (Ormsby, 1945) and production moved away from the region. However, this region has cool summer temperatures and long grain filling period suitable for cereals grown as a spring crop. In addition, spring cereals have a nitrogen demand more aligned with natural soil nitrogen cycles. Unfortunately, the availability of relatively poor quality spring wheat cultivars coupled with the availability of limited and expensive land, and the supply of large amount of grains from the Prairies provinces (Bomke et al., 1991), results in limited local production, and only supplies 10% the food grains consumed locally while food self-sufficiency was 85% 40-50 years ago (ESE, 2007). Currently, there are hundreds of high yielding cultivars available in Canada that are hybridized, patented and mostly selected under high chemical input conditions. Therefore, a constant supply of recently developed or new cultivars is available to the region’s growers. However, tremendous genetic diversity exists in wheat and barley cultivar collections including those considered heritage cultivars (i.e., pre 1960 introduction).  These heirloom cultivars were selected under low-input production so are thought to grow well without conventional chemical inputs and may be well suited for sustainable, low-input production (Rempel, 2008). However, decisions to grow a cultivar are rarely based on information from local trials. Therefore, comparative cultivar trials, including both 3  heirloom and commercial cultivars, conducted under local conditions and organic guidelines can provide important information for interested farmers. 1.1.1 Soil degradation: An emerging issue in small grain production Soil degradation and declining land productivity are significant issues for conventional small grain production. Farmers typically use an intensive monoculture-based farming system with high reliance on agrochemicals to maintain crop yields. However, over time, intensive agrochemical use promotes soil degradation and erosion (Liu et al., 2009; McGill et al., 1981; Dumanski et al., 1986), increases air and water pollution (Louis et al., 1996), accumulates chemical residues in food (Oates and Cohen, 2009), reduces biodiversity (McLaughlin and Mineau, 1995), and increases greenhouse gas emissions (Campbell et al., 1995). These consequences have serious implications for food security of both rural and urban populations. In addition, as soils become less productive, farmers’ earnings decrease making it more difficult to sustain their livelihoods. In Canada, soil health and quality are the most significant agricultural issues. Farmers in the Canadian prairies typically follow chemical intensive practices to maintain soil productivity and that compensate for the effects of increased loss of organic matter, soil erosion, acidification and salinization. The annual estimated loss from soil erosion in terms of lost productivity on the prairies is between 350-450 million dollars (Dumanski et al., 1986) of which 40-45% loss is governed by water erosion. The top soil losses in the prairies exceed the rate of soil formation with the annual loss of more than 117 and 160 million tons of soil from water and wind erosion, respectively (Sparrow, 1984). These losses significantly reduce soil productivity through nutrient removal, organic matter 4  degradation, and reduced soil water holding capacity. In terms of grain yield, annual losses are near 4.6 million tons, 15% of which cannot be compensated for by additional fertilizer application (Sparrow, 1984). Conventional high-till cereal production increases the rate of organic matter loss from the top soil. The average loss of organic matter ranges between 36 to 49 percent in chernozemic soils of the prairies (McGill et al., 1981). In addition, nearly 2.2 million hectares of land in the prairies suffer from salinization from the use of synthetic fertilizers, with an estimated annual economic loss between 104-257 million CAD (Dumanski et al., 1986). These important soil quality issues suggest that more effort is needed to develop environmentally and economically sustainable production systems for small grain producers. Furthermore, it is equally important to restore the degraded soil by using integrated agroecological approaches in crop production and soil management. One strategy that may meet these goals is to intercrop grain legumes with small grains under organic production conditions. 1.2 Intercropping: An Alternative to Conventional Small Grain Production Intercropping is defined as growing of two or more crops simultaneously on the same land during a single growing season (Ofori and Stern, 1987). It can meet several ecological goals including increasing biological diversity, promoting species interaction and enabling natural nutrient regulation (Hauggaard-Nielsen et al., 2007). Also, intercropping provides a number of additional benefits including reducing soil erosion (Lithourgidis et al., 2011), increasing weed suppression (Bulson et al., 1997; Haymes and Lee, 1999), increasing 5  moisture retention (Ghanbari et al., 2010), maintaining soil fertility (Hauggaard-Nielsen et al., 2009), and increasing nutrient cycling (Hauggaard-Nielsen et al., 2003) and biological nitrogen fixation (Bulson et al., 1997; Jensen, 1996). It provides an opportunity to improve agriculture through increased production (Hauggaard-Nielsen et al., 2007), enhanced soil conservation (Lithourgidis et al., 2011) and significant labour savings (Thurston, 1996). Typically, intercrop components are from different species or families with one crop of primary importance (e.g., food) while the other primarily providing some other benefit (e.g., N2 fixation). An effective intercrop combination is one that produces greater total yield on a piece of land and uses resources more efficiently than would otherwise be used when each crop is grown as a monoculture (Inal et al., 2007). Beans are a group of valuable legume species being assessed as intercrops in small grain cropping systems (Ghanbari-Bonjar and Lee, 2002; Gooding et al., 2007; Haymes and Lee, 1999; Pristeri et al., 2006). Other legumes used as an intercrop in sustainable wheat and barley production include pea, (Pisum sativum L.; Ghaley et al., 2005; Subedi, 1997), lentil, (Lens culinaris L.; Dusa, 2009) and red clover, (Trifolium pratense L.; Blaser et al., 2006). The combination of a non-N2-fixing cereal (i.e., wheat, barley) with a N2-fixing leguminous species (i.e., bean, pea) can provide multiple benefits over monoculture production (Ofori and Stern, 1987; Trenbath, 1974) as legumes improve soil fertility through the legume-rhizobia symbiosis (Jensen, 1986; 1996). This combination also fits well within the principles of organic farming since it is practiced without the use of agrochemicals or synthetic N fertilizers (USDA, 1980). Therefore, growing small grains with grain legumes under organic farming practices is seen as a strong component of a farm-wide production system that fulfills economic and environmental sustainability concerns. 6  In wheat and barley intercrop research, many studies have included pea, while few assessed common bean (Phaseolus vulgaris L.) or fava bean (Vicia faba L.). Furthermore, the effect of species ratios and spatial configuration within an organic production context has yet to be investigated. Similarly, most of the previous research on intercropping systems has only assessed traditional performance metrics i.e., yield, disease and pest pressure, crop competition, and weed control (Ghaley et al., 2005; Gooding et al., 2007; Hauggaard-Nielsen et al., 2003; 2009; Jensen, 1996; Lauk and Lauk, 2008; Subedi, 1997). However, metrics related to environmental sustainability also need to be measured. These include N-use efficiency (i.e., biological nitrogen fixation and transfer to the companion plants), net ecosystem CO2 exchange (NEE), ecosystem respiration (Re), gross ecosystem photosynthesis (GEP) also referred to as gross primary productivity of the cropland, carbon sequestration or net ecosystem productivity (NEP), water use efficiency (WUE), and their association with crop performance, grain yield, and biomass production. 1.3 Nitrogen Transfer between Legumes and Associated Non-legume Plants Nitrogen is an essential element in crop production and often the most limiting nutrient in agro-ecosystems. In addition, N management in small grain production is especially challenging for farmers due to the large acreage planted and the observed increases in fertilizer prices, emission of nitrous oxide (N2O) from these fertilizers, and their potential to contaminate ground and surface water sources (Ferguson et al., 1999). Effective nitrogen management, therefore, is a key to improving soil health, environmental quality, and financial returns from crop production. With this context, it is important to understand crop nitrogen requirements and the amount of N present in the system in order to supply 7  optimum N levels for profitable yields, while also protecting the environment (Campbell et al., 1995; Robertson, 1997). Biological nitrogen fixation (BNF) by the legume component helps to fulfill the nitrogen requirement of the companion species through improved soil fertility and the potential transfer of nitrogen through root exudates and root connections. Advances in plant N research suggest that a plant can acquire N from companion plants through transfer (He et al., 2003; Stern, 1993) that usually occurs between a donor (i.e., a N2-fixing plant) and a receiver (i.e., a non N2-fixing plant), a process termed inter-plant N transfer (Johansen and Jensen, 1996; Stern, 1993). It is defined as ‘a process of N fixation and deposition from one plant and subsequent transfer or uptake by another plant’ (Jensen, 1996). There are two different pathways through which N-transfer occurs in plants, i.e., direct and indirect N-transfers. Direct N-transfer occurs through the activities of mycorrhizae and their hyphal network connecting donor and receiver plants, commonly known as common mycorrhizal networks (CMN) (Habte, 2000; Newman, 1988). Mycorrhizae can form CMN by extending their hyphae from the roots of mycorrhizal plants to the roots of non-mycorrhizal species when planted in close proximity thus, facilitating transfer (He et al. 2003; Newman, 1988). Indirect N-transfer however, is related to the release of soluble nitrogen (e.g., NH4+, NO3-) from the legumes to the soil and subsequent movement to the roots of receiver plants through mass-flow or diffusion (San-nai and Ming-pu, 2000). Alternatively, mycorrhizal hyphae in the receiver’s roots may absorb and translocate the N released by the donor plant (San-nai and Ming-pu, 2000). Nitrogen transfer is particularly evident when soil nitrogen is limited (Fujita et al., 1992). 8  A number of reports have revealed the significance of inter-plant N transfer by using isotopic nitrogen variation using 15N labelled fertilizers (He et al., 2003; Stern, 1993) and 15N natural abundance methods (Shearer and Kohl, 1988). Results from 15N studies, however, vary greatly for the amount of N transferred (i.e., ≤5 to 20% of the N in the receiver plants) from N2-fixing donor to the non-N2-fixing receiver (He et al., 2003; 2009). Some reports indicate that inter-plant N transfer occurs and may increase the growth of the grass community when planted with N2-fixing forage legumes (Brophy et al., 1987; Heichel and Henjum, 1991). Despite these observations of inter-plant N transfer, there are a number of questions yet to be investigated. These include: 1) Is inter-plant N transfer within a growing season occurring? 2) If occurring, what are the effects of N transfer on donor crop performance? 3) What level of variation exists among individual legume species and cultivars in terms of N transfer? and 4) Does spatial arrangement affect the extent of N fixation and transfer? 1.4 Estimating Nitrogen Fixation and Transfer using 15N Isotope Methods The most useful and commonly used methods for estimating N2 fixation are classified into three groups: nitrogen accumulation, acetylene reduction, and use of 15N, with each method having its own advantages and limitations. The 15N isotopic methods are considered the most precise for studies in complex biological systems because N has several stable isotopes available for monitoring. Isotopes are ‘atoms of the same element that differ in atomic mass due to differences in the number of neutrons contained in the atoms' nuclei’ (He et al., 2009). There are several known isotopes of nitrogen (i.e., 10N, 11N, 11mN, 12N, 13N, 14N, 15N, 16N, 17N, 18N, 19N, 20N, 21N, 22N, 23N, 24N and 25N), but the most easily detectable are 9  radioactive and not suitable for this research because of half-lives of less than 11 min (He et al., 2009). Although the radioactive isotopes can be traced and have been used in N2 fixation studies, the technical difficulties involved do not allow for their general use under agricultural conditions (Warembourg, 1993). Two stable isotopes of nitrogen useful for longer-term research are 14N and 15N. They occur naturally in the environment and are most commonly used in ecological and agronomic research. Of the two isotopes, 14N is more abundant (~99.6337%) than 15N (~0.3663%) in the atmosphere with their ratio (i.e., 0.0036765) remaining constant (He et al., 2009). The stability of this atmospheric ratio is the reason why atmospheric N2 is used as a ‘standard’ in mass spectrometric analysis of 15N (Knowles and Blackburn, 1993; Mariotti, 1983). However, the ratio of isotopes is normally different in the soil environment since biochemical and physiological processes discriminate against 15N due to its greater atomic mass (He et al., 2009). By using these naturally occurring processes (natural 15N abundance method, δ15N, ‰), or by artificially inducing them through the addition of 15N, either in the atmosphere (15N2 method) or in the soil (15N labelled fertilizer method, often called the 15N isotope dilution method, usually expressed as atom %), it is possible to estimate the amount of N derived from biological fixation. Of the three isotopic methods, 15N natural abundance (δ15N) and 15N labelling methods have been most commonly used in BNF and transfer studies (He et al., 2003; Newman, 1988; Stern, 1993). Both of these methods are considered appropriate for longer-term field studies as they provide information on the extent of N added to soil through BNF (Hogberg, 1997), N input from fertilizers (Robinson, 2001), the extent of N cycling (Boddey et al., 2000), and possible identification of alternate N sources available to plants (Dawson et al., 10  2002). The 15N natural abundance method was deemed most appropriate for this research and is further discussed below. 1.4.1 15N natural abundance method The 15N natural abundance method is considered a precise alternative for N2 fixation and transfer studies to either the 15N labelled fertilizer method or the classic N accumulation method (Shearer and Kohl, 1988). In this method, endogenous N is used to estimate the relative contribution of two sources (i.e., soil and atmosphere) to a common sink. Therefore, it does not require an added tracer or artificially labelled fertilizer. This method uses the differences in 15N abundance (δ15N, ‰ 15N) between atmospheric N2 and soil N to estimate the relative contribution of symbiotically fixed N to plant-soil systems. The difference is usually small but able to be measured precisely and calculated using the following equation (Shearer and Kohl, 1988): δ15N (‰) = 1000 x (R sample – R standard)/ R standard…………………………………………………………..1 where the subscript ‘sample’ refers to the experimental sample and the ‘standard’ is typically atmospheric N2 (δ15N = 0; Mariotti, 1983). R is the ratio of the concentration of 15N to the total N in the sample under investigation. This may be written as R = 15N / (15N + 14N) or R = 15N/14N. The first equation is generally more useful when the subject is source identification with the latter more useful when the subject is isotope discrimination (Shearer and Kohl, 1988). At the level of natural abundance, these two definitions are operationally indistinguishable because the difference in δ15N values calculated using these two equations is negligible i.e., much smaller than the error of measurement. 11  The percentage of plant N derived from atmospheric N2 (% NDFA) is calculated according to Shearer and Kohl (1986) as follows: % NDFA = 100 x (δ15Nref − δ15Nleg) / (δ15Nref − δ15Nfix)……………………………………………………2 In this equation, δ15Nref is the δ15N value of the non-N-fixing reference plants grown alone and dependent on soil N; δ15Nleg is the δ15N value from the nodulating and potentially N2-fixing legumes (grown in mixed culture in the case of intercropping) where fixed N and soil N are both available as N sources; and δ15Nfix is the δ15N value for the nodulating N2-fixing plants when they are totally dependent on biological nitrogen fixation (BNF) as their N source. Therefore, inoculated N2-fixing plants should be grown in N-free nutrient media to determine δ15N value for the nodulating N2-fixing plants (δ15Nfix). The δ15N of biologically fixed N (δ15Nfix) is usually less than the atmospheric δ15N (= 0) and is often lies between −1 and −2‰ (Shearer and Kohl, 1991). The amount of N transferred from donor to receiver plants in an intercropping system can be calculated as one-way N transfer from N2-fixing legumes to the non- N2-fixing receiver as follows (He, 2002): % N transfer = 100 x (δ15N receiver mono - δ15N receiver intercrop) / δ15N receiver mono……..3 In some cases, N can be transferred from the non-N2-fixing donor to the N2-fixing receiver and is calculated as: % N transfer = 100 x (δ15N receiver intercrop - δ15N receiver mono) / δ15N receiver mono…….4 One of the major advantages of 15N natural abundance method lies in its minimum disturbance to the plant–soil system that makes it possible to trace long-term 15N variation in agro-ecosystems (Shearer and Kohl, 1986; 1988). The similarity between the 15N natural 12  abundance method and the 15N enrichment method is that they both require a reference plant to estimate the amount of N2 fixed symbiotically and transferred to the non-N2-fixing plant. The accuracy of these methods depends on the selection of appropriate reference materials to avoid the difficulties associated with the soil’s spatial and temporal variation in δ15N. Care must be taken that the δ15N values for soil derived nitrogen be the same in N2-fixing and reference plants (Shearer and Kohl, 1986). Although an ideal non-N2-fixing reference plant having similar root architecture and shoot morphology is very difficult to find, studies of grain legumes such as common bean, fava bean, pea and soybean have used non-nodulating cereals such as wheat, barley, and even rapeseed as reference plants (Warembourg, 1993). The 15N natural abundance method cannot be applied to all sites. This method requires that the soil be homogeneous so that the variation in soil N across the test site is smaller than the amount of biologically fixed nitrogen. This method gives reliable results in soils with low N as N2 fixation, translocation or cycling processes are normally inhibited under high soil N levels. This method is also based on the assumption that biological and chemical processes in soil (e.g., mineralization) prefer 14N as these processes discriminate against the heavier 15N form (Yoneyama, 1996) thereby enriching the soil with 15N compared to the atmosphere. This results in a significant difference (usually    3–4‰) in the δ15N values between soil and the N derived from other sources (i.e., atmosphere). In general, soil derived N shows higher δ15N values compared to atmospheric N2 resulting in a greater δ15N value in non-N2-fixing plants (Shearer and Kohl, 1986).  13  1.5 Understanding Wheat and Barley Root Architecture Increasing our understanding and characterization of inter- and intra-specific variation of root architecture has implications in plant ecology, agronomy, and resource use efficiency. A plant’s root architecture is an important trait in crop breeding and improvement programs designed to develop improved cultivars with tolerance to drought and mineral toxicity, water and nutrient uptake efficiency and lodging resistance (Manske and Vlek, 2002). This is especially true for small grain improvement programs that screen and select appropriate crops and cultivars for specific soil and climatic conditions. Also, root architecture is considered crucial in determining crop adaptability to marginal environments, especially in the areas with limited water, nitrogen and phosphorus availability. In cereal-legume intercropping systems, root growth and architecture play important roles in determining which crops or cultivars are best suited to co-cultivate. In addition to crop genotype, root growth and architecture are affected by soil type and nutrient and water supplies in the rhizosphere. In general, shorter, thicker, and more branched roots develop in compacted soils whereas non-compacted soils promote thinner and longer root systems (Dexter, 1987). Cholick et al. (1977) and Vlek et al. (1996) suggest that small grains produce thinner roots under water or nutrient stressed conditions, and display a significant plasticity in root growth to help adapt to marginal soil conditions. Furthermore, plants often respond to marginal soil conditions by increasing nutrient uptake efficiency (Egle et al., 1999) through altering root growth and patterns (Horst et al., 1996) and by increasing root to shoot ratios (Manske and Vlek, 2002). 14  Wheat and barley normally develop three to seven primary roots that constitute up to 14% of the volume of the entire root system (Manske and Vlek, 2002). These primary roots grow first and are important in early crop establishment while the secondary roots develop later throughout the vegetative period (Klepper, 1991). The secondary roots grow shallower and horizontally further from the stem with their number positively correlated with tillering ability (Hockett, 1986). Wheat genotypes are classified as ‘high input’ and ‘low input’ based on the number of tillers, harvest index-HI, and root architecture (Manske et al., 2000). High input wheat genotypes normally possess fewer tillers, higher harvest index, and shorter and coarser roots (i.e., greater root diameters) while the root systems of low-input genotypes normally possess more tillers, lower harvest index, longer, and thinner roots that allow for greater soil exploration (Masnke et al., 2000; Vlek et al., 1996). Root architecture plays a significant role in water and nutrient uptake by plants. Root length and diameter significantly affect nutrient and water uptake efficiencies in small grains (Jones et al., 1989). The important feature of wheat and barley is that they acquire the vast majority of their nutrients, including nitrogen, from their secondary roots shallow in the soil profile, typically in the upper 10 cm (Bole, 1977). Unfortunately, conventional selection under high input conditions has inadvertently co-selected for shorter and coarser root systems. Therefore, wheat breeding programs designed to improve water and nutrient uptake should include selection for longer and thinner root systems allowing plant roots to explore a greater soil volume. As root architecture strongly affects plant performance, understanding the inherent variation among cultivars is important for both plant breeders and farmers. There remains a great need to accurately characterize and associate root architectures with both 15  inheritance and production performance. In addition, characterizing root architecture variation can help link our fundamental knowledge across plant science disciplines, e.g., plant ecology, plant physiology, and agronomy (Bodner et al., 2013). Finally, significantly more research has been conducted on the above-ground plant parts compared with below-ground parts, despite its accepted importance (Manske and Vlek, 2002). Therefore, we assessed heirloom and commercial cultivars of wheat and barley to improve our understanding of the variation in small grain root architecture and to assess their potential for low input sustainable agriculture. 1.6 CO2 Uptake, Respiration and Carbon Sequestration Carbon dioxide (CO2) is the primary greenhouse gas (GHG) associated with human activities and accounts for approximately 84% of all GHG emissions (USEPA, 2013). CO2 concentrations in the atmosphere have been rising, from approximately 315 ppm in 1959 to a current atmospheric average of 401 ppm (UCSD, 2014), and are projected to reach as high as 500-1000 ppm by 2100 (IPCC, 2007). Soil plays a crucial role in the global carbon (C) cycle (Houghton et al., 1995; Schimel, 1995) as a major sink for atmospheric C (Schlesinger and Andrews, 2000) through soil organic matter (SOM) accumulation. The soil organic carbon (SOC) pools in agricultural systems, however, are currently in disequilibrium with the environment as the losses attributed to decomposition exceed the gains associated with biomass addition (Jarecki and Lal, 2003). This suggests development of agricultural systems that fix more CO2 (i.e., greater gross ecosystem photosynthesis- GEP) with the release of less CO2 (i.e., ecosystem respiration- Re) which would help balance, and ultimately move to positive CO2 movement between agricultural ecosystems and the atmosphere, a term referred to as net ecosystem CO2 exchange (NEE). Furthermore, it is 16  essential to enhance net SOM gains through simultaneously increasing plant biomass deposition and decreasing decomposition to reduce agricultural emissions of GHGs. Crop plants are the primary source of new carbon that enters the soil in agricultural systems.  Through photosynthesis, plants fix atmospheric CO2 to produce carbohydrates (Beedlow et al., 2004) which drive the growth of new tissues. However, not all carbohydrates fixed by plants are used for growth as nearly half is lost as CO2 during respiration (Cambardella, 2005). A portion of the remaining carbohydrate is available for transfer to the soil through different plant parts e.g., leaves, stem, root exudates, etc. which over time, eventually transform into stable soil organic matter. Plants require adequate N for photosynthesis and growth leading to increased SOM and carbon stores (Beedlow et al., 2004). However, different species have different N requirements with N2-fixing legumes requiring less soil nitrogen compared to non-N2-fixing species such as cereals. When these two types are planted together in an intercropping system, the legume component may provide additional N to the cereal thereby inducing a positive growth response in it. If this is true, planting N2-fixing legumes with N-demanding cereals (e.g., wheat, barley) under low input organic systems should provide greater yields than with monoculture production. Therefore, in addition to quantifying the amount of C accumulated in grains and shoot biomass, it is important to measure CO2 movement between an agricultural ecosystem and the atmosphere, a term referred to as net ecosystem CO2 exchange (NEE), and ecosystem respiration (Re) to calculate gross ecosystem photosynthesis - GEP (i.e., ecosystem respiration (Re) minus NEE, often referred to as gross primary productivity of the cropland), and net ecosystem 17  productivity - NEP (i.e., NEE with a negative sign). This information allows for the assessment of intercrop systems’ potential to help mitigate agricultural GHG emissions. 1.7 Water Use Efficiency Water use efficiency (WUE) in agronomy is often defined as the crop yield per unit of water consumed. However, there are various ways of interpreting ‘yield’ (i.e., grain or total biomass) and ‘water consumption’ (i.e., total water input, total water evapotranspired or total water transpired) (VanLoocke et al., 2012). Regardless of how WUE is defined, the increasing scarcity of and competition for water resources for agriculture is pressing us to design more water efficient production systems, especially for rain-fed locations. WUE in crop production can be improved by adopting crop management practices that reduce evapotranspiration, surface run-off and drainage, and by effective N management that promotes rapid early crop growth that shades the soil thereby reducing additional evapotranspirative losses (Gaiser et al., 2004), and through breeding and selection to acquire more C (i.e., biomass) in exchange for the water transpired by the crop, i.e., improving crop transpiration efficiency (Condon et al., 2004). Intercropping may improve the production system’s WUE as it increases water uptake and storage in root zones through the presence of diverse root systems, and reduces inter-row evaporation and excessive transpiration by promoting crop growth that shades the soil creating a protected microclimate (Zhang et al., 2012). Plant carbon isotopic composition values (δ13C) can be considered a proxy of intrinsic water use efficiency of crop plants (WUE) (Condon et al., 1987; 2002) where less negative δ13C values indicate higher WUE and more negative δ13C values indicate lower WUE. The 18  basis of using δ13C values as a proxy of intrinsic WUE of plants lies on the fact that biochemical reactions (e.g., photosynthesis) discriminate against the heavier 13C isotope as it is less reactive than 12C. Therefore, the isotopic composition (i.e., 13C/12C) reflects the effect of plant water status on photosynthesis throughout the cropping season where greater 12C content is linked to increased photosynthesis relative to transpiration. Therefore, measuring δ13C values and calculating intrinsic WUE of wheat in monoculture and intercrop systems may allow the assessment of system wide WUE. 1.8 Research Goal and Specific Objectives The overarching goal of this project is to increase the sustainability of small scale farming systems through modification of the predominant cereal-based cropping system with the integration of grain legumes as an intercrop component. This is aimed to maintain or increase overall productivity of the system while reducing N fertilizer inputs and promoting increased environmental benefits for society and economic benefits for farmers. The specific objectives of this project were to: 1) Evaluate heirloom and commercial cultivars of cereals and legumes for plant performance metrics (e.g., grain yield, 1000 seed weight, protein content, days to heading, harvest index, disease incidence and severity, nodulation) and their potential for inclusion in cereal:legume intercrop trials; 2) Identify the most functional genotype pairings for intercrop synergies (i.e., N-fixation and transfer, C sequestration, etc.) based on plant traits (i.e., root growth and architecture, maturation dates, canopy cover, yield, disease resistance, etc); 19  3) Identify intercropping combinations and designs that maximize synergies, as compared to monoculture plots, including N and water use efficiencies, C sequestration and productivity metrics; 4) Quantify the amount of biologically fixed nitrogen introduced by different legume genotypes and the amount transferred to wheat or barley across various spatial arrangements; 5) Determine the carbon fluxes and WUE as affected by genotype and spatial arrangement, and; 6) Recommend the optimal combination of practices that are both productive and environmentally sustainable.   20  CHAPTER 2: CULTIVAR EVALUATION TRIAL  A version of this chapter has been published as Chapagain, T. and A. Riseman (2012), Evaluation of Heirloom and Commercial Cultivars of Small Grains under Low Input Organic Systems. American Journal of Plant Sciences 3 (5): 655-669. This study was conducted at the Centre for Sustainable Food Systems at UBC Farm in Vancouver, BC, during 2010-cropping season (May to September) to assess plant performance metrics of heirloom and commercial cultivars of small grains available in the region, and their potential in a small grain:legume intercropping system. The experimental site is located at 49° 15' 3" N and 123° 14' 20" W, at an altitude of 100 m above mean sea level. Research was conducted under natural climatic conditions and organic growing context. 