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Kiln drying optimization for quality hem-fir lumber Shahverdi, Mahdi 2015

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KILN DRYING OPTIMIZATION FOR QUALITY HEM-FIR LUMBER   by Mahdi Shahverdi M.Sc., The University of Tehran, 2008   A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in  The Faculty of Graduate and Postdoctoral Studies (Forestry)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  December 2015  © Mahdi Shahverdi, 2015 Abstract  Western hemlock is a dominant coastal species in British Columbia, Canada. This species is commonly marketed with amabilis fir as Pacific Coast Hemlock or hem-fir. Hem-fir is difficult to dry, mostly because of the existence of wetwood and large initial moisture content variation. The dried lumber will likely end up with a large final moisture content difference resulting in increased drying defects and decreased lumber quality and factory productivity. In this study, application of green chain moisture-based sorting coupled with drying schedule modifications were considered as ways to improve final moisture content variation within and between kiln dried hem-fir lumber.  There were two research phases. The first (without sorting), aimed to develop a modified drying schedule whereas in the second, the developed schedule was used along with a standard industrial schedule. Additionally, there was a green moisture content pre-sorting component in the second phase where freshly cut specimens were sorted based on their initial moisture content into three groups, i.e., mixed, low, and high moisture. To assess the specimen kiln dried quality, final moisture content variation, moisture content gradient, drying rate, warp, surface and internal checks, shrinkage, and casehardening were assessed. Data analysis revealed that there was no significant difference between the drying runs in terms of final moisture content variation, except in the high initial moisture content group. High initial moisture content sorting helped to reduce the final moisture content variation. The modified schedule, when there was a high initial moisture content sorting, also improved the uniformity of final moisture content in comparison to the industrial schedule. Moreover, neither the moisture sorting nor the drying schedule did affect the final moisture content variation for the low and mixed initial moisture content groups. Therefore, the green moisture-based pre-sorting was statistically effective just in the sorted group with high initial moisture content and where the modified schedule was used.          Preface This thesis entitled “Kiln drying optimization for quality hem-fir lumber” presents the research conducted by Mahdi Shahverdi, based on the initial research question by the supervisor, Prof. Stavros Avramidis. The proposed methodology in this manuscript is original, unpublished, independent work by the author.     Table of Contents  Abstract .......................................................................................................................................... ii Preface ........................................................................................................................................... iii Table of Contents ......................................................................................................................... iv List of Tables ............................................................................................................................... vii List of Figures ............................................................................................................................... ix List of Abbreviations ................................................................................................................... xi Acknowledgements ..................................................................................................................... xii 1. Introduction .............................................................................................................................. 1 2. Literature Review ..................................................................................................................... 3 2.1 Pacific Coast Hemlock ......................................................................................................... 3 2.1.1 Distribution ..................................................................................................................... 3 2.1.2 Properties and application .............................................................................................. 3 2.2 Wood drying ......................................................................................................................... 4 2.2.1 Reasons for drying wood ................................................................................................ 4 2.2.2 Water in wood ................................................................................................................ 4 2.2.3 Kiln design ..................................................................................................................... 5 2.2.4 Drying schedules ............................................................................................................ 7 2.3 Drying defects ...................................................................................................................... 8 2.3.1 Shape distortions (warp) ................................................................................................. 9 2.3.2 Surface checks .............................................................................................................. 12 2.3.3 Internal checks (honeycomb) ....................................................................................... 12 2.3.4 Drying stresses ............................................................................................................. 13 2.3.5 Internal moisture gradients ........................................................................................... 14 2.4 Wetwood ............................................................................................................................ 15 2.5 Sorting ................................................................................................................................ 16 2.6 Drying of Pacific Coast Hemlock ...................................................................................... 17 2.7 Objective ............................................................................................................................ 21 3. Materials and Methods .......................................................................................................... 22 3.1 Materials ............................................................................................................................. 22 3.2 Initial moisture content and basic density .......................................................................... 22 3.3 Sampling ............................................................................................................................. 22 3.3.1 Phase 1 .......................................................................................................................... 22 3.3.2 Phase 2 .......................................................................................................................... 23 3.4 Shrinkage and warp measurements .................................................................................... 24 3.5 Kiln schedules and drying procedure ................................................................................. 25 3.5.1 Kiln schedules for phase 1 ............................................................................................ 26 3.5.2 Kiln schedules for phase 2 ............................................................................................ 28 3.6 Post-drying measurements ................................................................................................. 28 3.6.1 Lumber dimensions ...................................................................................................... 28 3.6.2 Shape distortions .......................................................................................................... 28 3.6.3 Moisture gradient and final moisture content ............................................................... 29 3.6.4 Casehardening .............................................................................................................. 30 3.6.5 Surface checking and honeycomb ................................................................................ 31 3.7 Statistical analysis .............................................................................................................. 33 3.7.1 Statistical analysis for phase 1 ...................................................................................... 33 3.7.2 Statistical analysis for phase 2 ...................................................................................... 33 4. Results and Discussion ........................................................................................................... 35 4.1 Phase 1 ................................................................................................................................ 35 4.1.1 Basic density ................................................................................................................. 35 4.1.2 Initial moisture content ................................................................................................. 36 4.1.3 Drying time and rate ..................................................................................................... 37 4.1.4 Final moisture content .................................................................................................. 39 4.1.5 Final moisture content gradient .................................................................................... 41 4.1.6 Shrinkage ...................................................................................................................... 46 4.1.7 Shape distortions .......................................................................................................... 48 4.1.8 Surface checks .............................................................................................................. 54 4.1.9 Internal checks .............................................................................................................. 55 4.1.10 Casehardening ......................................................................................................... 55 4.2 Phase 2 ................................................................................................................................ 57 4.2.1 Basic density ................................................................................................................. 57 4.2.2 Initial moisture content ................................................................................................. 58 4.2.3 Drying time and rate ..................................................................................................... 60 4.2.4 Final moisture content .................................................................................................. 62 4.2.5 Final moisture content gradient .................................................................................... 64 4.2.6 Shrinkage ...................................................................................................................... 71 4.2.7 Shape distortion ............................................................................................................ 73 4.2.8 Surface checks .............................................................................................................. 81 4.2.9 Internal checks .............................................................................................................. 82 4.2.10 Casehardening ......................................................................................................... 82 5. Conclusions ............................................................................................................................. 85 5.1 Recommendations .............................................................................................................. 86 References .................................................................................................................................... 87  List of Tables Table 2.1. Summary of drying defects by cause (Denig et al. 2000). ............................................. 9 Table 3.1. Treatments applied in phase 2. .................................................................................... 24 Table 3.2. Industrial drying schedule (IS). ................................................................................... 27 Table 3.3. Modified 1 drying schedule (MS1). ............................................................................. 27 Table 3.4. Modified 2 drying schedule (MS2). ............................................................................. 27 Table 3.5. Modified drying schedule (MS) used in phase 2 (selected from phase 1). .................. 28 Table 3.6. ANOVA table used in assessing the possible differences between the treatments (treatment=drying schedules, i=experimental unit, j=treatment, nT=number of experimental units measured over all treatments). .................................................................................... 33 Table 3.7. ANOVA table used in assessing the possible differences in terms of interaction and main effects (factor A: drying schedule with 2 levels, factor B: Mi with 3 levels, i=experimental unit, j=factor A level, k=factor B level, nT=number of experimental units measured over all treatments). ............................................................................................. 34 Table 4.1. Basic density statistics for the runs in phase 1............................................................. 35 Table 4.2. Analysis of variance for basic density. ........................................................................ 35 Table 4.3. Initial moisture content statistics for the three runs. .................................................... 36 Table 4.4.  Analysis of variance for initial moisture content. ....................................................... 37 Table 4.5. Final moisture content statistics for the three runs. ..................................................... 39 Table 4.6. Analysis of variance for final moisture content. .......................................................... 39 Table 4.7. Paired sample t-test grouping for final moisture content. ............................................ 40 Table 4.8. Shell moisture content statistics for the three runs. ..................................................... 41 Table 4.9. Analysis of variance for shell moisture content. .......................................................... 42 Table 4.10. Paired sample t-test grouping for shell moisture content. ......................................... 42 Table 4.11. Core moisture content statistics for the three runs. .................................................... 43 Table 4.12. Analysis of variance for core moisture content. ........................................................ 44 Table 4.13. Paired sample t-test grouping for core moisture content. .......................................... 44 Table 4.14. Difference between shell-and-core moisture content statistics for the three runs. .... 45 Table 4.15. Analysis of variance for difference between shell-and-core moisture content. ......... 46 Table 4.16. Paired sample t-test grouping for difference between shell-and-core moisture content............................................................................................................................................... 46 Table 4.17. Shrinkage statistics for the three runs. ....................................................................... 46 Table 4.18. Analysis of variance for shrinkage. ........................................................................... 47 Table 4.19. Paired sample t-test grouping for shrinkage. ............................................................. 48 Table 4.20. Bow statistics for the three runs. ................................................................................ 48 Table 4.21. Analysis of variance for bow. .................................................................................... 49 Table 4.22. Crook statistics for the three runs. ............................................................................. 50 Table 4.23. Analysis of variance for crook. .................................................................................. 51 Table 4.24. Cup statistics for the three runs.................................................................................. 51 Table 4.25. Analysis of variance for cup. ..................................................................................... 51 Table 4.26. Twist statistics for the three runs. .............................................................................. 52 Table 4.27. Analysis of variance for twist. ................................................................................... 