2.1 Materials and Methods 2.1.1 Climate description of the study area Climatic data are summarized for the experimental site during the spring-summer season (June to September) of 2010 (Table 2.1). Average day-time temperature over the cropping season was 17.1°C, with the warmest days in August, whereas the average night-time temperature was 14.6°C. The average daily soil temperature at 10 cm and 20 cm depth was 18.9°C and 18.6°C, respectively. Monthly average of solar irradiance was 590.3 W m-2. The monthly precipitation average was 61.5 mm with July receiving the least rain and September receiving the most. Total precipitation during June to September was 245.8 mm. The 24-hour average for relative humidity (RH) ranged from 73.2 to 83.8 in July and September, respectively. 21  2.1.2 Soil and site description Four random composite soil samples were collected at the time of plot establishment to characterize soil fertility (i.e., pH, EC, organic matter, total N, and available P, K, Ca, Mg, Cu, Zn, Fe, Mn and B). The average values are listed (Table 2.2). The soil was a coarse textured sandy loam of the Bose series (Bertrand et al., 1991) with low to moderate fertility. Soil was fairly homogeneous across the test site. The site was not used for grain production in prior years but was a designated area for seasonal vegetable cultivation. The land has been managed under organic guidelines for more than the 10 years and therefore does not include any prohibited chemicals/substances. 2.1.3 Experimental details Commercial and heirloom cultivars of wheat, barley, pea, lentil, fava bean, kidney bean, and soybean were sourced from farmers in BC, Agriculture and Agri-Food Canada, and various states throughout the USA (i.e., Alaska, California, Colorado, Connecticut, Idaho, Maine, Oregon, Vermont, Wisconsin, and Washington). Commercial and heirloom cultivar descriptions and planting details are listed (Table 2.3, 2.4, Appendix L). All cultivars listed were provided with the same level of management. Seeds were cleaned as necessary, counted (except for commercial cultivars for which 1000 seed weights were provided), and weighed to calculate the appropriate seeding rate. Wheat and barley cultivars were sown using a hand seeder (Jang Clean Hand Seeder, Jang Automation Co. Ltd., Cheongju-city, South Korea) with adjustable sprockets (Front: 11, Rear: 14), and seed plates (AA-6 for wheat and barley, G-12 for pea) whereas grain legumes were planted by hand along the line using the seed rate as specified. 22  Spring cereals were planted at 12 cm spacing in late May (28-30 May, 2010) targeting 280-300 viable plants m-2. Therefore, assuming a >80% germination rate, a seed density of 350 seed m-2 for wheat and barley cultivars was used. Our seed densities for pea, lentil, fava bean, kidney bean and soybean were 66, 200, 33, 33, and 33 seeds m-2, respectively, targeting 60, 160, 30, 30 and 30 viable plants m-2. This was a non-replicated trial with both the commercial and heirloom cultivar plots measured 9m x 3m however, the plot was divided into three subplots of 3m x 3m, and data were collected from 2 different areas of 0.5 x 0.5m2 within each subplot and averaged, serving as one sample. Sowing depth varied with seed size and ranged from 3-4 cm for small seeds like wheat, barley and lentil, and 4-5 cm for larger seeds like fava bean and kidney bean. Plot layout was alternated between wheat, barley and legumes to minimize out-crossing between cultivars. Plots were equipped with a sprinkle irrigation system for timely irrigation during long dry periods. No external fertilizers, pesticides or fungicides were used on test plots throughout the growing season. 2.1.4 Data collection and analysis Plant-based parameters: Data were recorded for plant height (from soil surface to the tip of apical leaf), number of effective tillers (heads) m-2, days to harvest, spike length, seed spike-1, grain yield (t ha-1), 1000 seed weight, harvest index [HI, defined as a ratio of economic yield (grain yield) to the total plant mass (grain yield + shoot biomass)], and seed weight to volume ratio. Chlorophyll concentration index (CCI) was measured using handheld chlorophyll meter (Model CCM 200 plus, Opti-Sciences Inc., New Hampshire, USA) on the flag leaf and the 3rd leaf during early growth stage (30 DAS). Spike color was a determinant 23  of maturity and considered ready for harvest when spikelets were straw-colored and 80% of the grains of the spike were in the hard-dough stage. The plots were sampled by harvesting the above ground biomass from 2 different areas of 0.5 x 0.5 m2 within each subplot, leaving 10 cm stubble. Crop material was dried at 60oC and threshed. Grain was ground to fine powder (<0.6 mm) and analyzed for total nitrogen, according to the Kjeldahl method (Appendix A) and converted to crude protein levels (%N x 5.8 for wheat and barley, and %N x 6.25 for pea and beans) (Jones, 1931). Each sample was replicated thrice. Grain yield, 1000 grain weight, and protein concentrations were expressed at 12.5% moisture. Crop management parameters: General observations were made 30 and 70 days after sowing (DAS) on the type and number of weeds present and insect pest and disease pressures with regard to type and nature of damage. Cereal stem, leaf and head diseases of economic importance including Fusarium (Fusarium spp.), Barley Stripe (Helminthosporium gramineum), Scald or Leaf Blotch (Rhynchosporium secalis), Stem/Leaf/Stripe/Yellow/Brown Rust (Puccinia spp.), Septoria Leaf Spot or Glume Blotch (Septoria tritici) were monitored and noted over the course of the season. Plants were assessed for disease resistance at Zadoks growth stages (ZGS) as devised by Zadoks et al. (1974) and expanded by Tottman (1987). Disease assessments were conducted on five random plants from each plot. Rating was done according to the assessment key (Table 2.5, Figure 2.1) used by the Eco-friendly Crop Rotation Project operated in Delta, BC by the Delta Farmers’ Institute & Faculty of Land and Food Systems, UBC, Canada (Temple, 2009). Lodging was assessed before harvest on a 0-10 scale (i.e., 0 for 100% erect plants, and 10 for complete lodging of whole plot) based on visual observation. The angle of lodging was 24  also assessed. Plants that were completely bent down to the ground (60 to 90o) with all spikes touching the soil surface were considered completely lodged while the plants up to 60o without having spikes contacting the soil surface were considered partially lodged. The scores were averaged and transformed into percentages. Legume nodulation: Nodulation was assessed by examining the roots of 3 randomly selected plants, 30 and 70 DAS, from each plot. Measurements included earliness of nodulation, total nodule number, color and distribution followed by the visual nodulation scores as described in Table 2.6. Visual scoring used a 0 to 5 scale and was based on nodule number, size, pigmentation and distribution (Corbin et al., 1977). The scores from all plants were added and then divided by the number of plants to obtain a mean nodule score. Data were compiled and subjected to analysis using MSTAT-C (MSU, 1993). Simple correlation coefficients and coefficients of determination were determined between selected parameters using Statistical Package for the Social Sciences (SPSS) software. 2.2 Results and Discussion 2.2.1 Plant-based parameters Wheat: The response of commercial and heirloom wheat cultivars on key vegetative and reproductive parameters is shown (Table 2.7). In general, heirloom cultivars showed notable response in a number of parameters compared with commercial cultivars including later maturity, taller plants, greater number of spikes m-2, longest spike, higher number of seed spike-1, and greater seed weight to volume ratio. There existed significant variation among the heirloom cultivars while the commercial cultivars were more uniform for a number of plant based parameters. Significant variation was also observed between 6-row 25  hulless and 2-row hulled cultivars with 2-row hulled-type showing higher disease resistance but with lower grain yield and HI. Commercial cultivars displayed the highest 1000 seed weights, grain weights and HIs (Table 2.7). Heirloom cultivars matured 1-4 weeks later as compared to the commercial cultivars, though harvest date varied. ‘Pacific Blue Stem’ took 135 days to harvest followed by ‘Einkorn’ and ‘Red Fife’ (125 days) while ‘Sounders’ and ‘Reward’ matured the earliest (95 days). Except for ‘Snowbird’ and ‘Snowstar’, commercial cultivars were near the average of 105 days to harvest. ‘Snowstar’ and ‘Snowbird’ matured 5-15 days earlier than the other commercial cultivars. Heirloom cultivars produced taller plants compared to commercial cultivars. The tallest cultivar was ‘Red Fife’ (135 cm) followed by ‘Red Bobs’ (133 cm), and ‘Reward’ (127 cm). Commercial cultivars produced short to medium plants, the shortest being the ‘Strongfield’ (98 cm) accompanied by the heirloom ‘Sounders’ (100 cm). The earliest heirloom cultivar ‘Reward’ produced taller plants (127 cm) while the latest commercial cultivar ‘Strongfield’ produced the shortest (98 cm) plant. Except for ‘Red Fife’, heirloom cultivars produced greater numbers of spikes m-2 compared to commercial cultivars (Table 2.7). The lowest spike density (419 m-2) in ‘Red Fife’ was due low germination rate (as low as 20%). However, the spike density of 419 was achieved as it produced greater number of tillers plant-1.  The commercial cultivar ‘Lillian’ showed similar responses. ‘Red Fife’, a 6-row hulless heirloom cultivar, produced the longest spikes (10.6 cm) followed by ‘Calcutta’ and ‘Pacific Blue Stem’ (9.3 cm) while ‘Red Bobs’ gave the highest 26  number of seed spike-1. However, 2-row heirloom hulled wheat (e.g., Emmer and Enkorn series) produced the shortest spikes with the fewest number of seeds spike-1 resulting in comparatively lower grain yields than 6-row hulless cultivars (Table 2.7). The 6-row heirloom hulless cultivars (e.g., ‘Reward’, ‘Glenn’, ‘Cerebs’, ‘Red Bobs’, and ‘Sounders’) produced grain yields (5.2, 5.1, 4.9, 4.6, and 4.6 t ha-1, respectively) comparable to the commercial cultivars. Despite having a moderate number of seeds spike-1 (39) and comparatively higher 1000 seed weight (44 g), ‘Red Fife’ produced lower yield (4.1 t ha-1) and could be associated with fewer spikes m-2. The heirloom cultivars typically had lower HI as they produced taller plants (i.e., greatest biomass). The cultivar ‘Pacific Blue Stem’ had the lowest yield (2.5 t ha-1) and HI (21%) which may be due to the spikes containing unfilled spikelets with mold developing, perhaps due to the later harvest. Among commercial cultivars, ‘Scarlet’, a 6-row hulless, gave the longest spikes (9.2 cm) with a moderate number of seeds spike-1 (39), the highest 1000 seed weight (48 g) resulting in highest grain yields (5.4 t ha-1) and HI (48.4%). It was followed by ‘Norwell’ with the highest number of seeds spike-1 (42), good 1000 seed weight (45 g), and grain yield (5.3 t ha-1). Heirloom wheat showed greater weight to volume ratios compared to commercial cultivars with ‘Glenn’ and ‘Reward’ displaying the greatest weight to volume ratio (0.85:1). The ratio was lowest in 2-row hulled wheat (e.g., Emmer and Enkorn series) as the hulled (with awn) and longer grains occupied more volume but were lighter in weight. The ratio was highest in the hulless cultivars with smaller sized and more uniform seeds. 27  Overall, the yield from commercial cultivars was greater than the Canadian yield average (~3 t ha-1). This finding is in line with the reports of Halstead (2007) who reported the yield of two different cultivars ‘Reaper’ and ‘Monopol’ as 5.8 t ha-1 and 7.2 t ha-1, respectively, when grown at the UBC Farm. Similar yield responses were reported by Kidwell et al. (2009) in eastern Washington using other cultivars. They found the grain yield averages of ‘Kelse’, ‘WestBred 926’, ‘Tara 2002’, and ‘Hank’ as 5.2, 5.3, 5.4, and 5.7 t ha-1, respectively. In addition, Temple (2009) also reported a yield of 5.5 t ha-1 from ‘Norwell’ when working with spring wheat grown by farmer co-operators in Delta, BC. Barley: Production characteristics of the commercial and heirloom barley cultivars are presented (Table 2.8). Overall, heirloom and commercial cultivars did not differ materially with respect to a number of plant based parameters including plant height, spike length, and seed weight to volume ratio. However, a number of heirloom cultivars displayed greater responses including earliness, number of spikes m-2, grain yield, and seed weight to volume ratio (Table 2.8). A clear difference was observed in maturity times between hulless (e.g., ‘Purple’, ‘Sunshine’, ‘Dolma’, ‘Andie’, Excelsior’, ‘Himalayan’, ‘Jet’, ‘Ethiopian’ and ‘CDC Gainer’) and hulled (e.g., ‘Oxbridge, ‘Westminster’, ‘Decanter’, ‘Copeland’ and ‘Camus’) cultivars with the hulless-types maturing 1-2 weeks earlier than the hulled-types. This was true for both the 2 and 6-row hulless cultivars with 2-row hulless (e.g., ‘Jet’, ‘Ethiopian’ and ‘CDC Gainer’) and 6-row hulless (e.g., ‘Purple’, ‘Sunshine’, ‘Dolma’, ‘Andie’, Excelsior’ and ‘Himalayan’) maturing 1-2 weeks earlier than 2-row hulled-types (e.g., ‘Oxbridge, ‘Westminster’, ‘Decanter’, ‘Copeland’ and ‘Camus’). One exception was the 6-row hulless cultivar ‘Hooded’ that required 100 days to mature. 28  Except for ‘CDC Gainer’ and ‘Copeland’, 2-row cultivars produced the shortest plants (65-80 cm) compared with 6-row cultivars. UK hulled barley ‘Oxbridge’ produced the shortest plants (65 cm) while the Canadian hulless ‘CDC Gainer’ and hulled ‘Copeland’ produced the tallest plants (100 cm). UK spring barleys (e.g., ‘Oxbridge’, ‘Westminster’ and ‘Decanter’) produced greater number of spikes m-2 compared to other commercial cultivars. The fewer spikes in ‘Hooded’ (358 m-2), a 6-row hulless barley, was due to poor germination (30%). The 6-row hulless cultivars (e.g., ‘Burbank’, ‘Sunshine’, ‘Hooded’, ‘Purple’, ‘Dolma’, ‘Andie’, Excelsior’ and ‘Himalayan’) produced greater numbers of seeds spike-1 and seed weight to volume ratios but typically consisted of shorter spikes, lower 1000 seed weight, grain yield and HI than 2-row cultivars. On the other hand, the 2-row hulled cultivars (e.g., ‘Oxbridge, ‘Westminster’, ‘Decanter’, ‘Copeland’ and ‘Camus’), displayed greater 1000 seed weight, yield and HI but consisted of lower weight to volume ratios than the 2-row hulless cultivars (e.g., ‘Jet’, ‘Ethiopian’ and ‘CDC Gainer’). The 2-row UK spring barley ‘Oxbridge’ had the highest yield (6.9 t ha-1) followed by ‘Westminster’ (5.8 t ha-1) and ‘Decanter’ (5.6 t ha-1) while the other commercial barleys yielded slightly more than 5 t ha-1 (Table 2.8). Hulless barleys had the greatest weight to volume ratio (up to 0.86:1) with 6-rowed cultivars showing slightly higher ratios than 2-row hulless cultivars. Black barleys also appeared promising with 2-row ‘Jet’ producing the highest yield (5.5 t ha-1) followed by 6-row hulless ‘Hooded’ (4.2 t ha-1). The cultivars ‘Sunshine’ and ‘Dolma’, 6-row brown barleys, also produced greater yields (4.9 t ha-1) compared to other hulless barleys. 29  Legumes: Production traits of the different legume crops and cultivars are shown (Table 2.9). The heirloom peas ‘Corgi’, ‘De Grace’, ‘Snowbird’, and ‘Golden’ were early maturing (75-80 DAS) with greater shell to seed ratio (up to 1:6.4) but produced relatively lower yields, 1000 seed weights, and seed weight to volume ratios compared to the commercial pea cultivar ‘Reward’. ‘Reward’ produced higher yields although there was significant variation between the sampled plants and the remaining plot (3 t ha-1 vs. 1.2 t ha-1, respectively) due to poor germination affecting plant density. Neither lentil cultivar produced satisfactory results in terms of yield though they had excellent vegetative growth and flowered. However, most of the pods were barren and/or underdeveloped, perhaps due to low temperature. The cultivar ‘Essex’ produced relatively good pods containing white seeds whereas ‘Crimson’ had more pods plant-1 but containing no or only undersized brown seeds. Among fava bean cultivars (Table 2.9), heirloom cultivar ‘Bergeron’ matured earliest (95-100 DAS) producing the shortest plants (63.8 cm), while ‘Crimson Flowered’ matured latest (120-125 DAS). Except for ‘Bergeron’, all other cultivars required at least two harvests at 10 day intervals, with ‘Andy’ and ‘Windsor requiring three. The cultivar ‘Bell’ developed an upright growth habit and produced the highest number of pods plant-1 (7.6) containing relatively small round seeds that gave the highest seed weight to volume ratio (0.81:1) and yield (2.9 t ha-1). Cultivars ‘Andy’, ‘Windsor’ and ‘Crimson Flowered’ produced longer pods than ‘Bell’ (23, 14.6 and 10.3 cm, respectively) containing flat large-sized seeds. As a result, 1000 seed weight was highest in ‘Windsor’ (1512.8 g) followed by ‘Andy’ (1383.6 g). Kidney beans, although requiring a relatively long growing season (approximately 120 days), did well under UBC’s climate (Table 2.9). On an average, cultivars produced ~4 t ha-1. 30  Cultivar ‘Candy’, a vine-type kidney bean, had the longest plants (97.2 cm) followed by ‘Black Turtle’ (89.4 cm). On cultivar ‘Candy’, pods rotted before maturity because they were not trellised and received a significant amount of rain while ripening. However, ‘Black Turtle’ pods did not rot, perhaps due to their shorter more round pods that were held above the soil surface. Cultivar ‘Golden Rocky’, a dwarf bush bean cultivar, matured 20 days earlier than other cultivars producing a relatively good yield (4.2 t ha-1) and the greatest seed weight to volume ratio (0.88:1). Soybean cultivars ‘Black Jet’ and ‘Edamame’ were the latest to mature (130-135 DAS) compared with other legumes (Table 2.9). Plant density was low in ‘Edamame’ (20 m-2) due to poor germination but displayed dwarf bushy growth habit. Cultivar ‘Black Jet’ produced the tallest plants (79.8 cm) with fewer pods plant-1 (24 vs. 27 in ‘Edamame’) and shorter pods (5 vs. 6 cm in ‘Edamame’). However, ‘Black Jet’ had higher yield (3.4 t ha-1 compared to 2 t ha-1 in ‘Edamame’) but most likely due to greater plant density. Cultivar ‘Edamame’ produced large-sized yellow seeds that resulted in greater 1000 seed weight (380.7 g) compared to ‘Black Jet’ (273.8 g). 2.2.2 Management-based parameters Weed pressure: The most common weeds were Common Chickweed (Stellaria media L.), Green Smartweed (Polygonum lapathifolium L.), Prostrate Knotweed (Polygonum aviculare L.), Pigweed (Amaranthus spp.), Crab Grass (Digitaria spp.), Barnyard Grass (Echinochloa crusgalli L.), Black nightshade (Solanum nigrum L.), and Field horsetail (Equisetum arvense L.). Common Chickweed, an excellent colonizer that forms a succulent mat on the soil surface, covered the whole field starting 20 DAS. Pigweed was observed early in the season 31  in wheat and barley plots along with the chickweed. Other weeds gradually infested the plots during mid to late season. Wheat and barley plots, with moderate to good plant density, grew well despite the weed pressure. No weeding/cultivation was done except for hilling the legumes. Disease pressure: The most prevalent diseases encountered at our test site included stripe and stem rusts (Puccinia spp.) and Septoria leaf blotch (Septoria spp.), with most commercial plots showing some infection starting at the end of June and continuing through mid-September. Except for ‘Lillian’ and ‘Snowbird’, commercial wheat cultivars were moderate to highly susceptible to Stripe rust (Table 2.10). Septoria leaf blotch infection was most severe on ‘Strongfield’, 30 DAS. However stripe/stem rust were most severe on ‘Snowstar’ and ‘Scarlet’ followed by ‘Norwell’ and ‘Strongfield’ cultivars. ‘Lillian’ was the most resistant commercial wheat cultivar against these diseases followed by ‘Snowbird’. Except for ‘Pacific Blue Stem’, heirloom wheat cultivars displayed intermediate to high disease resistance compared with commercial cultivars (Table 2.10). The 2-row hulled wheat (e.g., Emmer and Einkorn series) were among the most highly resistance cultivars followed by the 6-row heirloom cultivars. Heirloom 6-row wheat cultivars ‘Red Bobs’, ‘Red Fife’, ‘Calcutta’ and ‘Red Wheat’ displayed the highest overall performance rating, 30 DAS, with ‘Red Fife’ producing dark green leaves with the highest chlorophyll concentration index (18.4 and 16.1 in flag and 3rd leaves, respectively). However, the heirloom wheat e.g.,  ‘Red Wheat’ ‘Cerebs’, ‘Black Bearded’, ‘Red Bobs’ and ‘Calcutta’ displayed high plant lodging percentage compared to the commercial cultivars (Table 2.10), and could be associated 32  with the plant height as well as the location of the trial plots (the border plots in the south-west direction were observed with increased lodging due to wind). Among the barley cultivars, UK spring barleys (‘Westminster’, ‘Decanter’ and ‘Oxbridge’) displayed the least disease severity compared with heirloom and other commercial cultivars (Table 2.11). Hulless cultivars ‘Sunshine’, ‘Andie’ and ‘Ethiopian’ were moderately susceptible to stripe rust disease whereas the majority of cultivars including, ‘CDC Gainer’, ‘Purple’, ‘Hooded’, ‘Jet’, ‘Dolma’, ‘Excelsior’, ‘Himalayan’ and ‘Burbank’ showed intermediate resistance. Commercial cultivars (e.g., ‘McGwire’, ‘Copeland’ and ‘Camus’) were moderate to highly susceptible to stripe rust disease. The barley cultivars showed variable response with respect to lodging intensity. In general, 6-row cultivars displayed greater lodging compared to 2-row cultivars (Table 2.11). Heirloom cultivars ‘Excelsior’ and ‘Himalayan’, both 6-rowed and hulless cultivars, despite of having dwarf plants, showed complete lodging (>80%) whereas ‘Purple’, ‘Dolma’, ‘CDC Gainer’ and ‘Burbank’ displayed only partial lodging (40-60%).  The 2-row UK spring barleys (‘Westminster’, ‘Decanter’, ‘Oxbridge’) and black seeded heirloom ‘Jet’ showed no lodging. Besides the activity of six-spotted lady bird beetles, no insect damage was observed. Root growth and nodulation: Heavy nodulation and deep penetrating root systems are desirable traits for sustainable organic farming as they have the genetic potential to fix atmospheric nitrogen and acquire water from deep in the soil profile. Through qualitative assessment, legume cultivars differed in several parameters including degree of nodulation, total root mass, and depth of rooting. Kidney bean (‘Candy’) and fava bean 33  (‘Andy’, ‘Bell’ and ‘Windsor’) cultivars displayed good nodulation during the later stages of growth (flowering to pod setting), indicating good potential for N2 fixation. In these cultivars, 10 or more pink-red nodules were observed in the crown-root zone and elsewhere on the root system. Cultivars ‘Reward’ (pea), ‘Crimson’ and ‘Essex’ (lentil), on the other hand, produced nodule-like structures approximately 20 DAS but disappeared as the plants matured. The reason behind no or few numbers of nodules could be because no pre-plant inoculation was used and these crops were planted in new sites. 2.2.3 Protein content Grain protein concentration (GPC) has a major impact on the end-use quality of products made from hard wheat and barley. Therefore, this trait is typically a high priority in wheat and barley improvement programs aimed at improving bread-making or malting qualities. High protein contents are required for wheat used for baking pan breads and blending, typically >13% for Canadian Western Red Spring wheat and 11-13% for UK wheat, with lower levels used for other types of bread, noodles or other food uses. In barley, low protein levels (generally below about 11%) are required for malting, brewing and distilling, with higher levels resulting in reduced quality (Shewry, 2006). Wibberley (1989), on the other hand, reported the minimum required protein content for bread wheat as 11% whereas for malting barley, it is desirable to be below 9.4%. A clear difference was observed between commercial and heirloom wheat cultivars for protein content (Table 2.12). Overall, heirloom cultivars showed higher protein contents with the highest level in ‘Einkorn’ (16.2%) followed by ‘Emmer- 2’ (15.4%) and ‘Reward’ (15%). The higher protein level in the heirloom cultivars demonstrates their suitability for 34  baking and blending purpose compared to the commercial cultivars. However, the highest yielding commercial cultivar, ‘Scarlet’, contained the lowest protein content (9.2%). Except for the heirloom cultivars, no significant difference in protein content was observed between the UK spring barleys (i.e., ‘Oxbridge’, ‘Westminster’, and ‘Decanter’) and other commercial cultivars (Table 2.12). Commercial cultivars had lower protein levels (8-9.6%), most appropriate for malting purposes. The heirloom black barley cultivar ‘Jet’ had the highest protein content (13.7%) followed by ‘Dolma’ (13.6%) and ‘Purple’ (12.8%), a level desirable for livestock feed. Variation in protein levels was observed in wheat and barley cultivars when grown under different environments and management practices. Halstead (2007) reported the protein content in ‘Red Fife’ as 9%, 1.4% less than observed in this experiment. Similarly, Temple (2009) observed higher protein levels in ‘Norwell’ (13.1%) and ‘Scarlet’ (11.5%) when grown under different management practices in Delta, BC. Some researchers have observed that the grain protein is higher in conventional systems than in organic systems (Poutala et al., 1993; Starling and Richards, 1993). In contrast, Shier et al. (1984) and Ryan et al. (2004) reported no differences in grain protein levels of spring wheat grown in organic and conventional cropping systems, which they attributed to adequate soil nutrient levels in both systems. 2.3 Conclusions This trial assessed performance of heirloom and commercial cultivars of wheat, barley, and several legume crops and cultivars. Above all, the tested wheat and barley cultivars 35  performed well under organic management systems at the UBC Farm. The following conclusions have been made and will be used to structure future trials:  There was significant variation in yield among both heirloom wheat (2.5 to 5.2 t ha-1) and barley (2.9 to 6.9 t ha-1) cultivars. The heirloom wheats ‘Reward’, ‘Glenn’, ‘Cerebs’, ‘Sounders’ and ‘Red Bobs’ produced comparable grain yields (~5 t ha-1) to the commercial cultivars with greater resistance to stripe rust disease. Hulled wheat cultivars (e.g., Emmer and Einkorn Series) displayed high resistance to stripe rust disease. Similarly, 2-row UK spring barleys (e.g., ‘Oxbridge’, ‘Westminster’ and ‘Decanter’) and heirloom cultivar (e.g., ‘Jet’) displayed higher yield and resistance to disease compared to other commercial and the 6-row heirloom cultivars. Furthermore, hulled barleys showed strong resistance to stripe rust disease. Therefore, this trial has demonstrated the potential value of heirloom wheat and barley cultivars in terms of yield and disease resistance.  Heirloom wheat cultivars showed higher protein levels most desirable for baking and blending purposes as compared to the commercial cultivars, with ‘Einkorn’ displaying the highest level (16.2%). The highest yielding commercial wheat ‘Scarlet’ displayed the lowest protein content (9.2%). The heirloom black-seeded barleys contained higher protein levels most suitable for animal feed. No significant difference was observed between commercial and UK spring barleys. The UK spring barleys contained lower protein levels most suitable for malting purposes.  Among the commercial cultivars, ‘Scarlet’ and ‘Norwell’ appeared to be best in terms of grain yield and yield related parameters. Similarly, ‘Camus’, ‘McGwire’, and 36  ‘Copeland’ barleys showed only marginal yield differences with moderate to high susceptibility to stripe rust.  Most of the barley cultivars matured 2-4 weeks earlier than the wheat cultivars. The coincidence in harvesting time (80-90 DAS) showed that barley can be successfully integrated with pea and lentil for combined harvesting. Hulless barley appeared to be best suited to early pea (‘Snowbird, ‘Corgi’, ‘De Grace’ and ‘Golden’) and lentil (‘Crimson’, and ‘Essex’) while hulled barley could be integrated with mid to late cultivars (e.g., ‘Reward’ pea). Early wheat cultivars (e.g., ‘Sounders’, ‘Reward’, ‘Snowstar’, and ‘Snowbird’) showed potential with late peas whereas late wheat appeared to be best suited to fava beans, kidney beans, and soybeans. However, some fava bean cultivar may require multiple harvests over time.  The significant variation among heirloom cultivars for plant based parameters, disease resistance and protein content suggests the possibility of crop improvement through an accelerated breeding program. Therefore, heirloom cultivars should be considered for inclusion in cultivar-improvement programs.  As a seed crop, soybean, fava bean and kidney bean requires early planting (i.e., late April to early May). Also, lentil appeared to be sensitive to the low temperatures experienced during the end of the season as they produced excellent vegetative growth but contained no or only underdeveloped brown seeds making them inappropriate for late-spring planting.  37  Table 2.1 Meteorological data† during 2010 cropping season at UBC Farm, Vancouver, Canada. Month Mean Air Temperature (°C) Mean Soil Temperature (°C) at different depth Relative Humidity (%) Solar Irradiance1  (W m-2) Total Rainfall (mm) Day Night 24hours 10-cm 20-cm Day Night 24hours Day Night 24hours Day Night 24hours June 15.1 (21) 12.8 13.9 18.2 18.6 18.4 17.6 18.1 17.9 76.3 83.2 79.7 569 (1419) 57.4 July 18.6 (28.9) 15.8 17.4 20.3 21 20.6 19.6 20.3 19.9 69.7 77.7 73.2 779  (1424) 6.6 August 18.9 (30) 16.1 17.6 19 19.5 19.3 18.7 19.3 19 70.1 78.2 73.9 603 (1345) 61.2 September 15.7 (22.6) 13.8 14.7 17.3 17.7 17.5 17.3 17.7 17.5 79.7 87.9 83.8 411 (1188) 120.6 Average 17.1 14.6 15.9 18.7 19.2 18.9 18.3 18.9 18.6 73.9 81.8 77.7 590.3 61.5 †Source: UBC Climate Station adjacent to Totem Park, 1 km northwest of UBC farm; and 1Daytime averages Figures in parenthesis under mean air temperature column indicate the highest temperature in respective months Figures in parenthesis under solar energy column indicate the highest intensity of solar radiation on the earth surface in respective months   38  Table 2.2 Soil properties† at site (prior to sowing i.e., spring 2010) at UBC Farm, Vancouver, Canada. Sample # pH  Buffered pH Total C (%) EC (mmhos/cm) Total N (%) P (ppm) K (ppm) Ca (ppm) Mg (ppm) Cu (ppm) Zn (ppm) Fe (ppm) Mn (ppm) B (ppm) 1 5.6 6.6 6.8 0.88 0.29 178 240 3050 160 0.6 15 25 45 0.5 2 5.4 6.5 6.6 1.28 0.32 130 280 3100 175 0.6 12 30 38 0.7 3 5.6 6.7 6.4 0.98 0.30 162 225 2600 175 0.6 13 30 35 0.7 4 5.5 6.5 5.5 1.20 0.30 108 200 2100 155 0.6 9.3 25 24 0.5 Average 5.5 6.5 6.32 1.085 0.302 144.5 236.3 2713 166 0.6 12.3 27.5 35.5 0.6 †Analyses conducted by Pacific Soil Analysis Inc., Richmond, Canada   39  Table 2.3 Small grain cultivars used for performance evaluation during 2010 spring season at UBC Farm, Vancouver, Canada. Crop Cultivar Type/ Characteristics 100 Seed Weight (g) Seeding Density (m2)  Seed Rate (g m-2) Source Wheat Commercial Cultivars Scarlet Hard red spring wheat, 6-row, awned 4.2 350 (12cm- row) 15 AAFC1, Canada Lillian  Canada western red spring wheat, 6-row, awnless 3.7 350 (12cm- row) 13 AAFC1, Canada Snowstar  Hard white spring wheat, 6-row, awnless 2.9 350 (12cm- row) 10 AAFC1, Canada Norwell  Hard red spring wheat, 6-row, awned 4.0 350 (12cm- row) 14 BC, Canada Strongfield  Canadian Western Amber Durum, 6-row, awned 4.6 350 (12cm- row) 16 BC, Canada Snowbird Hard white spring wheat, 6-row, awnless 3.4 350 (12cm- row) 12 BC, Canada Heirloom Cultivars Red Fife Hard red spring wheat, 6-row, awnless 3.8 350 (12cm- row) 14 BC, Canada Glenn  Hard red spring wheat, 6-row, awned 2.5 350 (12cm- row) 9 Maine, USA Red Wheat  6-row, awned, from the hills of Sicily, Italy 3.4 350 (12cm- row) 12 BC, Canada Red Bobs- 222  Hard red spring wheat, 6-row, awnless 3 350 (12cm- row) 11 BC, Canada Calcutta  Hard red spring wheat, 6-row, awned 2.8 350 (12cm- row) 10 BC, Canada Cerebs  Hard red spring wheat, 6-row, awned 3.4 350 (12cm- row) 12 BC, Canada Sounders  Hard red spring wheat, 6-row, awnless 2.3 350 (12cm- row) 8.5 BC, Canada Emmer- 1  Primitive, 2-row, flat and long spike, hulled, awned 9.1 350 (12cm- row) 32 BC, Canada Emmer- 2  Primitive, 2-row, flat but short spike, hulled, awned 6.5 350 (12cm- row) 23 BC, Canada Einkorn Primitive, 2-row, hulled, flat black spike, awned 3 350 (12cm- row) 11 BC, Canada Black Bearded  Tall, beautiful large head, 6-row, awned 4.6 350 (12cm- row) 16.5 Minnesota, USA 40  Crop Cultivar Type/ Characteristics 100 Seed Weight (g) Seeding Density (m2)  Seed Rate (g m-2) Source Reward  Hard red, Canadian heirloom, 6-row, awnless 4.2 350 (12cm- row) 15 Washington, USA Pacific Blue Stem  White spring, 6-row, awnless 5.3 350 (12cm- row) 19 Oregon, USA Barley Commercial  Cultivars Copeland  2-row, awned, hulled, malting type 4.5 350 (12cm- row) 16 BC, Canada McGwire  2-row, awned, hulless, malting type 4.2 350 (12cm- row) 15 BC, Canada Camus  2 row, awned and hulled 4.9 350 (12cm- row) 17 AAFC1, Canada Oxbridge  2-row, awned, hulled, UK spring barley 4.7 350 (12cm- row) 17 BC, Canada Westminster  2-row, awned, hulled, UK spring barley 5.4 350 (12cm- row) 19 BC, Canada Decanter  2-row, awned, hulled, UK spring barley 4.5 350 (12cm- row) 16 BC, Canada CDC Gainer  2-row, awned, Canadian hulless, malting type 4.4 350 (12cm- row) 16 BC, Canada Sunshine 6-row, awned, early, hulless barley 3.4 350 (12cm- row) 12 Alaska, USA   Heirloom Cultivars Purple (Black) 6-row, awned, hulless, brown-seeded barley 4.2 350 (12cm- row) 15 BC, Canada Hooded (Black) 6-row, awnless, hulless, brown-seeded barley 3.3 350 (12cm- row) 12 BC, Canada Jet (Black) 2-row, awned, hulless, black-seeded barley 3.7 350 (12cm- row) 13 Idaho, USA Dolma 6-row, awned, hulless, easy threshing 3.3 350 (12cm- row) 12 Idaho, USA Andie  6-row, awnless, hulless 3.2 350 (12cm- row) 12 California, USA Ethiopian Hulless 2-row, awned, hulless, heat resistant 4.2 350 (12cm- row) 15 California, USA Excelsior (Black) 6-row, awned, hulless, brown-seeded barley 4.3 350 (12cm- row) 15 BC, Canada Himalayan  6-row, awned, hulless 3.9 350 (12cm- row) 14 BC, Canada Burbank (Brown) 6-row, awned, hulless, easy threshing 2.4 350 (12cm- row) 9 Maine, USA 1Agriculture and Agri-Food Canada 41  Table 2.4 Legume crops and cultivars used for evaluation during 2010 cropping season at UBC Farm, Vancouver, Canada. Crop Name of Cultivar Cultivar Characteristics Sowing Density  (seed m-2) Sourcing Area Pea  Reward Powdery mildew resistance field pea 66 (30x5 cm2) AAFC1, Canada  Snowbird  Very early, dwarf plants, entire pods are edible 66 (30x5 cm2) Wisconsin, USA  Corgi  Small round dark green pod, very sweet and prolific 66 (30x5 cm2) California, USA  Golden  Edible yellow pods, purple flowers, good bearer 66 (30x5 cm2) Maine, USA  De Grace  Early, no disease, compact, better than modern sugar 66 (30x5 cm2) Connecticut, USA Fava bean  Crimson Flowered  Short red edible flower, excellent in salads, smaller bushes, bright green seeds 33 (30x10 cm2) Washington, USA  Bergeron  Early maturity, one-picking, dwarf plant and short pod 33 (30x10 cm2) Vermont, USA  Windsor  Bush type, classic heir-loom variety of flat bean 33 (30x10 cm2) Maine, USA  Bell  Short pod, small and roundish seed 33 (30x10 cm2) BC, Canada  Andy  Longer growing season, tall plant and longest pod 33 (30x10 cm2) BC, Canada Broad bean/Kidney bean  Artec Red Kidney  Dry kidney bean, bush-type, dark amber seed 33 (30x10 cm2) BC, Canada  Red Kidney  Dry kidney bean, bush-type, red seed 33 (30x10 cm2) BC, Canada  Black Turtle  Dry bush bean, small and black seed 33 (30x10 cm2) BC, Canada  Candy  Dry kidney bean, vine-type, colored seed with red spots  33 (30x10 cm2) BC, Canada  Golden Rocky  Dry bush bean, black seeded with white eye 33 (30x10 cm2) BC, Canada 42  Crop Name of Cultivar Cultivar Characteristics Sowing Density  (seed m-2) Sourcing Area Soybean  Black Jet  Tall plant, black seed, grain type 33 (30x10 cm2) BC, Canada  Edamame  Dwarf plant, yellow seed, vegetable type 33 (30x10 cm2) BC, Canada Lentil  Crimson Brown lentils with red cotyledons 200 (20x2.5 cm2) AAFC1, Canada  Essex Green lentil with yellow cotyledons 200 (20x2.5 cm2) ARS2, Pullman, USA 1Agriculture and Agri-Food Canada; and 2Agricultural Research Service/USDA   43  Table 2.5 Disease assessment key adopted during 2010 spring trial at UBC Farm, Vancouver, Canada. Score Description 1 Highly resistant: no visible symptoms 2 Highly resistant: occasional symptoms of infection including necrotic flecks and small stripes without sporulation 3 Resistant: symptoms evident and may include stripes with necrosis and chlorosis, limited sporulation, and affected leaf area up to 15%  4 Moderately resistant: sporulating areas arranged in stripes, some chlorosis and necrosis, and affected leaf area up to 30% 5 Intermediate: Sporulating areas arranged in stripes with some chlorosis, and affected leaf area up to 50% 6 Moderately susceptible: sporulating stripes and affected leaf area up to 70% 7 Moderately susceptible to susceptible: sporulating stripes merging into broader leaf areas supporting symptoms, chlorosis and necrosis evident, leaf area affected up to 90% 8 Susceptible: sporulation across the whole leaf surface with no stripes but with evidence of chlorotic areas 9 Highly susceptible: abundant sporulation across the whole leaf area with no evidence of stripes 10 Dead leaf   44  Table 2.6 Rating key for nodule assessment (after Corbin et al., 1977) in legume during 2010 cropping season at UBC Farm, Vancouver, Canada. Field Assessment Key Mean Score and Indication Score Visual Observation Mean Nodule Score Indication 0 No nodulation 0 No nodulation and no N2 fixation 1 <5 in the crown-root zone (regarded as the region up to 5 cm below the first lateral roots) with no nodules on elsewhere on the root system 0-1 Very poor nodulation and probably little or no N2 fixation 2 5-10 in the crown-root zone with <5 nodules on elsewhere on the root system 1-2 Poor nodulation and probably little N2 fixation 3 >10 in the crown-root zone with <5 nodules on elsewhere on the root system 2-3 Fair nodulation; N2 fixation may not be sufficient to supply the N demand of the crop 4 >10 in the crown-root zone with 5-10 nodules on elsewhere on the root system 3-4 Good nodulation; good potential for N2 fixation 5 >10 in the crown-root zone with >10 nodules on elsewhere on the root system 4-5 Excellent nodulation; excellent potential for N2 fixation 45  Table 2.7 Response of commercial wheat cultivars to organic production systems during 2010 cropping season at UBC Farm, Vancouver, Canada. Type Cultivar Days to Harvest Harvest Height  (cm) No. of Spike m-2 Spike Length (cm) Seed Spike-1 1000 Seed Weight  (g) Grain Yield  (g m-2) Grain Yield1 (t ha-1) HI2 (%) W:V3 Commercial Cultivars Lillian 105 (100-105) 104 461 7.5 33.3 41.7 440 4.4 45.9 0.82 Scarlet 105 (105-110) 103 500 9.2 38.7 48.0 544 5.4 48.4 0.83 Norwell 105 (105-110) 114 588 8.2 42.0 44.7 525 5.3 42.7 0.84 Snowstar 100 (95-100) 103 726 6.9 34.0 32.7 472 4.7 45.5 0.81 Strongfield 110 (105-110) 98 426 6.0 36.7 42.7 500 5.0 46.1 0.83 Snowbird 100 (95-100) 122 655 6.2 34.0 39.5 477 4.8 43.2 0.82 Heirloom Cultivars Red Fife 125 (120-125) 135 419 10.6 38.7 43.7 407 4.1 37.4 0.81 Glenn 110 (105-110) 109 602 7.3 38.3 40.0 505 5.1 42.4 0.85 Red Wheat 100 (100-105) 109 574 6.7 27.3 40.5 361 3.6 30.5 0.82 Red Bobs 105 (100-105) 133 704 9.1 50.0 37.7 462 4.6 32.5 0.80 Calcutta 105 (105-110) 114 722 9.3 31.7 34.4 420 4.2 31.9 0.80 Cerebs 105 (105-110) 122 588 8.5 29.3 34.7 488 4.9 41.9 0.78 Sounders 95 (95-100) 100 712 7.3 31.3 38.5 458 4.6 36.5 0.83 46  Type Cultivar Days to Harvest Harvest Height  (cm) No. of Spike m-2 Spike Length (cm) Seed Spike-1 1000 Seed Weight  (g) Grain Yield  (g m-2) Grain Yield1 (t ha-1) HI2 (%) W:V3 Emmer- 1 110 (110-115) 105 722 5.5 29.0 40.6 377 3.8 37.7 0.65 Emmer- 2 105 (105-110) 108 628 5.6 21.3 42.4 389 3.9 43.7 0.67 Einkorn 125 (120-125) 126 544 7.2 36.3 26.6 281 2.8 36.1 0.49 Black Bearded 105 (105-110) 116 702 6.8 41.0 39.3 448 4.5 31.0 0.75 Reward 95 (95-100) 127 826 7.2 27.7 41.0 520 5.2 32.5 0.85 Pacific Blue Stem 135 (135-140) 118 668 9.3 24.0 32.0 252 2.5 21.2 0.74 SEM (±)  3.67 5.23 14.5 1.02 3.99 2.82 32 0.31 2.66 0.04 LSD0.05  7.35 10.5 29 2.05 8 5.65 65 0.65 5.32 0.08 1Calculated at 12.5% moisture; 2Harvest Index; 3 Seed weight to volume ratio; SEM = Standard Error of the Mean; and LSD = Least Significant Difference   47  Table 2.8 Performance of commercial and heirloom barley cultivars to organic production during 2010 cropping season at UBC Farm, Vancouver, Canada. Type Cultivar Days to  Harvest Harvest Height (cm) No. of Spike m-2 Spike Length (cm) Seed Spike-1 1000 Seed Weight  (g) Grain Yield (g m-2) Grain Yield1 (t ha-1) HI2  (%) W:V3 Commercial Cultivars Copeland 95 (90-95) 100 565 7.6 27.7 53.0 510 5.1 45.5 0.66 McGwire 90 (90-95) 73 594 9.0 27.0 40.1 520 5.2 46.9 0.83 Camus 95 (90-95) 81 510 7.8 26.7 54.0 498 5.0 53.8 0.68 Oxbridge 95 (90-95) 65 766 7.9 21.3 55.3 690 6.9 53.8 0.66 Westminster 100 (100-105) 80 804 7.8 23.3 57.7 580 5.8 52.9 0.71 Decanter 100 (100-105) 71 804 8.2 26.0 57.9 560 5.6 57.8 0.68 CDC Gainer 90 (90-95) 100 880 8.5 22.0 38.5 507 5.1 39.0 0.79 Sunshine 85 (80-85) 92 668 6.4 50.0 31.1 496 4.9 42.0 0.79 Heirloom Cultivars Purple (Black) 85 (80-85) 87 496 6.0 38.0 46.9 388 3.9 45.2 0.86 Hooded (Black) 100 (100-105) 92 358 7.6 46.0 38.3 423 4.2 48.3 0.79 Jet (Black) 80 (80-85) 75 736 6.9 15.7 48.5 552 5.5 29.2 0.73 Dolma 80 (75-80) 78 656 5.9 34.3 36.3 488 4.9 41.7 0.78 Andie  80 (75-80) 92 658 5.5 36.0 34.3 420 4.2 37.7 0.81 Ethiopian Hulless 85 (80-85) 85 576 7.1 15.7 49.8 444 4.4 34.4 0.77 Excelsior (Black) 90 (90-95) 82 532 5.4 33.0 42.9 297 2.9 43.1 0.83 Himalayan 80 (80-85) 89 648 6.5 36.7 39.3 420 4.2 41.8 0.77 Burbank 95 (90-95) 102 500 5.8 52.0 38.7 450 4.5 32.1 0.81 48  Type Cultivar Days to  Harvest Harvest Height (cm) No. of Spike m-2 Spike Length (cm) Seed Spike-1 1000 Seed Weight  (g) Grain Yield (g m-2) Grain Yield1 (t ha-1) HI2  (%) W:V3 SEM (±)  3.49 4.18 12.5 0.85 3.45 3.22 32 0.29 3.12 0.05 LSD0.05  7.0 8.36 25 1.7 6.9 6.45 65 0.6 6.25 0.1 1Calculated at 12.5% moisture; 2Harvest Index; 3Seed weight to volume ratio; SEM = Standard Error of the Mean; and LSD = Least Significant Difference   49  Table 2.9 Performance of legume cultivars to the organic production during 2010 cropping season at UBC Farm, Vancouver, Canada. Crop Cultivar Days to Seed Harvest Harvest Height (cm) No. of Plant m-2 No. of Pod Plant-1 Pod Length (cm) No. of Seed Pod-1 Seed Yield (g plot-1) Grain Yield1  (t ha-1) 1000 Seed Weight (g) Seed to Shell Ratio W:V2 Pea  Reward* 90 (85-90) 95 46 3.8 5.6 5.3 298 3.0  207 3.7 0.88  Snowbird 80 (75-80) - - - - - 104 1.0 143 5.2 0.81  Corgi 80 (75-80) - - - - - 92 0.9 168 4.6 0.73  Golden 80 (80-85) - - - - - 166 1.7 177 6.4 0.79  De Grace 80 (75-80) - - - - - 89 0.9 128 3.7 0.80 SEM (±)  3.59 - - - - - 14.3 0.14 8.54 0.21 0.06 LSD0.05  7.2 - - - - - 28.6 0.29 17.1 0.42 0.13 Fava bean  Crimson Flowered 125 (120-125) 106 32 5.6 10.3 3.2 265 2.6 1090 2.6 0.65  Bergeron 95 (95-100) 64 28 4.0 7.0 3.2 251 2.5 718 2.3 0.74  Windsor 115 (110-120) 100 24 7.6 14.6 4.2 171 1.7 1513 2.4 0.61  Bell 110 (110-120) 100 32 7.6 7.7 3.8 292 2.9 533 2.6 0.81  Andy 115 (110-120) 123 28 6.8 23.0 5.6 279 2.8 1384 1.8 0.69 SEM (±)  4.25 7.36 1.5 1.25 1.31 0.72 18.65 0.19 15.75 0.25 0.06 LSD0.05  8.5 14.7 3.0 2.5 2.62 1.45 37.3 0.38 31.5 0.5 0.12 50  Crop Cultivar Days to Seed Harvest Harvest Height (cm) No. of Plant m-2 No. of Pod Plant-1 Pod Length (cm) No. of Seed Pod-1 Seed Yield (g plot-1) Grain Yield1  (t ha-1) 1000 Seed Weight (g) Seed to Shell Ratio W:V2 Broad bean/Kidney bean  Artec Red Kidney 120 (120-125) 58 32 8.0 16.2 4.8 425 4.3 737 2.3 0.79  Red Kidney 110 (110-115) 51 32 8.4 12.5 3.6 483 4.8 631 2.7 0.84  Candy 120 (120-125) 97 30 11.2 14.8 3.0 388 3.9 821 2.1 0.77  Black Turtle 110 (110-115) 89 32 17.2 8.6 6.2 418 4.2 171 3.2 0.83  Golden Rocky 100 (100-105) 25 24 16.0 12.0 3.8 423 4.2 273 3.0 0.88 SEM (±)  3.79 5.43 1.23 1.51 1.55 0.84 21.42 0.22 17.53 0.18 0.05 LSD0.05  7.6 10.8 2.45 3.02 3.10 1.68 42.8 0.43 35.1 0.36 0.1 Soybean  Black Jet 130 (130-135) 80 32 24.4 5.1 2.0 345 3.4 274 - 0.72  Edamame 130 (130-135) 41 20 27.4 6.1 2.4 204 2.0 381 - 0.71 Lentil  Crimson 80 (80-85) 40 160 23.4 1 1.6 77 0.8 34 2.9 0.81  Essex 85 (80-85) 44 188 16.4 1.2 1.8 98 1.0 41 2.3 0.85 1Calculated at 12.5% moisture; 2Seed weight to volume ratio; * Commercial pea cultivar; SEM = Standard Error of the Mean; and LSD = Least Significant Difference 51  Table 2.10 Performance of commercial and heirloom wheat cultivars during 2010 cropping season at UBC Farm, Vancouver, Canada. Type Cultivar Chlorophyll Concentration  Index (71 mm2), 30 DAS Performance Assessment/rating*,  30 Days after Seeding Rating, 70 DAS Remarks Flag Leaf 3rd Leaf Greenness Disease1 Pests Overall Disease2 Lodging (%) Commercial Lillian 14.83 12.75 8 2 1 8 2 0 Poor germination but good tillering (up to 6/plant), no disease Scarlet 16.98 11.55 8 2 1 9 8 0 Good stand, vigorous but diseased Norwell 15.25 16.55 8 2 1 9 7 0 Good stand, vigorous but diseased Snowstar 14.03 14.23 8 2 1 8 8 0 Good stand, vigorous but diseased Strongfield 17.50 11.15 7 6 1 6 7 0 Septoria Leaf Blotch Snowbird 13.22 17.17 8 2 1 9 4 10 Good stand, low disease Heirloom Red Fife 18.45 16.10 9 2 1 9 4 20 Poor germination but good tillering (up to 6/plant), low disease Glenn - - 9 4 1 8 4 0  Red Wheat - - 9 1 1 9 4 90 Lodging: Partial 40, complete 60% Red Bobs - - 9 1 1 10 5 50 Partial lodging Calcutta - - 9 1 1 9 5 40 Partial lodging Cerebs - - 8 1 1 8 5 60 Lodging: Partial 40, complete 60% Sounders - - 8 1 1 8 5 0  Emmer- 1 - - 8 1 1 8 2 60 Partial lodging 52  Type Cultivar Chlorophyll Concentration  Index (71 mm2), 30 DAS Performance Assessment/rating*,  30 Days after Seeding Rating, 70 DAS Remarks Flag Leaf 3rd Leaf Greenness Disease1 Pests Overall Disease2 Lodging (%) Emmer- 2 - - 8 1 1 8 4 0  Einkorn - - 8 1 1 8 1 0  Black Bearded - - 8 1 1 8 5 20 Complete lodging Reward - - 8 1 1 8 4 0  Pacific Blue Stem - - 8 1 1 8 8 0  *Rated as 1-10, 1 being the lowest and 10 highest; 1Assessment for Septoria leaf blotch and scald; 2Assessment for stripe rust; and DAS = Days after Seeding   53  Table 2.11 Performance of commercial and heirloom barley cultivars during 2010 cropping season at UBC Farm, Vancouver. Type Cultivar Chlorophyll Concentration Index  (71 mm2), 30 Days after Seeding Performance Assessment/rating*,  30 Days after Seeding Rating,  70 Days after Seeding Remarks Flag Leaf 3rd Leaf Greenness Disease1 Pests Overall Disease2 Lodging (%) Commercial  Cultivars Copeland 15.60 13.87 6 4 1 8 7 20 Disease susceptible McGwire 15.55 14.03 6 4 1 7 8 0 Disease susceptible Camus 15.97 18.00 8 2 1 8 7 20 Disease susceptible Oxbridge - - 8 1 1 9 4 0  Westminster - - 8 1 1 9 2 0  Decanter - - 8 1 1 9 2 0  CDC Gainer - - 8 1 1 8 5 40 Partial lodging Sunshine - - 8 1 1 8 7 0  Heirloom Cultivars Purple - - 8 1 1 8 5 60 Partial lodging Hooded - - 8 1 1 8 5 0  Jet - - 7 1 1 8 5 0  Dolma - - 8 1 1 9 5 40 Partial lodging Andie - - 8 1 1 9 6 0  Ethiopian Hulless - - 6 1 1 7 7 0  Excelsior - - 8 1 1 7 5 90 Complete lodging 90% Himalayan - - 8 1 1 9 5 80 Complete lodging 80% Burbank - - 8 1 1 8 5 60 Partial lodging *Rated as 1-10, 1 being the lowest and 10 highest; 1Assessment for Septoria leaf blotch and scald; and 2Assessment for stripe rust 54  Table 2.12 Protein content of wheat and barley cultivars grown under organic production systems during 2010 cropping season at UBC Farm, Vancouver, Canada. Type Cultivar Nitrogen  (%) Protein (%) End Uses Type Cultivar Nitrogen  (%) Protein  (%) End Uses WHEAT BARLEY Commercial Cultivars Lillian 2.01 11.5 Baking/bread type Commercial Cultivars  Copeland 1.38 8.0 Malting type Scarlet 1.62 9.2 Cake/pastry/malting McGwire 1.49 8.6 Malting type Norwell 1.81 10.3 Cake/pastry/noodles Camus 1.66 9.6 Malt/feed Snowstar 1.74 9.9 Cake/pastry Oxbridge 1.39 8.1 Malting type Strongfield 2.01 11.4 Baking/bread type Westminster 1.57 9.1 Malting type Snowbird 2.08 11.9 Baking/bread type Decanter 1.54 8.9 Malting type Heirloom  Cultivars Red Fife 1.82 10.4 Noodles/pastry/cake CDC Gainer 1.37 7.9 Malting type Glenn 2.17 12.4 Baking/bread type Sunshine 1.62 9.4 Malt/feed Red Wheat 2.49 14.2 Baking/bread type Heirloom  Cultivars Purple 2.20 12.8 Feed type Red Bobs 2.32 13.2 Baking/bread type Hooded 2.31 13.4 Feed type Calcutta 2.61 14.9 Baking/bread type Jet 2.36 13.7 Feed type Cerebs 2.10 12.0 Baking/bread type Dolma 2.35 13.6 Feed type Sounders 2.04 11.6 Baking/bread type Andie 2.11 12.3 Feed type Emmer- 1 2.35 13.4 Baking/bread type Ethiopian Hulless 2.24 13.0 Feed type Emmer- 2 2.69 15.4 Baking/bread type Excelsior 2.01 11.7 Feed type Einkorn 2.85 16.2 Baking/bread type Himalayan 2.05 11.9 Feed type Black Bearded 2.60 14.8 Baking/bread type Burbank 2.25 13.1 Feed type 55  Type Cultivar Nitrogen  (%) Protein (%) End Uses Type Cultivar Nitrogen  (%) Protein  (%) End Uses Reward 2.64 15.0 Baking/bread type  Pacific Blue Stem 1.93 11.0 Baking/bread type SEM (±)  0.45  SEM (±)  0.34  LSD0.05  0.91  LSD0.05  0.69  SEM = Standard Error of the Mean; and LSD = Least Significant Difference  56           Figure 2.1 Disease assessment score and severity of leaf damage in wheat and barley. Please refer to Table 2.5 for details.   57  CHAPTER 3: WHEAT AND BARLEY ROOT ARCHITECTURE  A version of this chapter has been published as Chapagain, T., L. Super and A. Riseman (2014), Root Architecture Variation in Wheat and Barley Cultivars. American Journal of Experimental Agriculture 4 (7): 849-856. This chapter presents major activities and outcomes of root architecture experiment that assessed heirloom and commercial cultivars of wheat and barley to improve our understanding of the variation in small grain root architecture, and to see their potential for improved nutrient uptake and drought tolerance. This study also compared laboratory based root architecture measures with 2010-cultivar field performance data. 3.1 Materials and Methods 3.1.1 Cultivar selection Heirloom and commercial cultivars of hard red spring wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) that performed well (i.e., high yield, protein content, and disease resistance) in cultivar trials (Chapagain and Riseman, 2012) were selected for root architecture experiments. These included five wheat cultivars (commercial cvs. ‘Scarlet’ and ‘Norwell’ and heirloom cvs. ‘Red Fife’, ‘Glenn’, and ‘Reward’) and four barley cultivars (commercial cvs. ‘Oxbridge’ and ‘Camus’ and heirloom cvs. ‘Dolma’ and ‘Jet’). 3.1.2 Seed treatment Seeds were surface sanitized in 70% ethanol for 5 minutes followed by rinsing thrice with distilled water under aseptic conditions. After rinsing, seeds were left to imbibe in distilled water for 12 hours. 58  3.1.3 Study design and set-up We used a completely randomized design (CRD) with five replications for each cultivar. Seedlings were grown on germination paper (10”x10”, Anchor Paper Co. Seed Solution, Saint Paul, MN) following a modified version of B. Snyder and J. Lynch (Department of Horticulture, Penn State University, PA, USA, personal communication). In brief, we used two sheets of blotting paper (Anchor Paper Co., St. Paul, MN, USA) and cut a notch (1 cm wide and 4 cm long) at the center of the top edge of each sheet. Then, we placed two pieces of paper without notches on top. These layers were then placed in a large, clear bag (10”x11”, SC Johnson and Son Limited, Brantford, ON, Canada) and moistened completely with 0.5 mM CaSO4 (MW 136) solution. Next, a germination cradle was prepared; this was achieved by pressing the paper without notches into the underlying notch. One seed was then placed embryo side down into the germination cradle. This germination unit (i.e., bag, moistened paper and seed) was then secured with two binder clips to a similar sized sheet of plexiglass, and held at a 45 degree angle. The germination units were kept in a growth chamber (Controlled Environments Ltd., Winnipeg, MB, Canada) set at 25oC and 60% relative humidity and grown for 10 days. Light was provided using fluorescent lights at an intensity of 90 µmols m-2 s-1 for 16 hours each day.  All germination units were periodically moistened with 0.5 mM CaSO4 to prevent drying. 3.1.4 Root architecture data analysis After 10 days, the paper and seedlings were removed from the bags and scanned on a calibrated, lighted flatbed scanner at 300 dpi. Scans were then analyzed by WinRHIZO software (WinRHIZO Pro 2009c, Regent Instruments Inc.). WinRHIZO data were 59  transferred to MSTAT-C for statistical analyses (MSU, 1993). Metrics calculated with WinRHIZO include: total root length, surface area, average diameter, root volume, number of tips, and branching angle. We also dried samples, in a drying oven at 70oC for 48 hours, and then weighed them to calculate dry root weight, dry shoot weight, and subsequently shoot to root ratios. These results were compared to parameters previously measured in the field for these cultivars in performance trials (Chapagain and Riseman, 2012). 3.2 Results and Discussion 3.2.1 Wheat root architecture Root architecture metrics for commercial and heirloom wheat are shown (Table 3.1). In general, heirloom cvs. ‘Glenn’ and ‘Reward’ displayed notable differences (i.e., longer root, greater surface area and higher number of tips) compared with the commercial cvs. ‘Scarlet’ and ‘Norwell’. Overall, the commercial cultivars showed coarser roots (i.e., higher root diameter), greater volume, higher dry root weight, and shoot to root ratios compared to the heirloom cultivars, with cv. ‘Scarlet’ displaying the highest values. There is significant variation among the heirloom cultivars with cv. ‘Reward’ displaying the highest surface area, diameter, root volume, and number of tips compared to cv. ‘Red Fife’ and cv. ‘Glenn’. The lowest shoot:root ratio (0.88) was observed in heirloom wheat cv. ‘Reward’ indicating the greatest biomass partitioning to the roots among all cultivars and a trait associated with drought tolerance potential (Bernier et al., 1995). The commercial cultivars were more uniform for a number of parameters including surface area, diameter, volume, and angle of branching (Table 3.1). Heirloom cultivars with typically longer and thinner roots, 60  greater surface area, more tips, and higher branching angles, are predicted to have larger and deeper root systems than the commercial cultivars. Root length distribution across diameter classes in heirloom and commercial wheat cultivars is shown (Figure 3.1). Heirloom cultivars produced thinner roots than commercial cultivars with 75-95% of all roots within the <0.5 mm diameter class compared with 50-75% in commercial cultivars. Cultivar ‘Glenn’ possessed the highest percentage (95%) of thin roots while the commercial cvs. ‘Scarlet’ and ‘Norwell’ displayed the lowest percentage, i.e., coarsest. 3.2.2 Barley root architecture Barley cultivars also showed significant variation in most root parameters including length, area, volume, and angle of branching (Table 3.2). No trends differentiating commercial and heirloom cultivars are identified. The heirloom cv. ‘Jet’, however, produced the longest roots with the greatest surface area along with the highest branching angle and the lowest shoot:root ratio compared to all other cultivars (Appendix K). Figure 3.2 shows root length distribution by diameter class (mm) in barley cultivars. The heirloom barley cv. ‘Jet’ produced the finest roots with almost 100% roots falling in <0.5 mm diameter class followed by the commercial cv. ‘Oxbridge’ (>90%). Commercial barley cv. ‘Camus’ displayed the coarsest roots (0.5-1.0 mm) compared to either heirloom cultivar. 3.2.3 Root architecture association with field performance Field performance of both heirloom and commercial cultivars, grown under low input organic conditions, are presented (Table 3.3). There exists variation for the association between wheat root architecture (Table 3.1, Figure 3.1) and plant performance metrics 61  (Table 3.3). In general, the heirloom wheat cultivars produced tall plants with long internodes (Table 3.3) and longer finer more branched root systems (Table 3.1) compared to the commercial cultivars. However, they also tended to lodge more than the commercial cultivars due to their taller culms. The commercial cultivar cv. ‘Scarlet’, with its greatest root diameter, root volume, dry root weight, and shoot:root ratios (Table 3.1) produced higher grain yield, harvest index [HI, defined as a ratio of economic yield (grain yield) to the total above ground biomass (grain yield + shoot biomass)], and 1000 seed weight (Table 3.3) compared to the heirloom cultivars suggesting that cultivars with the shorter (i.e., more feeder or surface) roots are also suitable under organic systems. Unlike wheat, barley did not show any meaningful associations between root metrics and field performance (Table 3.2, 3.3). Among the few heirloom and commercial wheat and barley cultivars assessed in this study, significant variation was observed for many root architectural parameters. A number of reports link root architecture with traits associated with low-input production including nutrient uptake efficiency, culm strength, and drought tolerance. Jones et al. (1989) showed that root diameter is one of the most important determinants of nutrient uptake efficiency with thinner roots having greater efficiency. Furthermore, several reports support the association between thinner roots and improved P and water uptake (Jones et al., 1989; Manske et al., 1996). In wheat, it has been reported that many wild forms and landraces possess large root systems with thin roots, but tend to lodge because of their tall culms (Manske, 1989; Vlek et al., 1996). Last, Bernier et al. (1995) suggested that plants with low shoot:root ratio possess a water stress avoidance potential while plants with a higher ratios are more likely to suffer from water stress. The variation observed among these few 62  heirloom and commercial cultivars indicates significant variation persists in these germplasm pools, and is available to breeders interested in developing cultivars for low-input agriculture. 3.3 Conclusions This study assessed the variation among heirloom and commercial cultivars of wheat and barley for several root architectural traits. Our assessment showed significant variation among heirloom and commercial wheat cultivars and between root and agronomic performance traits. Overall, heirloom wheat cultivars displayed longer and thinner roots, more surface area, higher number of tips, and greater branching angle compared to commercial cultivars. These traits are often associated with resistance to drought stress and improved P uptake. The commercial cultivars, on the other hand, generally displayed coarser roots and greater shoot:root ratios. There exists variation between heirloom and commercial wheat cultivars for the association between root architecture and plant performance. Barley, however, did not show any meaningful associations between root metrics and field performance. Overall, the longer and finer roots, and the lowest shoot:root ratio of some heirloom cultivars (e.g., ‘Reward’ wheat and ‘Jet’ barley) suggest they may be useful candidates for inclusion in breeding programs designed to improve nutrient uptake efficiency and drought tolerance.   63  Table 3.1 Root architecture metrics for heirloom and commercial wheat cultivars. Cultivar Root Length (cm) Surface Area (cm2) Average Diameter (mm) Root Volume (cm3) No. of Tips Branching Angle (degrees) Dry Root Weight (mg) Shoot:Root Ratio Scarlet-C 64.8 9.43 0.47 0.11 85 35.7 11.4 1.41 Norwell-C 57.0 7.92 0.46 0.09 52 34.7 8.6 1.05 Red Fife-H 65.6 5.81 0.33 0.05 87 37.2 7.0 1.07 Glenn-H 75.5 8.18 0.34 0.07 66 35.0 9.7 1.22 Reward-H 71.4 9.62 0.43 0.10 103 35.6 9.7 0.88 SEM (±) 1.69 0.87 0.04 0.01 4.0 0.62 0.76 0.11 LSD0.05 4.80 2.47 0.11 0.03 11.37 1.76 2.16 0.31 C = Commercial cultivar, H = Heirloom cultivars, SEM = Standard Error of the Mean, and LSD = Least Significant Difference 64  Table 3.2 Root architecture metrics for heirloom and commercial barley cultivars. Cultivar Root Length (cm) Surface Area (cm2) Average Diameter (mm) Root Volume (cm3) No. of Tips Branching Angle (degrees) Dry Root Weight (mg) Shoot:Root Ratio Oxbridge-C 80.3 8.2 0.33 0.07 139 34.8 7.4 1.09 Camus-C 73.4 9.7 0.42 0.10 250 34.3 8.1 1.15 Jet-H 100.1 11.1 0.35 0.10 197 36.2 7.2 0.83 Dolma-H 84.6 8.5 0.43 0.09 137 35.4 10.0 1.06 SEM (±) 3.40 0.62 0.03 0.01 12.1 0.64 0.59 0.09 LSD0.05 9.67 1.76 0.08 0.28 34.4 1.82 1.67 0.25 C = Commercial cultivar, H = Heirloom cultivars, SEM = Standard Error of the Mean, and LSD = Least Significant Difference   65  Table 3.3 Field performance of small grain cultivars grown under low input organic conditions during 2010 spring season at UBC Farm, Vancouver, Canada. Cultivar Plant Height at Harvest (cm) Grain Yield (t ha-1) Harvest Index (%) 1000 Seed Weight (g) Wheat Scarlet (C) 103 5.4 48.4 48.0 Norwell (C) 114 5.3 42.7 44.7 Red Fife (H) 135 4.1 37.4 43.7 Glenn (H) 109 5.1 42.4 40.0 Reward (H) 127 5.2 32.5 41.0 SEM (±) 3.67 0.31 2.66 2.82 LSD0.05 7.35 0.65 5.32 5.65 Barley Oxbridge (C) 65 5.8 53.8 55.3 Camus (C) 81 5.0 53.8 54.0 Jet (H) 75 5.5 29.2 48.5 Dolma (H) 78 4.9 41.7 36.3 SEM (±) 3.49 0.29 3.12 3.22 LSD0.05 7.0 0.6 6.25 6.45 C = Commercial cultivar, H = Heirloom cultivars, SEM = Standard Error of the Mean, and LSD = Least Significant Difference 66   Figure 3.1 Root length (cm) distribution in diameter classes (mm) in wheat cultivars.  Figure 3.2 Root length (cm) distribution in diameter classes (mm) in barley cultivars.    020406080<0.5 0.5 - 1.0 1.0 -1.5Root Length (cm) Root Diameter Class (mm) Scarlet Norwell Red Fife Glenn Reward020406080100<0.5 0.5 - 1.0 1.0 -1.5Root Length (cm) Root Diameter Class (mm) Oxbridge Camus Jet Dolma67  CHAPTER 4: WHEAT-BEANS INTERCROPPING  One component of this chapter has been published in Crop Science as Chapagain, T. and A. Riseman (2014), Intercropping Wheat and Beans: Effects on Agronomic Performance and Land Productivity (DOI: 10.2135/cropsci2013.12.0834).  A second component of this chapter has been accepted for publication in Nutrient Cycling in Agroecosystems as Chapagain, T. and A. Riseman, Nitrogen Transformation, Water Use Efficiency and Ecosystem Productivity in Monoculture and Wheat-Bean Intercropping Systems. This study was conducted at the Centre for Sustainable Food Systems at UBC Farm in Vancouver, BC, during 2011 and 2012 cropping seasons (May to September) to investigate the effects of species ratios and spatial configuration on plant performance and system productivity within an organic production system. In addition, the effects of the proportion of genotype and their spatial configurations on N-use efficiency (i.e., biological nitrogen fixation and transfer to the companion plants), CO2 fixation (i.e. gross ecosystem photosynthesis - GEP), net ecosystem productivity (NEP) or carbon sequestration, water use efficiency (WUE), and their association with biomass yield and quality were also assessed. The experimental site is located at 49° 15' 3" N and 123° 14' 20" W, at an altitude of 100 m above mean sea level. Research was conducted under rainfed conditions using organic production practices.   