53 Table 4.28. Paired sample t-test grouping for twist. ..................................................................... 54 Table 4.29. Total length and percentage of surface check in correlation to the total specimens’ length.................................................................................................................................... 54 Table 4.30. Analysis of variance for surface checks. ................................................................... 55 Table 4.31. Paired sample t-test grouping for surface checks. ..................................................... 55 Table 4.32. Casehardening statistics for the three runs. ............................................................... 55 Table 4.33. Analysis of variance for casehardening. .................................................................... 56 Table 4.34. Paired sample t-test grouping for casehardening. ...................................................... 57 Table 4.35. Basic density statistics for the runs in phase 2........................................................... 57 Table 4.36. Analysis of variance for basic density. ...................................................................... 57 Table 4.37. Initial moisture content statistics for the six runs. ..................................................... 58 Table 4.38. Actual and adjusted drying times for the drying runs. ............................................... 61 Table 4.39. Drying rate (%/hour) at different moisture contents. ................................................. 62 Table 4.40. Final moisture content statistics for the six runs........................................................ 63 Table 4.41. Shell moisture content statistics for the six runs........................................................ 65 Table 4.42. Analysis of variance for shell moisture content. ........................................................ 66 Table 4.43. Core moisture content statistics for the six runs. ....................................................... 67 Table 4.44. Analysis of variance for core moisture content. ........................................................ 68 Table 4.45. Difference between shell-and-core moisture content statistics for the six runs. ....... 69 Table 4.46. Analysis of variance for difference between shell-and-core moisture content. ......... 71 Table 4.47. Shrinkage statistics for the six runs. .......................................................................... 71 Table 4.48. Analysis of variance for shrinkage. ........................................................................... 73 Table 4.49. Bow statistics for the six runs (mean values are the difference between measured bow before and after drying). ............................................................................................... 73 Table 4.50. Analysis of variance for bow. .................................................................................... 75 Table 4.51. Crook statistics for the six runs (mean values are the difference between measured crook before and after drying). ............................................................................................ 75 Table 4.52. Analysis of variance for crook. .................................................................................. 77 Table 4.53. Cup statistics for the six runs (mean values are the difference between measured cup before and after drying). ...................................................................................................... 77 Table 4.54. Analysis of variance for cup. ..................................................................................... 79 Table 4.55. Twist statistics for the six runs (mean values are the difference between measured twist before and after drying). .............................................................................................. 79 Table 4.56. Analysis of variance for twist. ................................................................................... 80 Table 4.57. Total length and percentage of surface check in correlation to the total specimens’ length.................................................................................................................................... 81 Table 4.58. Analysis of variance for surface checks. ................................................................... 81 Table 4.59. Casehardening statistics for the six runs. ................................................................... 82 Table 4.60. Analysis of variance for casehardening. .................................................................... 84  List of Figures  Figure 2.1. Distribution of western hemlock (left) and amabilis fir (right) (Wikipedia)................ 3 Figure 2.2. Schematic of a conventional kiln drying and the auxiliary parts (Simpson 1991). ...... 6 Figure 2.3. Shape distortions caused by the annual ring orientations and anisotropic shrinkage (Simpson 1991). ................................................................................................................... 8 Figure 2.4. Different types of shape distortion (Pratt 1974). ........................................................ 11 Figure 2.5. Surface checks in red oak (Simpson 1991). ............................................................... 12 Figure 2.6. Internal checks in the cross section of red oak (Simpson 1991). ............................... 13 Figure 2.7. Development of drying stresses during the drying process, (a) early and (b) later in drying (Anonymous 2010). ................................................................................................ 14 Figure 2.8. Moisture gradient and stress relationship during different stages of drying process of 50-mm-thick red oak (Anonymous 2010). ......................................................................... 15 Figure 3.1. Schematic of cutting and labeling pattern of green lumber in phase 1. ..................... 23 Figure 3.2. Schematic of cutting and labeling pattern of green lumber in phase 2. ..................... 24 Figure 3.3. Digital caliper used to measure dimension change. ................................................... 25 Figure 3.4. The 1-m (3-ft) laboratory drying kiln with the stickered package. ............................ 25 Figure 3.5. The 2.4-m (8-ft) drying kiln with the stickered package. ........................................... 26 Figure 3.6. Corresponding measurement points for the various warp cases (Simpson 1991). ..... 29 Figure 3.7. Aluminum table (left) and digital dial gauge (right) used to measure different types of distortions. .......................................................................................................................... 29 Figure 3.8. Measuring the shell-and-core moisture contents of dried specimens using a resistance pin-type moisture meter (left); oven-drying method for moisture content measurement (right). ................................................................................................................................. 30 Figure 3.9. Schematic of selection pattern for casehardening test from each dried package. ...... 30 Figure 3.10. Cutting pattern for measuring casehardening. .......................................................... 31 Figure 3.11. Summary of all the experiments carried out in the current project. ......................... 32 Figure 4.1. Initial moisture contents distribution for the drying runs. .......................................... 36 Figure 4.2. Drying curves for each of the three runs. ................................................................... 37 Figure 4.3. Adjusted drying curves for each of the three runs. ..................................................... 38 Figure 4.4. Drying rate at different moisture contents. ................................................................. 38 Figure 4.5. Distribution of final moisture content. ....................................................................... 40 Figure 4.6. Shell moisture content distribution for the three runs. ............................................... 41 Figure 4.7.  Core moisture content distribution for the three runs. ............................................... 43 Figure 4.8. Difference between shell-and-core moisture content distribution for the three runs. 45 Figure 4.9. Shrinkage distribution in the three runs in phase 1. ................................................... 47 Figure 4.10. Bow distribution in the three runs. ........................................................................... 49 Figure 4.11. Crook distribution in the three runs. ......................................................................... 50 Figure 4.12. Cup distribution in the three runs. ............................................................................ 52 Figure 4.13. Twist distribution in the three runs. .......................................................................... 53 Figure 4.14. Casehardening distribution in the three runs. ........................................................... 56 Figure 4.15. Initial moisture content distributions for the drying runs. ........................................ 59 Figure 4.16. Drying curves for the drying runs. ........................................................................... 60 Figure 4.17. Adjusted drying curves for each of the drying runs. ................................................ 61 Figure 4.18. Distribution of final moisture content through the six runs. .................................... 64 Figure 4.19.  Shell moisture content distribution for the six runs................................................. 65 Figure 4.20.  Core moisture content distribution for the six runs. ................................................ 67 Figure 4.21. Difference between shell-and-core moisture content distributions for the six runs. 69 Figure 4.22. Shrinkage distribution in the six runs. ...................................................................... 72 Figure 4.23. Bow distribution in the six runs................................................................................ 74 Figure 4.24. Crook distribution in the six runs. ............................................................................ 76 Figure 4.25. Cup distribution in the six runs. ............................................................................... 78 Figure 4.26. Twist distribution in the six runs. ............................................................................. 80 Figure 4.27. Casehardening distribution in the six runs. .............................................................. 83      List of Abbreviations  M Moisture content (%) iM Initial moisture content (%) Mf Final moisture content (%) Ms Shell moisture content (%) Mc Core moisture content (%) Memc Equilibrium moisture content (%) Mfsp Fiber saturation point moisture content (%) H Relative humidity (%) MiM Mixed (unsorted) initial moisture content group (%) MiH High initial moisture content group (%) MiL Low initial moisture content group (%) IS Industrial drying schedule MS1 Modified 1 drying schedule MS2 Modified 2 drying schedule T Temperature (oC)   Acknowledgements  I would like to convey my appreciation to my supervisor Prof. Stavros Avramidis for his support and advice during my studies as a graduate student.  My gratitude goes to Dr. Luiz Oliveira for his time and advice as a member of my committee. I would again like to thank Dr. Luiz Oliveira and his crew, Dr. Ciprian Lazarescu and Mr. Phil Star at FPInnovations for allowing me to use their lab facilities and also helping me throughout the experiments.  Thank you Morteza Taiebat and Amir Sohi for lending me a helping hand during the experiments.  Thank you Prof. Tony Kozak for your help regarding the statistical analysis of the data. 1 1. Introduction  Based on volume, western hemlock is a dominant coastal species in British Columbia, Canada (Middleton and Munro 2001). This species is commonly marketed with amabilis fir (they grow and harvested together from mixed forests) as Pacific Coast Hemlock (PCH or hem-fir), and the mix is normally comprised of 70-75% western hemlock (Tsuga heterophylla) and 25-30% amabilis fir (Abies amabilis) (Elustondo and Oliveira 2009). The mature standing volume of western hemlock is about 1.3 billion m3 and it is roughly 18% of the total volume of growing softwood stock in the province (COFI, 2000).  As in most cases and before lumber can be used in construction, remanufacturing, etc., it needs to be systematically dried. Kiln drying is a key stage in the chain of lumber manufacturing that turns out pieces of lumber with dimensional stability, higher strength, increased biological durability, reduced weight and thereby, minimized handling and shipping costs. Convective kiln drying is the most commonly used method to artificially remove water from wood and to reach a targeted moisture content within a reasonable drying time (Oltean et al. 2011). At the same time, kiln drying could give rise to defects that would reduce the grade and value of lumber. Some defects become obvious as they occur whereas others may not be realized until a later product manufacturing stage is commenced (i.e., remanufacturing).  Drying schedules are records that contain air temperature, humidity and velocity sets as a function of time or moisture content that have specifically developed for various species and lumber cross-sectional sizes (Simpson 1991). Optimized drying schedules are paramount for the production of high quality kiln-dried lumber and they can have a direct effect on drying times, drying costs and defects, i.e., shape distortions, residual stresses, cracks, and moisture content gradients between and within lumber pieces in the kiln (Cabardo 2007). Drying schedules for softwoods are normally divided into three stages, namely, heating, drying and conditioning, the latter not always used especially in the production of structural lumber. Presorting of green lumber before drying based on different parameters, e.g. basic density, initial moisture content, annual ring orientation, slope of grain, among other is an idea that has been explored in the past for optimizing drying quality (Choong and Fogg 1989, Simpson 1991, Oliveira et al. 1994, Swett and Milota 1999, Dening et al. 2000, Elustondo and Oliveira 2009). Since one of the difficulties in drying hem-fir lumber is the significant final moisture content 2 variation, presorting was thought as a means of alleviating this issue. Presorting is aimed to decrease the variability among the kiln stacks which would later help to get more favorable outcomes after the drying process depending on the purposes, i.e. better quality, lower final moisture content variation, and shorter drying time (Simpson 1991). Uneven drying conditions may occur when green lumber with different moisture contents is mixed in the kiln. This also may be intensified after drying, when there is a final moisture content variability within/among the lumber/stack because of natural variability in initial moisture content or drying rate, heartwood and sapwood, or wetwood in the lumber (which is common in western hemlock), or difference of drying conditions in various parts of the kiln. Therefore, it is impossible to ensure that all the dried lumber have the same final moisture content. The distribution of initial moisture content in lumber combined with inherent variability in lumber physical properties and random fluctuations in kiln drying parameters all contribute to dispersion in the final moisture (Cronin et al. 1997). Final (post-drying) moisture content variation can result in problems in subsequent processing and use of the kiln dried lumber. It could result in residual stresses which later will lead to warping, checking, and saw blade pinching in manufacture and use which all will reduce dried lumber value and yield. Thus, presorting of lumber based on their initial moisture content is likely to reduce over-drying and under-drying of the lumber at the end of drying process. In the current study, application of green chain moisture-based sorting coupled with modified drying schedules were considered to examine if the final moisture content variation within the PCH’s kiln stacks can be improved.            3 2. Literature Review  2.1 Pacific Coast Hemlock 2.1.1 Distribution Western hemlock which is the dominant species in British Columbia (Burns and Honkala 1990), grows along both the west and east sides of the Coast Ranges, from sea level to mid elevations, as well as in the Interior wet belt west of the Rocky Mountains (Parish 1995). Amabilis fir also grows along the coast between southern Alaska and northern California at mid to high elevations (Fig. 2.1). Since the both species have close characteristics, these species are usually harvested, processed, and marketed together (Bradic 2005). Mixed stands of PCH in British Columbia grow throughout the interior and coastal forests extending from Alaska southward (Fig. 2.1).    Figure 2.1. Distribution of western hemlock (left) and amabilis fir (right) (Wikipedia).   2.1.2 Properties and application The species have a medium to fine-textured wood (Alden 1995). It is fairly straight and even grained. Both the heartwood and the sapwood are almost white light color. The sapwood, though, is sometimes lighter and usually is not distinctive from the heartwood (Isenberg, 1980). The annual rings are distinctive, and the transition from earlywood to latewood is gradual (Panshin 4 and deZeeuw 1980). The wood is mostly free of resin and has no odor except the case the heartwood contains wet-wood with some extractives (Kozlik 1970, Ward and Pong 1980).  