68  4.1 Materials and Methods 4.1.1 Climate description of the study area Climate data are summarized for the experimental site during the spring-summer seasons (May to September) of 2011 and 12 (Table 4.1). Mean air temperatures at 1.5 m above the ground over the two cropping seasons ranged from 15.0 to 15.1°C, with the warmest days in August (17.5 to 18.2°C). The mean soil temperature at the 20 cm depth ranged from 17.9°C in year 1 to 18.3°C in year 2. Monthly average solar irradiance ranged from 389 to 404 W m-2, with the higher values in June-August. The average monthly precipitation was 42.4 and 32.3 mm in year 1 and 2, respectively. The least monthly precipitation (2.4 mm) occurred in August of year 2 while the highest monthly precipitation (78 mm) occurred in May of year 1. Year 2 was dry compared to year 1 with greater levels of solar irradiance associated with lower precipitation and relative humidity. 4.1.2 Soil and field description The soil was moderately well drained coarse textured sandy loam with low to moderate fertility. According to the Canadian system of soil classification, it was a Duric Humo-Ferric Podzol which is typified by a contact between reddish brown sub-soils and the greyish transition to the basal glacial till (AAFC, 1998). The specific soil type was a Haplorthod, according to the American system of soil classification (USDA-SCS, 1992), which is usually found with forest vegetation, the land cover prior to clearing for agriculture. Three random soil samples from across the whole test site were collected (0-15 cm depth) at the time of plot establishment and showed acceptably homogeneous conditions. The average pH, organic matter content, total N, δ15N, P and K were 5.8, 119 g kg-1, 3.6 g kg-1, 3.74 ‰, 156 69  mg kg-1 and 193 mg kg-1 based on dry soil, respectively. Additional samples were taken from two different areas within each plot before planting (Spring-2011) and after final harvest (Fall-2012), and sent to an analytical laboratory (Pacific Soil Analysis Inc., Richmond, Canada) to determine soil mineral N (NH4+ and NO3-) content. The site had not been used for grain production in previous years but had been used for annual vegetable cultivation. The site had been managed under organic vegetable production guidelines for more than the 10 years using green manures and compost. 4.1.3 Experimental details Cultivars of hard red spring wheat (Triticum aestivum cv. ‘Scarlet’), common bean (Phaseolus vulgaris cv. ‘Red Kidney’ and ‘Black Turtle’) and fava bean (Vicia faba cv. ‘Bell’) that performed well (i.e., in terms of synchronized maturity for combined harvesting, yield potential, protein content, and nodulation potential in beans) in previous cultivar trials (Chapagain and Riseman, 2012) were selected for intercropping trials. Common bean (bush type with steep basal roots) and the fava bean (upright growth with a well-developed tap root which produces extensive fibrous root architecture) were chosen to assess the impact of different genera (Vicia and Phaseolus) and different cultivars (common bean cv. ‘Red Kidney’ or ‘Black Turtle’) on companion wheat plants. Over two years of study, plants were grown on the same plots under organic and rain-fed conditions, and managed equally across combinations. Research plots (4m x 3m) were laid out in a randomized complete block design (RCBD) with five treatments and four replications for each crop combination (Figure 4.1). Treatments consisted of wheat and beans grown as monocultures, and wheat cv. ‘Scarlet’ 70  intercropped with either a common bean cultivar (cv. ‘Red Kidney’, or cv. ‘Black Turtle’), or a fava bean cultivar (cv. ‘Bell’) in rows of 1:1, 2 wheat:1 bean and broadcast arrangements (Appendix I). In monoculture, wheat and beans were planted in rows at the recommended plant densities targeting 300 and 24 viable plants m-2, respectively. Row and mixed arrangements used a proportional replacement design in which the proportion of species was varied as the monoculture densities differed between the two species (Jolliffe, 2000). Row intercropping consisted of planting wheat and bean at 30 cm spacing in alternate rows of 1:1 targeting 150 wheat and 12 bean plants m-2, and in 2:1 row arrangements targeting 200 wheat and 8 bean plants m-2. In the mixed arrangement, seeding densities of wheat and bean were reduced by one half of monoculture densities targeting 150 and 12 plants m-2, respectively, and broadcasted evenly in cultivated plots. This resulted in different combined densities as species proportions changed. There was a gap at least 50 cm wide between plots to minimize treatment interactions, and 1 meter wide gap between blocks to facilitate management. Bean seeds were inoculated with commercial rhizobia (Garden Inoculant for Beans, EMD Crop Bioscience, WI, USA) and planted immediately. Wheat and common bean cv. ‘Black Turtle’ were sown in mid-May (15-16 May) in rows using a hand seeder (Jang Clean Hand Seeder, Jang Automation Co. Ltd., Cheongju-city, South Korea) with adjustable sprockets (Front: 11, Rear: 14), and seed plates (G-12 for wheat and AA-6 for BT) whereas common bean cv. ‘Red Kidney’ and fava bean cv. ‘Bell’ were hand seeded the same day. Sowing depth varied with seed size and ranged from 3-4 cm for wheat and 5-6 cm for beans. No fertilizers, pesticides or fungicides were used throughout the growing season. 71  4.1.4 Data collection and analysis Plant-based parameters: Data were recorded for plant height (from soil surface to the tip of apical leaf), number of effective tillers (spikes) m-2, days to harvest, number of nodules (in beans), pod or spike length, seed number, grain yield (t ha-1), 1000 seed weight (g), and harvest index [HI, defined as a ratio of economic yield (grain yield) to the total above ground biomass (grain yield + shoot biomass)]. Chlorophyll concentration index (CCI) was measured using a handheld chlorophyll meter (Model CCM 200 Plus, Opti-Sciences Inc., New Hampshire, USA) on the flag leaf and the 3rd leaf prior to the flowering (50 DAS). Nodulation was assessed by counting and inspecting the nodules of 3 randomly selected bean plants in both monoculture and intercrop plots prior-to-flowering (i.e., 50 days after sowing) following a procedure similar to Chapagain and Riseman (2012). Spike or pod color was a determinant of maturity and considered ready for harvest when they were straw-colored and 80% of the grains of the spike were in the hard-dough stage. Plants in the middle section of each plot, leaving two rows on either side, were harvested at maturity for yield measurements. Sub-samples were collected from two different 1 m2 areas within each plot, and averaged. Shoots of beans and wheat plants were harvested by hand leaving 5 cm tall stubble, oven dried at 70°C for 72 hours, and threshed separately by a stationary thresher. Individual crop yield (grain and total biomass) was calculated to permit comparison of yields, land equivalent ratios (LER) and N contents with those when they were grown alone. Relative and total intercrop productivity: The benefits of multispecies systems i.e., system productivity, was estimated using the Land Equivalent Ratio (LER, Mead and Willey, 1980) 72  that compares the yields obtained by growing two or more species together with yields obtained by growing the same crops as monocultures. The LER for two intercrop species in proportional replacement design was calculated as follows: LER = intercrop yieldw/mono yieldw + intercrop yieldb/mono yieldb where subscript w indicates wheat and subscript b indicates bean. The yields of mono and intercrop species were calculated as t ha-1. Intercropped plots with LER values greater than 1.0 were considered advantaged combinations, whereas plots with LER values less than 1.0 were considered disadvantaged combinations. Grain yield was expressed at 12.5% moisture. LER in terms of total plant mass (grain + shoot biomass) production was also calculated. Intercrop productivity was also assessed in terms of Total Land Output (TLO, Jolliffe and Wanjau, 1999) as follows: TLO = wheat yield + bean yield Intercrop plots with greater TLO values compared to monoculture plots showed a yield advantage. Tissue N, C, 15N and 13C analysis: Plant tissue samples for N and C analyses were prepared from the shoots (i.e., leaves and stem) and grains separately of both nodulated bean and non-fixing wheat plants harvested at maturity while samples for 15N and 13C analyses were prepared from all aboveground biomass harvested at pod or grain filling stages in bean and wheat, respectively. They were bulked by plot and species and dried at 70oC for 72 hours and subsequently homogenized into a fine powder using a 115 V Wig-L-Bug grinding mill (International Crystal Laboratories, Garfield, NJ, USA). The subsamples, 2-3 mg each, were weighed into tin capsules using a Mettler AT20 micro-balance (Toledo, OH), and analyzed 73  for total N, C, δ15N and δ13C by high-temperature flash combustion using an elemental analyzer (Vario EL Cube elemental analyzer, Elementar Analysensysteme GmbH, Hanau, Germany) coupled by continuous flow to an isotope ratio mass spectrometer (Isoprime isotope ratio mass spectrometer, Isoprime Ltd., Cheadle, UK). The percentage of plant N derived from atmospheric N2 (% NDFA), based on the natural variation in the abundance of 15N, was calculated according to Shearer and Kohl (1988) as follows: % NDFA = 100 x (δ15Nref − δ15Nleg) / (δ15Nref − δ15Nfix)  where δ15Nref is the δ15N value for the non-fixing wheat reference plant grown alone and dependent on soil N; δ15Nleg is the δ15N value for the nodulating and potentially N2-fixing beans grown in mixed culture where fixed N and soil N are available as N sources; and δ15Nfix is the δ15N value for the nodulating beans when they are totally dependent on biological N fixation (BNF) as the N source. In addition, the quantification of N transferred to the companion wheat plants was determined by using the following formula (He, 2002): % N transfer = 100 x (δ15N wheat mono - δ15N wheat intercrop) / δ15N wheat mono where δ15N wheat mono is the δ15N value for wheat when they are grown alone and dependent on soil N, and δ15N wheat intercrop is the δ15N value for companion wheat plants grown in intercrop plots. In order to calculate the δ15Nfix value for beans, identical cultivars were grown separately in plant boxes filled with quartz sand, and supplied with N-free media and commercial rhizobia (Garden Inoculant for beans, EMD Crop Bioscience, WI, USA) as inoculum. The medium was prepared following the modified version of Mae and Ohira (1981) and 74  contained: 50 mM Fe-EDTA, 50 mM KCl (MW 74.55), 0.5M K2SO4 (MW 174.26), 1M KH2PO4 (MW 136.09), 0.5 M MgSO4·7H2O (MW 246.49), 1M CaCl2 (MW 110.98) as macroelements; and 0.5 mM CuSO4·5H2O (MW 249.7), 25 mM H3BO3 (MW 61.84), 2 mM ZnSO4·7H2O (MW 287.55), 2 mM MnSO4·H2O (MW 169.01), and 0.5 mM Na2MoO4·2H2O (MW 241.9) as microelements. The macro and microelement solutions were prepared separately with distilled water, and then poured at 5-10 ml per day into plant boxes each containing 4 plants. The δ13C values from plant samples were considered as proxy for direct measurement of water use efficiency (WUE) (Condon et al., 1987; 2002). In this method, less negative δ13C values indicate higher WUE whereas more negative δ13C values indicate lower WUE. Grain nitrogen values were converted to crude protein levels as %N x 6.25 for beans, and %N x 5.8 for wheat (Jones, 1931). Total N and C yields were derived by using grain and shoot biomass yield, and N and C content in grain and shoot biomass in each crop component. Gross ecosystem photosynthesis, ecosystem respiration and net ecosystem productivity measurements: Field measurements of net ecosystem CO2 exchange (NEE) in cropland (i.e., monoculture and intercrop plots) and ecosystem respiration (Re) were conducted at the soil surface using a dynamic closed automated chamber connected to a portable CO2 gas analyzer by following a procedure similar to that of Jassal et al. (2010). The automated chamber consisted of a PVC cylinder that was equipped with a calibrated photosensor (RainWise Quantum Solar Sensor, RainWise Inc., Bar Harbor, ME, USA) for the measurement of photosynthetically active radiation (PAR), an ordinary axial fan to ensure 75  uniform CO2 concentration in the chamber, and outlet vent tube of 15 cm long and 3 mm internal diameter to prevent pressure differences between the chamber and the atmosphere. The cylinder dimensions were 19.5 cm internal diameter, 60.8 cm height, and 1 cm wall thickness. The chamber effective volume when deployed was 20.34 dm3 while the surface area covered by the chamber was 0.0298 m2. The cylinder was inserted to a depth of about 2 cm below the soil surface during field measurements. The CO2 gas analyzer unit consisted of an infrared gas analyzer (IRGA) (model LI-820, LI-COR Inc., Lincoln, NE), a 21X data logger (model 21X, Campbell Scientific Inc. (CSI), Logan, UT, USA), an AC linear pump (model SPP-40GBLS-101, GAST Manufacturing Corp., Benton Harbor, MI, USA), and a data storage module (SM192, CSI.). The IRGA was calibrated in the UBC Biometeorology and Soil Physics Laboratory with cylinders of CO2 in dry air calibrated using standards provided by the Canadian Greenhouse Gases Measurement Laboratory, Meteorological Service of Canada, Downsview, Ontario. The effective volume was assumed to be approximately 12% higher than the geometric headspace volume, due to the near-surface soil porosity and the adsorption of CO2 on the soil surface and chamber walls (Jassal et al., 2010; 2012). NEE in a cropland was measured from two different areas within each plot by placing the chamber on the soil surface three times a day (i.e., morning, afternoon and evening) at 25, 50 and 75 days after sowing enclosing the plants (Appendix J). This was followed by the measurement of Re by placing the chamber on bare soil plus plant roots after harvesting. When measuring NEE and Re, the pump was turned on 1 minute before chamber placement on the soil surface and continued for 3 minutes. The IRGA and the axial fan in the cylinder were kept on between measurements. The time rate of change in the CO2 mole fraction in 76  the chamber headspace (dC/dt, µmol mol-1 s-1) during a period of 90 seconds beginning 20 seconds after chamber closure, which was found to be linear, was used to calculate the flux, F (µmol m-2 s-1) as follows (Jassal et al., 2005): F =             where P is the atmospheric pressure (Pa), R is the universal gas constant (8.314 J mol-1 K-1), T is the temperature of the chamber air (K), V is the geometric volume of the chamber headspace (0.02034 m3), A is the surface area covered by the chamber (0.0298 m2), and a is the ratio of the effective volume to the geometric volume of the chamber (i.e., 1.12). Since the rate of increase in relative humidity in the chamber was less than 2% minute-1 over the 90 seconds, the water vapour dilution effect was estimated to be less than 1% of F, and was therefore neglected (Welles, 2001). Gross ecosystem photosynthesis - GEP (i.e., Re minus NEE), often referred to as gross primary productivity of the cropland, and net ecosystem productivity - NEP (i.e., NEE with a negative sign, often referred to as seasonal net carbon sequestration) were calculated for all planting arrangements. The micromole values of NEP were converted to mg C m-2 hr-1 using a conversion factor of 43.2 (Jassal et al., 2005). When NEE is positive, the ecosystem is releasing C to the atmosphere while when negative, the ecosystem is absorbing C from the atmosphere. Crop management parameters: General observations were made 30 and 70 days after sowing (DAS) on the type, number and the amount of weeds present, and insect pest and disease pressures with regard to type and nature of damage. Diseases of economic importance e.g., Scald or Leaf Blotch (Rhynchosporium secalis), 77  Stem/Leaf/Stripe/Yellow/Brown Rust (Puccinia spp.), and Septoria Leaf Spot or Glume Blotch (Septoria tritici) were monitored and noted over the course of the season as suggested by Chapagain and Riseman (2012). Data analysis: The data collected were analyzed using MSTAT-C (MSU, 1993) and MATLAB (Mathworks-MATLAB and Simulink for Technical Computing, Natick, MA, USA). Analyses of variance were performed on individual plot data for plant performance metrics, yields, C and N accumulation. Fisher’s least significant differences were calculated with 5% significance levels in MSTAT-C using the error variance from the analysis. Simple correlation coefficients and coefficients of determination were determined between selected parameters using Statistical Package for the Social Sciences (SPSS) software. 4.2 Results 4.2.1 Soil mineral nitrogen and δ15N content Pre-plant plots were homogenous and showed uniform distribution of soil mineral N (Table 4.2). Soil samples taken after final harvest (Fall-2012) showed monoculture fava bean cv. ‘Bell’ plots displayed the highest soil mineral N balance (+0.7 mg NH4+ and +6 mg NO3- kg-1 dry soil) compared with common bean cv. ‘Red Kidney’ (+0.4 mg NH4+ and +4 mg NO3- kg-1 dry soil) or ‘Black Turtle’ (+0.5 mg NH4+ and +3 mg NO3- kg-1 dry soil) plots. Both N pools declined in the wheat monoculture plots (-0.9 mg NH4+ and -5.8 mg NO3- kg-1 dry soil) (Table 4.2). Wheat-common bean intercrop plots displayed a less negative N balance compared to wheat monoculture plots (Table 4.2). The wheat-fava bean cv. ‘Bell’ combination in 1:1 arrangement was the only plot that showed the highest mineral N 78  balance (+0.2 mg NH4+ and +1.1 mg NO3-  kg-1 dry soil) compared to all other intercrop combinations.  The average δ15N values of nodulating legumes grown in N-free media were -1.34 ‰ (fava bean cv. ‘Bell’), -1.04 ‰ (common bean cv. ‘Black Turtle’) and -0.97 ‰ (common bean cv. ‘Red Kidney’) while the non-fixing wheat reference plants grown in field as monoculture had average δ15N value of 2.87 ‰ (data not shown). There was sufficiently a large difference between soil δ15N (3.74 ‰) and atmospheric δ15N (0 ‰) in order to measure dilution effects as suggested by Shearer and Kohl (1988).  4.2.2 Plant performance indices Grain yield and LER values from monoculture and wheat-bean intercrop combinations are shown (Table 4.3). In monocultures, the yield of ‘Red Kidney’ increased significantly from 2.3 t ha-1 to 3 t ha-1 from year 1 to year 2 (average 2.6 t ha-1, Figure 4.2). Common bean cv. ‘Black Turtle’ and fava bean cv. ‘Bell’ also displayed similar trends. Grain yields of wheat across monoculture plots were similar. However, yields declined from 3.4 t ha-1 in year 1 to 3 t ha-1 in year 2 (average 3.2 t ha-1, Figure 4.2). These trends (i.e., legumes increasing and wheat decreasing) were similar in intercrop plots. Grain yields of wheat and bean components in intercrop plots were lower than their monocultured counterparts due to reduced seed densities. However, wheat grain yield from wheat-fava bean plots were relatively higher than wheat-common bean combinations with the highest yield (3.1 t ha-1) from the 2:1 arrangement (Figure 4.2). In addition, the productivity of mixtures (i.e., Total Land Outputs - TLO and Land Equivalent Ratio - LER) were significantly higher in intercrop plots with the higher values observed in year 2 79  across all cultivar combinations (Table 4.3). Among the intercrop combinations, wheat-fava bean cv. ‘Bell’ in row arrangement displayed the highest land productivity (32 to 50%) compared to their sole crops (Table 4.3). This was true when planted in rows of 1:1 (up to 50%) or 2:1 (up to 32%), with the average TLOs of 4.36 and 4 t ha-1, respectively. Wheat-common bean cv. ‘Red Kidney’ also showed higher TLO and LER in row arrangements with the highest TLO (4.05 t ha-1) and LER (1.33) in the 2:1 arrangement which resulted in a 33% greater land productivity. Plots with 1:1 arrangement showed 13% higher land productivity than sole crops. Mixed planting arrangements across all cultivar combinations did not produce significantly different LER values from monoculture plots. Wheat-common bean cv. ‘Black Turtle’ did not show significant effects on LER values, though the 1:1 arrangement produced 14% more yield compared to the sole crops. The TLO and LER values calculated using total biomass (all above ground biomass) production in monoculture and intercrop plots displayed similar trends as when calculated with grain yield (Table 4.4). Lower grain yields and LER with common beans were associated with poor plant performance metrics (i.e., CCI, number of pods, seed number, and 1000 seed test weight) in year 1 (Table 4.5, Appendix B). However, performance improved significantly in year 2 for the common bean cv. ‘Red Kidney’ showing higher values for 1000 seed weight and grain protein content in 2:1 arrangements (Table 4.5). The common bean cv. ‘Black Turtle’, on the other hand, displayed higher 1000 seed weight, biomass nitrogen content and grain protein in mixed planting arrangements compared to row intercropping. Compared to monoculture plots, common bean in intercrop plots displayed reduced biomass N which 80  significantly increased biomass C:N ratios (Table 4.5). The performance of fava bean cv. ‘Bell’, however, was relatively more stable than either common bean cultivars over the two years. Unlike beans, the performance of wheat declined over time in both monoculture and intercrop plots (Table 4.3, Appendix B). In addition, wheat components in wheat-common bean combinations displayed significantly lower 1000 seed weight and harvest index in year 2 (Table 4.5, Appendix B) probably due to increased competition with beans. Wheat from all intercrop plots displayed increased biomass and grain nitrogen content with the highest values from the highest bean density (i.e., 1:1 arrangement) in year 2. This resulted in lower biomass C:N ratios and higher grain protein levels compared to the wheat monoculture plots (Table 4.5). 4.2.3 Biological N2 fixation and transfer Intercropping increased nodulation, percent N derived from symbiotic N2 fixation, and transfer to the companion wheat plants (Table 4.6). The number of nodules and the proportion of nitrogen fixed by beans were significantly higher in intercrop plots as compared to their monoculture counterparts. Fava bean cv. ‘Bell’ developed 60 to 80% more nodules in intercrops resulting in 10-12% more N derived from symbiotic N2 fixation compared to when grown as a monoculture. Fava bean cv. ‘Bell’ in 1:1 arrangement displayed the highest amount of N (average of 96 kg ha-1) compared to other bean cultivars of which 74 kg (77%) was derived from symbiotic N2 fixation (Table 4.6). Similarly, nodules of common bean cvs. ‘Red Kidney’ and ‘Black Turtle’ increased by 38-71% and 46-69%, respectively, in intercrops as compared to their monoculture plots 81  (Table 4.6). Common bean in intercrop plots also fixed more N2 (up to 12% increase) than their sole stands. The rate of biological N fixation improved in year 2 as compared to year 1 with fava bean cv. ‘Bell’ fixing the most (average of 72% of total biomass N in year 1 to 89% in year 2) in the 2:1 arrangement, and common bean cv. ‘Red Kidney’ fixing the most (average of 57% in year 1 to 75% in year 2) in the 1:1 arrangement (Table 4.6).  N-transfer rates between the legume and wheat varied with legume genotypes and spatial arrangements (Table 4.6). The greatest transfer rates were in the wheat-fava bean cv. ‘Bell’ arrangements with the 1:1 plots highest at 13% followed by 2:1 and mixed planting arrangements at 11%. The highest amount of N-transfer, however, observed in wheat-fava bean cv. ‘Bell’ in the 2:1 arrangement (i.e., 7.8 kg of N in companion wheat). Wheat-common bean cv. ‘Red Kidney’ transferred an average of 4% while common bean cv. ‘Black Turtle’ did not transfer any N to the companion wheat (Table 4.6). The rate of N transfer improved in year 2 as compared to year 1 with fava bean cv. ‘Bell’ in the 1:1 arrangement transferring the most (average of 12% of N in wheat biomass in year 1 to 14% in year 2). Common bean cv. ‘Red Kidney’ in the 1:1 arrangement transferred an average of 5% of N in wheat biomass in year 1 to 7% in year 2 (Table 4.6).  4.2.4 N and C accumulation in biomass Monocultured legumes accumulated more N in grains and shoots than their intercrop components with the greatest amount in the fava bean cv. ‘Bell’ plot (average of 132 kg ha-1 of which 90 kg was derived from BNF) while common bean cvs. ‘Red Kidney’ and ‘Black Turtle accumulated 125 and 106 kg ha-1, respectively, of which 69 kg ha-1 in common bean cv. ‘Black Turtle’ and 58 kg ha-1 in common bean cv. ‘Red Kidney’ were derived from BNF 82  (Table 4.6). Lower N content in intercrop plots was associated with both reduced biomass production and lower biomass N content. Bean and wheat accumulated significantly more N in the grain than in the shoot biomass. However, C accumulation was slightly higher in shoot biomass than in the grain (Table 4.7). Wheat in intercrops displayed increased grain N percentage compared to wheat grown as a monoculture. However, the total grain N yield decreased with increasing bean density (Table 4.7). Wheat biomass N content in intercrop plots increased with increasing bean density (i.e., higher in 1:1 than 2:1). However, the total amount of N accumulated in biomass decreased with increasing bean density due to a reduction in wheat biomass (Table 4.7). Beans in intercrop plots also displayed reduced biomass N and a decrease in total N perhaps due to increased competition as densities increased. All intercrop plots accumulated more N (i.e., 1.1 to 29.4 kg ha-1 higher) in shoot biomass compared to monocultured wheat but not more than any monocultured bean (Table 4.7). The wheat-fava bean cv. ‘Bell’ in 1:1 arrangement, however, accumulated the highest with an average of 34 kg N ha-1, an amount higher than monocultured fava. Wheat-fava bean cv. ‘Bell’ combinations accumulated the highest amount of N among intercrop plots with 84-176% increases over wheat monoculture plots, with the highest gain in the 1:1 arrangement. Biomass N accumulation in wheat-common bean cv. ‘Red Kidney’ or ‘Black Turtle’ combinations were 18-50% and 42-63% higher, respectively, than wheat monoculture (Table 4.7). Wheat-fava bean cv. ‘Bell’ in 1:1 arrangement displayed the 83  highest total N (grain plus shoot biomass) yield (150 kg N ha-1) followed by wheat-common bean cv. ‘Red Kidney’ (129 kg ha-1) in the 2:1 arrangement. The most shoot biomass C was produced by the wheat-fava bean cv. ‘Bell’ 1:1 arrangement plot (214 g C m-2 y-1, i.e. 26% higher) followed by the 2:1 arrangement (195 g C m-2 y-1, i.e., 15% higher) compared to wheat monoculture plots (Table 4.7). Wheat-common bean cvs. ‘Red Kidney’ or ‘Black Turtle’, however, did not accumulate different amounts of C compared to wheat monoculture plots. In addition, the total biomass C produced (i.e., grain plus shoot biomass) was highest in the wheat-fava bean cv. ‘Bell’ 1:1 plots (396 g C m-2 y-1) followed by the 2:1 arrangement (365 g C m-2 y-1). A strong correlation (r2=0.98) was observed between the amount of N and C in beans (Appendix D). Wheat components in wheat-common bean cv. ‘Red Kidney’ and Wheat-fava bean cv ‘Bell’ plots showed a very strong and positive relationships (r2=0.77 and 0.67, respectively) between the accumulated N and C (Appendix E). In addition, wheat components in wheat-fava bean cv. ‘Bell’ displayed very strong association between grain yield and N content (r2=0.98), as well as between grain yield and biomass C accumulation (r2=0.95) (Appendix F). 4.2.5 Net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem photosynthesis and net ecosystem productivity Average daytime NEE, Re, GEP and NEP in monoculture and intercrop plots are presented in Table 4.8 with NEE, GEP and NEP varying by spatial arrangement. The greatest GEP values were observed during the mid-growth stage (50 days after seeding i.e., just prior to flowering, Figure 4.3a, 4.3b, 4.3c) in all planting arrangements. 84  Cropped areas averaged 164%-202% more CO2 fixation (i.e., greater GEP) than CO2 loss (i.e., Re) from bare soil plus plant roots with the highest GEP from the wheat-common bean cv. ‘Red Kidney’ in the 2:1 arrangement. However, NEP in wheat-common bean cv. ‘Red Kidney’ (2:1 arrangement) was lower than the wheat-fava bean cv. ‘Bell’ plots in the 1:1 arrangement. Wheat-fava bean cv. ‘Bell’ in the 1:1 arrangement displayed the greatest NEP (Figure 4.4a, 4.4b, 4.4c) resulting in the sequestration of the most C with a seasonal average rate of 208 mg C m-2 hr-1 (i.e., 7% higher than wheat monoculture plots). Bean monoculture and all intercrop plots displayed greater NEP in year 2 as compared to year 1. Wheat-fava bean cv. ‘Bell’ and wheat-common bean cv. ‘Red Kidney’ in the 2:1 arrangements also showed greater NEP compared to wheat monoculture plots (Table 4.8). Mixed crop arrangements, on the other hand, displayed the least NEP leading to lower C sequestration compared to all other combinations. Beans in intercrop plots fixed less CO2 than monocultured beans. However, the proportion of CO2 fixed by the wheat component was higher in row intercrop plots than monocultured wheat (data not shown). 4.2.6 Water use efficiency The effect of genotype and spatial arrangement on tissue δ13C values in monoculture and intercrop plots is presented (Table 4.9). Wheat in wheat-common bean cv. ‘Red Kidney’ and wheat-fava bean cv. ‘Bell’ combinations displayed less negative δ13C values compared to monocultured wheat indicating that the intrinsic WUE of wheat is improved when grown with common bean cv. ‘Red Kidney’ or fava bean cv. ‘Bell’, with improved WUE in year 2 as compared to year 1. Table 4.9 shows that values are higher (less negative) for common 85  bean cv. ‘Black Turtle’, but lower (more negative) for fava bean cv. ‘Bell’ relative to their monocultures. Common bean cv. ‘Red Kidney’ has a variable response. The δ13C values of the common bean cv. ‘Black Turtle’ were higher (less negative) when grown in combination with wheat (Table 4.9) indicating that WUE of the common bean cv. ‘Black Turtle’ improved when intercropped. This particular legume, however, did not influence the δ13C values of the companion wheat. 4.2.7 Crop competition, weed and disease pressure Higher biomass of common beans in year 2 suppressed the growth of wheat resulting in reduced 1000 seed weight, HI, and yield (Table 4.3, 4.5). Wheat growth and grain qualities were significantly affected in all planting arrangements of wheat-common bean cv. ‘Black Turtle’ combinations compared with wheat-fava bean cv. ‘Bell’ and wheat-common bean cv. ‘Red Kidney’. Wheat-fava bean exhibited the least competition (Table 4.10) regardless of planting arrangement or production year, possibly due to their upright growth habit. The most common weeds in either monoculture or intercrop plots were common chickweed (Stellaria media L.), green smartweed (Polygonum lapathifolium L.), prostrate knotweed (Polygonum aviculare L.), pigweed (Amaranthus spp.), crab grass (Digitaria spp.), barnyard grass (Echinochloa crusgalli L.), black nightshade (Solanum nigrum L.), and field horsetail (Equisetum arvense L.). Pigweed was observed early in the season along with chickweed. Common chickweed, an excellent colonizer that forms a succulent mat on the soil surface, was the predominant weed from mid to late season. All crop plots grew well with 3 manual weedings, 15, 30 and 45 days after sowing. In general, less late-season weeds were observed in the wheat-fava bean plots compared with wheat-common bean 86  plots. Wheat-common bean cv. ‘Black Turtle’ plots were impacted the most by weed pressure. Total weed biomass was greater in bean monoculture plots than wheat and was greatest early to mid-season compared with late-season. Weed biomass in intercrop plots was reduced as wheat density increased. In general, the occurrence of wheat disease was low over the two production years. When present, the most prevalent diseases included stripe and stem rusts (Puccinia spp.) and Septoria leaf blotch (Septoria spp.). No significant differences were observed among treatments regarding the occurrence or the extent of disease. Septoria leaf blotch infection was most severe early in the season whereas stripe and stem rusts were most severe mid to late season. 4.3 Discussion Our results indicate multiple benefits of organic intercropping compared to monoculture plots including higher yields and greater LER. In organic production systems, higher yields and greater land productivity are possible when wheat is intercropped with common bean. For example, Bulson et al. (1997) reported the highest LER value (1.29) among pure and intercropped plots when wheat and bean were intercropped at 75% the recommended density while, Hauggaard-Nielsen et al. (2009) found a 25% to 30% grain yield increase in intercrop plots compared to monoculture plots. They attributed the higher yields in intercrop plots to a more efficient use of limited plant resources (i.e., water, light, and nutrients) compared to monoculture plots. Sahota and Malhi (2012) also reported that intercropping required 7-17% less land than monoculture crops to produce the same level of yield. Chen et al. (2004) compared a barley, Hordeum vulgare L.- pea intercrop system 87  with monoculture plots and identified higher LER in the intercrop plots, ranging from 1.05 to 1.24 on a biomass basis, and from 1.05 to 1.26 on a grain protein basis. Our research identified changes in wheat grain quality associated with intercrop planting. In support, intercropping was found to be effective in enhancing wheat grain quality by increasing grain nitrogen and sulfur content resulting in higher protein and thus, more suitable for baking (Gooding et al., 2007). The extent of change, however, may depend on the density of legume species used in the intercrop. Bulson et al. (1997) found an increase in grain N and protein content while increasing bean densities in intercrops. Lauk and Lauk (2008) also showed a positive association of pea density with increased protein content of the cereal grains. However, they further noted the formation of smaller grains in cereals with increased pea density resulting in the substantial decreases in grain yield. We observed less late-season weed growth in wheat-fava bean intercrop plots compared with monoculture plots. This is similar to the findings of Bulson et al. (1997) and Haymes and Lee (1999) who reported reduced weed growth in intercrop plots compared with monocultured wheat. Hauggaard-Nielsen et al. (2007) further noticed reduced diseases occurrence when cereal grains are intercropped with legumes. However, we did not observe a change in disease incidence among our plots. The proportion of legume species in intercrop plots can affect biomass yield and quality. We observed an increased yield and N content of wheat biomass in intercrop plots compared to monocultured wheat. Bulson et al. (1997) also showed a positive association between increased bean densities and higher biomass N content in the wheat component. Similarly, Ghanbari-Bonjar and Lee (2002), and Lithourgidis and Dordas (2010) working 88  with wheat-bean intercrop found greater forage dry matter and greater crude protein compared to the monocultured wheat. In addition, Putnam et al. (1986) demonstrated that intercropping corn with soybean increases forage yield and crude protein content by 11-51% compared to sole corn plots. Therefore cereals, when intercropped with legumes, often display higher biomass and grain quality that significantly affects nutritional interests (Lithorgidis et al., 2011). Biological nitrogen fixation by beans can supplement or replace the nitrogen requirement of the subsequent crop. This is especially true under low soil N conditions (Fujita et al. 1992; Lunnan 1989). Our results showed that wheat N requirement can be reduced by intercropping with bean through direct N-transfer. We found that beans transferred up to 8 kg N ha-1 to the companion wheat plant, and have accumulated 6-22 kg N ha-1 through shoot biomass when planted as an intercrop. This further shows that N transfer occurred within a season at a greater rate from higher bean (common bean cv. ‘Red Kidney’ and fava bean cv. ‘Bell’) density plots in row arrangements (1:1), perhaps due to physical co-location of the root systems that facilitate more direct N transfer between species. Increase in N transfer in the second year could be due to combination of within year and residual legume N inputs from the first year mineralizing and becoming available to the wheat in the second year. The benefits of other legume-based intercrops have been shown through direct plant-to-plant N transfer, however, significant variation is reported in the amount of N transferred (i.e., ≤5 to 20% of the N in the receiver plants) (He et al., 2003; 2009; Johansen and Jensen 1996). Wheat-bean intercropping appeared to be very important for the development of sustainable food production systems as they recycle both atmospheric CO2 and N into the 89  production of grains or plant biomass (i.e., living matter). Our studies identified multiple benefits of organic intercropping related to these two important elements i.e., higher in-field nitrogen use efficiency, N2 fixation and transfer to companion wheat, greater ecosystem productivity (i.e., GEP and NEP), C sequestration, and improved WUE in wheat. Interestingly both common and fava beans fixed more N in intercrop plots than monoculture perhaps in response to the increased competition with wheat plants for soil N and promoting bean’s greater reliance on symbiotic N2-fixation. Hauggaard-Nielsen et al. (2009) reported that under organic conditions, total N recovery was greater in pea-barley intercrop plots than in the monoculture comparisons, and suggested a high degree of complementarities due to species interaction that enables natural regulation mechanisms between intercrop components. They further reported that pea-barley intercrops used nitrogen sources 17 to 31% more efficiently than by the monoculture plots due to the increased acquisition of soil mineral N by the barley component which promoted pea to rely more on internal N2-fixation. Izaurralde et al. (1992) reported increased N yield, greater N-fixation efficiency, and more shoot and root residue-N mineralization for subsequent crops when field pea and barley were intercropped. Prasad and Brook (2005) also reported a possibility of improving soil C and N by establishing cereal-legume intercrops as they increase agroecosystem complexity and enhance complementary use of resources in time and space. The inclusion of legumes with a cereal regulates the internal N cycle via N2 fixation (Schipanski et al., 2010) and reduces the amount of fertilizer required for crop growth (Inal et al., 2007). Intercropping cereals and legumes may stimulate greater GEP by increasing N availability from BNF and subsequently stimulating photosynthesis in the cereals (Hartwig et al., 2002; 90  Zanetti et al., 1997), and therefore may support greater overall ecosystem productivity. Also, increased CO2 fixation and reduced respiration (i.e., Re) is positively associated with increased NEP and WUE, with the greater values observed in year 2 as compared to year 1. Wheat in our intercrop plots produced increased biomass N, increased GEP (i.e., CO2 fixation) and greater water use efficiency resulting in greater NEP than monocultured wheat. This suggests a synergy is created when legumes are intercropped with cereals (Cardoso et al., 2007). Our experiment showed that soil respiration rates (Re) across all treatments were not affected by plot composition and were comparable with the values reported by Jassal et al. (2005) for our geographic zone (i.e., Vancouver, BC region). However, CO2 fixation (i.e., GEP) and biomass C yield were higher when wheat and fava bean were planted in 1:1 and 2:1 arrangements leading to the highest observed NEP, also referred to as seasonal net carbon sequestration, compared to all other crop combinations. The higher GEP and NEP from this intercrop combination also led to higher grain and above ground biomass yields with the highest grain (4.36 t ha-1) and total above ground biomass (9.23 t ha-1) production from the 1:1 arrangement. Dyer et al. (2012) reported an increase in soil organic carbon (SOC) concentration and a lowering of GHG emission rates from intercrop plots compared to when the legume and cereal were grown as monocultures. This suggests that increased GEP and associated C sequestration through biomass production improved SOC content.  Our observation of increased intrinsic WUE in wheat when grown with either fava bean cv. ‘Bell’ or common bean cv. ‘Red Kidney’ is perhaps related to improved N nutrition. As wheat N status is improved, photosynthesis is enhanced relative to transpiration rate (Livingston et al., 1999) leading to more water efficient grain and biomass production. In 91  addition, intercropping might help regulate source-sink relationship by creating special microclimatic situation, reduce inter-row evaporation, and excessive transpiration which together help enhance overall system water use efficiency (Zhang et al., 2012). The effect of wheat on improved WUE in common bean cv. ‘Black Turtle’, on the other hand, seems to be related to increased competition for water between wheat and bean. Overall, the specific intercrop combination of wheat (small grain) and bean (grain legume) may provide a new opportunity to better manage nutrients in a low-input small grain production system, one that fulfills both economic and environmental interests through higher land productivity, improved grain and biomass quality, increased GEP, NEP, WUE, and reduced reliance on mineral N fertilizer inputs and GHGs emissions. 4.4 Conclusions Our organically managed trials on intercropping systems revealed significant and positive responses from the interacting species on plant performance and overall system productivity. Wheat-fava bean combinations increased land productivity (32-50% higher) compared to monoculture counterparts with the highest values in a 1:1 arrangement while wheat intercropped with common bean produced better performance values in a 2:1 arrangement (i.e., 32% higher land productivity than monocultured wheat). Grain and non-harvested biomass nitrogen content of the wheat component increased significantly with a higher density of bean (i.e., 1:1 arrangement) while the total amount of N accumulated by wheat residues decreased with increasing bean density (i.e., in 1:1 arrangement) due to a reduction in wheat biomass. Total weed biomass in intercrop plots was reduced with increased wheat densities (i.e., 2:1 arrangement). 92  This study further demonstrated that intercropping wheat with fava bean gave the highest total biomass, higher amount of N derived from symbiotic N2 fixation, greater percent of N-transfer, higher N and C accumulation in aboveground biomass, improved GEP, NEP and WUE compared to wheat-common bean combinations, and monocultured wheat. For all bean cultivars, the number of nodules and the proportion of symbiotically fixed N were significantly higher in intercrop plots resulting in the accumulation of 18-176% more N in shoot biomass than in wheat monoculture plots. The highest rates of N-transfer (13%) were also observed in wheat-fava bean cv. ‘Bell’ combination when planted in the 1:1 arrangement. The highest C accumulation in plant biomass (214 g C m-2 yr-1, i.e., 26% higher than wheat monoculture) was also achieved in wheat-fava bean cv. ‘Bell’ (1:1) compared to wheat monoculture (170 g C m-2 yr-1). Wheat-fava bean cv. ‘Bell’ (1:1 arrangement) also showed the greatest NEP with a daytime average sequestration of 208 mg C m-2 hr-1 compared to other crop combinations. Wheat intercrops sequestered more C than their monoculture counterparts, perhaps related to increased N availability from the bean component. This study demonstrated that intercropping wheat with fava bean is an efficient strategy to increase land productivity, increased N and C accumulation, greater NUE, NEP and WUE than monocultures under low soil N and C conditions typical of organic systems. Furthermore, the wheat-fava bean cv. ‘Bell’ (1:1) combination appeared to be the most productive in terms of grain, N and C yields followed by wheat-fava bean cv. ‘Bell’ (2:1) and wheat-common bean cv. ‘Red Kidney’ (2:1) arrangements. 93  Table 4.1 Climate data† during the cropping seasons of 2011 and 2012 at UBC Farm, Vancouver, Canada. Month Mean Air Temperature at 1.5 m height (C) Solar Irradiance1 (W m-2) Total Precipitation (mm) Soil Temperature (20-cm depth) (C) Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 May 10.7 11.8 364 440 78.0 48.6 14.2 15.4 June 14.5 13.7 458 352 25.6 72.4 18.1 17.4 July 16.3 17.0 453 441 33.8 32.4 19.4 20.3 August 17.5 18.2 458 412 17.0 2.4 20.3 20.5 September 16.0 14.8 285 303 57.8 5.6 17.5 17.7 Average  SD 15.0 2.62 15.1 2.9 404 51.8 389 49.6 42.4 0.15 32.3 0.18 17.9 1.18 18.3 1.31  Total Rainfall   212 161   †Source: UBC Climate Station adjacent to Totem Park, 1 km northwest of UBC farm; 124-hour averages;  Y1 = year 1;  Y2 = year 2; and SD = Standard Deviation   94  Table 4.2 Soil mineral nitrogen (NH4+ and NO3-, mg kg -1 dry soil) at 0-15 cm depth before planting (Spring-2011) and after final harvest (Fall-2012) in monocultures and wheat-bean intercrop combinations. Treatments Before Planting  (BP) After Final Harvest  (AH) Mean Difference (AH-BP) NH4+ NO3- NH4+ NO3- NH4+ NO3- Wheat-common bean cv. ‘Red Kidney’ combinations RK Monoculture 4.3 25.0 4.7 29.0 0.4 4.0 Wheat:RK (1:1) 4.0 27.0 3.8 26.1 -0.2 -0.9 Wheat:RK (2:1) 4.3 26.3 3.9 23.8 -0.4 -2.5 Wheat-RK (mixed) 3.3 25.7 2.9 24.5 -0.4 -1.2 Wheat Monoculture 4.1 28.6 3.2 22.8 -0.9 -5.8 SEM (±) 0.34 0.99 0.47 1.13 0.10 0.59 LSD0.05 NS NS 1.34 3.21 0.28 1.68 Wheat-common bean cv. ‘Black Turtle’ combinations BT Monoculture 3.3 28.0 3.8 31.0 0.5 3.0 Wheat:BT (1:1) 3.0 26.0 2.8 24.9 -0.2 -1.1 Wheat:BT (2:1) 3.0 27.7 2.7 26.1 -0.3 -1.6 95  Treatments Before Planting  (BP) After Final Harvest  (AH) Mean Difference (AH-BP) NH4+ NO3- NH4+ NO3- NH4+ NO3- Wheat-BT (mixed) 3.7 28.3 3.2 26.6 -0.5 -1.7 Wheat Monoculture 3.9 27.5 3.0 21.7 -0.9 -5.8 SEM (±) 0.29 1.98 0.31 1.61 0.14 0.41 LSD0.05 NS NS 0.88 4.58 0.40 1.17 Wheat-fava bean cv. ‘Bell’ combinations Bell Monoculture 4.0 27.3 4.7 33.3 0.7 6.0 Wheat:Bell (1:1) 4.3 27.7 4.5 28.8 0.2 1.1 Wheat:Bell (2:1) 4.3 26.0 4.3 26.5 0.0 0.5 Wheat-Bell (mixed) 4.5 28.7 4.4 28.9 -0.1 0.2 Wheat Monoculture 4.5 29.0 3.6 23.2 -0.9 -5.8 SEM (±) 0.34 1.68 0.38 1.24 0.15 0.39 LSD0.05 NS NS 1.08 3.53 0.43 1.11 RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference   96  Table 4.3 Grain yields, land equivalency ratios and total land output values from monocultures and wheat-bean intercrop combinations. Treatments Grain Yield  (t ha-1): Y1 Grain Yield ( t ha-1): Y2 Land Equivalent Ratio Total Land Outputs Bean Wheat Bean Wheat Y1 Y2 Y1 Y2 Wheat-common bean cv. ‘Red Kidney’ combinations RK Monoculture 2.30 - 2.96 - 1.00 1.00 2.30 2.96 Wheat:RK (1:1) 0.50 2.66 2.51 1.15 1.01 1.23 3.16 3.66 Wheat:RK (2:1) 0.53 2.92 2.95 1.68 1.10 1.56 3.46 4.63 Wheat-RK (mixed) 0.69 2.33 1.86 1.52 1.00 1.14 3.02 3.38 Wheat Monoculture - 3.35 - 2.99 1.00 1.00 3.35 2.99 SEM (±) 0.24 0.17 0.13 0.22 0.04 0.08 0.18 0.17 LSD0.05 0.68 0.48 0.37 0.63 NS 0.23 0.51 0.48 Wheat-common bean cv. ‘Black Turtle’ combinations BT Monoculture 2.79 - 3.84 - 1.00 1.00 2.79 3.84 Wheat:BT (1:1) 0.82 2.66 2.70 0.86 1.09 0.99 3.49 3.56 Wheat:BT (2:1) 0.58 3.09 3.01 1.09 1.13 1.15 3.66 4.10 97  Treatments Grain Yield  (t ha-1): Y1 Grain Yield ( t ha-1): Y2 Land Equivalent Ratio Total Land Outputs Bean Wheat Bean Wheat Y1 Y2 Y1 Y2 Wheat-BT (mixed) 0.56 2.86 1.81 0.92 1.05 0.78 3.42 2.73 Wheat Monoculture - 3.35 - 2.99 1.00 1.00 3.35 2.99 SEM (±) 0.28 0.14 0.22 0.19 0.05 0.06 0.14 0.18 LSD0.05 0.80 0.40 0.63 0.54 NS 0.17 0.40 0.51 Wheat-fava bean cv. ‘Bell’ combinations Bell Monoculture 2.20 - 2.78 - 1.00 1.00 2.20 2.78 Wheat:Bell (1:1) 1.19 3.20 2.41 1.91 1.50 1.51 4.39 4.32 Wheat:Bell (2:1) 0.46 3.66 1.41 2.46 1.30 1.33 4.12 3.87 Wheat-Bell (mixed) 0.58 2.54 1.15 1.86 1.02 1.04 3.12 3.01 Wheat Monoculture - 3.35 - 2.99 1.00 1.00 3.35 2.99 SEM (±) 0.22 0.18 0.20 0.22 0.07 0.08 0.27 0.20 LSD0.05 0.63 0.51 0.57 0.63 0.20 0.23 0.77 0.57 RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference 98  Table 4.4 Total biomass (grain plus shoot biomass) yields, land equivalency ratios and total land output values from monocultures and wheat-bean intercrop combinations. Treatments Total Biomass Yield (t ha-1): Y1 Total Biomass Yield (t ha-1): Y2 Land Equivalent Ratio Total Land Outputs Bean Wheat Bean Wheat Y1 Y2 Y1 Y2 Wheat-common bean cv. ‘Red Kidney’ combinations RK Monoculture 4.92  - 5.43  - 1.00 1.00 4.92 5.43 Wheat:RK (1:1) 1.01 5.59 4.42 2.73 0.99 1.22 6.60 7.15 Wheat:RK (2:1) 1.04 6.03 5.01 3.65 1.06 1.46 7.07 8.66 Wheat-RK (mixed) 1.41 4.90 3.19 3.38 0.98 1.09 6.31 6.57 Wheat Monoculture  - 7.11  - 6.79  1.00 1.00 7.11 6.79 SEM (±)  0.55 0.27 0.28 0.55 0.03 0.08 0.26 0.37 LSD0.05  1.56 0.77 0.80 1.56 NS 0.23 0.74 1.05 Wheat-common bean cv. ‘Black Turtle’ combinations BT Monoculture 5.00  - 6.84 -  1.00 1.00 5.00 6.84 Wheat:BT (1:1) 1.38 5.54 5.00 2.21 1.06 1.06 6.92 7.21 Wheat:BT (2:1) 0.92 6.50 5.55 2.90 1.10 1.24 7.42 8.45 99  Treatments Total Biomass Yield (t ha-1): Y1 Total Biomass Yield (t ha-1): Y2 Land Equivalent Ratio Total Land Outputs Bean Wheat Bean Wheat Y1 Y2 Y1 Y2 Wheat-BT (mixed) 0.90 5.90 3.86 2.43 1.01 0.92 6.80 6.29 Wheat Monoculture  - 7.11  - 6.79  1.00 1.00 7.11 6.79 SEM (±) 0.57 0.20 0.36 0.58 0.04 0.08 0.22 0.39 LSD0.05 1.62 0.57 1.02 1.65 NS 0.23 0.63 1.11 Wheat-fava bean cv. ‘Bell’ combinations Bell Monoculture 4.08  - 5.83  - 1.00 1.00 4.08 5.83 Wheat:Bell (1:1) 2.37 6.59 5.24 4.25 1.51 1.52 8.96 9.49 Wheat:Bell (2:1) 0.87 7.58 3.02 5.59 1.28 1.34 8.45 8.61 Wheat-Bell (mixed) 1.10 5.28 3.39 4.09 1.01 1.18 6.38 7.48 Wheat Monoculture  - 7.11  - 6.79  1.00 1.00 7.11 6.79 SEM (±) 0.43 0.29 0.40 0.49 0.07 0.10 0.32 0.43 LSD0.05 1.22 0.83 1.14 1.39 NS 0.28 0.91 1.22 RK = Red Kidney; BT = Black Turtle; Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least Significant Difference  100  Table 4.5 1000 seed weights, biomass C:N and grain protein content of wheat and bean components in monocultures and wheat-bean intercrop combinations. Treatments Bean Performance Wheat Performance 1000 Seed Weight (g) Biomass C:N Grain Protein (%) 1000 Seed Weight (g) Biomass C:N Grain Protein (%) Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Wheat-common bean cv. ‘Red Kidney’ combinations RK Monoculture 435 482 52.7 50.7 19.8 20.4 - - - - - - Wheat:RK (1:1) 421 488 73.9 72.5 23.3 22.6 45.7 34.2 115 110 10.0 11.0 Wheat:RK (2:1) 447 511 74.0 63.4 24.0 24.8 47.7 37.7 127 120 10.1 10.2 Wheat-RK (mixed) 410 489 69.1 71.1 23.3 23.7 47.3 35.9 132 127 10.3 10.2 Wheat Monoculture - - - - - - 45.7 39.5 137 138 10.0 9.0 SEM (±)  6.66 9.88 2.91 2.29 0.56 0.57 1.37 1.29 4.71 4.64 0.32 0.37 LSD0.05  18.9 28.1 8.28 6.52 1.59 1.62 NS 3.67 13.4 13.2 NS 1.05 Wheat-common bean cv. ‘Black Turtle’ combinations BT Monoculture 143 158 46.6 49.3 22.8 23.5 - - - - - - Wheat:BT (1:1) 134 173 71.8 66.1 23.9 24.8 46.1 29.2 108 101 10.2 10.6 101  Treatments Bean Performance Wheat Performance 1000 Seed Weight (g) Biomass C:N Grain Protein (%) 1000 Seed Weight (g) Biomass C:N Grain Protein (%) Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Wheat:BT (2:1) 137 169 73.8 66.8 22.4 23.4 46.1 28.3 105 107 10.0 10.0 Wheat-BT (mixed) 136 180 60.9 52.3 23.4 25.5 46.4 26.0 114 114 10.2 10.0 Wheat Monoculture - - - - - - 45.7 39.5 137 138 10.0 9.0 SEM (±)  1.95 4.00 3.91 3.02 0.68 0.69 1.42 1.87 5.91 6.54 0.23 0.25 LSD0.05  5.55 11.4 11.1 8.59 NS 1.96 NS 5.32 16.8 18.6 NS 0.71 Wheat-fava bean cv. ‘Bell’ combinations Bell Monoculture 394 445 36.2 34.5 25.1 25.9 - - - - - - Wheat:Bell (1:1) 390 519 39.2 39.8 25.9 25.2 49.1 37.6 113 107 10.4 11.7 Wheat:Bell (2:1) 358 518 43.2 45.7 25.5 26.8 49.2 38.9 113 122 10.1 10.2 Wheat-Bell (mixed) 406 534 36.5 35.6 25.9 25.8 47.4 38.0 127 136 9.6 9.9 Wheat Monoculture - - - - - - 45.7 39.5 137 138 10.0 9.0 SEM (±)  12.6 13.9 1.81 1.83 0.42 0.61 1.05 1.26 4.57 5.2 0.38 0.28 LSD0.05  35.9 39.8 5.15 5.21 NS NS 2.98 NS 13.0 14.8 NS 0.80 RK = Red Kidney; BT = Black Turtle; Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least Significant Difference  102  Table 4.6 Nodule numbers, total N yield, biological nitrogen fixation and transfer by legume in wheat-bean intercrop combinations during 2011-12 at UBC Farm, Vancouver, Canada.  Treatments Year 1 Year 2 Nodules1 Plant-1 Total N Yield (kg ha-1) BNF2 (%) Transfer (%) BNF2 (kg ha-1) Transfer (kg ha-1) Nodules1 Plant-1 Total N Yield (kg ha-1) BNF2 (%) Transfer (%) BNF2 (kg ha-1) Transfer (kg ha-1) Wheat-common bean cv. ‘Red Kidney’ combinations RK Monoculture 6 95 47 - 45 - 15 118 62 - 73 - Wheat:RK (1:1) 10 22 57 4.6 13 1.9 26 103 75 6.7 77 2.7 Wheat:RK (2:1) 9 24 60 2.4 14 1.2 22 131 71 4.7 93 2.4 Wheat-RK (mixed) 11 30 50 3.3 15 1.5 18 79 63 5.4 50 2.4 SEM (±) 1.31 3.67 3.25 - 2.92 - 1.38 4.13 3.44 - 4.21 - LSD0.05 3.69 10.4 9.24 - 8.31 - 3.93 11.7 9.78 - 11.9 - 103  Treatments Year 1 Year 2 Nodules1 Plant-1 Total N Yield (kg ha-1) BNF2 (%) Transfer (%) BNF2 (kg ha-1) Transfer (kg ha-1) Nodules1 Plant-1 Total N Yield (kg ha-1) BNF2 (%) Transfer (%) BNF2 (kg ha-1) Transfer (kg ha-1) Wheat-common bean cv. ‘Black Turtle’ combinations BT Monoculture 5 101 49 - 50 - 8 149 60 - 89 - Wheat:BT (1:1) 8 35 57 -7.6 20 -3.1 11 121 67 -1.1 81 -0.5 Wheat:BT (2:1) 7 23 57 -13.5 13 -6.5 15 128 62 -6.8 79 -3.3 Wheat-BT (mixed) 7 24 51 -9.8 12 -4.2 13 91 58 -3.9 53 -1.7 SEM (±) 0.77 4.66 2.47 - 3.69 - 0.86 4.94 2.08 - 2.72 - LSD0.05 2.19 13.3 7.02 - 10.5 - 2.45 14.1 5.91 - 7.74 - 104  Treatments Year 1 Year 2 Nodules1 Plant-1 Total N Yield (kg ha-1) BNF2 (%) Transfer (%) BNF2 (kg ha-1) Transfer (kg ha-1) Nodules1 Plant-1 Total N Yield (kg ha-1) BNF2 (%) Transfer (%) BNF2 (kg ha-1) Transfer (kg ha-1) Wheat-fava bean cv. ‘Bell’ combinations Bell Monoculture 21 111 62 - 69 - 40 152 75 - 115 - Wheat:Bell (1:1) 34 62 72 11.9 45 6.5 75 129 81 13.9 104 7.6 Wheat:Bell (2:1) 33 23 72 11.8 17 7.7 78 75 89 11.2 67 8.0 Wheat-Bell (mixed) 33 30 75 10.8 23 4.9 66 75 87 10.9 65 5.1 SEM (±) 1.74 4.35 2.18 - 3.17 - 3.67 4.48 3.02 - 3.96 - LSD0.05 4.95 12.4 6.21 - 9.01 - 10.4 12.7 8.59 - 11.3 -  150 days after sowing; 2BNF = Biological Nitrogen Fixation; RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference  105  Table 4.7 Organic carbon and nitrogen yield from grain and shoot biomass in monocultures and wheat-bean intercrop combinations during 2011-12 at UBC Farm, Vancouver, Canada. Treatments Carbon Yield : 2011 (g C m-2 y-1) Carbon Yield : 2012 (g C m-2 y-1) Nitrogen Yield : 2011 (kg/h) Nitrogen Yield : 2012 (kg/h) Grain Shoot Total Grain Shoot  Total Grain Shoot Total Grain Shoot Total Wheat-common bean cv. Red Kidney combinations RK Monoculture 97 113 210 125 119 244 74 21 95 97 21 118 Wheat:RK (1:1) 135 153 288 154 154 308 64 13 77 111 18 129 Wheat:RK (2:1) 145 160 305 195 175 370 73 15 88 149 22 171 Wheat-RK (mixed) 131 148 279 143 142 285 69 14 83 100 15 115 Wheat Monoculture 142 170 312 128 169 297 58 12 70 53 12 65 SEM (±)  5.97 5.9 11.9 6.68 5.44 12.1 1.8 1.1 2.9 10.7 0.96 11.7 LSD0.05  17.0 16.9 33.9 19.0 15.5 34.5 5.1 3.1 8.2 30.6 2.73 33.4 Wheat-common bean cv. Black Turtle combinations BT Monoculture 119 90 209 163 123 286 82 19 101 124 25 149 Wheat:BT (1:1) 147 151 298 153 147 300 79 16 95 123 19 142 Wheat:BT (2:1) 154 167 321 175 179 354 75 17 92 132 23 155 106  Treatments Carbon Yield : 2011 (g C m-2 y-1) Carbon Yield : 2012 (g C m-2 y-1) Nitrogen Yield : 2011 (kg/h) Nitrogen Yield : 2012 (kg/h) Grain Shoot Total Grain Shoot  Total Grain Shoot Total Grain Shoot Total Wheat-BT (mixed) 143 152 295 113 154 267 72 15 87 91 23 114 Wheat Monoculture 142 170 312 128 169 297 58 12 70 53 12 65 SEM (±)  4.49 9.82 14.3 8.85 6.7 15.5 3.9 0.9 4.8 11.1 0.75 11.8 LSD0.05  12.8 27.9 40.7 25.2 19.1 44.2 11.1 2.5 13.6 31.5 2.13 33.7 Wheat-fava bean cv. Bell combinations Bell Monoculture 91 81 172 115 129 244 88 23 111 115 37 152 Wheat:Bell (1:1) 184 200 384 182 227 409 104 27 131 130 42 172 Wheat:Bell (2:1) 175 191 366 166 200 366 84 20 104 105 26 131 Wheat-Bell (mixed) 133 145 278 128 196 324 67 16 83 79 35 114 Wheat Monoculture 142 170 312 127 169 296 58 12 70 53 12 65 SEM (±)  12.3 15.7 28.0 5.8 10.6 16.4 5.8 1.3 7.1 8.4 2.43 10.8 LSD0.05  35.1 44.6 79.7 16.4 30.2 46.6 16.5 3.6 20.2 23.8 6.91 30.8 RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference   107  Table 4.8 Daytime† averages of net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem photosynthesis and net ecosystem productivity in monocultures and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. Treatments Year : 2011 Year : 2012 NEEa (µmol CO2 m-2 s-1) Reb (µmol CO2 m-2 s-1) GEPc (µmol CO2 m-2 s-1) NEPd (mg C   m-2 hr-1) NEEa (µmol CO2 m-2 s-1) Reb (µmol CO2 m-2 s-1) GEPc (µmol CO2 m-2 s-1) NEPd (mg C  m-2 hr-1) Wheat-common bean cv. ‘Red Kidney’ combinations RK Monoculture -4.67 4.90 9.57 202 -5.17 4.60 9.77 223 Wheat:RK (1:1) -3.15 4.47 7.62 136 -3.65 4.17 7.82 158 Wheat:RK (2:1) -4.47 4.84 9.31 193 -4.97 4.54 9.51 214 Wheat-RK (mixed) -2.64 4.73 7.37 114 -3.14 4.43 7.57 136 Wheat Monoculture -4.67 4.49 9.16 202 -4.37 4.19 8.56 189 SEM (±)  0.21 0.27 0.47 12.5 0.54 0.24 0.45 15.9 LSD0.05  0.59 NS 1.35 35.6 1.54 NS 1.28 45.2 108  Treatments Year : 2011 Year : 2012 NEEa (µmol CO2 m-2 s-1) Reb (µmol CO2 m-2 s-1) GEPc (µmol CO2 m-2 s-1) NEPd (mg C   m-2 hr-1) NEEa (µmol CO2 m-2 s-1) Reb (µmol CO2 m-2 s-1) GEPc (µmol CO2 m-2 s-1) NEPd (mg C  m-2 hr-1) Wheat-common bean cv. ‘Black Turtle’ combinations BT Monoculture -4.09 4.72 8.81 177 -4.59 4.42 9.01 198 Wheat:BT (1:1) -2.34 3.88 6.22 101 -2.84 3.58 6.42 123 Wheat:BT (2:1) -2.68 4.51 7.19 116 -3.18 4.21 7.39 137 Wheat-BT (mixed) -1.89 4.52 6.41 82 -2.39 4.22 6.61 103 Wheat Monoculture -4.67 4.49 9.16 202 -4.37 4.19 8.56 189 SEM (±)  0.23 0.27 0.44 16.3 0.6 0.28 0.49 17.4 LSD0.05  0.65 NS 1.26 46.4 1.71 NS 1.39 49.5 Wheat-fava bean cv. ‘Bell’ combinations Bell Monoculture -3.01 4.78 7.79 130 -3.31 4.48 7.79 143 109  Treatments Year : 2011 Year : 2012 NEEa (µmol CO2 m-2 s-1) Reb (µmol CO2 m-2 s-1) GEPc (µmol CO2 m-2 s-1) NEPd (mg C   m-2 hr-1) NEEa (µmol CO2 m-2 s-1) Reb (µmol CO2 m-2 s-1) GEPc (µmol CO2 m-2 s-1) NEPd (mg C  m-2 hr-1) Wheat:Bell (1:1) -4.68 4.06 8.74 202 -4.98 3.76 8.74 215 Wheat:Bell (2:1) -4.50 3.88 8.38 194 -4.80 3.58 8.38 207 Wheat-Bell (mixed) -3.25 4.09 7.34 140 -3.55 3.79 7.34 153 Wheat Monoculture -4.67 4.49 9.16 202 -4.37 4.19 8.56 189 SEM (±)  0.17 0.28 0.32 12.7 0.46 0.29 0.47 17.8 LSD0.05  0.50 NS 0.91 36.1 1.31 NS 1.34 50.6 †Averages of 25, 50 and 75 days after seeding; 1Net ecosystem CO2 exchange (NEE); 2Ecosystem respiration; 3Gross ecosystem photosynthesis also referred to as gross primary productivity of the cropland; 4Net ecosystem productivity; RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference  110  Table 4.9 δ13C values in plant shoot tissue in monocultures and wheat-bean intercrop combinations during 2011-12 at UBC Farm, Vancouver, Canada. Treatments  Year : 2011 Year : 2012 δ13C Legume δ13C Wheat δ13C Legume δ13C Wheat Wheat-common bean cv. ‘Red Kidney’ combinations Red Kidney Monoculture -28.22  -27.31   Wheat:Red Kidney (1:1) -28.97 -29.64 -28.06 -28.73 Wheat:Red Kidney (2:1) -27.71 -29.36 -26.81 -28.45 Wheat-Red Kidney (mixed) -27.83 -29.59 -26.92 -28.68 Wheat Monoculture   -29.95  -30.26 SEM (±)  0.21 0.23 0.18 0.24 LSD0.05  0.59 0.65 0.51 0.68 Wheat-common bean cv. ‘Black Turtle’ combinations Black Turtle Monoculture -27.57  -27.66   Wheat:Black Turtle (1:1) -26.62 -30.12 -26.71 -29.69 Wheat:Black Turtle (2:1) -26.85 -29.93 -26.94 -29.82 111  Treatments  Year : 2011 Year : 2012 δ13C Legume δ13C Wheat δ13C Legume δ13C Wheat Wheat-Black Turtle (mixed) -26.16 -30.17 -26.25 -29.96 Wheat Monoculture   -29.95  -30.26 SEM (±)  0.21 0.19 0.19 0.20 LSD0.05  0.59 NS 0.54 0.58 Wheat-fava bean cv. ‘Bell’ combinations Bell Monoculture -28.37  -27.46   Wheat:Bell (1:1) -28.79 -29.31 -27.88 -28.40 Wheat:Bell (2:1) -28.74 -29.36 -27.83 -28.45 Wheat-Bell (mixed) -29.27 -29.48 -28.36 -28.57 Wheat Monoculture   -29.95  -30.26 SEM (±) 0.19 0.18 0.19 0.20 LSD0.05  0.54 0.51 0.54 0.58 RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference   112  Table 4.10 Crop on crop and crop on weed competition in wheat-bean intercrop combinations. Treatments Crop on Crop Competitions1 Weed Infestation Scores2 Wheat-RK Wheat-BT Wheat-Bell Wheat-RK Wheat-BT Wheat-Bell 30 DAS 70 DAS 30 DAS 70 DAS 30 DAS 70 DAS Year 2011 Cereal:legume (1:1) 2-1 2-1 1-1 7 7 8 8 5 4 Cereal:legume (2:1) 2-1 2-1 1-1 8 7 8 8 4 4 Mixed Cropping 1-1 2-1 1-1 7 6 8 7 5 4 Year 2012 Cereal:legume (1:1) 1-2 1-2 1-1 6 4 8 7 4 3 Cereal:legume (2:1) 1-2 1-2 1-1 6 4 8 8 4 3 Mixed Cropping 1-2 1-2 1-1 6 3 8 7 3 4 Monoculture - Wheat  7 4 8 8 5 4 Monoculture - Legumes 6 4 6 6 4 3 11-1 no competition; 1-2: beans dominate wheat; 2-1: wheat dominates beans; 2 0 = no weed, and 10 = highly infested; RK = Red Kidney; BT = Black Turtle; and DAS = days after sowing   113                                    Wheat-common bean cv. ‘Red Kidney’ plots        Wheat-common bean cv. ‘Black Turtle’ plots          Wheat-fava bean cv. ‘Bell’ plots Figure 4.1 Field layout and treatment composition in completely randomized block design. T1 indicates monocultured legumes, T2 indicates wheat and legumes in rows of 1:1; T3 indicates wheat and legumes in rows of 2 wheat:1 legume; T4 indicates broadcast planting arrangements; and T5 indicates monocultured wheat plots T3 T2 T4 T1 T5 T1 T2 T5 T5 T3 T2 T4 T4 T1 T5 T3 T3 T2 T4 T1 T1 T2 T4 T3 T5 T5 T2 T3 T4 T3 T1 T2 T3 T5 T4 T1 T5 T1 T2 T4 T3 T1 T5 T4 T2 T4 T1 T2 T2 T3 T1 T5 T5 T2 T3 T4 T4 T1 T5 T3 S N E W 114      Figure 4.2 Grain yield of wheat and bean components in monocultures and intercrop combinations.  RK, BT and Bell are bean cultivars   2.6 1.5 1.7 1.3 3.3 1.8 1.8 1.2 2.5 1.8 0.9 0.9 1.9 2.3 1.9 1.8 2.1 1.9 2.6 3.1 2.2 3.2 012345Yield (t/ha) Treatments Bean Wheat115     Figure 4.3 Daytime average gross ecosystem photosynthesis (µmol CO2 m-2 s-1) in monocultures and wheat-bean intercrop combinations during 25, 50 and 75 days after sowing. 6.65 5.66 6.72 5.05 6.14 12.69 9.80 12.40 8.89 11.59 9.67 7.73 9.10 8.47 8.87 051015RK Mono (1:1) (2:1) (mixed) Wheat MonoGEP (µmol CO2 m-2 s-1)  Planting Arrangements 4.3a. wheat-common bean cv. 'Red Kidney'combinations 25 DAS 50 DAS 75 DAS6.29 4.98 5.54 5.11 6.14 11.53 7.66 9.02 7.91 11.59 8.91 6.32 7.28 6.51 8.87 051015BT Mono (1:1) (2:1) (mixed) Wheat MonoGEP (µmol CO2 m-2 s-1)  Planting Arrangements 4.3b. wheat-common bean cv. 'Black  Turtle' combinations 25 DAS 50 DAS 75 DAS5.41 6.22 5.56 5.81 6.14 10.17 11.25 10.86 8.87 11.59 7.79 8.74 8.71 7.34 8.87 051015Bell Mono (1:1) (2:1) (mixed) Wheat MonoGEP (µmol CO2 m-2 s-1)  Planting Arrangements 4.3c. Wheat-fava bean cv. 'Bell' combinations 25 DAS 50 DAS 75 DAS116     Figure 4.4 Daytime average net ecosystem productivity (µmol CO2 m-2 s-1) in monocultures and wheat-bean intercrop combinations during 25, 50 and 75 days after sowing. 2.71 1.87 2.71 2.04 2.49 7.13 4.93 6.73 3.74 6.55 4.92 3.40 4.72 2.89 4.52 02468RK Mono (1:1) (2:1) (mixed) Wheat MonoNEP (µmol CO2 m-2 s-1)  Planting Arrangements 4.4a. wheat-common bean cv. 'Red Kidney'combinations 25 DAS 50 DAS 75 DAS2.39 1.43 1.61 1.18 2.49 6.29 3.76 4.24 3.10 6.55 4.34 2.59 2.93 2.14 4.52 02468BT Mono (1:1) (2:1) (mixed) Wheat MonoNEP (µmol CO2 m-2 s-1)  Planting Arrangements 4.4b. wheat-common bean cv. 