An average basic density value ranges between 377 and 423 kg/m3, and green moisture content also between 69 and 85% for amabilis fir and western hemlock in British Columbia, respectively (Nielson et al. 1985). Similar results for green moisture content were also reported by Dobie et al. (1966). The total volumetric oven-dry shrinkage is relatively high, 13% and 12% for amabilis fir and western hemlock, respectively (FPL 2010). Western hemlock may also contain wetwood which is formed in the heartwood zone that are related to bacterial activity. This area has a higher moisture content and density than the adjacent parts, and is difficult to dry (Schroeder and Kozlik 1972, Schneider and Zhou 1989). Details on this topic are given in section 2.4. PCH is commonly used for general construction, roof decking and plywood manufacturing and the wood also machines satisfactorily, sands smoothly, glues easily, and has high nail and screw holding abilities (Alden 1995). Its strength and nailing characteristics make it a popular construction material in North America and overseas (Burns and Honkala 1990, Anonymous 1997, Anonymous 2003). It is used for laminating stock and the production of glue laminated and solid beams. Other uses include: doors, windows, staircase parts, interior finish, floors, suspended ceilings, ladders, pilings, poles and railway ties and other purposes where a high-grade softwood is needed (Burns and Honkala 1990, Parish 1995).   2.2 Wood drying 2.2.1 Reasons for drying wood Kiln drying of wood is a key stage in the chain of wood processing. It produces pieces of lumber, chips, and veneer with dimensional stability, improvement of mechanical properties, increased biological durability, preparation for application of some treatments (gluing, preservative, fire retardant), improvement of dye-ability and trimming, reduced weight and thereby, minimized handling and shipping costs. 2.2.2 Water in wood Hygroscopicity of wood is a crucial physicochemical factor affecting the drying process. In other words, when wood is placed in an environment, depending on the relative humidity (H) 5 and temperature (T), it takes up or loses the water until the water potential in wood and the surrounding environment reaches equilibrium (Shahverdi et al. 2012).  The amount of water in the wood is commonly referred to as the percentage of moisture content on dry-basis. Moisture content is the mass of moisture in wood expressed as a percentage of the oven-dry mass which is calculated from the following equation (Siau 1995):            (1) where M = moisture content (%), w = mass of moist wood (g), wo = oven-dry mass of wood (g), dried at 102	3oC for 24 hours.  There are two forms of moisture in wood, namely, bound or hygroscopic water and free or capillary water. Bound water is believed to be hydrogen bonded to hydroxyl groups, primarily in cellulose and hemicelluloses, and to a lesser extent to the hydroxyl groups in lignin. The free water is held by weak capillary forces in the lumens and requires less energy to be removed. The moisture content in equilibrium with the relative humidity of the air is called the equilibrium moisture content (Memc) (Siau 1995). The fiber saturation point (Mfsp) is the moisture content corresponding to saturation of the cell wall with no free water in the voids. Mfsp ranges between 25 to 35%, and in practice is considered to be around 30%. Below Mfsp, mechanical and physical changes (e.g. shrinkage) begin to take place (Haygreen and Bowyer 1996, Simpson 1991). In an ideal situation, when all free water has been evaporated then bound water starts to evaporate (Tiemann 1906). The energy required to remove bound water from the cell walls is greater than the one required to evaporate free water from the lumens.  2.2.3 Kiln design There are different methods and techniques for drying wood, such as, conventional drying, air drying, dehumidification, radio frequency vacuum drying, superheated steam drying, superheated steam vacuum drying, microwave drying, etc. The industrially used kiln is commonly called the conventional or convective kiln (Fig. 2.2). Such kiln comprises of one or more chambers designed to provide and control heat, humidity, and air circulation necessary for the favorable drying of lumber. As the wood dries, the relative humidity (H) and temperature are systematically changed. The kilns are designed to operate within 6 a specific range of temperatures, which mostly depends on the species to be dried and quality and end use of the dried lumber.   Figure 2.2. Schematic of a conventional kiln drying and the auxiliary parts (Simpson 1991).   Drying is a process in which water is evaporated from the wood. Even though the evaporation requires the greatest heat load, a number of other factors will add to the total heat requirement: 1) heat to warm the kiln machinery, 2) heat to warm the lumber stack, consisting of wood and water, 3) heat to raise the kiln air to the required temperature, 4) heat to warm fresh air inhaled, 5) heat lost to wet air exhausted, 6) heat lost as a result of unwanted leaks from the kiln (Bachrich 1980). This energy would be directly or indirectly generated and passed through the kiln using the air. If indirect, heat is generated by a hot fluid (hot water, steam, and thermal oil) which flows through the embedded pipes and gives off its heat to the kiln medium. Electric heating would be another source of heating which can be used together with the heating fluid.  Air circulation is another factor affecting the performance of any wood drying kiln. A reasonable air velocity is required across the lumber pile for several reasons such as to deliver heat to lumber piles and remove the moisture from the lumber surface. Typical air velocity in conventional kilns is also about 1-1.5 m/s (Bradic 2005). In steam heated kilns the moisture is 7 supplied by a low pressure/wet steam spray system, which thoroughly distributed in the kiln by the circulating air as a means of controlling of H. Ventilation is also done in the conventional kilns to diminish the relative humidity within the kiln. At the same time that the moisture is evaporated from the wood, the air is enriched with humidity and should be vented according when it exceeds the required H defined in the drying schedule and colder and drier air inhaled. The cold and dry air is heated to dry-bulb temperature (TDB) and venting will stop when the H has been reduced. In this way, the temperature and H are maintained in the kiln according to the drying schedule (Bachrich 1980).   2.2.4 Drying schedules The need for high-quality dried products has motivated researchers to establish wood drying schedules for different lumber dimensions and wood species. Drying schedules are tables that contain air temperature, humidity and velocity sets as a function of time or moisture content that have specifically developed for various species and lumber cross-sectional sizes. Drying conditions in a kiln, established by the schedule, can affect the quality of lumber. Drying schedule is, in fact, a compromise between the need to dry lumber as fast as possible and, at the same time, to avoid conditions that will cause related defects. In addition, the development of drying stresses should be taken into account because they may cause defects at the end of the process (e.g. surface and internal cracks, warp). A proper schedule is the one in which the drying stresses do not exceed the wood strength at any given M and temperature (Anonymous 2010). Drying schedules vary based on different criteria, i.e., species, initial moisture content, thickness, grade, and end use of dried lumber (Anonymous 2010). Hardwoods are usually dried by the moisture-based schedules in which the drying conditions are changed when the lumber reaches to a certain level of moisture contents. Softwoods are, on the other hand, dried by time-based kiln schedules in which the drying conditions are changed when certain period of time is passed, regardless of the level of moisture content (Simpson 1991). A typical conventional drying schedule is comprised of two main steps: 1) temperature is increased and relative humidity decreased to dry the wood down to the Mfsp while removing the free water; 2) the temperature and H are either increased or held constant to remove as much bound water as required to get to the desired target moisture content (Brunner-Hildebrand 1987). 8 There are some ways to modify the drying schedule itself which is based on the observations of a kiln operator. The general proposed schedule for a specific species, for instance, might not have a significant negative effect on the dried wood quality, which means that the wood is likely to tolerate a more severe schedule without developing serious defects. The intention of using the end product of drying process is also crucial for the modification since the dried product does not, in some cases, need to be free of defects. The main three means of modifying a drying schedule are: 1) pick up a higher wet-bulb depression (shifting to the higher wet-bulb depression schedule number). It might result in minor surface and end checks which are generally acceptable for many uses; 2) increase the dry-bulb temperature (shifting to the higher dry-bulb temperature number); 3) modify certain steps within a schedule by changing the dry- and wet-bulb temperatures. In general, any of these modifications should be made with caution and several charges should be dried before making any modification in the schedule (Simpson 1991).  2.3 Drying defects Drying defects are of the most costly items in drying of lumber. They cost the softwood and hardwood lumber industries millions of dollars every year in lost value and lost volume (Simpson 1991). Almost all forms of wood drying defects are attributable to the anisotropic shrinkage potentials during drying (Fig. 2.3). Denig et al. (2000) summarized the drying defects together with their causes as shown in Table 2.1.   Figure 2.3. Shape distortions caused by the annual ring orientations and anisotropic shrinkage (Simpson 1991). 9 Table 2.1. Summary of drying defects by cause (Denig et al. 2000). Cause Defect Drying too rapid   Surface checks  End checks  Internal checks (honeycomb)  Splits and cracks  Collapse Drying too slow   Fungal stain  Mold  Mildew  Decay  Warp, especially cup  Chemical stains  Checking Poor stacking   Warp, especially bow  Uneven drying Operational errors   Lumber is too wet  Lumber is too dry  Residual tension set Miscellaneous defects   Ring failure, shake  Checked or loosened knots  Heart split Processing defects   Raised, chipped, fuzzy, or torn grain  Planer splits  Warp during and after machining  Saw pinching (tension set defect)  Bad odors (related to bacteria) Gluing problems, especially end splits and open joints   2.3.1 Shape distortions (warp)  Shape distortion refers to any type of deviation in the lumber surface and/or edges from the straight line, or any change in the angles of each corner. Much of the shape distortion which occurs during drying is because of uneven shrinkage in all directions of a piece of lumber. Shrinkage along the grain is actually very small and is mostly neglected. However, it is not always 10 the same and there are some cases that shrinkage occurs appreciably along the length, occasionally as much as 1 or 2%, such as in reaction or juvenile wood (Pratt 1974).  2.3.1.1 Twist  Twist is the turning of one of the corners of a lumber, so that they are no longer in the same plane (Fig. 2.4). Spiral or interlocked grain contribute to the occurrence of this type of defect in the dried lumber (Boladis 1972, Simpson 1991, Dening et al. 2000, Forsberg and Warensjo 2001). As a result, this could be attributed to the differential shrinkage in such lumber (Pratt 1974). In addition, they found out the lumber containing these characteristics can sometimes be dried reasonably flat by using appropriate stacking procedures. However, there are some contradictory studies showing no or little correlation between grain angle and this type of defect (Shelly et al. 1979, Beard et al. 1993). 2.3.1.2 Bow Bow is a flatwise deviation from a straight line drawn from end to end of a lumber (Fig. 2.4). This is often the result of not sawing the lumber parallel to the bark. It is associated with longitudinal shrinkage in juvenile wood near the pith, reaction wood, and spiral grain. So, the cause is the difference in longitudinal shrinkage on opposite faces of a lumber. Moreover, this type of defect can also be the result of poor stacking, for example: stickers are not aligned and/or too far apart, stickers are not uniform in thickness, or foundations are uneven (Simpson 1991, Dening et al. 2000).  2.3.1.3 Crook (spring)  Crook is an edgewise deviation (Fig. 2.4). This type of defect is often a result of improper sawing patterns or crooked logs such that the rings, when viewed from the end of the piece of lumber, are off center edge-to edge. Often the wood closer to the center of the tree shrinks more than does the wood closer to the bark. Although good stacking practices also help reducing the crook, but they are not as effective against this type of warp as they are against cup, bow, and twist (Simpson 1991, Dening et al. 2000).    11 2.3.1.4 Cup  Cup is a flatwise deviation from a straight line drawn across the width of a lumber (Fig. 2.4). It appears fairly early in the drying process and becomes progressively worse as the drying continues. This kind of defect is a result of the differential shrinkage between the two faces of a piece of lumber. In general, the greater the difference between tangential and radial shrinkage, the greater the degree of cup.  Since the tangential shrinkage is greater than radial one, so the flatsawn lumber cups toward the face that was closest to the bark. A flatsawn lumber cut near the bark tends to cup less than a similar lumber cut near the pith because the growth ring curvature is less near the bark. Flatsawn lumber from small-diameter trees is more likely to cup than those from large-diameter trees. The quartersawn lumber does not cup and cup is actually a natural tendency of flatsawn lumber. Thinner lumber cups less than thicker ones. Cup can cause excessive losses of lumber in machining, for example, the pressure of planer rollers often splits cupped lumber. Cup can be reduced by avoiding over-drying, putting weights on top of the lumber packages, and good stacking.  Figure 2.4. Different types of shape distortion (Pratt 1974).    12 2.3.2 Surface checks  Surface checks develop on the surface of a piece of lumber during drying (Fig. 2.5). They are caused by tension stresses that develop in the outer part of lumber as the drying progresses. When the drying stresses exceed the tensile strength of wood perpendicular to the grain they start to emerge. It means that these stresses may become great enough to tear the outer fibers apart which later will cause the surface checking (Bramhall and Wellwood 1976, Simpson 1991). Since the shrinkage in the direction of the growth rings is greater, so the checking is most likely to occur mainly on the flatsawn surface of lumber and on the edges of quarter-sawn lumber. This type of check is often occurs along the rays which form planes of weakness (Pratt 1974). Surface checks, however, could be closes up when the stress reversal happens (McMillen 1958). Surface checking is more likely during the first stage of drying process, when the lumber is green and loses one-third of its moisture. So, the moisture gradients is considerable in the first steps of drying; though in some softwoods the danger is still exist through the drying. In general, the main cause of surface checking is drying the lumber too fast in the first steps, and the result is even worse when the H is also too low, velocity is too high, and excessive temperatures are applied (Pratt 1974, Simpson 1991, Dening et al. 2000; Keey et al. 2000). Accordingly, Keey et al. (2000) suggest that this can be minimized by maintaining high relative humidity at the first steps of drying, which will later prevent surface shrinkage and increase the plasticity of the wood to accommodate the stresses.   Figure 2.5. Surface checks in red oak (Simpson 1991).  2.3.3 Internal checks (honeycomb) Honeycomb is an internal crack caused by a tensile failure across the grain of the wood and usually occurs along the wood rays (Fig. 2.6). When the internal tension stresses develop in 13 the inner parts of lumber, this type of cracks starts to occur. This is more probable when the core has still high moisture content (more than fiber saturation point) and the drying temperature is tried to be increased. So, we can prevent this defect by avoiding application of high temperatures when the wood has still free-water inside. In the other words, before safely raising the temperature, the core moisture content (Mc) of lumber should have been dropped below the Mfsp to avoid emergence of honeycomb (Simpson 1991). The problem is that in many cases the defect is not found until the lumber is processed. This type of drying defects will then bring about significant losses of lumber.    Figure 2.6. Internal checks in the cross section of red oak (Simpson 1991).  2.3.4 Drying stresses  Shrinkage is the driving force behind drying stresses so that without shrinkage, no drying stresses would be expected. At the very beginning of drying (stage I exists from green moisture to 2/3 of that), no shrinkage happens and so the lumber is stress-free. Followed by that and at the beginning of the second drying stage (stage II begins at 2/3 of green moisture and continues to 30% moisture), shrinkage occurs close to the surface. At this moment, if a piece of the lumber is cut into slices, the outer slices would have a shorter length than the inner ones since the tensile and compressive stresses are formed in the outer surfaces and inner layers, respectively. During this stage, surface checking is likely as well. As the drying proceeds and in the third drying stage (stage III exists from 30% moisture to the Mf), the core layer dry under tensile stress (which are smaller than outer parts) and outer layer dry under compressive stress (Fig. 2.7). This phenomenon is known as stress reversal. The residual stress level depends on many parameters (growth history, sawing pattern, drying conditions, thickness, species etc.) which cause most of the problems when it comes to drying optimization (McMillen 1958, Perre 2007). Fig. 2.8 depicts the moisture content gradient and residual stresses relationship at the end of a typical drying process. 14  Figure 2.7. Development of drying stresses during the drying process, (a) early and (b) later in drying (Anonymous 2010). 2.3.5 Internal moisture gradients  The process of removing water from a piece of wood can be divided into three main stages. Stage 1 is when the wood is fully wet and the free water flows from the core towards the surface layers. In this stage, the evaporation rate is high and the surface layers start to be dried depending on the permeability of drying wood itself. During this constant drying rate period, the gradient is the steepest since the free water from the shell is removed much faster than the one from the core (Fig. 2.8). As the drying proceeds and into stage II, M begins to drop towards Mfsp and the drying rate decreases. In this range, the free water still keeps moving towards the outer layers by the diffusion process and shrinkage occurs in there. Followed by stage II, the fluid movement just happens by the diffusion process into stage III and the drying rate drops significantly. Shrinkage and stress reversal result in emerging of drying stresses. Accordingly, during all these stages, the surface layers’ moisture is lower than the inner parts and it is mostly the case even when the drying process terminated, which is called moisture gradient. In other words, moisture gradient refers to a condition where each of the dried lumber in a kiln charge have a different level of M that deviates from the Mf. Not only this will cause lots of drawbacks (warp, residual stresses, cracks, losses etc.), but the lumber with a great M gradients should be rejected since the average lumber Mf is either 15 above or below an acceptable range for specific purposes (construction, furniture etc.) (Simpson 1991, Rohrbach 2008).   Figure 2.8. Moisture gradient and stress relationship during different stages of drying process of 50-mm-thick red oak (Anonymous 2010). 2.4 Wetwood Western hemlock is one of the species which carries wetwood (wet-pocket, sinker heartwood). Some areas in heartwood includes portions of abnormal wood termed wetwood or sinker or heavy wood. Schroeder and Kozlik (1972) believe that the end product of a reaction by the tree to injury, in which additional extractives are also deposited, is the source of forming wetwood.  In contrast to the adjacent normal heartwood, this type of wood has higher initial moisture content, extractives, and specific gravity, but lower drying rate (Kozlik 1970, Schroeder and Kozlik 1972). Higher specific gravity can be explained by the higher extractive contents of 16 this abnormal wood. A greatly low permeability area, resulted by extractives deposition, prevents loss of moisture during heartwood formation. This phenomenon will result in a decreased final moisture content uniformity at the later of the drying (Kozlik 1970, Simpson 1991). Simpson (1991) mentioned that the typical kiln drying time for western hemlock dimension lumber to the final moisture content of 19% is 78 h for normal heartwood (65% green moisture content), 115 h for sapwood (170% green moisture content), and 160 h for wetwood (145% green moisture content).  2.5 Sorting  Sorting of green lumber (presorting)  has been studied based on different parameters, e.g. species, basic density, initial moisture content, heartwood and sapwood, wetwood, annual ring orientation, slope of grain, grade, thickness, and length (Simpson 1991, Dening et al. 2000). One of the difficulties in drying hem-fir lumber, however, is a significant final moisture content variation within and/or among the lumber. Green moisture content in western hemlock ranges from 55% in heartwood to 143% in sapwood, and for amabilis fir ranges from 55% in heartwood to 164% in sapwood (Nielson et al. 1985). Even though these two species are of, more or less, the same characteristics, but they show different behaviors when they come to drying. Even with exactly the same initial moisture contents, they can dry at different rates which is because of variations in species, basic density, percentage of sapwood and heartwood, percentage of juvenile, presence of compression wood, lumber dimension, slope of grain, annual rings orientation, non-uniform drying conditions inside the kiln, and last but not least presence of wetwood (Elustondo and Oliveira 2009).   So, the presorting is aimed to decrease the variability among the kiln stacks which would later help to get more favorable outcomes after the drying process depending on the purposes, i.e. better quality, lower final moisture content variation, less moisture content gradient through the shell-and-core, and shorter drying time. Presorting of lumber based on their initial moisture content is likely to reduce the chance of having over-dried and under-dried lumber at the end of drying process. This would consequently decrease the final moisture content variation among the kiln stack. Smith and Dittman (1960) did the sorting on white fir (Abies concolor) into three groups of heartwood, sinker, and sapwood which later resulted in a uniform drying within each sort. 17 Oliveira et al. (1994) presorted hem-fir baby squares based on basic density and species to evaluate the influence of presorting on the drying time, shrinkage, and moisture content gradient between the core and shell. Three species groups of mixed hem-fir, hemlock, and amabilis fir were considered for species separation, together with two groups of low and high basic densities. All of them were then dried by the same drying schedule. Species separation showed that there was not an improvement in the final moisture content distributions. Basic density separation, though, revealed that groups of low density lumber resulted in a reduction of volumetric shrinkage, drying times, moisture content gradient between core and shell, and also variability comparing to the ones with high density. Kozlik (1981) studied the shrinkage of western hemlock heartwood lumber dried by conventional (85oC) and high-temperature (110oC) kiln schedules which equilibrated to 11, 6, and 0% moisture content. Specimens divided into two groups of end-matched 50×150 mm (2 inch by 6-inch) western hemlock dimension lumber and vertical grain 50 × 150 mm (2-inch by 6-inch) clear lumber containing varying amounts of wetwood. There were four classifications depending on the amount of wetwood which samples contains; 1) normal, no wetwood, 2) streak, 3 - 13 mm wide (1/8 – 1/2-inch-wide) sinker heartwood, 3) band, 13 to 25 mm (1/2 - 1-inch); 4) sinker, 25 mm (1 inch) wide or more. Samples with normal heartwood shrank similarly with either schedules. Conventional drying of matched specimens resulted in lower amount of shrinkage than high-temperature drying of band, streak, and sinker heartwood specimens. Total shrinkage was approximately equal for the four heartwood classifications. Shrinkage adjustment of the vertical-grain specimens to a 90° ring angle did not show any differences in total shrinkage except in one-thirds of comparisons in the tangential plane. Density sorted western hemlock lumber of 114 mm by 114 mm was dried and then equilibrated to Japanese moisture content by Wallace et al. (2003). Beside the promising results with density sorting, it was suggested that a Mf of 15% at the core would balance end-use stability and drying time as the lumber is equalized to the Japanese conditions.  2.6 Drying of Pacific Coast Hemlock The most common degrades found in 50 mm (2-inch) western hemlock planks result from excessive warping and non-uniformity in final moisture content (Kozlik, 1963). He argues that kiln drying schedules proposed by governmental and private research agencies generally are 18 conservative and schedule adjustment can be recommended to the most mills which have got modern conventional dry kilns. Then he examined the influence of different equilibrium moisture contents, dry-bulb temperatures, and air velocities on 50 × 250 mm (2 by 10-inch) western hemlock dimension lumber. The results showed that an initial dry-bulb temperature of 80oC can be tolerated by the species without increased degrade. Equilibrium moisture content (Memc) of 9% used in the initial conditions can be followed by conditions for 6% Memc for western hemlock when the average moisture content of the wood has reached 22%. Velocity of at least 122 meters per minute is suggested which results in a uniform final moisture content. Abner (1964) considered two ways to improve the moisture uniformity in kiln dried western hemlock lumber. One was presorting based on weight classes and the other one was to develop schedules. The first approach (green weight sorting) was successful in reducing the moisture non-uniformity. However, the drawback with this method is that twice as many sorts are needed on the green chain. So, he chose the second approach which was to develop proper schedules for reducing moisture non-uniformity. Moreover, two basic types of schedules were used in drying of 38 mm (1-½ inch) western hemlock dimension lumber. The first schedule is an equalizing type schedule where drying slows up at the end by setting up an equilibrium moisture content of 10 to 12% in the kiln, which prevents the fast drying pieces from becoming over-dried while allowing drying of the slower drying pieces. The second schedule is a constant drying schedule combined with 6 hours of conditioning. The quality of the dried lumber with the either schedules was approximately the same. The advantage of constant drying schedule was using shorter kiln residence time. The other schedule (equalization schedule) had the advantage of reducing the possibility of over-drying because higher equilibrium moisture content at the later stage of the schedule prevented the lumber from drying below about 10%. Extending the drying time to 132 hours and using a longer equalizing period were also examined and showed that it could dry the lumber to an average moisture content of around 14% and finally reduced the number of pieces over 19% moisture content to 5%. It was concluded that fast, severe schedules increase the drying degrade and result in poor moisture uniformity. Kozlik (1970) studied drying of western hemlock heartwood to a uniform final moisture content. He maintains that the two obstacles that industries are encountered with during processing of this species include the wide variation in moisture content after kiln drying and large losses in grade raised by shake. Shake is actually a separation of the annual rings parallel to the rings. This 19 defect is often related to a weakening of the wood in the standing tree by bacterial action (Denig et al. 2000). Since shake occurs in the living tree, degrade loss from shake is an unavoidable, and it can only be eliminated by proper trimming in the sawmill. The presence of wetwood will result in a decreased final moisture content uniformity at the later of the drying. He compared industrial kiln schedule with a revised high temperature schedule (above 100oC) when drying of 50×100, 50×150, and 50×200 mm (2 by 4, 2 by 6, and 2 by 8-inch) dimension western hemlock lumber. The high temperature schedule reduced total drying time, though did not affect the uniformity of final moisture content. Espenas (1971) studied the effect of drying conditions on the shrinkage of 38 mm (1½ inches) square by 380 mm (15 inches) long of western hemlock. Specimens were dried under different temperatures (32, 66, 180, 93, 102, and 110oC) and Memc of 6, 9, 12, and 6%. At the end of drying and after cooling, the samples were placed in a humidity room with the same Memc as the lumber dried to allow them to reach equilibrium. The higher temperature resulted in higher shrinkage compared to the lower temperatures. Shrinkage was also greater with drying conditions set for 12% Memc than when drying conditions for the lower Memc. Accordingly and depending on the Memc conditions, shrinkage was increased by a factor of up to 2.1. Schroeder and Kozlik (1972) also addressed the wide variation in final moisture content of western hemlock as an obstacle in drying of the wood. They also consider the presence of wetwood in the heartwood as a source for lacking uniformity of final moisture content in the dried samples which was also approved by Kozlik and Hamlin (1972).  In another work by Kozlik and Hamlin (1972), pre-steaming of western hemlock lumber was considered as a possible means of minimizing variability in final moisture content. 50 mm (2 inch) thick dimension lumber in 100, 150, and 200 mm (4, 6, and 8-inch) widths were studied. 4 to 24 hours of pre-steaming followed by drying with either conventional or high-temperature schedules did not decrease non-uniformity. Moreover, high-temperature and conventional schedules were also applied without pre-steaming treatment. The overall drying time reduced for high-temperature schedule when compared to industrial schedules. Degrade was not increased by high-temperature schedule and the final moisture content uniformity was also improved. Segregation of wetwood on the green chain was also done based on the presence of wetwood, offering improvement in final moisture content uniformity and total reduction of the kiln time. 20 Bramhall and Wellwood (1976) proposed using of special conventional and high-temperature schedules when drying western hemlock which is or is not mixed with amabilis fir. Mackay and Oliveira (1989) also proposed a conventional drying schedule when drying upper grades western hemlock and amabilis fir (hem-fir) down to 10-12% moisture content. Milota et al. (1993) suggest using of equalization at the end of the drying process as a recognized way to improve the Mf variability, though western softwood mills for having shorter drying times are not willing to consider that. Milota (2000) also considered the effect of conventional and high-temperature drying on warp and shrinkage of hem-fir stud. 50 × 100 mm (2 by 4-inch) hem-fir stud lumber was dried at conventional (82oC) and high-temperatures (116oC to 132oC). In the drying schedules used, the wet-bulb temperature changed during the drying. By increasing temperature from 82oC to 115oC, the drying time will be approximately halved. Lumber dried at higher temperatures might have a greater percentage of wet pieces than ones dried to the same Mf at 82oC. Drying at higher temperatures resulted in greater thickness shrinkage. So, it might be necessary to increase target size by 0.13 to 0.25 mm (0.005 to 0.010 inch) for a 40 mm thick piece when using the high-temperature schedules. Drying wood at high temperature reduced the average amounts of twist and particularly bow and crook measured, though not significantly. However, the number of pieces exceeding the limits allowed by the grading rules seemed to be more a function of final moisture content than drying temperature. Bradic and Avramidis (2007) applied a mixed time-moisture based schedule to figure out the influence of juvenile-wood on the drying quality of hem-fir baby-squares. Wet-bulb depression through the initial drying stages is very low to minimize the surface checking and other drying defects early in the cycle on thick hem-fir timbers. Wet-bulb depression and dry-bulb temperature increased in a step-wide mode until reaching the highest temperature level at the beginning of the step 9. The drying continued until the desired average final moisture content was reached. The 9th step followed by the conditioning treatment during which the dry-bulb and wet-bulb depression were reduced. The results also showed that there was highest bow, twist and surface checks when the pith was in the center of the lumber. When the pith was close to the sides of the cross section, lumber had a lower quality, though was acceptable based on industrial grading rules. Rohrbach et al. (2014) studied the effect of conventional drying schedules and equalization for one week on western hemlock quality. The intense drying schedule along with a conditioning reduced casehardening, though that increased the twist and diamonding than the milder schedule. 