'Black  Turtle' combinations 25 DAS 50 DAS 75 DAS1.74 2.66 3.01 2.32 2.49 4.58 6.99 6.29 4.48 6.55 3.16 4.83 4.65 3.40 4.52 02468Bell Mono (1:1) (2:1) (mixed) Wheat MonoNEP (µmol CO2 m-2 s-1)  Planting Arrangements 4.4c. Wheat-fava bean cv. 'Bell' combinations 25 DAS 50 DAS 75 DAS117  CHAPTER 5: BARLEY-PEA INTERCROPPING  A version of this chapter has been published in Field Crops Research as Chapagain, T. and A. Riseman (2014), Barley-Pea Intercropping: Effects on Land Productivity, Carbon and Nitrogen Transformations (DOI: 10.1016/j.fcr.2014.06.014).  This study was conducted at the Centre for Sustainable Food Systems at UBC Farm in Vancouver, BC, during 2011 and 2012 cropping season (May to September) to observe the effects of the proportion of barley and pea genotype and their spatial configurations on crop performance, land productivity, biological N fixation and transfer, gross ecosystem photosynthesis (GEP), and net ecosystem productivity (NEP) within an organic production system. The experimental site is located at 49° 15' 3" N and 123° 14' 20" W, at an altitude of 100 m above mean sea level. Research was conducted under natural climatic conditions using organic production practices. 5.1 Materials and Methods 5. 1.1 Climate description of the study area Climatic data for the experimental site during the spring-summer seasons (May to September) of 2011 and 2012 have been presented in Table 4.1 of the previous section (please refer to 4.1.1). 5.1.2 Soil and site description Soil in the experimental field was a Duric Humo-Ferric Podzol according to the Canadian system of soil classification (AAFC, 1998) whereas it was a Haplorthod in the American system (USDA-SCS, 1992). Four random soil samples from across the whole test site were 118  collected from 0-15 cm depth at the time of plot establishment to characterize soil fertility (i.e., pH, organic matter, total N, δ15N, and available P, K, Ca, Mg, Cu, Zn, Fe, Mn and B). The soil was moderately well drained coarse textured sandy loam with low to moderate fertility. Soil was homogeneous with a pH value of 5.9, organic matter content of 117 g kg-1, total N content of 3.5 g kg-1, δ15N of 3.02 ‰, P of 144 mg kg-1, and K of 183 mg kg-1 based on dry soil. Additional soil samples were taken from two different areas within each plot before planting (Spring-2011) and after final harvest (Fall-2012), and sent to an analytical laboratory (Pacific Soil Analysis Inc., Richmond, Canada) to determine soil mineral N (NH4+ and NO3-) content. The site had not been used for grain production in previous years but had been used for annual vegetable cultivation. The site had been managed under organic vegetable production guidelines for more than the 10 years using green manures and compost. 5.1.3 Experimental details Barley cv. ‘Oxbridge’ and pea cv. ‘Reward’ were selected for intercropping trials based on agronomic performance (i.e., synchronized maturity for combined harvest, yield, protein content and nodulation potential in pea) from cultivar evaluation trials (Chapagain and Riseman, 2012). Plants were grown on the same plots under organic and rain-fed conditions over two years of study, and managed equally across combinations. Research plots (4m x 3m) were arranged in a randomized complete block design (RCBD) with five treatments and four replications (Figure 5.1). Treatments consisted of barley cv. ‘Oxbridge’ and pea cv. ‘Reward’ grown as monocultures, and intercropped in rows of 1:1, 2 barley : 1 pea, and broadcast (Appendix I). In monocultures, barley and pea were planted in 119  rows at the recommended plant density targeting 400 and 60 viable plants m-2, respectively. Row and mixed intercropping consisted of planting barley and pea in proportional replacement design in which the combined density of the population varied as the proportions of the species changed (Jolliffe, 2000). The 1:1 arrangement consisted of planting barley and pea in alternate rows targeting 200 and 30 plants m-2, respectively, whereas, 2:1 arrangement targeted 300 barley and 20 pea plants m-2. In broadcast arrangement, seeding densities of barley and pea were reduced by one half of monoculture densities targeting 200 and 30 plants m-2, respectively, and broadcasted and incorporated evenly into the soil. Barley grown as a monoculture was considered the non-N2-fixing reference plant in analyses. There was a gap at least 50 cm wide between plots to minimize treatment interactions, and 1 meter wide gap between blocks to facilitate management. Pea seeds were inoculated with commercial rhizobia (Garden Inoculant for pea, EMD Crop Bioscience, WI, USA) and planted immediately after inoculation. Barley and pea were sown in mid-May (15-16 May) in rows using a hand seeder (Jang Clean Hand Seeder, Jang Automation Co. Ltd., Cheongju-city, South Korea) with adjustable sprockets (Front: 11, Rear: 14), and seed plates (G-12 for barley and N-6 for pea). Sowing depth varied with seed size and ranged from 3-4 cm for barley and 4-5 cm for pea. No fertilizers, pesticides or fungicides were used. 5.1.4 Data collection and analysis Plant-based parameters: Data were recorded for plant height (from soil surface to the tip of apical leaf), number of effective tillers (spikes) m-2, days to harvest, number of nodules (in pea), pod or spike length, seed number, grain yield (t ha-1), 1000 seed weight, and harvest 120  index [HI, defined as a ratio of economic yield (grain yield) to the total above ground biomass (grain yield + shoot biomass)]. Chlorophyll concentration index (CCI) was measured using a handheld chlorophyll meter (Model CCM 200 Plus, Opti-Sciences Inc., New Hampshire, USA) on the flag leaf and the 3rd leaf prior to the flowering (50 DAS). Nodulation was assessed by counting and inspecting the nodules of 3 randomly selected pea plants in both monoculture and intercrop plots prior-to-flowering (i.e., 50 days after sowing) following a procedure similar to Chapagain and Riseman (2012).  Spike or pod color was a determinant of maturity and considered ready for harvest when they were straw-colored and 80% of the grains of the spike were in the hard-dough stage. Plants in the middle section of each plot, leaving two rows on either side, were harvested at maturity for yield measurements. Sub-samples were collected from two different 1 m2 areas within each plot, and averaged. Shoots of pea and non-N2-fixing barley reference plants were harvested by hand leaving 5 cm tall stubble, oven dried at 70°C for 72 hours, and threshed separately by a stationary thresher. Individual crop yield (grain and shoot biomass) was calculated to permit comparison of yields, land equivalent ratios (LER) and N contents with those when they were grown alone. Relative and total intercrop productivity: System productivity was estimated using the Land Equivalent Ratio (LER) which compares the yield obtained by intercropping two or more species together with yields obtained by growing the same crops as monocultures. The LER for two intercrop species in proportional replacement design were calculated as follows (Mead and Willey, 1980): LER = intercrop yieldbarley/mono yieldbarley + intercrop yieldpea/mono yieldpea  121  The yields of mono and intercrop species were calculated as t ha-1. Intercropped plots with LER values greater than 1.0 produced a yield advantage while plots with values less than 1.0 showed a yield disadvantage. Grain yield was expressed at 12.5% moisture. LER in terms of total plant mass (grain + shoot biomass) production was also determined. Intercrop productivity was also assessed in terms of Total Land Output (TLO, Jolliffe and Wanjau, 1999) as follows: TLO = barley yield + pea yield Intercrop plots with greater TLO values compared to monoculture showed a yield advantage. Tissue N, C, 15N and 13C analyses: Plant tissue samples for N and C analyses were prepared from the shoots (i.e., leaves and stem) and grains separately of both nodulated pea and non-fixing barley plants harvested at maturity while samples for 15N and 13C analyses were prepared from all aboveground biomass harvested at pod or grain filling stages in pea and barley, respectively. Samples were dried at 70oC for 72 hours and subsequently homogenized into fine powder (<6 mm) using a 115 V Wig-L-Bug grinding mill (International Crystal Laboratories, Garfield, NJ, USA). The subsamples, 2-3 mg each, were then weighed into tin capsules using a Mettler AT20 micro-balance (Toledo, OH), and analyzed for total N, C, δ15N and δ13C by high-temperature flash combustion using an elemental analyzer (Vario EL Cube elemental analyzer, Elementar Analysensysteme GmbH, Hanau, Germany) coupled by continuous flow to an isotope ratio mass spectrometer (Isoprime isotope ratio mass spectrometer, Isoprime Ltd., Cheadle, UK). 122  The percentage of plant N derived from atmospheric N2 (% NDFA), based on the natural variation in the abundance of 15N, was calculated according to Shearer and Kohl (1988): % NDFA = 100 x (δ15Nref − δ15Nleg) / (δ15Nref − δ15Nfix)  where δ15Nref is the δ15N value for the non-fixing barley reference plant grown alone and dependent on soil N; δ15Nleg is the δ15N value for the nodulating and potentially N2-fixing pea grown in intercrop plots where fixed N and soil N are available as N sources; and δ15Nfix is the δ15N value for the nodulating pea plant when they are totally dependent on biological nitrogen fixation as the N source. In addition, the quantification of N transferred to the companion barley plant was determined by using the following formula (He, 2002): % N transfer = 100 x (δ15N barley mono - δ15N barley intercrop) / δ15N barley mono where δ15N barley mono is the δ15N value for the barley when they are grown alone and dependent on soil N, and δ15N barley intercrop is the δ15N value for the companion barley plants grown in intercrop plots. The estimates of N transfer are performed using treatment averages. In order to get the δ15Nfix value for pea, it was grown in plant boxes filled with quartz sand, and supplied with N-deficient media and commercial rhizobia (Garden Inoculant for pea, EMD Crop Bioscience, WI, USA) as inoculum. The medium was prepared following the modified version of Mae and Ohira (1981) and contained: 50 mM Fe-EDTA, 50 mM KCl (MW 74.55), 0.5M K2SO4 (MW 174.26), 1M KH2PO4 (MW 136.09), 0.5 M MgSO4·7H2O (246.49), 1M CaCl2 (MW 110.98) as macroelements; and 0.5 mM CuSO4·5H2O (MW 249.7), 25 mM H3BO3 (MW 61.84), 2 mM ZnSO4·7H2O (MW 287.55), 2 mM MnSO4·H2O (MW 123  169.01), and 0.5 mM Na2MoO4·2H2O (MW 241.9) as microelements. The macro and microelement solutions were prepared separately with distilled water, and then poured at 5-10 ml per day into plant boxes each containing 4 plants. Grain nitrogen values were converted to crude protein levels as %N x 6.25 for pea, and %N x 5.8 for barley (Jones, 1931). Total N and C yields were derived by using grain and shoot biomass yield, and N and C content in grain and shoot biomass in each crop component. Gross ecosystem photosynthesis, ecosystem respiration and net ecosystem productivity measurements: Field measurements of net ecosystem CO2 exchange (NEE) in cropland (i.e., monoculture and intercrop plots) and ecosystem respiration (Re) were conducted at the soil surface using a dynamic closed automated chamber connected to a portable CO2 gas analyzer by following a procedure similar to that of Jassal et al. (2010). The automated chamber consisted of a PVC cylinder that was equipped with a calibrated photosensor (RainWise Quantum Solar Sensor, RainWise Inc., Bar Harbor, ME, USA) for the measurement of photosynthetically active radiation (PAR), an ordinary axial fan to ensure uniform CO2 concentration in the chamber, and outlet vent tube of 15 cm long and 3 mm internal diameter to prevent pressure differences between the chamber and the atmosphere. The cylinder dimensions were 19.5 cm internal diameter, 60.8 cm height, and 1 cm wall thickness. The chamber effective volume when deployed was 20.34 dm3 while the surface area covered by the chamber was 0.0298 m2. The cylinder was inserted to a depth of about 2 cm below the soil surface during field measurements. The CO2 gas analyzer unit consisted of an infrared gas analyzer (IRGA) (model LI-820, LI-COR Inc., Lincoln, NE), a 21X data logger (model 21X, Campbell Scientific Inc. (CSI), Logan, 124  UT, USA), an AC linear pump (model SPP-40GBLS-101, GAST Manufacturing Corp., Benton Harbor, MI, USA), and a data storage module (SM192, CSI.). The IRGA was calibrated in the UBC Biometeorology and Soil Physics Laboratory with cylinders of CO2 in dry air calibrated using standards provided by the Canadian Greenhouse Gases Measurement Laboratory, Meteorological Service of Canada, Downsview, Ontario. The effective volume was assumed to be approximately 12% higher than the geometric headspace volume, due to the near-surface soil porosity and the adsorption of CO2 on the soil surface and chamber walls (Jassal et al., 2010; 2012). NEE in a cropland was measured from two different areas within each plot by placing the chamber on the soil surface three times a day (i.e., morning, afternoon and evening) at 25, 50 and 75 days after sowing enclosing the plants (Appendix J). This was followed by the measurement of Re by placing the chamber on bare soil plus plant roots after harvesting. When measuring NEE and Re, the pump was turned on 1 minute before chamber placement on the soil surface and continued for 3 minutes. The IRGA and the axial fan in the cylinder were kept on between measurements. The time rate of change in the CO2 mole fraction in the chamber headspace (dC/dt, µmol mol-1 s-1) during a period of 90 seconds beginning 20 seconds after chamber closure, which was found to be linear, was used to calculate the flux, F (µmol m-2 s-1) as follows (Jassal et al., 2005): F =             where P is the atmospheric pressure (Pa), R is the universal gas constant (8.314 J mol-1 K-1), T is the temperature of the chamber air (K), V is the geometric volume of the chamber headspace (0.02034 m3), A is the surface area covered by the chamber (0.0298 m2), and a is 125  the ratio of the effective volume to the geometric volume of the chamber (i.e., 1.12). Since the rate of increase in relative humidity in the chamber was less than 2% minute-1 over the 90 seconds, the water vapour dilution effect was estimated to be less than 1% of F, and was therefore neglected (Welles, 2001). Gross ecosystem photosynthesis - GEP (i.e., Re minus NEE), often referred to as gross primary productivity of the cropland, and net ecosystem productivity - NEP (i.e., NEE with a negative sign, often referred to as seasonal net carbon sequestration) were calculated for all planting arrangements. The micromole values of NEP were converted to mg C m-2 hr-1 using a conversion factor of 43.2 (Jassal et al., 2005). When NEE is positive, the ecosystem is releasing C to the atmosphere while when negative, the ecosystem is absorbing C from the atmosphere. Crop management parameters: General observations were made 30 and 70 days after sowing on the type, number and the amount of weeds present, and insect pest and disease pressures with regard to type and nature of damage. Disease of economic importance e.g., Scald or Leaf Blotch (Rhynchosporium secalis), Stem/Leaf/Stripe/Yellow/Brown Rust (Puccinia spp.), and Septoria Leaf Spot or Glume Blotch (Septoria tritici) were monitored and noted over the course of the season as suggested by Chapagain and Riseman (2012). Data analysis: Data were analyzed using MSTAT-C (MSU, 1993) and MATLAB (Mathworks- MATLAB and Simulink for Technical Computing, Natick, MA, USA). Analyses of variance were performed on individual plot data for plant performance metrics, yields, and C and N accumulation. Fisher’s least significant differences were calculated with 5% significance levels in MSTAT-C using the error variance from the analysis. Simple correlation 126  coefficients and coefficients of determination were determined between selected parameters using Statistical Package for the Social Sciences (SPSS) software. 5.2 Results 5.2.1 Soil mineral nitrogen and δ15N content Soil mineral N (NH4+ and NO3-) values from samples collected before planting and after final harvest are presented (Table 5.1). Pre-plant plots were homogenous and deemed suitable for 15N natural abundance studies as suggested by Shearer and Kohl (1988). After harvest, plots varied in their N content. Specifically, monoculture pea plots displayed the highest increase in mineral N (i.e., +0.6 mg NH4+ and +6.4 mg NO3-  kg-1 dry soil) whereas barley monoculture plots displayed the greatest decrease (i.e., -0.8 mg NH4+ and -4.4 mg NO3- kg-1 dry soil) (Table 5.1). Intercrop plots displayed intermediate N values with the greatest net increase of about +0.1 mg NH4+ and +0.7 mg NO3-  kg-1 dry soil from the 1:1 plots. The average δ15N value of nodulating pea grown in N-free media was -1.08 ‰ while the non-fixing barley reference plants grown in field as monoculture had average δ15N value of 2.38 ‰ (data not shown). There was sufficiently a large difference between soil δ15N (3.02 ‰) and atmospheric δ15N (0 ‰) in order to measure dilution effects as suggested by Shearer and Kohl (1988). 5.2.2 Plant performance indices Grain yield, land equivalency ratio (LER), and total land output (TLO), under monoculture and intercrop arrangements, are presented (Table 5.2). In monoculture plots, pea yield increased from 5.1 t ha-1 in year 1 to 5.4 t ha-1 in year 2 resulting in a two-year average of 127  5.3 t ha-1. However, barley yield declined over the 2 years from 4.3 t ha-1 in year 1 to 3.6 t ha-1 in year 2 with an average of 4 t ha-1. System productivity indices, TLO and LER, were generally higher in intercrop plots with productivity increasing between 12-32% compared to monoculture plots. The 2:1 arrangement produced the greatest increase (32%) and highest individual year and two-year average for LER values (1.48 and 1.32, respectively) with the same occurring for TLO values (6.53 t ha-1 and 5.9 t ha-1, respectively) (Table 5.2). The TLO and LER values calculated using total biomass production (i.e., all above ground tissue) displayed similar trends as when calculated with grain yield, with a 28% increase in land productivity from the 2:1 arrangement (Table 5.3). Pea in intercrop plots displayed significantly higher harvest index (HI) and increased C:N ratio compared to monoculture plots with the highest values from the 2:1 arrangement (Table 5.4). Intercropped pea displayed up to a 24% higher C:N ratio compared to monoculture plots due to reduced biomass N in intercrops. Pea grain protein, on the other hand, was not significantly affected by intercropping. Pea performance in intercrop and monoculture plots improved significantly in years 2 as compared with year 1, with increased plant biomass, longer and more plentiful pods, greater grain yield and total biomass. Barley in intercrop plots showed notable responses for chlorophyll concentration index- CCI, biomass C:N ratio and grain protein compared to monoculture plots (Table 5.4). Barley displayed the highest biomass N (thus lowering C:N ratio) and grain protein percentage when planted in the 1:1 arrangement. Unlike pea, the performance of barley declined over the two years in both monocultured and intercropped plots, with lower 1000 seed weight, lower HI, and lower yield across all arrangements (Table 5.2, Appendix C).  128  5.2.3 Biological N2 fixation and transfer Intercropping had a significant impact on nodulation, percent N derived from symbiotic fixation and N transfer to the companion barley plants (Table 5.5). The number of nodules and the proportion of nitrogen fixed by pea were significantly higher in intercrop plots as compared to monoculture pea plots. Pea in intercrop plots developed an average of 27-45% more nodules than in monoculture plots resulting in 9-17% more N derived from symbiotic N2 fixation. On average, the 1:1 arrangement generated the highest percent of biologically fixed N2 (72%) and the highest rate of N-transfer to barley (11%) compared to N transfer in the 2:1 arrangement (4%) and the mixed planting arrangement (2%). Pea in the 1:1 arrangement displayed the highest amount of aboveground biomass N (average of 108 kg ha-1) compared to other planting arrangements of which 78 kg (72%) was derived from symbiotic N2 fixation. Nitrogen fixation and transfer occurred within a season and improved significantly in year 2 as compared with year 1 (Table 5.5). Pea in the 1:1 arrangement fixed an average of 69% of total biomass N in year 1 to 76% in year 2, and transferred an average of 6% of N in barley biomass in year 1 to 16% in year 2 (Table 5.5).  5.2.4 Biomass N and C accumulation Monocultured pea accumulated the greatest N in biomass followed by all intercrop arrangements with the monocultured barley accumulating the least. Pea monoculture accumulated an average of 54 kg N ha-1 (Table 5.6) in shoot biomass of which 30 kg was derived from symbiotic N fixation. Pea in intercrop plots displayed reduced biomass N and a decrease in total N accumulation due to reduced total biomass. However, this amount still reduced the N requirement of the subsequent crop by 14-22 kg ha-1 (Table 5.6). 129  Compared to monoculture barley, the total amount of shoot biomass N accumulated in intercrop plots was 122-202% higher (Table 5.6). Barley in intercrop plots displayed increased biomass N compared to barley monoculture. However, the total amount of N accumulated by the barley component decreased slightly with increasing pea density (Table 5.6). Barley-pea in 1:1 arrangement accumulated the highest N in aboveground biomass (grain plus shoot biomass) (160 kg N ha-1) followed by 159 kg N ha-1 in the 2:1 arrangement. Barley and pea grown in 2:1 arrangements accumulated 53% more carbon (196 g C m-2 yr-1) in shoot biomass compared to the monoculture barley plots (128 g C m-2 yr-1) (Table 5.7). The 1:1 and mixed arrangements also accumulated more C in shoots than the monoculture barley plots with 48% and 36% higher C, respectively. However, the greatest amount of C accumulated in shoot biomass was from the monoculture pea plots (232 g C m-2 yr-1) while the least was accumulated in the barley monoculture plots. In addition, the total biomass C produced (i.e., grain plus shoot biomass) was highest in the 2:1 plots (442 g C m-2 y-1, i.e., 50% higher than monocultured barley (Table 5.7). In peas, strong correlations were observed between the amount of organic C and grain yield (r2=0.98) and harvest height (r2=0.90) (Appendix G). Also, a significant correlation was identified between biomass N and biomass C in pea (r2=0.99), and barley (r2=0.66) (Appendix H). 5.2.5 Net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem photosynthesis and net ecosystem productivity Daytime averages of NEE, Re, GEP and NEP in monoculture and intercrop plots are presented (Table 5.8) with NEE, GEP and NEP varying by spatial arrangement. The greatest 130  GEP values were observed during the mid-growth stage (50 days after seeding i.e., just prior to flowering, Figure 5.2) in all planting arrangements. Cropped areas averaged 148%-224% more CO2 fixation (i.e., greater GEP) than CO2 loss (i.e., Re) from bare soil plus plant roots with the highest GEP from the 2:1 arrangement. The 2:1 arrangement also displayed the greatest NEP resulting in the sequestration of the most C with a seasonal average rate of 229 mg C m-2 hr-1 (i.e., 10% higher than barley monoculture plots). Mixed crop arrangements, on the other hand, displayed the least NEP (Figure 5.3) leading to the lowest C sequestration compared to all other combinations (Table 5.8). Pea in intercrop plots fixed less CO2 than monocultured pea. However, the proportion of CO2 fixed by the barley component was higher in row intercrop plots than monocultured barley (data not shown). 5.2.6 Crop competition, weed and disease pressure The most common weeds in either monoculture or intercrop plots were common chickweed (Stellaria media L.), green smartweed (Polygonum lapathifolium L.), prostrate knotweed (Polygonum aviculare L.), pigweed (Amaranthus spp.), crab grass (Digitaria spp.), barnyard grass (Echinochloa crusgalli L.), black nightshade (Solanum nigrum L.), and field horsetail (Equisetum arvense L.). Pigweed was observed early in the season along with chickweed. Common chickweed, an excellent colonizer that forms a succulent mat on the soil surface, was the predominant weed from mid to late season. All crop plots grew well with 3 manual weedings, 15, 30 and 45 days after sowing. In general, total weed biomass was greater in barley and pea monoculture plots during early to mid-season compared 131  with late-season (Table 5.9). Weed biomass in intercrop plots was reduced as barley density increased. In general, the occurrence of barley disease was low over the two production years. When present, the most prevalent diseases included stem rusts (Puccinia spp.) and Septoria leaf blotch (Septoria spp.). No significant differences were observed among treatments regarding the occurrence or the extent of disease. Septoria leaf blotch infection was most severe early in the season whereas stripe and stem rusts were most severe mid to late season.  Higher biomass of pea suppressed reproductive growth of barley resulting into fewer filled grains, lower 1000 seed weight and HI of barley components when they were planted in 1:1 arrangement compared to all other planting arrangements (Table 5.9, Appendix C).  5.3 Discussion Our organically managed intercropping trials showed several benefits of pairing barley and pea including greater land productivity (12-32% higher compared to monocultured barley), higher biomass quality (increased N and protein content), higher C and N accumulation in aboveground biomass, and greater GEP and NEP. Higher yields and greater land productivity are reported when barley is intercropped with pea. However, the degree of success varied greatly with the growing conditions and the proportion of species used in the field (Hauggaard-Nielsen et al., 2009; Jensen, 1996; Lauk and Lauk, 2008). Our experiment indicated that increasing barley density in intercrops (i.e., 2:1 arrangement) yielded higher productivity (32%) than 1:1 or broadcast arrangements. Barley:pea in 1:1 and broadcast arrangements performed poorly due to pea shading the barley plants 132  resulting in a higher proportion of unfilled grains. Lauk and Lauk (2008) reported that increasing pea density in intercrops led to smaller grains and lower yields. Chen et al. (2004) reported that intercropping barley and winter pea (Pisum sativum sp. arvense) yielded 5-24% higher LER values based on biomass, and indicated that separate row arrangements were more advantageous than growing each species in separate fields. Similarly, Hauggaard-Nielsen et al. (2009) found 25-30% more grain yield in barley-pea intercrops due to better use of plant resources including water, light, and nutrients. Sahota and Malhi (2012) also reported that barley-pea intercrops required 7-17% less land than monoculture production to produce the same yield. The proportion of pea in the mixture affects the cereal’s yield and quality. Barley in our experiment displayed increased biomass N and grain protein content with increasing pea density and is perhaps related to more N available from the pea component and/or greater soil N uptake due to increased competition. Lauk and Lauk (2008) also showed a positive association of pea density with increased protein content of the cereal grain. Intercropping cereals with crops that increase the protein content of the forage has both nutritional and financial value (Lithourgidis et al., 2011). This was true for our experiment and other barley-pea combinations (Carr et al., 2004). Intercropping with a legume offers an opportunity for low input organic systems to better use N complementarity without compromising yield. This study demonstrated that pea fixed 9-18% more N in intercrop plots perhaps in response to the increased competition with barley plants for soil N and promoting pea’s greater reliance on symbiotic N2-fixation. Hauggaard-Nielsen et al. (2009) reported that pea-barley intercrops used nitrogen sources 17 to 31% more efficiently than by the monoculture plots. They further suggest that this 133  could in part be due to the increased acquisition of soil mineral N by the barley component which promoted pea to rely more on internal N2-fixation. Izaurralde et al. (1992) also reported increased N yield, greater N-fixation efficiency, and more shoot and root residue-N mineralization for subsequent crops when field pea and barley were intercropped. Biological nitrogen fixation by pea can supplement or replace the nitrogen requirement of the subsequent crop. This is especially true under low soil N conditions (Fujita et al., 1992; Lunnan, 1989). Our results showed that intercropping can increase soil N pools by 22-30 kg ha-1 through shoot biomass, and be available for use by the subsequent crop. Furthermore, the highest rate of N-transfer (up to 8.6 kg N ha-1, i.e., 16% N in barley) from pea was observed in the 1:1 arrangement compared to the 2:1 or mixed planting arrangement. This further shows that N transfer occurred within a season at a greater rate from higher pea density plots in row arrangements (1:1), perhaps due to physical co-location of the root systems that facilitate more direct N transfer between species. The benefits of legume-based intercrop have been shown through direct plant-to-plant N transfer but with significant variation reported in the amount of N transferred, i.e., ≤5 to 20% of the N in the receiver plants (He et al., 2003; 2009; Johansen and Jensen, 1996). Only limited information is available regarding NEE, GEP and NEP from temperate cereal-legume intercrop systems, with no reports specifically for barley and pea combinations. When a legume and non-legume species are planted together in an intercropping system, the legume might positively affect the performance of the non-legume species through increased N availability in the system (Hartwig et al., 2002; Zanetti et al., 1997), and therefore may support greater overall ecosystem productivity. Our 2:1 arrangement fixed the greatest amount of CO2 (i.e., greatest GEP) and sequestered higher C in soil (i.e., greatest 134  NEP) compared to the 1:1, mixed or barley monoculture plots. Ecosystem respiration rates across all treatments were not affected by plot composition and were comparable with the values reported by Jassal et al. (2005) for our geographic zone (i.e., Vancouver, BC region). Dyer et al. (2012) also reported an increase in soil organic carbon (SOC) concentration and a lowering of GHG emission rates compared to when either crop was grown as a monoculture. Overall, the specific intercrop combination of barley and pea may provide a new opportunity to better manage nutrients in a small grain production system, one that fulfills both economic and environmental interests through higher land productivity, improved grain and biomass quality, increased GEP and NEP, and reduced reliance on mineral fertilizer inputs. 5.4 Conclusions Our trials on barley-pea intercrop arrangements revealed significant and positive responses for higher total land outputs (TLO) and land equivalent ratios (LER), thereby increasing land productivity compared to monoculture counterparts. Biomass and grain nitrogen content of the barley component increased significantly with a higher pea density (i.e., 1:1 arrangement) while the total amount of N accumulated by pea decreased with increasing barley density (i.e., in 2:1 arrangement) due to a reduction in pea biomass. Intercropping was associated with increased nodulation, percent N derived from symbiotic N2 fixation, N and C accumulation in aboveground biomass, soil mineral N balance, and greater NEP thereby sequestering C with a seasonal daytime average rate of 229 mg C m-2 hr-1 (i.e., 10% higher than barley monoculture plots). This study demonstrated that intercropping barley and pea is an efficient strategy to achieve higher land productivity, N and C yields, and higher C sequestration than when barley was grown as a monoculture, 135  and that increased leaf chlorophyll concentration coupled with greater availability of N and CO2 fixation were associated with higher NEP and yields. Also, planting barley and pea in rows of 2:1 appeared to be the most productive arrangement compared to other combinations.   136  Table 5.1 Soil mineral nitrogen (NH4+ and NO3-; mg kg -1 dry soil) before planting (Spring-2011) and after final harvest (Fall-2012) in monocultures and intercrop plots. Treatments Before Planting (BP) After Final Harvest (AH) Mean Difference (AH-BP) NH4+ NO3- NH4+ NO3- NH4+ NO3- Pea Monoculture 3.3 27.0 3.9 33.4 0.6 6.4 Barley:Pea (1:1) 3.2 25.7 3.3 26.4 0.1 0.7 Barley:Pea (2:1) 3.2 25.2 3.0 25.4 -0.2 0.2 Barley-Pea (mixed) 3.2 25.0 3.0 25.4 -0.2 0.4 Barley Monoculture 3.0 26.0 2.2 21.6 -0.8 -4.4 SEM (±)  0.10 0.69 0.18 1.03 0.08 0.34 LSD0.05  NS NS 0.51 2.93 0.23 0.97 SEM = Standard Error of the Mean; and LSD = Least Significant Difference   137  Table 5.2 Grain yields, land productivity, biomass C:N and grain protein from monoculture and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. Treatments Grain Yield  (t ha-1): Y1 Grain Yield (t ha-1): Y2 LER1 TLO2 Pea Barley Pea Barley Y1 Y2 Y1 Y2 Pea Monoculture 5.14 - 5.41 - 1.00 1.00 5.15 5.41 Barley:Pea (1:1) 1.87 3.06 3.10 2.37 1.07 1.23 4.93 5.47 Barley:Pea (2:1) 1.57 3.65 3.57 2.96 1.15 1.48 5.22 6.53 Barley-Pea (mixed) 1.82 3.17 2.78 2.35 1.09 1.16 4.99 5.13 Barley Monoculture - 4.31 - 3.61 1.00 1.00 4.31 3.61 SEM (±)  0.45 0.18 0.34 0.23 0.06 0.08 0.14 0.29 LSD0.05  1.28 0.51 0.97 0.65 NS 0.23 0.40 0.83 1Land Equivalent Ratio (Mead and Willey, 1980); 2Total Land Output (Jolliffe and Wanjau, 1999); Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least Significant Difference    138  Table 5.3 Total biomass (grain plus shoot biomass) yields, land equivalency ratios and total land output values from monocultures and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. Treatments Total Biomass Yield (t ha-1): Y1 Total Biomass Yield (t ha-1): Y2 LER1 TLO2 Pea Barley Pea Barley Y1 Y2 Y1 Y2 Pea Monoculture 11.02 - 10.13 - 1.00 1.00 11.02 10.13 Barley:Pea (1:1) 3.82 5.28 5.34 4.74 1.07 1.25 9.10 10.08 Barley:Pea (2:1) 2.94 6.15 5.95 5.61 1.12 1.45 9.09 11.56 Barley-Pea (mixed) 3.27 5.44 4.61 4.65 1.05 1.17 8.71 9.26 Barley Monoculture - 7.25 - 6.52 1.00 1.00 7.25 6.52 SEM (±)  1.11 0.26 0.72 0.25 0.05 0.07 0.38 0.47 LSD0.05  3.16 0.74 2.05 0.71 NS 0.20 1.08 1.34 1Land Equivalent Ratio (Mead and Willey, 1980); 2Total Land Output (Jolliffe and Wanjau, 1999); Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least Significant Difference    139  Table 5.4 Harvest index, biomass C:N, chlorophyll concentration, and grain protein content in monocultures and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. Treatments Pea Performance Barley Performance HI1 (%) Biomass C:N CCI2 Biomass C:N Grain Protein (%) Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Pea Monoculture 46.7 53.4 44.1 41.7 - - - - - - Barley:Pea (1:1) 48.9 58.2 42.5 42.1 14.7 13.3 104 107 9.0 9.3 Barley:Pea (2:1) 55.7 60.5 54.4 51.4 15.2 14.7 123 120 8.0 8.1 Barley-Pea (mixed) 53.3 60.3 49.7 52.9 14.4 13.8 115 113 8.2 8.2 Barley Monoculture - - - - 10.2 10.4 123 128 7.1 7.3 SEM (±)  1.12 1.03 1.83 1.68 0.89 0.72 2.76 2.40 0.26 0.31 LSD0.05  3.19 2.93 5.21 4.78 2.53 2.05 7.85 6.83 0.74 0.88 1Harvest Index; 2Chlorophyll Concentration Index per 71mm2; Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least Significant Difference    140  Table 5.5 Nodule numbers, total N yield, biological nitrogen fixation and transfer by pea in monoculture and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. Treatments Nodules Plant-1 Total N Yield (kg ha-1) BNF1 (%) Transfer (%) BNF1 (kg ha-1) Transfer (kg ha-1) Year 1 Pea Monoculture 4 244 52 - 127 - Barley:Pea (1:1) 5 85 69 5.6 59 2.9 Barley:Pea (2:1) 5 66 60 1.5 40 0.8 Barley-Pea (mixed) 6 74 55 0.3 41 0.2 SEM (±) 0.52 6.18 2.39 - 5.67 - LSD0.05 1.48 17.6 6.80 - 16.1 - Year 2 Pea Monoculture 7 248 58  144 - Barley:Pea (1:1) 11 130 76 16.6 100 8.6 Barley:Pea (2:1) 9 141 68 6.3 96 3.5 Barley-Pea (mixed) 10 108 78 3.6 84 1.7 SEM (±) 0.69 7.56 3.12 - 6.43 - LSD0.05 1.96 21.5 8.87 - 18.3 - 1Biological Nitrogen Fixation; SEM = Standard Error of the Mean, and LSD = Least Significant Difference   141  Table 5.6 Average nitrogen yield from grain and shoot biomass in monocultures and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. Treatments Grain N (kg ha-1) Shoot Biomass N  (kg ha-1) Total N Yield (kg ha-1) Pea Barley Total Pea Barley Total Pea Monoculture 192  192 54  54 246 Barley:Pea (1:1) 86 43 129 22 9 31 160 Barley:Pea (2:1) 87 46 133 16 10 26 159 Barley-Pea (mixed) 77 39 116 14 9 23 139 Barley Monoculture  47 47  10 10 57 SEM (±) 6.5 3.0 6.3 5.45 0.70 4.15 12.3 LSD0.05 18.6 8.6 17.9 15.5 NS 11.8 34.9 SEM = Standard Error of the Mean, and LSD = Least Significant Difference   142  Table 5.7 Average carbon yield from grain and shoot biomass in monocultures and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. Treatments Grain C (g C m-2 y-1) Shoot Biomass C (g C m-2 y-1) Total C Yield (g C m-2 y-1) Pea Barley Total Pea Barley Total Pea Monoculture 221  221 232  232 453 Barley:Pea (1:1) 106 115 222 91 100 190 412 Barley:Pea (2:1) 108 139 247 83 113 196 443 Barley-Pea (mixed) 96 114 210 72 102 174 384 Barley Monoculture  166 166  128 128 294 SEM (±) 9.62 7.78 9.60 12.9 4.4 9.44 16.1 LSD0.05 27.4 22.1 27.3 36.7 12.6 26.8 45.8 SEM = Standard Error of the Mean, and LSD = Least Significant Difference   143  Table 5.8 Daytime† averages of net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem photosynthesis and net ecosystem productivity in monocultures and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. Treatments Leaf Area (cm2) NEE1 (µmol CO2 m-2 s-1) Re2 (µmol CO2 m-2 s-1) GEP3 (µmol CO2 m-2 s-1) NEP4 (mg C m-2 hr-1) Legume Plant -1 Barley Tiller -1 Pea Monoculture 957 - -4.16 5.42 9.58 180 Barley:Pea (1:1) 515 60 -4.27 5.26 9.53 184 Barley:Pea (2:1) 729 81 -5.31 5.20 10.51 229 Barley-Pea (mixed) 436 68 -3.21 4.98 8.19 139 Barley Monoculture - 65 -4.80 5.30 10.10 207 SEM (±)  67.6 2.5 0.23 0.30 0.63 27.6 LSD0.05  192.3 7.2 0.68 NE 1.79 78.5 †Averages of 25 (PAR: 1404 µmol photons m-2 s-1, and inside chamber temperature 32.5oC), 50 (PAR: 1545 µmol photons m-2 s-1, and inside chamber temperature 34.6oC), and 75 (PAR: 1482 µmol photons m-2 s-1, and inside chamber temperature 32.3oC) days after seeding; 1Net ecosystem CO2 exchange; 2Ecosystem respiration; 3Gross ecosystem photosynthesis also referred to as gross primary productivity of the cropland; 4Net ecosystem productivity; RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference  144  Table 5.9 Crop on crop and crop on weed competition in barley-pea intercrop combinations during 2011-12 at UBC Farm, Vancouver, Canada. Treatments Crop on Crop Competitions1 Weed Infestation Scoring2 Year 1 Year 2 Year 1 Year 2 30 DAS 70 DAS  30 DAS  70 DAS Pea Monoculture 0 0 7 2 6 2 Barley:Pea (1:1) 1-2 1-2 5 4 4 4 Barley:Pea (2:1) 1-1 1-1 4 4 4 4 Barley-Pea (mixed) 1-1 1-1 4 3 3 2 Barley Monoculture 0 0 6 4 5 4 11-1 no competition; 1-2: legume dominates cereals; 20 = no weed, and 10 = highly infested; and DAS = days after seeding   145          Figure 5.1 Field layout and treatment composition in completely randomized block design. T1 indicates monocultured pea, T2 indicates barley and pea in rows of 1:1; T3 indicates barley and pea in rows of 2 barley:1 pea; T4 indicates broadcast planting arrangements; and T5 indicates monocultured barley plots   T1 T5 T4 T2 T3 T4 T3 T2 T2 T3 T5 T1 T5 T1 T4 T2 T1 T5 T3 T4 S N E W 146    Figure 5.2 Daytime average gross ecosystem photosynthesis (µmol CO2 m-2 s-1) in monocultures and barley-pea intercrop plots during 25, 50 and 75 days after sowing.  Figure 5.3 Daytime average net ecosystem productivity (µmol CO2 m-2 s-1) in monocultures and barley-pea intercrop plots during 25, 50 and 75 days after sowing.   6.54 6.34 6.74 5.82 5.81 12.62 12.72 14.49 10.56 13.88 9.58 9.53 10.31 8.19 10.61 0246810121416Pea Mono (1:1) (2:1) (mixed) Barley MonoGEP (µmol CO2 m-2 s-1)  Planting Arrangements 25 DAS 50 DAS 75 DAS2.61 2.35 2.93 1.77 2.65 5.70 6.18 7.70 4.65 6.96 4.16 4.27 5.31 3.21 4.80 0246810Pea Mono (1:1) (2:1) (mixed) Barley MonoNEP (µmol CO2 m-2 s-1)  Planting Arrangements 25 DAS 50 DAS 75 DAS147  CHAPTER 6: CONCLUSIONS AND FUTURE NEEDS This dissertation has investigated the performance of heirloom and commercial small grain cultivars, wheat and barley root architectures, and the effects of species proportion and spatial configuration in cereal-legume intercropping systems. The findings from the studies have made several contributions to the current literature and have enhanced our understanding in the following:  Cultivar trials demonstrated significant variation in plant performance and yield among both heirloom wheat and barley cultivars with some heirloom wheat (i.e., ‘Reward’, ‘Glenn’, ‘Cerebs’, ‘Sounders’ and ‘Red Bobs’) and barley (i.e., ‘Jet’) produced comparable grain yields to the commercial cultivars. The heirloom wheat and barley cultivars displayed greater resistance to stripe rust disease of which hulled wheat and barley cultivars showed strong resistance compared to hulless type. Heirloom wheat cultivars showed higher protein levels most desirable for baking and blending purposes as compared to the commercial cultivars, with ‘Einkorn’ displaying the highest level (16.2%). The heirloom black-seeded barleys contained higher protein levels most suitable for animal feed. The UK spring barleys (i.e., ‘Oxbridge’, ‘Westminster’ and ‘Decanter’) contained lower protein levels most suitable for malting purposes.  The coincidence in harvesting time (80-90 DAS) showed that barley can be successfully integrated with pea and lentil for combined harvesting. Early wheat cultivars (e.g., ‘Sounders’, ‘Reward’, ‘Snowstar’, and ‘Snowbird’) showed possibility 148  with late peas whereas late wheat appeared to be best suited to fava beans, kidney beans, and soybeans.  The root architectures of the heirloom wheat and barley cultivars indicate they may be better suited for low phosphorus and/or drought conditions, typical of low input or organic production. The root architectures of the commercial cultivars, on the other hand, were deemed more suitable for high input conditions. There exists a positive association between root length, surface and yield potential when heirloom wheat cultivars were grown under low input conditions. Longer and finer roots, and the lower shoot:root ratio in some heirloom cultivars further suggest breeding potential for improved nutrient uptake efficiency and drought tolerance in wheat and barley. Furthermore, two-year’s study on cereal-legume intercropping systems revealed significant and positive responses for several plant performance metrics and overall system productivity (Table 6.1). Intercropping displayed the highest total land outputs (TLO) and land equivalent ratios (LER), thereby significantly increasing land productivity (up to 50%) over monoculture counterparts. The experiment further demonstrated that:  Inter-plant N-transfer occurs within a growing season though the extent of transfer varied between legume genotypes. This study also revealed that pairing genotypes with similar root architectures that occupy the same root zone (e.g., wheat cv. ‘Scarlet’ and fava bean cv. ‘Bell’) transferred greater amounts of N (up to 13%) to the companion wheat plants compared to other legume genotypes with dissimilar    149  Table 6.1 Summary of the effects of genotypes and spatial configurations on agronomic and ecosystem metrics over monocultured plots. Treatments Cereal Biomass C:N Cereal Grain Protein %N-fixation by Legumes N-transfer Net  Ecosystem  Productivity Water  Use  Efficiency Land Equivalent Ratio Total Land Outputs Wheat-common bean cv. ‘Red Kidney’ combinations Wheat:RK (1:1) ↓ ↑ ↑ Yes ↓ ↑ ns ns Wheat:RK (2:1) ↓ ↑ ↑ Yes ↑ ↑ ↑ ↑ Wheat-RK (mixed) ns ns ns Yes ↓ ↑ ns ns Wheat-common bean cv. ‘Black Turtle’ combinations Wheat:BT (1:1) ↓ ↑ ns No ↓ ns ns ns Wheat:BT (2:1) ↓ ↑ ns No ↓ ns ns ns Wheat-BT (mixed) ↓ ↑ ns No ↓ ns ns ns Wheat-fava bean cv. ‘Bell’ combinations Wheat:Bell (1:1) ↓ ↑ ↑ Yes ↑ ↑ ↑ ↑ Wheat:Bell (2:1) ↓ ↑ ↑ Yes ↑ ↑ ↑ ↑ Wheat-Bell (mixed) ns ↑ ↑ Yes ↓ ↑ ns ns 150  Treatments Cereal Biomass C:N Cereal Grain Protein %N-fixation by Legumes N-transfer Net  Ecosystem  Productivity Water  Use  Efficiency Land Equivalent Ratio Total Land Outputs Barley-pea combinations Barley:Pea (1:1) ↓ ↑ ↑ Yes ns ns ns ↑ Barley:Pea (2:1) ↓ ↑ ↑ Yes ↑ ns ↑ ↑ Barley-Pea (mixed) ↓ ↑ ↑ Yes ns ns ns ↑ RK = Red Kidney; BT = Black Turtle; and ns = Not Significant  151  root architectures (e.g., wheat cv. ‘Scarlet’ and common bean cv. ‘Red Kidney’ or ‘Black Turtle’). Increase in N transfer in the second year could be due to combination of within year and residual legume N inputs from the first year mineralizing and becoming available to the wheat in the second year.  No significant effect of N transfer on ‘donor’ legume performance was observed in intercrops. However, biomass N content in legumes was slightly reduced in intercrop plots compared to monocultured legumes, perhaps related to the transfer of N to the non-N2-fixing counterparts.  Significant variation was observed among the legume genotypes in terms of biological N2 fixation and transfer to the companion wheat and barley plants. Fava bean cv. ‘Bell’ fixed the greatest amount of atmospheric N (>80% of total plant N) and transferred the greatest amount of biologically fixed N (13% of N in wheat biomass) to the wheat counterpart.  The extent of N fixation and transfer was higher in high legume density plots (i.e., 1:1 arrangement) compared to the 2:1 and broadcast arrangements. The difference, however, was relatively small between the spatial arrangements.  Compared to the monocultured wheat and barley, the forage yield and quality of intercrops improved. A positive association was observed between increased legume densities and higher biomass and grain N content in the cereal component. Therefore, cereals when intercropped with legumes displayed higher nutritional value and were deemed more suitable as animal food and fodder. 152   Legume genotypes differed in their BNF contribution with the higher rate of N2 fixation and transfer in row intercrops. This led to the stimulation of CO2 fixation by wheat and barley in intercrop plots leading to the greater amounts of carbon assimilation and soil organic matter addition.  Wheat showed increased intrinsic water use efficiency (WUE) when grown with either fava bean cv. ‘Bell’ or common bean cv. ‘Red Kidney’ perhaps related to improved N nutrition that enhance photosynthesis relative to transpiration rate leading to more water efficient grain and biomass production.  Cropland (both monoculture and intercrop plots) fixed the most CO2 during mid-growth stage (i.e., 50-60 days after seeding, just prior to flowering). Wheat-fava bean cv. ‘Bell’ in the 1:1 arrangement displayed the greatest NEP sequestering C at a seasonal daytime average rate of 208 mg C m-2 hr-1 (i.e., 7% higher than wheat monoculture plots). Similarly, barley-pea in the 2:1 arrangement displayed the greatest NEP with the sequestration of 229 mg C m-2 hr-1 (i.e., 10% higher than barley monoculture plots).  Intercrop plots displayed both selection and complementary effects on the performance of co-occurring species.  Selection differences were observed for light interception or radiation uptake, nitrogen fixation and transfer to the cereal counterparts, and crop growth, yield and total biomass production in monoculture and intercrop combinations. Wheat-fava and barley-pea combinations displayed greater response due to their upright growth habit than wheat-common bean combinations. Complementary effects were observed mainly on ecosystem 153  productivity metrics when the cereal component received more nitrogen from its legume counterpart leading to the greater photosynthesis, relative to transpiration, leading to more water efficient grain and biomass production.  Common bean cv. ‘Black Turtle’ did not transfer any N to the wheat component nor improve NEP or WUE of the wheat in intercrop plots. Indeed, increased biomass of common beans in Year 2 in intercrop plots suppressed wheat growth, grain filling, 1000 seed test weight, and harvest index leading to lower yield and LER values compared to monocultured wheat. Similarly, pea when intercropped with barley in the 1:1 arrangement also provided shading effects on barley resulting to fewer filled grains, lower 1000 seed test weight, yield and LER than other planting arrangements. Overall, this research demonstrated that intercropping can be a viable option to increase land productivity, to improve grain and biomass quality of non-N2-fixing cereals, to increase N and C accumulation, NUE, GEP, NEP and WUE than monocultures under low soil N and C conditions typical of organic systems. Furthermore, intercropping helps decrease reliance on synthetic N-fertilizers, increase soil organic matter concentrations, and carbon sequestration thereby improving soil health and environmental quality. The wheat-fava bean cv. ‘Bell’ in the 1:1 and 2:1 arrangements, and barley-pea in the 2:1 arrangement appeared to be the most productive combinations compared to monoculture and other intercropping arrangements. Future research/directions: This research revealed several advantages of cereal-legume intercropping over monoculture systems in terms of land productivity, nitrogen and water use efficiencies, carbon accumulation and NEP in organic system.  However, a number of 154  limitations need to be addressed before the adoption and effective deployment of intercropping to large agricultural production:  The contribution of legume genotypes may differ with the soil type, topography, and growing environment. For example, acidic soils with limited phosphorus availability may lessen N contribution in the system. Similarly, high soil N or mineral N-fertilizer application is known to inhibit BNF. Therefore, it is important that we carry out multiyear experiments in different locations using similar treatments to confirm these results across a wider range of agro-climatic situations.   Another factor to consider while using organic intercropping is weed control during early stage of crop establishment. Hand weeding practice might be practical in small scale agriculture with plentiful labor, but would be difficult in medium to large agricultural production.  For effective dissemination or adoption of intercropping technologies in medium to large agricultural production, it is essential that wheat and barley are planted and harvested together with beans and pea, respectively. This can be achieved only when the combined planter and harvester are available making it suitable to mechanized agricultural systems. In addition to the grain harvests, there is a tremendous potential of increasing forage quality (i.e., quality of green fodder, silage, etc.) by integrating legumes into the grass community.  Despite their tremendous contribution to improve soil fertility, legumes are often not preferred by smallholder/resource-poor farmers compared to cereals, largely attributed to their lack of short-term benefits (e.g., food and income). Furthermore, most basic research on cereal-legume intercropping systems has little direct 155  involvement by farmers, particularly resource-poor farmers. Consequently, there is lack of information and knowledge about the role of legume integration in the soil fertility management among smallholder farmers. This situation needs to be improved by conducting participatory intercropping trials in the farmer’s fields and with their strong involvement.   156  LITERATURE CITED Agriculture and Agri-Food Canada- AAFC (1998). The Canadian system of soil classification (3rd edition). NRC Research Press, Ottawa. pp. 115. Agriculture and Agri-Food Canada- AAFC (2014). Canada: Outlook of principle food crops (Online). Available: http://www.agr.gc.ca/eng/industry-markets-and-trade/statistics-and-market-information/by-product-sector/crops/crops-market-information-canadian-industry/canada-outlook-for-principal-field-crops/canada-outlook-for-principal-field-crops-2013-10-16/?id=1382366483303 (Retrieved: March 14, 2014). Beedlow, P. A., D. T. Tingey, D. L. Phillips, W. E. Hogsett and D. M. Olszyk (2004). Rising atmospheric CO2 and carbon sequestration in forests. Frontiers in Ecology and the Environment 2 (6): 315-322. Bernier, P. Y., M. S. Lamhamedi and D. G. Simpson (1995). Shoot:root ratio is of limited use in evaluating the quality of container conifer stock. Natural Resources Canada, Canadian Forest Service-Quebec, Sainte-Foy, Quebec, and British Columbia Ministry of Forests, Kalamalka Research Station, Vernon, British Columbia, Canada. Bertrand, R. A., G. A. Hughes-Games and D.C. Nikkel (1991). Soil management handbook for the lower Fraser Valley. BC Ministry of Agriculture, Fisheries and Food, Abbotsford, BC. Blaser, B. C., L. R. Gibson, J. W. Singer and J. L. Jannink (2006). Optimizing seeding rates for winter cereal grains and frost-seeded red clover intercrops. Agronomy Journal 98: 1041-1049. 157  Boddey, R. M., M. B. Peoples, B. Palmer and P. J. Dart (2000). Use of the 15N natural abundance technique to quantify biological nitrogen fixation by woody perennials. Nutrient Cycling in Agroecosystems 57: 235-270. Bodner, G., D. Leitner, A. Nakhforoosh, M. Sobotik, K. Moder and H. P. Kaul (2013). A statistical approach to root system classification. Frontiers in Plant Science 4:1-15. Bole, J. B. (1977). Uptake of tritiated water and phosphorus by roots of wheat and rape. Plant and Soil 46: 297-307. Bomke, A. A., W. D. Temple, G. E. Kennedy, L. Cain and M. J. Langlet (1991). Intensive winter cereal production system for south coastal British Columbia. Agri-food Regional Development Subsidiary Agreement Project # 23007. British Columbia Ministry of Agriculture, Fisheries and Food, Victoria, BC. Brophy, L. S., G. H. Heichel and M. P. Russelle (1987). Nitrogen transfer from forage legumes to grass in a systematic planting design. Crop Science 27: 753-758. Bulson, H. A. J., R. W. Snaydon and C. E. Stopes (1997). Effects of plant density on intercropped wheat and field beans in an organic farming system. Journal of Agricultural Science 128: 59-71. Cambardella, C. A. (2005). Carbon cycle in soils, formation and decomposition. USDA Agricultural Research Service, Ames, USA. pp. 170. Campbell, C. A., R. J. K. Myers and D. Curtin (1995). Managing nitrogen for sustainable crop production. Fertilizer Research 42: 277-296. 158  Canada Grains Council- CGC. (2014). Online statistical handbook. The Canada Grains Council, Winnipeg, Manitoba, Canada. Cardoso, E., M. A. Nogueira and S. Ferraz (2007). Biological N2 fixation and mineral N in common bean-maize intercropping or sole cropping in south-eastern Brazil. Experimental Agriculture 43: 319-330. Carr, P. M., R. D. Horsley and W. W. Poland (2004). Barley, oat and cereal-pea mixtures as dryland forages in the Northern Great Plains. Agronomy Journal 96: 677-684. Chapagain, T. and A. Riseman (2012). Evaluation of heirloom and commercial cultivars of small grains under low input organic systems. American Journal of Plant Sciences (3): 655-669. Chen, C., M. Westcott, K. Neill, D. Wichman, and M. Knox (2004). Row configuration and nitrogen application for barley- pea intercropping in Montana. Agronomy Journal 96: 1730- 1738. Cholick, F. A., J. R. Welsh and C. V. Cole (1977). Rooting patterns of semi-dwarf and tall winter wheat cultivars under dryland field conditions. Crop Science 17: 637-639. Condon, A. G., R. A. Richards and G. D. Farquhar (1987). Carbon isotope discrimination is positively correlated with grain yield and dry matter production in field-grown wheat. Crop Science 27: 996-1001. Condon, A. G., R. A. Richards, G. J. Rebetzke and G. D. Farquhar (2002). Increasing intrinsic water-use efficiency and crop yield. Crop Science 42: 122-131. 159  Condon, A. G., R. A. Richards, G. J. Rebetzke and G. D. Farquhar (2004). Breeding for high water-use efficiency. Journal of Experimental Botany 55 (407): 2447-2460. Corbin, E. J., J. Brockwell and R. R. Gault (1977). Nodulation studies on chickpea (Cicer arietinum). Australian Journal of Experimental Agriculture and Animal Husbandry 17: 126-134. Dawson, T. E., S. Mambelli, A. H. Plamboeck, P. H. Templer and K. P. Tu (2002). Stable isotopes in plant ecology. Annual Review of Ecology and Systematics 33: 507-559. Dexter, A. R. (1987). Compression of soil around roots. Plant and Soil 197: 401-406. Dumanski, J., D. Coote, G. Lucerek and C. Lok (1986). Soil Conservation in Canada. Journal of Soil and Water Conservation 41: 204-210. Dusa, E. M. (2009). Researches regarding the productivity of oat-lentil intercropping in the organic agriculture system. Research Journal of Agricultural Science 41 (1): 22-26. Dyer, L., M. Oelbermann and L. Echarte (2012). Soil carbon dioxide and nitrous oxide emissions during the growing season from temperate maize-soybean intercrops. Journal of Plant Nutrition and Soil Science 175: 394-400. Edible Strategies Enterprises- ESE (2007). Islands good food initiative-Contending with the local food access puzzle (Online). Available:   http://www.ediblestrategies.com/gfb.html (Retrieved: December 21, 2010). Egle, K., G. G. B. Manske, W. Romer and P. L. G. Vlek (1999). Improved phosphorus efficiency of three new wheat genotypes from CIMMYT in comparison with an older Mexican variety. Journal of Plant Nutrition and Soil Science 162: 353-358. 160  Ferguson, R. B., G. W. Hergert, J. S. Schepers and C. A. Ceaword (1999). Site-specific nitrogen management of irrigated corn. In: P. C. Robert, R. H. Rust and W. E. Larson (eds.) Proceedings of the fourth international conference on precision agriculture. ASA-CSSA-SSSA, Madison, WI. pp. 133-139. Food and Agriculture Organization of the United Nations- FAO (2013). FAO stat: crops. FAOSTAT Division, Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, Rome, Italy. Fujita, K., K. G. Ofosu-Budu and S. Ogata (1992). Biological nitrogen fixation in mixed legume-cereal cropping systems. Plant and Soil 141: 155-175. Gaiser, T., I. Barros, F. M. Lange and J. R. Williams (2004). Water use efficiency of maize/cowpea intercrop on a highly acidic tropical soil as affected by liming and fertilizer application. Plant and Soil 263: 165-171.  Ghaley, B. B., H. Hauggaard-Nielsen, H. Hogh-Jensen and E. S. Jensen (2005). Intercropping of wheat and pea as influenced by nitrogen fertilization. Nutrient Cycling in Agroecosystems 73: 201-212. Ghanbari, A., M. Dahmardeh, B. A. Siahsar and M. Ramroudi (2010). Effect of maize (Zea mays L.) - cowpea (Vigna unguiculata L.) intercropping on light distribution, soil temperature and soil moisture in and environment. Journal of Food, Agriculture and Environment 8: 102-108. Ghanbari-Bonjar, A and H. C. Lee (2002). Intercropped wheat (Triticum aestivum L.) and bean (Vicia faba L.) as a whole-crop forage: effect of nitrogen on forage yield and quality. The Journal of Agricultural Sciences 138 (3): 311-315. 161  Gooding, M. J., E. Kasyanova, R. Ruske, H. Hauggaard-Nielsen, E. S. Jensen, C. Dahlmann, P. von Fragstein, A. Dibet, G. Corre-Hellou, Y. Crozat, A. Pristeri, M. Romeo, M. Monti and M. Launay (2007). Intercropping with pulses to concentrate nitrogen and sulphur in wheat. Journal of Agricultural Science 14: 469-479. Habte, M. (2000). Mycorrhizal fungi and plant nutrition. In: J. A. Silva and R. Uchida (eds.). Plant nutrient management in Hawaii’s soils, approaches for tropical and sub-tropical agriculture, College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa. pp. 127-131. Halstead, M. A. (2007). Growing organic winter cereals on Vancouver Island. A report submitted to the Faculty of Land and Food Systems, University of British Columbia (UBC), Canada. Hartwig, U. A., A. Luscher, J. Nosberger and C. Van Kessel (2002). Nitrogen-15 budget in model ecosystems of white clover and perennial ryegrass exposed for four years at elevated atmospheric CO2. Global Change Biology 8: 194-202. Hauggaard-Nielsen, H., B. Jornsgaard, J. Kinane and E. S. Jensen (2007). Grain legume-cereal intercropping: The practical application of diversity, competition and facilitation in arable and organic cropping systems. Renewable Agriculture and Food Systems 23 (1): 3-12. Hauggaard-Nielsen, H., M. Gooding, P. Ambus, G. Corre-Hellou, Y. Crozat, C. Dahlmann, A, Dibet, P. von Fragstein, A. Pristeri, M. Monti and E. S. Jensen (2009). Pea-barley intercropping for efficient symbiotic N2-fixation, soil N acquisition and use of other nutrients in Europian organic cropping systems. Field Crops Research 113 (1): 64-71. 162  Hauggaard-Nielsen, H., P. Ambus and E. S. Jensen (2003). The comparison of nitrogen use and leaching in sole cropped versus intercropped pea and barley. Nutrient Cycling in Agroecosystems 65: 289-300. Haymes, R. and H. C. Lee (1999). Competition between autumn and spring planted grain intercrops of wheat (Triticum aestivum) and field bean (Vicia faba).  Field Crops Research 62 (2-3): 167-176. He, X. H. (2002). Nitrogen exchange between plants through common mycorrhizal networks. PhD Thesis. University of Queensland, Brisbane, Australia. He, X., C. Critchley and C. Bledsoe (2003). Nitrogen transfer within and between plants through common mycorrhizal networks (CMNs). Critical Reviews in Plant Sciences 22: 531-567. He, X. H., M. Xu, G. Y. Qiu and J. Zhou (2009). Use of 15N stable isotope to quantify nitrogen transfer between mycorrhizal plants. Journal of Plant Ecology 2 (3): 107-118. Heichel, G. H. and K. I. Henjum (1991). Dinitrogen fixation, nitrogen transfer, and productivity of forage legume-grass communities. Crop Science 31: 202-208. Hockett, E. A. (1986). Relationship of adventitious roots and agronomic characteristics in barley. Canadian Journal of Plant Science 66: 257-266. Hogberg, P. (1997). 15N natural abundance in soil-plant systems. New Phytologist 137: 179-203. Horst, W. J., M. Abdou and F. Wiesler (1996). Differences between wheat cultivars in acquisition and utilization of phosphorus. Z Pflanzenerniihrung Bodenkunde 159: 155-161. 163  Houghton, J. T., L. G. Meira Filho and J. Bruce (1995). Climate change. In: Radiative forcing of climate change and an evaluation of the IPCC’s 92 emission scenarios. Cambridge University Press, Cambridge, UK. Inal, A., A. Gunes, F. Zhang and I. Cacmak (2007). Peanut/maize inter-cropping induced changes in rhizosphere and nutrient concentrations in shoots. Plant Physiology and Biochemistry 45: 350-356. Intergovernmental Panel on Climate Change- IPCC. 2007. The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK. Izaurralde, R. C., W. B. McGill and N. G. Juma (1992). Nitrogen fixation efficiency, interspecies N transfer, and root growth in barley-field pea intercrop on a Black Chernozemic soil. Biology and Fertility of Soils 13 (1): 11-16. Jarecki, M. K. and R. Lal (2003). Crop management for soil carbon sequestration. Critical Reviews in Plant Sciences 22(6): 471-502. Jassal, R. S., T. A. Black and M. Novak (2005). Relationship between soil CO2 concentrations and forest-floor CO2 effluxes. Agricultural and Forest Meteorology 130: 176-192. Jassal, R. S., T. A. Black, J. A. Trofymow, R. Roy and Z. Nesic (2010). Soil CO2 and N2O flux dynamics in a nitrogen-fertilized Pacific Northwest Douglas-fir stand. Geoderma 157: 118-125. Jassal, R. S., T. A. Black, Z. Nesic and D. Gaumont-Guay (2012). Using automated non-steady-state chamber systems for making continuous long-term measurements of soil CO2 efflux in forest ecosystems. Agricultural and Forest Meteorology 161: 57–65. 