21 The equalization also found to be useful where internal moisture gradients are expected to further level off.   2.7 Objective The current study aims to investigate the application of green chain moisture-based sorting coupled with modified drying schedules for possible improvement of the final moisture content variation within Pacific Coast Hemlock lumber upon kiln drying. The results are expected to provide industry with an option for drying hemlock at reduced times and cost together with enhanced productivity and quality of produced lumber.                       22 3. Materials and Methods  3.1 Materials A total of 374 green western hemlock lumber were obtained from a local BC mill during the rainy fall period (middle of December). They were all 3600 mm (12 ft) long, and namely 50 x 100 mm (2 by 4 in) in cross-section. To minimize the moisture loss, all the lumber (before and after cutting) were wrapped in plastic and kept in a cold area for further processing.  3.2 Initial moisture content and basic density After removing the “reject” parts of 100 mm from each side of all the lumber to minimize the differences between moisture content along the green lumber, one cookie was cut from each end of lumber for the Mi and basic density (ρb) measurements in both phases (Fig. 3.1). The cut cookies were immediately weighed with an electric balance and their green volume was also measured by a digital caliper for ρb calculations. Finally, they were oven-dried at 103±2oC for 24 hours. The mean value of the two cookies was considered for each of the corresponding kiln specimens (Fig. 3.1).  3.3 Sampling The current study was divided into two phases. The first phase (without sorting) aimed to develop a modified drying schedule to be used in phase 2. In phase 2, the selected schedule from the last phase was used along with the standard industrial schedule. There was also a green moisture content pre-sorting in phase 2.  3.3.1 Phase 1 Each green specimen was cut into three kiln specimens of 50×100×900 mm (Fig. 3.1). Each of the three parts of an original green lumber was used towards an exclusive drying run, as shown in Fig. 3.1 (e.g. kiln specimen cut from the middle of the lumber and labeled as B was just considered for a separate drying run). Both ends of each kiln specimen were also coated right after cutting by polyvinyl acetate (PVA) glue to prevent excessive moisture loss. In phase 1, each run (kiln package) was comprised of 72 kiln specimens in 9 layers with 8 lumber in each layer. Moreover, the first phase aimed to develop a modified drying schedule to be used in the phase 2. 23  Figure 3.1. Schematic of cutting and labeling pattern of green lumber in phase 1.  3.3.2 Phase 2 In Phase 2, all the green specimens were to be sorted based on their Mi into three distinctive groups of mixed Mi (MiM or unsorted), low Mi (MiL), and high Mi (MiH). Each green specimen was cut into three kiln specimens of 50×100×900 mm, same way as in phase 1 (Fig. 3.2). Both ends of each kiln specimen were coated right after cutting by PVA glue to prevent excessive moisture loss. Since the presorting was important in this phase, the kiln specimens labeled as A and B (Fig 3.2). Firstly, the kiln specimens labeled as A were considered for two runs with MiM. For matching purposes and for having the same kiln packages with similar Mi mean and variability, the kiln specimens were placed in a descending order according to their Mi from 1 to 144. Then, they were placed in two separate subgroups, namely, the odd numbered kiln specimens were placed in one group and the even numbered ones in another group. Secondly, the kiln specimens labeled as B went towards the four runs with either MiL or MiH. In the same way as before, for matching purposes and for having the same kiln packages with similar qualities in terms of Mi mean and variability, the kiln specimens were placed in an ascending order according to their Mi from 1 to 288. However, this time, the first half (144 specimens) with lower Mi was divided into two subgroups representing the MiL groups and the remaining half (144 specimens) with higher Mi was again divided into two subgroups with the same way as before representing the MiH groups. 3600 mm (12 ft)900 mm50 mmKiln specimenCookie25 mm100 mm50 mm(2 in)A B C24  Figure 3.2. Schematic of cutting and labeling pattern of green lumber in phase 2.  Therefore, there were 6 groups all together, each with 72 kiln specimens (i.e., 2 groups of MiM, 2 groups of MiL, and 2 groups of MiH). In phase 2, each run (kiln package) was then comprised of 72 kiln specimens in 9 layers each with 8 lumber. Table 3.1 shows the number of variables and treatments in phase 2.   Table 3.1. Treatments applied in phase 2. Drying schedule Mi category Treatment Industrial Mixed Industrial –MiM Low Industrial –MiL High Industrial –MiH Modified Mixed Modified – MiM Low Modified –MiL High Modified –MiH  3.4 Shrinkage and warp measurements Digital calipers were used to measure the thickness at mid-length of the kiln specimens before and after drying for calculating shrinkage. Before measurement, a line was drawn to ensure that the same point before and after drying was always used for the corresponding measurements (Fig. 3.3). 3600 mm (12 ft)900 mm50 mmKiln specimenCookie25 mm100 mm50 mm(2 in)A B B25  Figure 3.3. Digital caliper used to measure dimension change. Twist, cup, bow, and crook were measured before drying on a shop-built aluminum table using a shop-built digital dial gauge (Figs. 3.6 and 3.7). The measurements were conducted on the points (where usually the greatest deflection happens) that were drawn on lumber to ensure that the same point before and after drying will be always used (Fig. 3.6). Detailed description of the shape deformation measuring protocol can be found in 3.5.4  3.5 Kiln schedules and drying procedure  Figs. 3.4 and 3.5 show the 1-m (3-ft) and 2.4-m (8-ft) conventional kilns were used in this study.   Figure 3.4. The 1-m (3-ft) laboratory drying kiln with the stickered package. 26  Figure 3.5. The 2.4-m (8-ft) drying kiln with the stickered package. 3.5.1 Kiln schedules for phase 1 The 1-m (3-ft) conventional laboratory kiln was used in phase 1. An industrially used drying schedule was first considered as a basis for further developments of drying schedules (Table 3.2). The industrial schedule (IS) was then intensified into two other faster schedules, called Modified 1 (MS1) and Modified 2 (MS2), which became faster respectively (Tables 3.3 and 3.4). MS1 had lower wet-bulb temperatures than the IS, though the dry-bulb temperature maintained at the same level as the IS. MS2 had not only lower wet-bulb temperatures but higher dry-bulb temperatures than the IS. So, the IS along with the other two schedules of MS1 and MS2 were considered for the phase 1 (there was no presorting yet). All drying runs were planned to stop at Mf =14%. Furthermore, no conditioning step was applied in the drying schedules. 27 Table 3.2. Industrial drying schedule (IS). Step Ramp time (h) Step duration (h) Elapsed time (h) Dry-bulb temperature (oC) Wet-bulb  temperature  (oC) Wet-bulb depression (oC) Relative humidity (%) Equilibrium moisture content (%) 1 (Heat-up) 8 - 8 60 60 0.0 100 24.6 2 4 - 12 71.1 68.9 2.2 90 16.7 3 6 - 18 76.7 72.8 3.9 84 13.5 4 - 12 30 76.7 72.8 3.9 84 13.5 5 6  36 82.2 74.4 7.8 72 9.4 6 - Until Mf=14% - 82.2 74.4 7.8 72 9.4  Table 3.3. Modified 1 drying schedule (MS1). Step Ramp time (h) Step duration (h) Elapsed time (h) Dry-bulb temperature (oC) Wet-bulb  temperature  (oC) Wet-bulb depression (oC) Relative humidity (%) Equilibrium moisture content (%) 1 (Heat-up) 8 - 8 60 60 0 100 24.6 2 4 - 12 71.1 66.7 4.4 81 13.0 3 6 - 18 76.7 67.9 8.7 67 9.0 4 - 12 30 76.7 67.9 8.7 67 9.0 5 6  36 82.2 62.7 19.5 41 5.0 6 - Until Mf=14% - 82.2 62.7 19.5 41 5.0  Table 3.4. Modified 2 drying schedule (MS2). Step Ramp time (h) Step duration (h) Elapsed time (h) Dry-bulb temperature (oC) Wet-bulb  temperature  (oC) Wet-bulb depression (oC) Relative humidity (%) Equilibrium moisture content (%) 1 (Heat-up) 8 - 8 65.6 60 5.6 76 11.9 2 4 - 12 76.7 66.7 10 63 8.3 3 6 - 18 82.2 67.9 14.3 53 6.4 4 - 12 30 82.2 67.9 14.3 53 6.4 5 6  36 87.8 62.7 25.1 32 3.9 6 - Until Mf=14% - 87.8 62.7 25.1 32 3.9 28 3.5.2 Kiln schedules for phase 2 The 1-m (3-ft) conventional laboratory kiln was used for drying of the specimens in the MiM category, while the other specimens in the other two Mi categories of MiL and MiH were dried using the 2.4-m (8-ft) conventional kiln. In phase 2, two drying schedules were used; the IS itself (Table 3.1) together with a selected modified schedule from phase 1 (Table 3.5). All drying runs were planned to stop at Mf =14%.  Table 3.5. Modified drying schedule (MS) used in phase 2 (selected from phase 1). Step Ramp time (h) Step duration (h) Elapsed time (h) Dry-bulb temperature (oC) Wet-bulb  temperature  (oC) Wet-bulb depression (oC) Relative humidity (%) Equilibrium moisture content (%) 1 (Heat-up) 8 - 8 60 60 0 100 24.6 2 4 - 12 71.1 66.7 4.4 81 13.0 3 6 - 18 76.7 67.9 8.7 67 9.0 4 - 12 30 76.7 67.9 8.7 67 9.0 5 6  36 82.2 62.7 19.5 41 5.0 6 - Until Mf=14% - 82.2 62.7 19.5 41 5.0  3.6 Post-drying measurements Followed by completion of each drying run, the specimens were cooled down in the kiln with the doors closed. Upon unloading the wood from the kiln, post-drying evaluations for each of the specimens were performed.  3.6.1 Lumber dimensions The thickness of each lumber was measured using a digital caliper at the mid-length on the same points which had already been marked (Fig. 3.3) as described in 3.3.  3.6.2 Shape distortions Warp was measured once before and again after drying. Twist, cup, bow, and crook were measured on a shop-built aluminum table (Fig. 3.7). Before drying some marks were drawn on lumber (where usually the greatest deflection happens) to ensure that the same point before and 29 after drying will be always used for the corresponding measurements (Fig. 3.6). In conjunction with the measuring table, shop-built digital dial gauge was used for these measurements (Fig. 3.7).     Figure 3.6. Corresponding measurement points for the various warp cases (Simpson 1991).    Figure 3.7. Aluminum table (left) and digital dial gauge (right) used to measure different types of distortions.  3.6.3 Moisture gradient and final moisture content The shell-and-core moisture contents (Ms and Mc, respectively) of the dried specimens were measured with a resistance pin-type moisture meter of 0.1% resolution at the mid-length of each specimen at 12.5 mm (shell) and 25 mm (core) depths (Fig. 3.8). In phase 1, lumber weight was the basis for determination of Mf. In phase 2 however, a cookie with 25 mm thickness was cut for Mf determination at the mid-length of all dried specimen right after drying and they were oven-dried at 103±2oC to a constant weight (Fig. 3.8).  30   Figure 3.8. Measuring the shell-and-core moisture contents of dried specimens using a resistance pin-type moisture meter (left); oven-drying method for moisture content measurement (right).  3.6.4 Casehardening Casehardening (residual drying stresses) was measured using one-third of lumber in each drying package according to the selection pattern provided in Fig. 3.9. Casehardening test samples (cookies) with dimensions equal to specimen’s full thickness and width, and a length of 25 mm were cut at the mid-length of each dried specimen (Fig. 3.10).   Figure 3.9. Schematic of selection pattern for casehardening test from each dried package. 31  Figure 3.10. Cutting pattern for measuring casehardening. In both phases, residual stresses intensity was determined by the prong response method (Fig. 3.10) using the equation below (Fuller 1995): 2lxxPR′−=                                                               (2) where, PR is prong response of test specimen (mm-1), x  is the distance between outer prong edges before cutting (mm), x′ is the distance between outer prong edges after cutting (mm), and l  is the length of each test sample’s prong.  3.6.5 Surface checking and honeycomb Frequency and length of surface checks were measured on every specimen at each four sides. Before drying, surface checks present on green specimens were identified (if any) and marked to enable differentiating them with the ones which were later developed during drying. Honeycombing in phase 1 was evaluated on the same cookies used for casehardening assessment (one-third of the kiln dried package for each run). In phase 2, however, that was evaluated on all the dried specimens using the same cookies already cut for final moisture content measurements. Summary of all the experiments applied is shown in the Fig. 3.11.     900 mm25 mm32 Figure 3.11. Summary of all the experiments carried out in the current project.    33 3.7 Statistical analysis 3.7.1 Statistical analysis for phase 1 Statistical analysis was carried out using SAS 9.4 software. One-way fixed-effects ANOVA was considered to test the possible significant differences among the treatments’ mean (i.e. three schedules). Table 3.6 shows the ANOVA matrix along with the sources of errors and corresponding calculations. F-test was used to determine the possible significant differences between the means. If there was a significant difference, then t-test for pairs of means was used to rank the treatments’ means. The significance level for all the tests was set at 0.05 (α=0.05). Moreover, the data in phase 1 met assumptions of analysis of variance (normality and equal variance).  Table 3.6. ANOVA table used in assessing the possible differences between the treatments (treatment=drying schedules, i=experimental unit, j=treatment, nT=number of experimental units measured over all treatments). Source Degree of Freedom (DF) Sum of Squares (SS) Mean Square (MS) F Treatments J - 1 21 1( )jnJTR jj iSS y y• ••= == −∑∑  TRTRTRSSMSdf=  TRMSMSE Error nT - J 21 1( )jnJij jj iSSE y y•= == −∑∑  ESSEMSEdf=   Total nT -1 21 1( )jnJijj iSSy y y••= == −∑∑     3.7.2 Statistical analysis for phase 2 Two-factor fixed-effects ANOVA (factorial design) was considered to test the main effects of the two factors (i.e. drying schedule with two levels and Mi with three levels), together with their interaction on the studied parameters. Table 3.7 shows the ANOVA table along with the sources of errors and corresponding calculations. F-test was used to determine the significance of interaction of the two factors as well as two main effects. If there was a significant difference, then t-test for pairs of means was used to rank the treatments’ means. The significance level for all the tests was set at 0.05 (α=0.05). Moreover, some of the data (cup, twist, Mi, Mf, Ms, Mc) in phase 2 did not meet assumptions of analysis of variance (normality and equal variance), so the logarithmic transformation was applied. 34 Table 3.7. ANOVA table used in assessing the possible differences in terms of interaction and main effects (factor A: drying schedule with 2 levels, factor B: Mi with 3 levels, i=experimental unit, j=factor A level, k=factor B level, nT=number of experimental units measured over all treatments). Source Degree of Freedom (DF) Sum of Squares (SS) Mean Square (MS) F Factor A J - 1 21 1( )K Jjk jk jSSA n y y• • •••= == −∑∑  ASSAMSAdf=  MSAMSE Factor B K – 1 21 1( )K Jjk kk jSSB n y y•• •••= == −∑∑  BSSBMSBdf=  MSBMSE A×B (J-1)(K-1) 21 1( )K Jjk jk k jk jSSAB n y y y y• •• • • •••= == − − +∑∑  ABSSABMSABdf=  MSABMSE Error nT – JK 21 1 1( )jknK Jijk jkk j iSSE y y•= = == −∑∑∑  ESSEMSEdf=   Total nT -1 21 1 1( )jknK Jijkk j iSSy y y•••= = == −∑∑∑                     35 4. Results and Discussion  4.1 Phase 1 4.1.1 Basic density The total average basic density for all the three runs (216 specimens) was 397.4 kg/m3, ranging from 310.1 to 546.2 kg/m3 with a standard deviation of 48.7 kg/m3. Table 4.1 lists statistics regarding the basic density and its variation through each of the drying runs.  Table 4.1. Basic density statistics for the runs in phase 1. Schedule Mean (kg/m3) St. Dev.1 (kg/m3) Min (kg/m3) Max (kg/m3) IS 402.2 45.5 310.1 543.4 MS1 392.9 54.7 321.8 546.2 MS2 397.1 46.0 311.2 531.1 1St.Dev.: Standard deviation  Basic density data reported in the literature are similar to the obtained data in the current study; 316 to 563 kg/m3 (Zhang et al. 1996), 261 to 540 kg/m3 (Li et al. 1997), 389 to 455 kg/m3 (Wallace 2001), and 302 to 511 kg/m3 (Sackey et al. 2004). Table 4.2 lists the results of statistical analysis of basic density between the specimens for the three runs. Based on the analysis, there was no significant difference between the treatments in terms of basic density.  Table 4.2. Analysis of variance for basic density.  Sum of Squares df Mean Square F P-value Between Groups 3131.649 2 1565.824 0.655 0.520 Within Groups 508958.775 213 2389.478   Total 512090.424 215    36 4.1.2 Initial moisture content  The initial moisture content of all the lumber ranged from 30.3 to 204%, with an average of 87.8% and standard deviation of 39.7% (Table 4.3).  Table 4.3. Initial moisture content statistics for the three runs. Schedule Mean (%) St. Dev. (%) Min (%) Max (%) IS 81.8 38.3 30.3 200.4 MS1 93.9 38.7 36.5 204.0 MS2 87.8 42.2 30.5 194.3   The initial moisture content distributions corresponding to each of the kiln drying packages are depicted in Fig. 4.1.   Figure 4.1. Initial moisture contents distribution for the drying runs.   02040608010012002468101210 30 50 70 90 110 130 150 MoreCumulative frequency (%)Piece countInitial moisture content (%)CountCumulativeIndustrial02040608010012002468101210 30 50 70 90 110 130 150 MoreCumulative frequency (%)Piece countInitial moisture content (%)CountCumulativeModified 102040608010012002468101210 30 50 70 90 110 130 150 MoreCumulative frequency (%)Piece countInitial moisture content (%)CountCumulativeModified 237 Statistical analysis showed that there is not a significant difference between the three runs in terms their Mi (Table 4.4).  