164  Jensen, E. S. (1986). Intercropping field bean with spring wheat. Vorträge für Pflanzenzüchtung 11: 67-75. Jensen, E. S. (1996). Grain yield, symbiotic N2 fixation and interspecific competition for inorganic N in pea-barley intercrops. Plant and Soil 18: 25-38. Johansen, A. and E. S. Jensen (1996). Transfer of N and P from intact or decomposing roots of pea to barley interconnected by an arbuscular mycorrhizal fungus. Soil Biology and Biochemistry 28: 73-81. Jolliffe, P. A. (2000). The replacement series. Journal of Ecology 88: 371-385. Jolliffe, P. A. and F. M. Wanjau (1999). Competition and productivity in crop mixtures: some properties of productive intercrops. Journal of Agricultural Science, Cambridge 132: 425-435. Jones, D. B. (1931). Factors for converting percentages of Nitrogen in foods and feeds into percentages of proteins. U. S. Department of Agriculture, Circular No. 183. Washington, D.C. Jones, G. P. D., G. J. Blair and R. S. Jessop (1989). Phosphorus efficiency in wheat-a useful selection criteria. Field Crops Research 21: 257-264. Kidwell, K. K., G. B. Shelton, V. L. DeMacon, X. M. Chen, J. S. Kuehner, B. Baik, D. A. Engle, A. H. Carter and N. A. Bosque-Perez (2009). Registration of ‘Kelse’ Wheat. Journal of Plant Registrations 3 (3): 269-272. Klepper, B. (1991). Root-shoot relationships. In: Y. Waisel, A. Eshel, U. Kafkafi (eds.). Plant Roots: The Hidden Half. Marcel Dekker, New York. pp 265-286. 165  Knowles, R. and T. H. Blackburn (1993). Nitrogen Isotope Techniques. Academic Press, San Diego, CA. Lauk, R and E. Lauk (2008). Pea-oat intercrops are superior to pea-wheat and pea-barley intercrops. Acta Agriculturae Scandinavica, Section B - Plant Soil Science 58 (2): 139-144. Lithourgidis, A. S. and C. A. Dordas (2010). Forage yield, growth rate, and nitrogen uptake of faba bean intercrops with wheat, barley, and rye in three seeding ratios. Crop Science 50: 2148-2158. Lithourgidis, A. S., C. A. Dordas, C. A. Damalas and D. N. Vlachostergios (2011). Annual intercrops: an alternative pathway for sustainable agriculture. Australian Journal of Crop Science 5 (4): 396-410. Liu, M., F. Hu, X. Chen, Q. Huang, J. Jiao, B. Zhang and H. Li (2009). Organic amendments with reduced chemical fertilizer promote soil microbial development and nutrient availability in a subtropical paddy field: The influence of quantity, type and application time of organic amendments. Applied Soil Ecology 42 (2): 166-175. Livingston, N. J., R. D. Guy, Z. J. Sun and G. J. Ethier (1999). The effects of nitrogen stress on the stable carbon isotope composition, productivity and water use efficiency of white spruce (Picea glauca (Moench) Voss) seedlings. Plant Cell & Environment 22: 281-289. Louis, A. H., D. L. Weigmann, P. Hipkins and E. R. Stinson (1996). Pesticides and Aquatic Animals: A Guide to Reducing Impacts on Aquatic Systems (Online). http://www.ext.vt.edu/pubs/waterquality/420-013/420-013.html (Retrieved: March 04, 2013). 166  Lunnan, T. (1989). Barley-pea mixtures for whole crop forage. Effect of different cultural practices on yield and quality. Norwegian Journal of Agricultural Sciences 3: 57-71. Mae, T. and K. Ohira (1981). The remobilization of nitrogen related to leaf growth and senescence in rice plants (Oryza sativa L.). Plant Cell Physiology 22: 1067-1074. Manske, G. G. B. (1989). The efficiency of the inoculation by the VA mycorrhizal fungi Glomus manihotis in spring wheat genotypes and its inheritance in F1- and R1 generations at different phosphate forms applied and different weather conditions. PhD dissertation at University of Gottingen, Germany. Abstract in English. Manske, G. G. B. and P. L. G. Vlek (2002). Root Architecture-Wheat as a Model Plant. In: Y. Waisel, A. Eshel and U. Kafkafi (eds.). Plant Roots: The Hidden Half. Marcel Dekkar Inc. Newyork. pp. 249-259. Manske, G. G. B., J. I. Ortiz-Monasterio, M. Van Ginkel, R. Gonzalez and P. L. G. Vlek (1996). Phosphorus uptake, utilization efficiency and grain yield of semi-dwarf wheat grown in acid or alkaline, P deficient soils. 5th International Wheat Conference, June 10-14, 1996, Ankara, Turkey. Manske, G. G. B., J. I. Ortiz-Monasterio, M. Van Ginkel, R. Gonzalez, S. Rajaram, E. Molina and P. L. G. Vlek (2000). Traits associated with improved P-uptake efficiency in CIMMYT's semi-dwarf spring bread wheat grown on an acid Andisol in Mexico. Plant and Soil 221: 189-204. Mariotti, A. (1983). Atmospheric nitrogen is a reliable standard for natural 15N abundance measurements. Nature 303: 685-7. McGill, W., C. A. Campbell, J. Dormaar, E. Paul and D. Anderson (1981). ‘Soil Organic Losses’, agriculture land: our disappearing heritage, Alberta Agriculture, pp. 72-133. 167  McLaughlin, A. and P. Mineau (1995). The impact of agricultural practices on biodiversity. Agriculture Ecosystems and Environment 55 (3): 201-212. Mead, R. and R. W. Willey (1980). The concept of land equivalent ratio and advantages in yields from intercropping. Experimental Agriculture 16: 217-228. Michigan State University- MSU (1993). MSTAT- C, A micro computer program for the design, management and analysis of agronomic research experiments. MSTAT Development Team, Michigan State University, USA. Newman, E. I. (1988). Mycorrhizal links between plants: Their functioning and ecological significance. Advances in Ecological Research 18: 243-270. Oates, L. and M. Cohen (2009). Human consumption of agricultural toxicants from organic and conventional food.  Journal of Organic Systems 4 (1): 48-57. Ofori, F. and W. R. Stern (1987). Cereal-legume intercropping system. Advance in Agronomy 41: 41-90. Oleson, B. (2010). The Wheat industry in Canada (Online). Available: http://www.acopiadores.com/publico/atodotrigo/The Wheat Industry in Canada.pdf   (Retrieved: May 05, 2010). Ormsby, M. A. (1945). Agricultural development in British Columbia. Agricultural History 19 (1): 11-20. Poutala, R. T., J. Korva and E. Varis (1993). Spring wheat cultivar performance in ecological and conventional cropping systems. Journal of Sustainable Agriculture 3: 63-83. 168  Prasad, R. B. and R. M. Brook (2005). Effect of varying maize densities on intercropped maize and soybean in Nepal. Experimental Agriculture 41: 365-382. Pristeri, A., C. Dahlmann, P. von Fragstein, M. J. Gooding, H. Hauggaard-Nielsen, E. Kasyanova and M. Monti (2006). Yield performance of faba bean - wheat intercropping on spring and winter sowing in European organic farming system. Paper presented at Joint Organic Congress, Odense, Denmark, May 30-31, 2006. Putnam, D. H., S. J. Herbert and A. Vargas (1986). Intercropped corn- soybean density studies. II. yield composition and protein. Experimental Agriculture 22: 373-381. Rempel, S. (2008). Demeter’s wheats: Growing local food and community with traditional wisdom and heritage wheat. Grassroots Solutions, Victoria, BC. Robertson, G. P. (1997). Nitrogen use efficiency in row-crop agriculture: Crop nitrogen use and soil nitrogen loss. In: L. Jackson (ed.). Ecology in Agriculture. Academic Press, New York. pp. 347-365. Robinson, D. (2001). δ15N as an integrator of the nitrogen cycle. Trends in Ecology and Evolution 16: 153-162. Ryan, M. H., J. W. Derrick and P. R. Dann (2004). Grain mineral concentrations and yield of wheat grown under organic and conventional management. Journal of Science Food and Agriculture 84: 207-216. Sahota, T. and S. Malhi (2012). Intercropping barley with pea for agronomic and economic considerations in northern Ontario. Agricultural Sciences 3: 889-895. 169  San-nai, J and Z. Ming-pu (2000). Nitrogen transfer between N2-fixing plant and non-N2-fixing plant. Journal of Forestry Research 11 (2): 75-80. Schimel, D. S. (1995). Terrestrial ecosystems and carbon cycle. Global Change Biology 1: 77-91. Schipanski, M., L. Drinkwater and M. Russelle (2010). Understanding the variability in soybean nitrogen fixation across agroecosystems. Plant and Soil 329: 379-397. Schlesinger, W. H. and J. A. Andrews (2000). Soil respiration and the global carbon cycle. Biogeochemistry 48: 7-20. Shearer, G. and D. H. Kohl (1988). Natural 15N abundance as a method of estimating the contribution of biologically fixed nitrogen to N2-fixing systems: Potential for non-legumes. Plant and Soil 110: 317-327. Shearer, G. B. and D. H. Kohl (1986). N2-fixation in field settings: estimations based on natural 15N abundance. Australian Journal of Plant Physiology 13: 699-756. Shearer, G. B. and D. H. Kohl (1991). The 15N natural abundance method for measuring biological nitrogen fixation: practicalities and possibilities. In: S. P. Flitton (ed.). Stable Isotopes in Plant Nutrition, Soil Fertility and Environmental Studies. International Atomic Energy Association, Vienna, Austria. pp. 103-115. Shewry, P. R. (2006). Improving the protein content and quality of temperate cereals: wheat, barley and rye. In: R. M. Welch and I. Cakmak (eds.).  Impacts of Agriculture on Human Health and Nutrition. Encyclopedia of Life Support Systems (EOLSS), Eolss Publishers, Oxford, UK. 170  Shier, N. W., J. Kelman and J. W. Dunson (1984). A comparison of crude protein, moisture, ash and crop yield between organic and conventionally grown wheat. Nutrition Reports International 30: 71-76. Sparrow, Hon. H. O. (1984). Soil at Risk, Canada’s eroding future. Standing Senate Committee on Agriculture, Fisheries and Forestry, Ottawa. pp. 181. Starling, W. and M. C. Richards (1993). Quality of commercial samples of organically grown wheat. Aspects of Applied Biology 36: 205-209. Statistics Canada (2014). Field and special crops (Online). Available: http://www.statcan.gc.ca/tables-tableaux/sum-som/l01/cst01/prim11a-eng.htm (Retrieved: March 14, 2014). Stern, W. R. (1993). Nitrogen fixation and transfer in intercropping systems. Field Crops Research 34: 335-56. Subedi, K. D. (1997). Wheat intercropped with tori (Brassica campestris var. toria) and pea (Pisum sativum) in the subsistence farming system of the Nepalese hills. The Journal of Agricultural Science 128 (3): 283-289. Temple, W. (2009). Progress report on Delta Farmers’ Institute & UBC Faculty of Land and Food Systems Eco-Friendly Crop Rotations Project. Faculty of Land and Food Systems, UBC, Canada. Thurston, D. (1996). Slash/mulch systems: Sustainable methods for tropical agriculture. Westview Press, Boulder, CO, USA. 171  Tottman, D. R. (1987). The decimal code for the growth stages of cereals, with illustrations. Annal Applied Biology 110: 441-454. Trenbath, B. R. (1974). Biomass productivity of mixtures. Advances in Agronomy 26: 177-210. United States Department of Agriculture- USDA (1980). Report and Recommendations on Organic Farming. US Department of Agriculture, Washington, DC. United States Department of Agriculture, Soil Conservation Service- USDA-SCS (1992). Soil taxonomy, a basic system of soil classification for making and interpreting soil surveys (2nd edition). US Department of Agriculture Handbook 436.  United States Environmental Protection Agency- USEPA. 2013. Overview of greenhouse gases: Nitrous oxide emissions (Online). Available: http://epa.gov/climatechange/ghgemissions/gases/n2o.html (Retrieved: October 10, 2013). University of California San Diego- UCSD. 2014. The keeling curve: A daily record of atmospheric carbon dioxide from SCRIPPS institution of oceanography at UC San Diego (Online). Available: http://keelingcurve.ucsd.edu  (Retrieved: April 21, 2014). VanLoocke, A., E. Tracy, M. Z. Twine and C. J. Bernacchi (2012). A regional comparison of water use efficiency for miscanthus, switchgrass and maize. Agricultural and Forest Meteorology 164: 82-95. Vlek, P. L. G., A. B. Liittger and G. G. B. Manske (1996). The potential contribution of arbuscular mycorrhiza to the development of nutrient and water efficient wheat. In: D. G. 172  Tanner, T. S. Payne and O. S. Abdalla (eds.). The 9th Regional Wheat Workshop for Eastern, Central and Southern Africa. CIMMYT, Ethiopia. pp. 28-46. Warembourg, F. R. (1993). Nitrogen fixation in soil and plant systems. In: R. Knowles and T. H. Blackburn (eds.). Nitrogen isotope techniques. Academic Press, Inc., Waltham. pp. 127-155. Welles, J. M., T. H. Demetriades-Shah and D. K. McDermitt (2001). Considerations for measuring ground CO2 effluxes with chambers. Chemical Geology 177: 3-13. Wibberley, E. J. (1989). Cereal Husbandry- 1st Edition. Farming Press Books, UK, pp-4. Yoneyama, T. (1996). Characterization of natural 15N abundance of soils. In: T. W. Boutton and S. I. Yamasaki (eds). Mass Spectrometry of Soils. Marcel Dekker, New York. pp. 205-223. Zadoks, J. C., T. T. Chang and C. F. Konzak (1974). A decimal code for the growth stages of cereals. Weed Research 14: 415-421. Zanetti, S., U. A. Hartwig, C. van Kessel, A. Luscher, T. Hebeisen, M. Frehner, B. U. Fischer, G. R. Hendrey, H. Blum and J. Nosberger (1997). Does nitrogen nutrition restrict the CO2 response of fertile grassland lacking legumes? Oecologia 112: 17-25. Zhang, F. Y., P. T. Wu, X. N. Zhao and X. F. Cheng (2012). Water saving mechanisms of intercropping system in improving crop land water use efficiency. Ying Yong Sheng Tai Xue Bao (Journal of Applied Ecology) 23 (5): 1400-1406. (Article in Chinese, abstract in English).    173  Appendix A Protocol adopted for N-determination in small grains using the Kjeldahl method. Reagents/ Chemicals Required  Conc. Sulfuric acid (H2SO4): 95-98%, nitrogen-free  Fisher’s Kjeltabs: Copper/Titanium tablets with 5.57 g K2SO4 + 0.0033g CuSO4 + 0.2 g TiO2  Sodium hydroxide (NaOH, 99.6-100.1%) O.1 N NaOH = 4g NaOH/litre and titrate against standard acid (0.1N HCl, for example) after adding 2-3 drops of phenolphthalein indicator to determine the exact normality of prepared solution; and 32% NaOH= 32 g/100 ml or 960 g/3 litre.  Hydrochloric acid (HCl, 36.5-38%) 0.5 N HCl = 42 ml HCl/litre and titrate against standard base (0.1 N NaOH, for example) after adding 2-3 drops of phenolphthalein indicator to determine the exact normality of prepared solution.  De-ionized water: Prepare all reagents and dilutions in de-ionized water  Boiling chips (Fisher’s Bioleezers Granules, B365-250)  Methyl red indicator (Dissolve 0.1 g of bromocresol green and 0.02 g of methyl red in 100 ml ethanol) Apparatus Required  Usual lab equipment (weighing balance of 0.1 mg accuracy, beakers, petriplates, etc.)   Kjeldahl digestion flasks (500-900 ml) or tubes 174   Digestion and distillation chamber   Burette (graduated in intervals of 0.01 ml or smaller), pipette, stand, etc. Sample Preparation   Grind grain sample (homogeneous and dried at 60-65°C, moisture content 13.5%) to <0.6mm size by a good sample blender. The particle size of the sample should ideally be reduced to a size < 1 mm. The speed of the digestion will be improved when small particle sizes are used. Sample Weight   Weigh 1 g sample (Expected nitrogen content 1 to 3% in wheat and barley, thereby contains 5 to 20% Protein) into a 900-ml Kjeldahl digestion flask. Use an analytical balance accurate to 0.1 mg for weighing samples. (Note: Reducing agent such as Sucrose (0.5 g) + Conc. H2SO4 (20 ml) will be added prior to digestion to include Nitrogen in nitrate form and variation in total nitrogen content will be observed than is achieved by using the normal (except reduction step) procedure). Digestion  Add catalyst, 1 Kjeltabs (Copper/Titanium tablets with 5.57 g K2SO4 + 0.0033g CuSO4 + 0.2 g TiO2).   Add 20 ml of Conc. H2SO4 into the digestion flask. Add boiling chips to prevent bumping while heating or boiling the sample.  Load the digestion tubes and run digestion chamber (BUCHI Digest System K-431, BUCHI Switzerland) for 2 hours (at 400°C) 175   After completion of the digestion step, allow the flask or tube for few hours to cool down (or overnight) at room temperature. (Using classical Kjeldahl apparatus, a general digestion procedure for routine use, requires a minimum of 2 hours total digestion. With the improved sample to sample temperature control, the “after boil” period is significantly reduced to 30-60 minutes. The term “boiling time” can be divided in two parts. First, the time it takes until the digest has cleared or become colourless, usually called “digestion time”. Next, the “after boil” time, to convert the last part of the nitrogen into a form that can be distilled, usually called “boil period”. In general, a “boiling time” two to three times the clearing time is usually sufficient to achieve complete recovery) Distillation   Add 75 ml of ammonia free water to the cooled acid digestion mixture. Dilution of the digestion mixture before making it alkaline and distilling prevents or minimizes caking and also reduces the likelihood of bumping.  Add NaOH (32% solution) to the diluted digestion mixture to make the total volume up to 200 ml. The solution now becomes strongly alkaline (pH of >11)  Connect flask containing diluted mixture of digestion to the condenser and mixed before heating and distillation begins. Additional boiling chips can be added just before distillation to reduce bumping, especially towards the end of the distillation as the solution becomes more concentrated.  Put 3-4 ml (Expected nitrogen content in sample 1.5 to 3%) of 0.5 N HCl in a receiving flask and increase volume by adding de-ionized water (up to 75 ml or as 176  necessary) so that the tip of the delivery tube immersed into the solution. Add 2-3 drops of Indicator (Methyl red) and place the flask under condenser of the distillation chamber (BUCHI Distillation Unit K-350, BUCHI Switzerland).  Distil for about 4 minutes. A distillation rate of about 25 ml/minute is adopted to collect 75-100 ml of condensate.   Allow delivery tubes to drain momentarily into the receiving flask before removal from the distillation apparatus. Rinse the end of the condenser before removal. Titration The ammonia is captured by a carefully measured excess of a standardized acid solution in the receiving flask. That solution is neutralized by a carefully measured standardized alkaline base solution such as sodium hydroxide (0.1 N NaOH). A color change is produced at the end point of the titration.  Titrate the condensate with 0.1 N NaOH solution till orange color appeared Calculations The calculations for % nitrogen or % protein must take into account which type of receiving solution was used and any dilution factors used during the distillation process. In the equations below, “N” represents normality. “ml blank” refers to the milliliters of base needed to back titrate a reagent blank if standard acid is the receiving solution, or refers to milliliters of standard acid needed to titrate a reagent blank if boric acid is the receiving solution. When standard acid is used as the receiving solution, the equation is: % Nitrogen =                                                                                                               177  Appendix B Performance of wheat and bean components in monocultures and wheat-bean intercrop combinations. Treatments Bean Performance Wheat Performance CCI1 Pods plant-1  (#) Harvest Index  (%) Spike Length  (cm) Seeds spike-1 (#) Harvest Index (%) Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Wheat-common bean cv. ‘Red Kidney’ combinations RK Monoculture 18.5 17.8 9.9 7.9 47.0 54.3 - - - - - - Wheat:RK (1:1) 15.1 17.2 4.8 9.2 48.5 57.2 7.2 6.5 33.9 28.0 47.2 42.1 Wheat:RK (2:1) 14.3 18.2 5.1 10.9 50.7 59.2 7.6 7.5 36.1 34.1 48.4 46.0 Wheat-RK (mixed) 16.6 17.4 5.9 7.4 46.8 59.3 6.8 7.0 31.4 30.0 47.6 44.9 Wheat Monoculture - - - - - - 6.9 6.9 33.1 29.5 47.1 43.9 SEM (±)  1.05 0.94 1.37 1.53 1.36 1.48 0.26 0.36 2.41 1.78 1.17 1.41 LSD0.05  2.99 NS 3.89 NS NS 4.21 NS NS NS 5.06 NS NS Wheat-common bean cv. ‘Black Turtle’ combinations BT Monoculture 22.6 21.6 16.4 14.3 55.8 56.1 - - - - - - Wheat:BT (1:1) 11.6 22.3 8.3 19.2 59.4 53.7 7.3 7.6 35.4 32.5 48.3 38.9 Wheat:BT (2:1) 15.4 24.1 8.8 20.9 63.2 54.4 7.4 7.3 33.7 32.4 47.4 37.6 178  Treatments Bean Performance Wheat Performance CCI1 Pods plant-1  (#) Harvest Index  (%) Spike Length  (cm) Seeds spike-1 (#) Harvest Index (%) Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Wheat-BT (mixed) 13.0 21.2 7.3 14.1 61.9 48.5 7.1 7.3 34.4 31.4 48.3 37.9 Wheat Monoculture - - - - - - 6.9 7.0 33.1 29.5 47.1 43.9 SEM (±)  1.65 1.33 1.15 0.93 1.15 1.39 0.19 0.23 1.63 1.4 1.56 1.19 LSD0.05  4.69 NS 3.27 2.65 3.27 3.95 NS NS NS NS NS 3.39 Wheat-fava bean cv. ‘Bell’ combinations Bell Monoculture 15.4 14.3 8.6 7.3 54.0 47.6 - - - - - - Wheat:Bell (1:1) 13.9 14.8 6.4 7.9 50.3 45.8 7.3 8.2 34.2 33.3 48.6 44.9 Wheat:Bell (2:1) 12.5 14.3 4.9 5.9 51.9 47.7 7.6 8.1 34.3 35.2 48.4 44.0 Wheat-Bell (mixed) 13.4 13.5 5.3 6.1 51.6 36.5 7.0 7.8 33.5 30.9 48.2 45.4 Wheat Monoculture - - - - - - 6.9 6.9 33.1 29.5 47.1 43.9 SEM (±)  1.04 0.92 0.54 0.63 1.85 1.81 0.21 0.34 1.05 1.76 1.37 1.27 LSD0.05  NS NS 1.54 NS NS 5.06 NS 0.97 NS 5.07 NS NS 1Chlorophyll Concentration Index (per 71mm2); Y1 = year 1; Y2 = year 2; RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference  179  Appendix C Performance of barley and pea components in monocultures and barley-pea intercrop combinations. Treatments Pea Performance Barley Performance CCI1 1000 Seed Weight (g) Grain Protein (%) 1000 Seed Weight (g) Harvest Index (%) Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Pea Monoculture 15.2 16.2 251 226 22.4 22.9 - - - - Barley:Pea (1:1) 16.7 16.4 243 248 21.6 21.6 48.1 41.8 57.9 50.0 Barley:Pea (2:1) 18.3 17.5 250 246 21.7 21.1 49.0 43.7 59.4 52.7 Barley-Pea (mixed) 16.0 16.2 243 243 21.1 20.7 49.8 40.5 58.3 50.5 Barley Monoculture - - - - - - 45.1 41.8 59.5 55.3 SEM (±) 0.59 0.64 3.99 3.94 0.52 0.82 1.79 1.18 0.95 1.38 LSD0.05 1.68 NS NS 11.2 NS NS NS NS NS 3.91 1Chlorophyll Concentration Index (per 71mm2); Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least Significant Difference  180  Appendix D Coefficients of determination (r2) between bean performance metrics in wheat-bean intercrop combinations. Common bean cv. ‘Red Kidney’ Common bean cv. ‘Black Turtle’  NP NS GY TW HI CCI C:N GP BN BC CS NP NS GY TW HI CCI C:N GP BN BC CS HH 0.26 0.08 0.26 0.22 0.08 0.05 0.38 0.03 0.36 0.36 0.16 0.77 0.06 0.86 0.32 0.38 0.58 0.42 0.00 1.00 0.98 0.59 NP - 0.34 0.92 0.15 0.01 0.10 0.48 0.37 0.98 0.98 0.50 - 0.21 0.90 0.56 0.32 0.61 0.27 0.08 0.96 0.96 0.66 NS - - 0.38 0.23 0.27 0.09 0.12 0.11 0.64 0.62 0.55 - - 0.17 0.06 0.02 0.08 0.04 0.00 0.26 0.29 0.13 GY  -  - - 0.10 0.00 0.13 0.48 0.52 1.00 1.00 0.62 -   - - 0.45 0.42 0.52 0.45 0.03 1.00 1.00 0.58 TW  -  -  - - 0.15 0.05 0.17 0.02 0.06 0.05 0.23  - -    - 0.23 0.52 0.06 0.30 0.94 0.92 0.49 HI  -  -  - -  - 0.25 0.06 0.04 0.27 0.28 0.02  - -  -  -  - 0.34 0.17 0.01 0.81 0.84 0.14 CCI  -  -  -  -  - - 0.09 0.18 0.59 0.61 0.00 -  -   - -  -  - 0.14 0.08 0.86 0.82 0.45 C:N  - -  -   - -  -  - 0.19 0.70 0.72 0.23 -  -  -  -  -  -  - 0.14 0.79 0.76 0.07 GP - - - - - - - - 0.98 0.98 0.30 - - - - - - - - 0.07 0.06 0.25 BN - - - - - - - - - 0.98 0.66 - - - - - - - - - 0.98 1.00 BC - - - - - - - - - - 0.64 - - - - - - - - - - 0.98 HH = Harvest Height; NP = Number of Pods plant-1; NS = Number of Seeds pod-1; GY = Grain Yield; TW = 1000 Seed Weight; HI = Harvest Index; CCI = Chlorophyll Concentration Index; C:N = Carbon to Nitrogen Ratios; GP = Grain Protein; BN = Biomass Nitrogen; BC = Biomass Carbon; and CS = Carbon Sequestration 181  Appendix E Coefficients of determination (r2) between wheat performance metrics in wheat-bean intercrop combinations.  Wheat-common bean cv. ‘Red Kidney’ Wheat-common bean cv. ‘Black Turtle’  SL NS GY TW HI CCI C:N GP BN BC CS SL NS GY TW HI CCI C:N GP BN BC CS HH 0.10 0.17 0.56 0.21 0.29 0.00 0.15 0.10 0.64 0.20 0.09 0.30 0.01 0.05 0.04 0.04 0.25 0.18 0.02 0.38 0.42 0.19 SL - 0.74 0.00 0.03 0.04 0.00 0.03 0.09 0.25 0.00 0.23 - 0.36 0.01 0.04 0.04 0.01 0.01 0.00 0.62 0.19 0.00 NS - - 0.02 0.07 0.18 0.05 0.03 0.05 0.35 0.03 0.15 - - 0.29 0.26 0.24 0.00 0.08 0.08 0.05 0.94 0.04 GY - - - 0.14 0.10 0.06 0.01 0.30 0.94 0.94 0.28 - - - 0.06 0.00 0.00 0.03 0.05 0.04 0.98 0.16 TW - - - - 0.44 0.16 0.00 0.06 0.04 0.29 0.03 - - - - 0.49 0.42 0.07 0.14 0.00 0.56 0.04 HI - - - - - 0.04 0.12 0.02 0.00 0.27 0.00 - - - - - 0.26 0.58 0.62 0.06 0.96 0.00 CCI - - - - - - 0.10 0.04 0.45 0.73 0.20 - - - - - - 0.18 0.00 0.00 0.88 0.02 C:N - - - - - - - 0.30 0.01 0.14 0.05 - - - - - - - 0.42 0.14 0.68 0.19 GP - - - - - - - - 0.29 0.31 0.38 - - - - - - - - 0.12 0.96 0.00 BN - - - - - - - - - 0.77 0.92 - - - - - - - - - 0.04 0.00 BC - - - - - - - - - - 0.90 - - - - - - - - - - 0.79 HH = Harvest Height; SL = Spike Length; NS = Number of Seeds pod-1; GY = Grain Yield; TW = 1000 Seed Weight; HI = Harvest Index; CCI = Chlorophyll Concentration Index; C:N = Carbon to Nitrogen Ratios; GP = Grain Protein; BN = Biomass Nitrogen; BC = Biomass Carbon; and CS = Carbon Sequestration 182  Appendix F Coefficients of determination (r2) between performance metrics in wheat-fava bean intercrop combinations. Wheat Performance Metrics Fava bean Performance Metrics  NP NS CCI C:N GY TW HI GP BN BC CS SL NS CCI C:N GY TW HI GP BN BC CS HH 0.19 0.28 0.03 0.04 0.11 0.32 0.19 0.34 0.04 0.05 0.00 0.05 0.03 0.04 0.00 0.06 0.19 0.01 0.41 0.13 0.16 0.01 NP - 0.00 0.35 0.14 0.86 0.05 0.23 0.01 0.69 0.17 0.00 - 0.21 0.30 0.08 0.17 0.21 0.05 0.03 1.00 0.98 0.01 NS - - 0.00 0.00 0.00 0.34 0.11 0.22 0.46 0.02 0.05 - - 0.05 0.03 0.04 0.01 0.00 0.00 0.06 0.05 0.00 CCI  -  - - 0.06 0.41 0.02 0.01 0.06 0.58 0.82 0.00 - - - 0.13 0.04 0.05 0.08 0.00 0.58 0.52 0.12 C:N  -  -  - - 0.11 0.02 0.01 0.00 0.39 0.00 0.23 - - - - 0.01 0.27 0.40 0.32 0.38 0.33 0.10 GY  -  -  - -  - 0.03 0.11 0.00 0.98 0.95 0.09 - - - - - 0.09 0.00 0.11 1.00 1.00 0.04 TW  -  -  -  -  - - 0.32 0.08 0.34 0.00 0.00 - - - - - - 0.12 0.02 0.16 0.12 0.00 HI  - -  -   - -  -  - 0.05 0.07 0.13 0.06 - - - - - - - 0.04 0.34 0.30 0.01 GP - - - - - - - - 0.55 0.74 0.12 - - - - - - - - 0.39 0.37 0.45 BN - - - - - - - - - 0.67 0.54 - - - - - - - - - 1.00 0.59 BC - - - - - - - -  - 0.48 - - - - - - - - - - 0.53 HH = Harvest Height; NP = Number of Pods plant-1; NS = Number of Seeds pod-1; GY = Grain Yield; TW = 1000 Seed Weight; HI = Harvest Index; CCI = Chlorophyll Concentration Index; C:N = Carbon to Nitrogen Ratios; GP = Grain Protein; SL = Spike Length; BN = Biomass Nitrogen; BC = Biomass Carbon; and CS = Carbon Sequestration 183  Appendix G Coefficients of determination (r2) between pea performance metrics in barley-pea intercrop combinations.  NP NS GY TW HI CCI C:N GP NN BNF NT PBN BC CS HH 0.38 0.08 0.83 0.48 0.30 0.29 0.03 0.38 0.42 0.14 0.02 0.86 0.90 0.55 NP - 0.04 0.21 0.15 0.12 0.06 0.14 0.16 0.40 0.00 0.00 0.35 0.37 0.14 NS - - 0.07 0.11 0.36 0.00 0.08 0.14 0.10 0.00 0.01 0.18 0.14 0.02 GY - - - 0.19 0.45 0.23 0.14 0.24 0.42 0.14 0.10 0.98 0.98 0.40 TW - - - - 0.03 0.04 0.04 0.41 0.01 0.00 0.05 0.27 0.31 0.34 HI - - - - - 0.01 0.16 0.10 0.25 0.00 0.06 0.67 0.62 0.15 CCI - - - - - - 0.06 0.02 0.27 0.17 0.00 0.29 0.34 0.05 C:N - - - - - - - 0.09 0.09 0.01 0.00 0.34 0.28 0.00 GP - - - - - - - - 0.02 0.16 0.17 0.77 0.79 0.34 NN - - - - - - - - - 0.05 0.01 0.86 0.88 0.01 BNF - - - - - - - - - - 0.71 0.35 0.38 0.05 NT - - - - - - - - - - - 0.56 0.64 0.12 PBN - - - - - - - - - - - - 0.99 0.83 BC - - - - - - - - - - - - - 0.88 HH = Harvest Height; NP = Number of Pods plant-1; NS = Number of Seeds pod-1; GY = Grain Yield; TW = 1000 Seed Weight; HI = Harvest Index; CCI = Chlorophyll Concentration Index; C:N = Carbon to Nitrogen Ratios; GP = Grain Protein; NN = Number of Nodules; BNF = Biological Nitrogen Fixation; NT = Nitrogen Transfer; PBN = Plant Biomass Nitrogen; BC = Biomass Carbon; and CS = Carbon Sequestration 184  Appendix H Coefficients of determination (r2) between barley performance metrics in barley-pea intercrop combinations.  SL NS GY TW HI CCI C:N GP PBN BC CS HH 0.07 0.05 0.07 0.35 0.13 0.32 0.01 0.05 0.56 0.38 0.02 SL - 0.40 0.02 0.00 0.14 0.05 0.30 0.12 0.37 0.04 0.18 NS - - 0.03 0.15 0.50 0.00 0.31 0.05 0.07 0.05 0.24 GY - - - 0.17 0.28 0.17 0.40 0.64 0.61 1.00 0.12 TW - - - - 0.35 0.50 0.04 0.09 0.96 0.71 0.20 HI - - - - - 0.07 0.45 0.20 0.25 0.81 0.23 CCI - - - - - - 0.03 0.12 0.69 0.71 0.17 C:N - - - - - - - 0.58 0.06 0.59 0.08 GP - - - - - - - - 0.32 0.85 0.18 PBN - - - - - - - - - 0.66 0.00 BC - - - - - - - - - - 0.17 HH = Harvest Height; SL = Spike Length; NS = Number of Seeds pod-1; GY = Grain Yield; TW = 1000 Seed Weight; HI = Harvest Index; CCI = Chlorophyll Concentration Index; C:N = Carbon to Nitrogen Ratios; GP = Grain Protein; PBN = Plant Biomass Nitrogen; BC = Biomass Carbon; and CS = Carbon Sequestration   185  Appendix I Performance of cereals and legumes in monocultures and intercropping systems. A. 20 days after sowing                          Pea monoculture          Barley monoculture       Barley:pea (1:1)               Barley:pea (2:1)        Barley-pea (mixed)   Common bean monoculture    Wheat monoculture        Wheat:common bean (1:1) Wheat:common bean (2:1)    Wheat-common bean (mixed)       Fava bean monoculture     Wheat monoculture            Wheat:fava bean (1:1)      Wheat:fava bean (2:1)             Wheat-fava bean (mixed)  186  B. 40 days after sowing                                                                                     Pea monoculture          Barley monoculture       Barley:pea (1:1)               Barley:pea (2:1)         Barley-pea (mixed)   Common bean monoculture    Wheat monoculture        Wheat:common bean (1:1)  Wheat:common bean (2:1)     Wheat-common bean (mixed)       Fava bean monoculture     Wheat monoculture            Wheat:fava bean (1:1)      Wheat:fava bean (2:1)             Wheat-fava bean (mixed)  187  C. 60 days after sowing                             Pea monoculture          Barley monoculture       Barley:pea (1:1)             Barley:pea (2:1)       Barley-pea (mixed)   Common bean monoculture    Wheat monoculture       Wheat:common bean (1:1) Wheat:common bean (2:1)   Wheat-common bean (mixed)       Fava bean monoculture     Wheat monoculture            Wheat:fava bean (1:1)      Wheat:fava bean (2:1)             Wheat-fava bean (mixed)  188  D. 80 days after sowing                              Pea monoculture          Barley monoculture       Barley:pea (1:1)              Barley:pea (2:1)       Barley-pea (mixed)   Common bean monoculture    Wheat monoculture       Wheat:common bean (1:1) Wheat:common bean (2:1)   Wheat-common bean (mixed)       Fava bean monoculture     Wheat monoculture            Wheat:fava bean (1:1)      Wheat:fava bean (2:1)             Wheat-fava bean (mixed)  189  E. 100 days after sowing                              Pea monoculture          Barley monoculture       Barley:pea (1:1)              Barley:pea (2:1)      Barley-pea (mixed)   Common bean monoculture    Wheat monoculture        Wheat:common bean (1:1)   Wheat:common bean (2:1)   Wheat-common bean (mixed)       Fava bean monoculture     Wheat monoculture            Wheat:fava bean (1:1)      Wheat:fava bean (2:1)             Wheat-fava bean (mixed)  190  Appendix J CO2 flux, leaf area and chlorophyll concentration index measurements in cereal-legume intercropping systems.                                      CO2 flux measurements using an automated chamber connected to the portable gas analyzer unit    Leaf area measurements               CCI measurements 191  Appendix K Root growth and nodulation in cereal and legume genotypes.                                                          Commercial barley            Heirloom barley          Common bean cv. ‘Black Turtle’         Fava bean, 30 days after sowing        Fava bean, 60 days after sowing      Common bean, 60 days after sowing  192  Appendix L Types of cultivars based on the arrangement of spike-lets and seed characteristics.              2-row type      6-row type        Awnless         Hulled barley              Hulless barley           Black barley, a heirloom cultivar 

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