Table 4.4.  Analysis of variance for initial moisture content.  Sum of Squares df Mean Square F P-value Between Groups 6241.255 2 3120.628 1.974 0.141 Within Groups 336740.928 213 1580.943   Total 342982.183 215     4.1.3 Drying time and rate Fig. 4.2 shows the drying curves of the three runs. These curves reveal that the moisture content decreased as drying proceeded by different rates since curve steepness indicate the rate by which the water is removed; the steeper curve, the higher drying rate. During the early stages of drying, there will be a steeper slope because of mainly free water evaporation. As the drying proceeds and the free water is removed, the drying slows down since bound water evaporation becomes the prevailing drying factor and the slope of the curve will start to flatten out thus indicating a decline in  drying rate. The overall drying times ranged from 66 to 159 hours. The MS2 schedule, the most severe one, by having the steepest drying curve took less time to reach the desired final moisture content. The IS by having the mildest drying condition was the longest one. MS1 schedule was in the middle of the two other schedules regarding the drying time.  Figure 4.2. Drying curves for each of the three runs.  To compare drying schedules it is necessary to have the same initial moisture contents for all the runs. For that reason, the moisture contents were normalized by taking the ratio of the Mi 0204060801000 40 80 120 160 200Moisture content (%)Time (hour)IndustrialModified 1Modified 238 and the current moisture content. The adjusted drying curves are depicted in Fig. 4.3. The most intensive schedule (MS2) still had the steepest drying curve, particularly at the beginning of removing free water. Following by that are MS1 and IS, respectively.   Figure 4.3. Adjusted drying curves for each of the three runs.  Fig. 4.4 also shows the drying rate curves versus different moisture contents. The most intense schedule (MS2), as mentioned above, had a higher drying rate throughout the drying process and at the different moisture levels, particularly where there is more free water, followed by the MS 1 and IS, respectively. Accordingly, the average drying rates for IS, MS1, and MS2 were 0.5, 1.3, and 1.5 %/hour, respectively.  Figure 4.4. Drying rate at different moisture contents.   0.00.20.40.60.81.00 40 80 120 160 200Moisture ratio, M\MiTime (hour)IndustrialModified 1Modified 2012340 20 40 60 80 100Drying rate (%/hour)Moisture content (%)IndustrialModified 1Modified 239 4.1.4 Final moisture content  Table 4.5 shows the statistics regarding the Mf obtained in all the three runs. Although the target moisture content of 14% was set for all the runs, but the results showed that the Mf  ranged from 2.1 to 37.5% with a standard deviation of 2.6 to 7.1%. In the IS, the standard deviation (2.6%) was different from the ones for the modified schedules (Table 4.5). In other words, IS resulted in lower Mf variation within the dried package, followed by the MS1 and MS2, respectively. Moreover, the coefficient of variation (CV) also indicated the same trend when variation between the treatments is considered. The most severe schedule (MS2) had the highest CV by 35.9% which was close to the less intense one (MS1) by 29.3%, followed by the lowest CV of 19.3% for the mildest drying schedule (IS). Table 4.5. Final moisture content statistics for the three runs. Schedule Mean (%) St. Dev. (%) CV1 (%) Min (%) Max (%) Drying time (h) IS 13.5 2.6 19.3 9.6 20.1 159 MS1 17.8 5.2 29.3 8.3 31.0 75 MS2 19.6 7.1 35.9 2.1 37.5 66 1CV: Coefficient of Variation (	  	 		)   Statistical analysis showed that there is a significant difference between the three runs in terms of Mf (Table 4.6). In general, a drying run was supposed to finish when the scale showed a target weight equivalent to the target moisture content and because of mechanical issues with the kiln scale, the runs ended up with different final moisture contents. As a result, drying runs were not just limited by the time-based schedule. Paired sample t-test also put the IS with lower Mf in a separate group than the modified schedules (Table 4.7).  Table 4.6. Analysis of variance for final moisture content.  Sum of Squares df Mean Square F P-value Between Groups 1355.126 2 677.563 23.962 0* Within Groups 5909.738 209 28.276   Total 7264.864 211    *:significant at a=0.05 40 Table 4.7. Paired sample t-test grouping for final moisture content. Treatment t-test grouping 1 2 IS 13.5*  MS1  17.8 MS2  19.6 *:Mean value Fig. 4.5 depicts the distribution of final moisture content individually for each of the three runs. As it is shown, IS resulted in a narrower Mf distribution compared to the modified schedules. The coefficient of variation also showed a lesser variation for this schedule than the MS1 and MS2. The standard deviation is theoretically supposed to drop as target moisture content reduces and so the moisture distribution is narrowed during drying, that is also the case here (Bradic 2005, Wada 2013). But, it should be considered that the Mf resulted from the IS ended at almost 5% lower than the ones from other two which would also describe the narrower distribution of Mf in this schedule. The most intense schedule (MS2) had a wider distribution in terms of Mf than the MS1 one (Fig. 4.5). In other words, there were more under-dried (M > 19%) and over-dried (M < 10%) specimens resulted from the former than in the latter.  Figure 4.5. Distribution of final moisture content. 02040608010012005101520250 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal moisture content (%)CountCumulativeIndustrial02040608010012005101520250 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal moisture content (%)CountCumulativeModified 102040608010012005101520250 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal moisture content (%)CountCumulativeModified 241 4.1.5 Final moisture content gradient 4.1.5.1 Shell moisture content  The average shell moisture content (Ms) for all the three runs was 17.6%, ranging from 8.4 to 39.2% and standard deviation of 1.7 to 5.6% (Table 4.8). The IS resulted in a lower Ms than the modified schedules which may be because in this schedule the specimens were dried to a lower final moisture content. Fig. 4.6 depicts the shell moisture content distribution through the three schedules. It is shown that the most intense schedule (MS2) resulted in a wider Ms distribution than MS1 and IS, respectively.   Table 4.8. Shell moisture content statistics for the three runs. Schedule Mean (%) St. Dev. (%) Min (%) Max (%) IS 12.5 1.7 8.4 18.0 MS1 17.7 5.1 8.9 33.8 MS2 22.6 5.6 12.3 39.2  Figure 4.6. Shell moisture content distribution for the three runs. 02040608010012005101520253035400 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal shell  moisture content (%)CountCumulativeIndustrial02040608010012005101520253035400 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal shell  moisture content (%)CountCumulativeModified 102040608010012005101520253035400 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal shell  moisture content (%)CountCumulativeModified 242  Statistical analysis also revealed that there is a significant difference between the schedules in terms of Ms (Table 4.9). The paired sample t-test indicates that all the three schedules were placed in separate groups (Table 4.10).   Table 4.9. Analysis of variance for shell moisture content.  Sum of Squares df Mean Square F Sig. Between Groups 3547.018 2 1773.509 89.588 0* Within Groups 4137.411 209 19.796   Total 7684.429 211    *:significant at a=0.05  Table 4.10. Paired sample t-test grouping for shell moisture content. Schedule t-test grouping 1 2 3 IS 12.5   MS1  17.7  MS2   22.6  4.1.5.2 Core moisture content  Core moisture content (Mc) was higher than the corresponding shell moisture content in all the three schedules (Table 4.11). The average Mc for all the three runs was 21.7%, ranging from 11.2 to 47% and standard deviation of 2.1 to 7% (Table 4.11). The IS resulted in a lower Mc than the modified schedules which may be because in this schedule the specimens, as already mentioned, were dried to a lower final moisture content. Fig. 4.7 depicts the Mc distribution through the three schedules. It is shown that the most intense schedule (MS2) resulted in more wet specimens in terms of Mc distribution than MS1 and IS, respectively.      43 Table 4.11. Core moisture content statistics for the three runs. Schedule Mean (%) St. Dev. (%) Min (%) Max (%) IS 14.7 2.1 11.2 22.5 MS1 21.8 6.9 12.1 41.0 MS2 28.7 7.0 14.2 47.0   Figure 4.7.  Core moisture content distribution for the three runs.  Statistical analysis also showed that there is a significant difference between the schedules in terms of Mc (Table 4.12). The paired sample t-test indicates that all the three schedules were placed in separate groups (Table 4.13).     02040608010012005101520253035400 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal core moisture content (%)CountCumulativeIndustrial02040608010012005101520253035400 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal core moisture content (%)CountCumulativeModified 102040608010012005101520253035400 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal core moisture content (%)CountCumulativeModified 244 Table 4.12. Analysis of variance for core moisture content.  Sum of Squares Df Mean Square F Sig. Between Groups 6897.983 2 3448.992 103.993 0* Within Groups 6931.629 209 33.166   Total 13829.612 211    *:significant at a=0.05  Table 4.13. Paired sample t-test grouping for core moisture content. Schedule t-test grouping 1 2 3 IS 14.7   MS1  21.8  MS2   28.7  4.1.5.3 Difference between shell-and-core moisture content  The difference between Ms and Mc was lower for the dried specimens by the IS than the corresponding values for MS1 and MS2 schedules, respectively (Table 4.14). The average difference between shell-and-core M for all the three runs was 4.1%, ranging from 0.4 to 20% and with a standard deviation of 2.2 to 6.1% (Table 4.14). The IS resulted in a lower difference between Ms and Mc than the modified schedules which may be because in this schedule the specimens, as already mentioned, were dried to a lower final moisture content. Difference between Ms and Mc is expected to decrease when drying is terminated at a lower M. The IS, as the mildest and the most conservative schedule, by having the lowest Mf resulted in the more uniform moisture difference between the dried specimens. Fig. 4.8 depicts the difference between Ms and Mc distributions amongst the three schedules. It is shown that the most intense schedule (MS2) resulted in the higher difference between Ms and Mc compared to MS1 and IS, respectively. The high variability of Ms and Mc could be explained by the fact that drying begins in the surface layers, while the core takes longer to dry. Therefore, the moisture content distribution is usually not uniform among the specimens depending on the drying schedule applied together with the corresponding drying rate. It is also worthy to mention that wetwood is another underlying cause of the high variability between the Ms and Mc (Sackey 2003). The difference between Ms 45 and Mc can be partially alleviated for PCH by applying conditioning and equalization treatments at the end of the drying process (Rohrbach 2008).  Table 4.14. Difference between shell-and-core moisture content statistics for the three runs. Schedule Mean (%) St. Dev. (%) Min (%) Max (%) IS 2.2 1.2 0.5 5.7 MS1 4.1 2.8 0.5 12.6 MS2 6.1 4.0 0.4 20   Figure 4.8. Difference between shell-and-core moisture content distribution for the three runs.  Statistical analysis also showed that there is a significant difference between the schedules in terms of the difference between shell-and-core moisture contents (Table 4.15). The corresponding paired sample t-test also indicated that all the three schedules were placed in separate groups (Table 4.16).   02040608010012005101520253035400 2 4 6 8 10 12 14 MoreCumulative frequency (%)Piece countMoisture content (%)CountCumulativeIndustrialDifference between shell  and core 02040608010012005101520253035400 2 4 6 8 10 12 14 MoreCumulative frequency (%)Piece countMoisture content (%)CountCumulativeModified 1Difference between shell  and core 02040608010012005101520253035400 2 4 6 8 10 12 14 MoreCumulative frequency (%)Piece countMoisture content (%)CountCumulativeModified 2Difference between shell  and core 46 Table 4.15. Analysis of variance for difference between shell-and-core moisture content.  Sum of Squares Df Mean Square F Sig. Between Groups 552.281 2 276.140 32.781 0* Within Groups 1760.596 209 8.424   Total 2312.877 211    *:significant at a=0.05  Table 4.16. Paired sample t-test grouping for difference between shell-and-core moisture content. Schedule t-test grouping 1 2 3 IS 2.2   MS1  4.1  MS2   6.1  4.1.6 Shrinkage  Shrinkage is an inevitable phenomenon that happens when water is removed below the fiber saturation point. Shrinkage can result in several drying defects (e.g. deformation, casehardening, surface checks, honeycombing). Therefore, control and reduction of shrinkage can alleviate drying defects. The average width shrinkage for all the three runs was 2.5%, ranging from 0.2 to 4.7% and standard deviation of 0.8 to 1% (Table 4.17). The shrinkage values were consistent with the ones reported by Zhang et al. (1996) and Avramidis and Hao (2004). The average width shrinkage was almost the same for the modified schedules, though the IS by having a milder condition experienced a higher shrinkage. Fig. 4.9 also depicts the width shrinkage distribution for different drying schedules applied. It can be seen that the IS had a higher shrinkage percentage than the modified schedules. Table 4.17. Shrinkage statistics for the three runs. Schedule  Mean (%) St. Dev. Min (%) Max (%) IS 2.9 0.8 1.3 4.4 MS1 2.2 0.9 0.2 4.0 MS2 2.3 1 0.3 4.7 47  Figure 4.9. Shrinkage distribution in the three runs in phase 1.  The analysis of variance table showed a significant difference between the drying schedules in terms of intensity of width shrinkage (Table 4.18). Paired sample t-test indicated that the IS, although that was milder than the others, resulted in a higher shrinkage percentage (Table 4.19). The drying process using the IS terminated at significantly a lower final moisture content of 4-6% lower than the corresponding values for the modified schedules (Table 4.5). Therefore, the IS by having a lower Mf resulted in a higher average shrinkage than the modified schedules.  Table 4.18. Analysis of variance for shrinkage.  Sum of Squares df Mean Square F Sig. Between Groups 25.052 2 12.526 15.667 0* Within Groups 164.698 206 0.80   Total 189.750 208    *:significant at a=0.05    020406080100120051015202530351 2 3 4 5Cumulative frequency (%)Piece countShrinkage (%)CountCumulativeIndustrial0204060801001200510152025301 2 3 4 5Cumulative frequency (%)Piece countShrinkage (%)CountCumulativeModified 10204060801001200510152025301 2 3 4 5Cumulative frequency (%)Piece countShrinkage (%)CountCumulativeModified 248 Table 4.19. Paired sample t-test grouping for shrinkage. Schedule t-test grouping 1 2 MS1 2.2  MS2 2.3  IS  2.9 4.1.7 Shape distortions 4.1.7.1 Bow  Table 4.20 lists the intensity of bow resulted by different drying schedules. These statistics are actually the differences between the bow measured before and after drying. The overall mean for all the runs was 0.33 mm ranging from -0.29 to 1.9 mm and standard deviation of 0.31 to 0.4 mm. The bow distribution is also depicted in Fig. 4.10 individually for all the three runs. As can be seen, there are positive and some negative values for bow resulted from all the schedules. The negative values come from the specimens which deformed in the opposite direction of the original one measured before drying.  It is reported in the literature that bow is associated with longitudinal shrinkage in juvenile wood near the pith, reaction wood, and spiral grain. Therefore, the cause is the difference in longitudinal shrinkage on opposite sides of a specimen. Moreover, this type of defect can also be the result of poor stacking. For example, stickers are not aligned and/or too far apart, stickers are not uniform in thickness, or foundations are uneven (Bendtsen 1978, Simpson 1991, Dening et al. 2000), though that was not the case in the current research.  Table 4.20. Bow statistics for the three runs. Runs Mean (mm) St. Dev. (mm) Min (mm) Max (mm) IS 0.31 0.31 -0.29 1.21 MS1 0.34 0.40 -0.13 1.90 MS2 0.33 0.34 -0.26 0.98   49  Figure 4.10. Bow distribution in the three runs.   The statistical analysis also showed that the drying schedules did not have a significant influence on the developed bow (Table 4.21).  Table 4.21. Analysis of variance for bow.  Sum of Squares df Mean Square F Sig. Between Groups 0.037 2 0.019 0.149 0.862 Within Groups 25.715 205 0.125   Total 25.752 207     4.1.7.2 Crook Table 4.22 shows the intensity of crook resulted by different drying schedules. These statistics are actually the differences between the crook before and after drying. The overall mean for all the runs was 0.3 mm ranging from -0.45 to 1.58 mm and standard deviation of 0.3 to 0.38 mm. The crook distribution is also depicted in Fig. 4.11 individually for all the three runs. As can be seen, there are positive and some negative values for crook resulted from all the schedules. The negative values come from the specimens which deformed in the opposite direction of the original one measured before drying. 0204060801001200510152025-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countBow (mm)CountCumulativeIndustrialDifference between initial and final bow 0204060801001200510152025-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countBow (mm)CountCumulativeModified 1Difference between initial and final bow 0204060801001200510152025-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countBow (mm)CountCumulativeModified 2Difference between initial and final bow 50 This type of defect is often a result of improper sawing patterns or crooked logs such that the rings, when viewed from the end of the piece of lumber, are off center edge-to edge. Often the wood closer to the center of the tree shrinks more than does the wood closer to the bark. Although good stacking practices also help reducing the crook, but they are not as effective against this type of warp as they are against cup, bow, and twist (Simpson 1991, Dening et al. 2000).   Table 4.22. Crook statistics for the three runs. Schedule Mean (mm) St. Dev. Min (mm) Max (mm) IS 0.28 0.3 -0.35 1.58 MS1 0.29 0.38 -0.24 1.3 MS2 0.33 0.37 -0.45 1.46   Figure 4.11. Crook distribution in the three runs. The statistical analysis also showed that the drying schedules did not have a significant influence on the developed crook (Table 4.23). 0204060801001200510152025-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countCrook (mm)CountCumulativeIndustrialDifference between initial and final crook0204060801001200510152025-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countCrook (mm)CountCumulativeModified 1Difference between initial and final crook0204060801001200510152025-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countCrook (mm)CountCumulativeModified 2Difference between initial and final crook51 Table 4.23. Analysis of variance for crook.  Sum of Squares df Mean Square F Sig. Between Groups 0.131 2 0.066 0.522 0.594 Within Groups 26.008 207 0.126   Total 26.139 209     4.1.7.3 Cup  Table 4.24 shows the intensity of cup resulted by different drying schedules. These statistics are actually the differences between the cup before and after drying. The overall mean for all the runs was 0.05 mm ranging from -0.73 to 0.81 mm and standard deviation of 0.19 to 0.32 mm. The cup distribution is also depicted in Fig. 4.12 individually for all the three runs. As can be seen, there are positive and some negative values for cup resulted from all the schedules. The negative values come from the specimens which deformed in the opposite direction of the original one measured before drying.   Table 4.24. Cup statistics for the three runs. Runs Mean (mm) St. Dev. Min (mm) Max (mm) IS 0.03 0.19 -0.3 0.63 MS1 0.02 0.32 -0.73 0.81 MS2 0.11 0.22 -0.27 0.56  The statistical analysis also showed that the drying schedules did not have a significant influence on the developed cup (Table 4.25).  Table 4.25. Analysis of variance for cup.  Sum of Squares df Mean Square F Sig. Between Groups 0.351 2 0.175 2.902 0.057 Within Groups 12.389 205 0.060   Total 12.740 207        52  Figure 4.12. Cup distribution in the three runs.   4.1.7.4 Twist Table 4.26 shows the intensity of twist resulted by different drying schedules. These statistics are actually the differences between the twist before and after drying. The overall mean for all the runs was 0.26 mm ranging from -1.08 to 2.62 mm and standard deviation of 0.5 to 0.58 mm. The twist distribution is also depicted in Fig. 4.13 individually for all the three runs. As can be seen, there are positive and some negative values for twist resulted from all the schedules. The negative values come from the specimens which deformed in the opposite direction of the original one measured before drying.  Table 4.26. Twist statistics for the three runs. Schedule Mean (mm) St. Dev. Min (mm) Max (mm) IS 0.11 0.5 -0.9 1.31 MS1 0.35 0.56 -0.52 1.84 MS2 0.32 0.58 -1.08 2.62  0204060801001200510152025303540-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 MoreCumulative frequency (%)Piece countCup (mm)CountCumulativeIndustrialDifference between initial and final cup0204060801001200510152025303540-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 MoreCumulative frequency (%)Piece countCup (mm)CountCumulativeModified 1Difference between initial and final cup0204060801001200510152025303540-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 MoreCumulative frequency (%)Piece countCup (mm)CountCumulativeModified 2Difference between initial and final cup53  Figure 4.13. Twist distribution in the three runs.  The statistical analysis also showed that the drying schedules had a significant influence on the developed twist (Table 4.27). Paired sample t-test indicated that the modified schedules (MS1 and MS2) resulted in statistically a higher twist than the IS (Table 4.28). That can be because of more harsh drying conditions (higher temperature and lower relative humidity) induced by the modified schedules.  Table 4.27. Analysis of variance for twist.  Sum of Squares df Mean Square F Sig. Between Groups 2.269 2 1.135 3.771 0.025* Within Groups 61.683 205 0.301   Total 63.952 207    *:significant at a=0.05  0204060801001200510152025303540-1.5 -1 -0.5 0 0.5 1 1.5 MoreCumulative frequency (%)Piece countTwist (mm)CountCumulativeIndustrialDifference between initial and final twist0204060801001200510152025303540-1.5 -1 -0.5 0 0.5 1 1.5 MoreCumulative frequency (%)Piece countTwist (mm)CountCumulativeModified 1Difference between initial and final twist0204060801001200510152025303540-1.5 -1 -0.5 0 0.5 1 1.5 MoreCumulative frequency (%)Piece countTwist (mm)CountCumulativeModified 2Difference between initial and final twist54 Table 4.28. Paired sample t-test grouping for twist. Schedule t-test grouping 1 2 IS 0.1142  MS2  0.3227 MS1  0.3455  4.1.8 Surface checks Table 4.29 shows the total length of checks in mm which indicates the sum of the length of surface checks for each run before and after drying in all the corresponding kiln specimens. The percentage also represents the total length of surface checks in each run in relation to the total length of all of the specimens in the corresponding run. As can be seen in Table 4.29, only the most intense schedule (MS2) caused some surface checking that was about 1.5% of the total length of all the specimens in this drying run. Table 4.29. Total length and percentage of surface check in correlation to the total specimens’ length.  Total length of check (mm) Percentage (%) Schedule length before drying length after drying Difference (before – after) length before drying length after drying Difference (before – after) IS 0 0 0 0 0 0 MS1 0 0 0 0 0 0 MS2 0 983 983 (out of 64800 mm) 0 1.52 1.52  The statistical analysis also showed that the drying schedules had a significant influence on the developed surface checks (Table 4.30). Paired sample t-test indicated that MS2 schedule resulted in a significantly higher surface check length (Table 4.31). Both the IS and MS1 did not have any influence on the surface checking. There were higher temperature and lower relative humidity applied in the early stages of MS2 schedule than the other two ones, which are of the main reasons behind the surface checking in this schedule.  55 Table 4.30. Analysis of variance for surface checks.  Sum of Squares df Mean Square F Sig. Between Groups 14843.149 2 7421.575 9.027 0.001* Within Groups 23021.238 28 822.187   Total 37864.387 30    *:significant at a=0.05  Table 4.31. Paired sample t-test grouping for surface checks. Schedule t-test grouping 1 2 IS 0  MS1 0  MS2  46.8  4.1.9 Internal checks The results showed that none of the drying schedules investigated led to occurrence of honeycomb in this study. This means that even the most intense schedule has still shown a promising result in term of this type of drying defect and can be used to dry PCH without any concern.  4.1.10 Casehardening  Shrinkage is the driving force behind the drying stresses. Table 4.32 shows the intensity of casehardening resulted from different drying schedules which measured according to section 3.4.4 in the materials and method. The overall mean for all the runs was 0.31 mm and standard deviation of 0.12 mm ranging from 0 to 0.68 mm. The casehardening distribution is also depicted in Fig. 4.14 individually for all the three runs. There is a tendency for the casehardening values resulted from the IS to be in the lower part of the plot with lower intensity when compared to the modified schedules. Table 4.32. Casehardening statistics for the three runs. Schedule Mean (mm) St. Dev. (mm) Min (mm) Max (mm) IS 0.12 0.10 0 0.32 MS1 0.41 0.12 0.22 0.68 MS2 0.39 0.13 0.23 0.65 56  Figure 4.14. Casehardening distribution in the three runs.  The statistical analysis also showed that the drying schedules had a significant influence on the intensity of residual stresses (Table 4.33). Paired sample t-test indicated that both MS1 and MS2 schedules resulted in a significantly higher casehardening than the IS (Table 4.34). Even though the IS terminated at a lower Mf, but application of harsher drying conditions (higher temperature and lower relative humidity) in the both modified schedules still resulted in significantly a higher casehardening.   Table 4.33. Analysis of variance for casehardening.  Sum of Squares df Mean Square F Sig. Between Groups 1.249 2 0.624 48.378 0* Within Groups 0.826 64 0.013   Total 2.075 66    *:significant at a=0.05 0204060801001200246810120 0.1 0.2 0.3 0.4 0.5 0.6 0.7Cumulative frequency (%)Piece countCasehardening (mm)CountCumulativeIndustrial0204060801001200246810120 0.1 0.2 0.3 0.4 0.5 0.6 0.7Cumulative frequency (%)Piece countCasehardening (mm)CountCumulativeModified 10204060801001200246810120 0.1 0.2 0.3 0.4 0.5 0.6 0.7Cumulative frequency (%)Piece countCasehardening (mm)CountCumulativeModified 257 Table 4.34. Paired sample t-test grouping for casehardening. Treatment t-test grouping 1 2 IS 0.12  MS2  0.39 MS1  0.41 4.2 Phase 2 4.2.1 Basic density  The total average basic density for the six runs (432 samples) was 388 kg/m3 with standard deviation of 5.8 kg/m3 and a range from 265 to 548 kg/m3. Table 4.35 shows some statistical data regarding the basic density and its variation for each of the drying runs.  Table 4.35. Basic density statistics for the runs in phase 2. Schedule – Mi category Mean (kg/m3) SD (kg/m3) CV (%) Min (kg/m3) Max (kg/m3) IS - MiM 386.68 47.66 12.32 274.53 516.79 MS - MiM 384.96 54.17 14.07 283.90 542.46 IS - MiH 394.27 46.09 11.69 290.66 506.53 MS - MiH 385.37 55.51 14.40 292.29 509.09 IS - MiL 384.26 60.35 15.71 265.35 527.43 MS - MiL 393.84 58.73 14.91 282.46 548.37   Table 4.36. Analysis of variance for basic density. Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 1297.2273 648.6136 0.22 0.8007 Schedule 1 13.2070 13.2070 0 0.9464 Mi_category*Schedule 2 6251.9316 3125.9658 1.07 0.3434  58 Table 4.36 shows the results of analysis of variance for basic density between the specimens for the six runs. Based on the analysis, there was no significant difference between the treatments in terms of basic density.  4.2.2 Initial moisture content  According to the specimen’s weight-based calculations and because there were few negative values in some of the kiln schedules in terms of the final moisture contents, then the adjusted values had to be used. Adjusted values were obtained based on the final moisture content of the cookies after drying process and were considered to recalculate the oven-dry weight of each of the lumber. So the initial moisture contents were also recalculated and considered in the whole part of the study. As already mentioned, the specimens were separated into three different categories according to their initial moisture contents, namely MiM, MiH, and MiL. The threshold between MiL and MiH was 72%. The mean Mi and standard deviation were respectively 86 and 38% for the MiM group, 112 and 27% for the MiH group, and 47 and 12.5% for the MiL group (Table 4.37). As it is expected, the lowest average moisture content was for the MiL group and the highest for the MiH group with the MiM group in the middle. The either of standard deviation or CV were higher in the MiM group since that comprises of  a wider range of specimens in terms of Mi and that was not sorted. The lower standard deviation and CV were for the MiL group.  Table 4.37. Initial moisture content statistics for the six runs. Schedule – Mi category Mean (%) St. Dev. (%) CV (%) Min (%) Max (%) IS - MiM 84.75 38.60 45.54 26.20 170.61 MS - MiM 87.16 36.79 42.20 38.27 170.01 IS - MiH 110.51 27.31 24.72 47.01 195.55 MS - MiH 114.05 27.19 23.85 57.64 179.20 IS - MiL 50.29 13.74 27.33 30.75 85.33 MS - MiL 44.30 11.29 25.48 25.45 70.21     where IS=original industrial schedule from phase 1 and MS=new modified schedule for phase 2 59  The initial moisture content distributions corresponding to each of the six kiln drying packages are depicted in Fig. 4.15. As already mentioned and as can be seen in the plots, groups with the MiM had a wider distribution than the other Mi classes. The MiH group tend to concentrate on the upper part of the graph with higher percentage of moisture content and MiL group conversely on the lower part of the graphs with lower Mi values.  Figure 4.15. Initial moisture content distributions for the drying runs. 020406080100120051015202510 30 50 70 90 110 130 150 MoreCumulative frequency (%)Piece countInitial moisture content (%)CountCumulativeIndustrial schedule - Mix M020406080100120051015202510 30 50 70 90 110 130 150 MoreCumulative frequency (%)Piece countInitial moisture content (%)CountCumulativeModified schedule - Mix M020406080100120051015202510 30 50 70 90 110 130 150 MoreCumulative frequency (%)Piece countInitial moisture content (%)CountCumulativeIndustrial schedule - High M020406080100120051015202510 30 50 70 90 110 130 150 MoreCumulative frequency (%)Piece countInitial moisture content (%)CountCumulativeModified schedule - High M020406080100120051015202510 30 50 70 90 110 130 150 MoreCumulative frequency (%)Piece countInitial moisture content (%)CountCumulativeIndustrial schedule - Low M020406080100120051015202510 30 50 70 90 110 130 150 MoreCumulative frequency (%)Piece countInitial moisture content (%)CountCumulativeModified schedule - Low M60 4.2.3 Drying time and rate Fig. 4.16 shows the drying curves of the six drying runs. These curves show that the moisture content decreased as drying proceeded by different rates. Steepness of the curve slope denotes the rate by which the water was removed; the steeper slope, the higher drying rate. During the early stages of drying, there will be a steeper slope because of the existence of free water with faster evaporation potential than bound water. As drying proceeds and the free water is removed, the drying slows down and the slope of curve will start to flatten out which is equivalent to a decline in the drying rate.  Figure 4.16. Drying curves for the drying runs.  Since the drying runs started with different initial moisture contents, drying terminated at different times for different drying schedules and Mi combinations (Table 4.38). Accordingly, the runs with a higher initial moisture contents (MiH) took longer to be dried than MiM and MiL categories, respectively. As regards to drying schedule, the MS, by having harsher drying conditions resulted in shorter drying time than its corresponding IS, except in the MiL category where no difference between the two schedules was observed. Therefore, the either of MS or IS along with the MiH category took the longest to be dried by almost 114-120 hours, followed by the MiM (102-113 hours) and MiL (48 hours) categories. 0204060801001201400 20 40 60 80 100 120 140Moisture content (%)Time (hour)Industrial - Mix MModified - Mix MIndustrial - High MModified - High MIndustrial - Low MModified - Low M61 The actual drying times were adjusted to include the time that was required for each of drying runs to reach almost 17% final moisture content (equivalent to IS-MiH drying time) (Table 4.38). Accordingly, the MS basically took shorter to reach the Mf of 17% than that of IS.  Table 4.38. Actual and adjusted drying times for the drying runs.  Schedule - Mi category IS - MiM MS - MiM IS-MiH MS - MiH IS - MiL MS - MiL Actual drying time (h) 113 102 120 114 48 48 Adjusted drying time (h) 110 80 120 80 48 36   To compare drying schedules it is necessary to have the same initial moisture contents for all the runs. So the moisture contents were normalized by taking the ratio of the Mi and the current moisture content. The adjusted drying curves are depicted in Fig. 4.17. The IS-MiM had the mildest drying slope and MS-MiL and MS-MiH had the steepest drying curve. The MS by having the harsher drying conditions (lower relative humidity and higher drying temperature) than the corresponding IS resulted in a faster drying process.   Figure 4.17. Adjusted drying curves for each of the drying runs.  0.00.20.40.60.81.00 20 40 60 80 100 120 140Moisture ratio, M/MiTime (h)Industrial - Mix MModified - Mix MIndustrial - High MModified - High MIndustrial - Low MModified - Low M62 Table 4.39 also shows the drying rates at different moisture contents. As expected, the drying rate was higher at higher moisture contents where there is still free-water in the lumens and that decreased as more water was removed. The runs within the lower range of M had the lowest drying rates that is because removal of the bound-water which takes much more energy than the free-water removal. MS (applied with different Mi categories) resulted in higher drying rate throughout the drying process than its corresponding IS which is because of higher drying intensity in the corresponding schedule. As regards the Mi category, High- Mi category resulted in a higher drying rate noticeably at early drying, which is because of existence of more free water in this group.  Table 4.39. Drying rate (%/hour) at different moisture contents. Schedule - Mi category Moisture content (%) 10-30 30-50 50-70 70-90 90-120 IS - MiM  0.31 0.45 0.69 0.85 - MS - MiM 0.37 1.03 1.05 1.49 - IS - MiH 0.31 0.98 1.13 1.41 1.53 MS - MiH 0.41 1.34 1.68 1.87 1.97 IS - MiL 0.33 0.45 - - - MS - MiL 0.41 0.51 - - -  4.2.4 Final moisture content Table 4.40 shows the statistics regarding the Mf obtained in all the six runs. Although the target moisture content of 14% was set for all the runs, but the results showed that the Mf ranged from almost 12 to 17% with the standard deviation of 2.67 to 3.34%. As regards the Mf variation within each of the drying packages, IS-MiH led to the highest variation than all the other runs by standard deviation of 3.34% (Mf ranged from 10.71 to 24.14%). That can be because of stopping the kiln at higher Mf in this run than the others (almost 17%). MS-MiH also resulted in the lowest Mf variation, which can be because this run was terminated at a lower Mf (almost 12%) which is supposed to decrease the standard deviation itself (Bradic 2005, Wada 2013).   63 Table 4.40. Final moisture content statistics for the six runs. Schedule - Mi category Mean (%) St. Dev. (%) CV (%) Min (%) Max (%) IS-MiM  15.34 3.00 19.57 9.43 24.24 MS - MiM 12.09 3.16 26.10 7.20 19.17 IS - MiH 17.02 3.34 19.62 10.71 24.14 MS - MiH 12.39 2.67 21.56 7.55 20.00 IS - MiL 16.21 3.07 18.92 10.53 24.53 MS - MiL 15.39 2.96 19.23 9.09 24.19   As regards the Mf variation between the drying runs, the F-test showed that there was no significant difference between them, except in the MiH category. Moisture sorting statistically improved the Mf variation exclusively when there was a MiH sorting. In this category, MS statistically helped to decrease the Mf variation than the corresponding IS. A possible explanation is that the specimens sorted in the MiH category, which have higher Mi, may contain high percentage of sapwood. In such a case, these specimens can be dried with a better variation by the MS. Therefore, the MS improved the uniformity of Mf when it was applied within the MiH category. As regards the similar Mf variation in MiL and MiM categories, EMC-based drying schedules will mostly result in a better Mf variation below the Mfsp than the temperature-based schedules. Therefore the MS as an EMC-driven schedule has already helped to improve the Mf variation. In other words, MS did not affect the improvement of Mf variation in either of MiM or MiL. Fig. 4.18 also depicts the distribution of final moisture contents individually for each of the six runs.      64 Figure 4.18. Distribution of final moisture content through the six runs.  4.2.5 Final moisture content gradient 4.2.5.1 Shell moisture content  The average shell moisture content (Ms) for all the six runs was 16.54%, ranging from 12.79 to 19.61% and standard deviation of 3.09 to 5.15% (Table 4.41). Fig. 4.19 depicts the shell moisture content distribution through all the six drying runs. It seems that the IS (along with either of low or MiH) by having more under-dried specimens resulted in a wider Ms distribution than the modified one.   0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal moisture content (%)CountCumulativeIndustrial schedule - Mix M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal moisture content (%)CountCumulativeModified schedule - Mix M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal moisture content (%)CountCumulativeIndustrial schedule - High M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal moisture content (%)CountCumulativeModified schedule - High M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal moisture content (%)CountCumulativeIndustrial schedule - Low M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal moisture content (%)CountCumulativeModified schedule - Low M65 Table 4.41. Shell moisture content statistics for the six runs.  Schedule - Mi category Mean (%) St. Dev. (%) CV (%) Min (%) Max (%) IS-MiM  18.74 4.79 25.57 11.50 37.00 MS - MiM 12.79 3.09 24.13 8.10 26.20 IS-MiH 19.61 5.15 26.26 10.50 32.80 MS - MiH 13.16 3.40 25.84 8.00 23.40 IS-MiL 18.54 4.09 22.05 11.30 33.00 MS - MiL 16.38 4.12 25.12 9.40 29.00  Figure 4.19.  Shell moisture content distribution for the six runs. 0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal shell  moisture content (%)CountCumulativeIndustrial schedule - Mix M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal shell  moisture content (%)CountCumulativeModified schedule - Mix M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal shell  moisture content (%)CountCumulativeIndustrial schedule - High M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal shell  moisture content (%)CountCumulativeModified schedule - High M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal shell  moisture content (%)CountCumulativeIndustrial schedule - Low M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal shell  moisture content (%)CountCumulativeModified schedule - Low M66  Statistical analysis showed that there is a significant difference between the runs in terms of Mi-category (Table 4.42). In this regard, paired-sample t-test showed that the MiL category resulted in significantly a higher Ms than the MiM and High-Mi categories. That can be a result of termination of the drying process at almost higher final moisture content in case of MiL category.  There was also a significant difference between the drying schedules applied in terms of Ms. In this regard, paired-sample t-test showed that the MS resulted in significantly a lower Ms than the IS. That can be correlated to stop drying in lower final moisture contents where the MS was used. There was also a significant interaction between the two factors applied (Mi category and dying schedule). Paired sample t-test showed a significant difference between following runs:  IS - MiM had significantly a higher Ms than that of MS -MiM, MS -MiH and MS - MiL.  MS - MiM had significantly a lower Ms than that of IS-MiH, IS-MiL, and MS - MiL.  IS-MiH had significantly a higher Ms than that of MS - MiH and MS - MiL.  MS - MiH had significantly a lower Ms than that of IS-MiL and MS - MiL.  IS-MiL had significantly a higher Ms than that of MS - MiL.  These results indicate that generally the MS along with either of MiL or MiH categories resulted in a lower Ms than the corresponding IS. That can be correlated to the lower average final moisture content of the specimens dried by MS.  Table 4.42. Analysis of variance for shell moisture content. Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 1.028378 0.514189 8.97 0.0002* Schedule 1 9.128331 9.128331 159.30 <.0001* Mi_category*Schedule 2 1.432818 0.716409 12.50 <.0001* *:significant at a=0.05  4.2.5.2 Core moisture content  As it was expected, the core moisture content (Mc) was higher than the corresponding shell moisture content in all the six schedules (Table 4.43). The average Mc for all the six runs was 20.41%, ranging from 16.63 to 22.61% and standard deviation of 3.54 to 5.59% (Table 4. 43). Fig. 4.20 depicts the core moisture content distribution through all the six drying runs. It seems that the IS (with either of MiL or MiH) almost had more under-dried specimens than the modified one. 67 Table 4.43. Core moisture content statistics for the six runs.  Schedule - Mi category  Mean (%) St. Dev. (%) CV (%) Min (%) Max (%) IS-MiM 21.75 5.59 25.71 13.40 41.50 MS - MiM 16.63 3.54 21.29 9.70 30.10 IS-MiH 22.61 5.36 23.71 11.30 37.50 MS - MiH 18.61 4.06 21.79 12.80 30.70 IS-MiL 22.55 5.19 23.02 12.00 37.00 MS - MiL 20.33 4.56 22.42 31.30 12.30 Figure 4.20.  Core moisture content distribution for the six runs. 0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal core moisture content (%)CountCumulativeIndustrial schedule - Mix M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal core moisture content (%)CountCumulativeModified schedule - Mix M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal core moisture content (%)CountCumulativeIndustrial schedule - High M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal core moisture content (%)CountCumulativeModified schedule - High M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal core moisture content (%)CountCumulativeIndustrial schedule - Low M0204060801001200510152025300 4 8 12 16 20 24 28 MoreCumulative frequency (%)Piece countFinal core moisture content (%)CountCumulativeModified schedule - Low M68 Statistical analysis showed that there is a significant difference between the runs in terms of Mi-categoty (Table 4.44). In this regard, paired-sample t-test showed that the MiM category resulted in significantly a lower Mc than the MiH and MiL categories. That can be a result of termination of the drying process at almost lower final moisture contents in case of MiM category which has led to a significant difference here. There was also a significant difference between the drying schedules applied in terms of Mc. In this regard, paired-sample t-test showed that the MS resulted in significantly a lower Mc than the IS. That can be correlated to stop the drying in lower final moisture contents where the MS was used. There was also a significant interaction between the two factors applied (Mi category and dying schedule). Paired sample t-test showed a significant difference between following runs:  IS-MiM had significantly a higher Mc than that of MS -MiM and MS -MiH.  MS -MiM had significantly a lower Mc than that of IS-MiH, IS-MiL, and MS -MiL.  IS-MiH had significantly a higher Mc than that of MS -MiH.  MS -MiH had significantly a lower Mc than that of IS-MiL.  These results indicate that generally the MS along with either of MiL or MiH categories resulted in a lower Mc than the corresponding IS. That can be correlated to stop the drying in lower final moisture contents where the MS was used. Table 4.44. Analysis of variance for core moisture content. Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 0.988673 0.494336 9.56 <.0001* Schedule 1 3.367253 3.367253 65.15 <.0001* Mi_category*Schedule 2 0.414063 0.207031 4.01 0.0190* *:significant at a=0.05 4.2.5.3 Difference between shell-and-core moisture content The average difference between shell-and-core M for all the six runs was 3.88%, ranging from 3 to 5.46% and standard deviation of 1.75 to 2.62% (Table 4.45). Fig. 4.21 depicts the difference between Ms and Mc distribution through the six drying runs.  69 Table 4.45. Difference between shell-and-core moisture content statistics for the six runs. Schedule - Mi category Mean (%) St. Dev. (%) CV (%) Min (%) Max (%) IS-MiM 3.00 2.19 72.79 0.30 9.40 MS - MiM 3.84 2.01 52.46 1.20 10.20 IS-MiH 3.00 1.81 60.26 0.40 7.70 MS - MiH 5.46 1.75 32.01 3.00 10.30 IS-MiL 4.01 2.50 62.23 0.60 10.30 MS - MiL 3.95 2.62 66.25 0.40 10.40  Figure 4.21. Difference between shell-and-core moisture content distributions for the six runs.  020406080100120051015202530350 2 4 6 8 10 12 14 MoreCumulative frequency (%)Piece countMoisture content (%)CountCumulativeIndustrial schedule - Mix MDifference between shell  and core 020406080100120051015202530350 2 4 6 8 10 12 14 MoreCumulative frequency (%)Piece countMoisture content (%)CountCumulativeModified schedule - Mix MDifference between shell  and core 020406080100120051015202530350 2 4 6 8 10 12 14 MoreCumulative frequency (%)Piece countMoisture content (%)CountCumulativeIndustrial schedule - High MDifference between shell  and core 020406080100120051015202530350 2 4 6 8 10 12 14 MoreCumulative frequency (%)Piece countMoisture content (%)CountCumulativeModified schedule - High MDifference between shell  and core 020406080100120051015202530350 2 4 6 8 10 12 14 MoreCumulative frequency (%)Piece countMoisture content (%)CountCumulativeIndustrial schedule - Low MDifference between shell  and core 020406080100120051015202530350 2 4 6 8 10 12 14 MoreCumulative frequency (%)Piece countMoisture content (%)CountCumulativeModified schedule - Low MDifference between shell  and core 70 Statistical analysis showed that there is a significant difference between the drying schedules applied in terms of the difference between shell-and-core moisture contents (Table 4.46). The corresponding paired sample t-test indicated that the MS led to significantly a higher difference between Ms and Mc. In other words, the IS, as the mildest and the most conservative schedule, by having a lower drying rate resulted in a more uniform moisture gradient through the dried specimens. In addition, there was also a significant difference in terms of Mi-sorting between the drying runs. The corresponding paired sample t-test revealed that the MiH category had a higher difference between Ms and Mc than both the MiM and MiL categories. There was no significant difference between the MiM and MiL categories in this regard.  There was also a significant interaction between the two factors applied (Mi category and dying schedule). Paired sample t-test showed a significant difference between following runs:   IS - MiM had significantly a lower difference between Ms and Mc than that of MS - MiM and MS - MiH.  MS - MiM had significantly a lower difference between Ms and Mc than that of MS - MiH.  IS - MiH had significantly a lower difference between Ms and Mc than that of MS - MiH.  MS - MiH had significantly a higher difference between Ms and Mc than that of IS - MiL and MS - MiL.  The high variability of Ms and Mc could be explained by the fact that drying begins in the surface layers, while the core takes longer to dry. Therefore, the moisture content distribution is usually not uniform among the specimens depending on the drying schedule applied together with the corresponding drying rate. It is also worthy to mention that wetwood is another underlying cause of the high variability between Ms and Mc (Sackey 2003). The difference between Ms and Mc can be partially alleviated for PCH by applying conditioning and equalization treatments at the end of the drying process (Rohrbach 2008).    71 Table 4.46. Analysis of variance for difference between shell-and-core moisture content. Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 4.375048 2.187524 5.18 0.0060* Schedule 1 12.465255 12.465255 29.49 <.0001* Mi_category*Schedule 2 9.961477 4.980738 11.78 <.0001* *:significant at a=0.05 4.2.6 Shrinkage  The average width shrinkage for all the six runs was 2.60%, ranging from 2.01 to 3.13% and standard deviation of 0.63 to 1.01% (Table 4.47). The shrinkage values were consistent with the one reported by Zhang et al. (1996) and Avramidis and Hao (2004). As regards the drying schedule within different Mi categories, IS by having a milder drying condition led to a lower shrinkage percentage than the MS. On the other hand and when Mi category is considered with either of drying schedules, there seems to be no noticeable difference between the Mi categories. Fig. 4.22 also depicts the width shrinkage distribution for different drying schedules applied. That shows that more of the specimens dried by the MS (within either of Mi categories) still tend to show larger shrinkages than the IS.   Table 4.47. Shrinkage statistics for the six runs. Schedule - Mi category Mean (%) SD (%) CV (%) Min (%) Max (%) IS - MiM 2.38 0.86 36.19 0.63 4.67 MS - MiM 3.13 0.90 28.85 1.35 5.19 IS - MiH 2.06 1.01 49.05 0.02 4.27 MS - MiH 3.11 0.97 31.03 1.02 5.23 IS - MiL 2.01 0.78 38.70 0.23 4.17 MS - MiL 2.92 0.63 21.45 1.69 4.99  72 Figure 4.22. Shrinkage distribution in the six runs. The analysis of variance table showed a significant difference between the drying schedules in terms of intensity of width shrinkage (Table 4.48). Paired sample t-test indicated that the MS resulted in a larger shrinkage percentage. It is also worthy to mention that drying terminated at lower final moisture contents where the MS was used which can be considered as a potential reason for the obtained results. However, Mi-sorting did not statistically influence the shrinkage percentage.  02040608010012001020304050601 2 3 4 5 6Cumulative frequency (%)Piece countShrinkage (%)CountCumulativeIndustrial schedule - Mix M02040608010012001020304050601 2 3 4 5 6Cumulative frequency (%)Piece countShrinkage (%)CountCumulativeModified schedule - Mix M02040608010012001020304050601 2 3 4 5 6Cumulative frequency (%)Piece countShrinkage (%)CountCumulativeIndustrial schedule - High M02040608010012001020304050601 2 3 4 5 6Cumulative frequency (%)Piece countShrinkage (%)CountCumulativeModified schedule - High M02040608010012001020304050601 2 3 4 5 6Cumulative frequency (%)Piece countShrinkage (%)CountCumulativeIndustrial schedule - Low M02040608010012014001020304050601 2 3 4 5 6Cumulative frequency (%)Piece countShrinkage (%)CountCumulativeModified schedule - Low M73 Table 4.48. Analysis of variance for shrinkage. Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 5.969375 2.984687 3.98 0.0641 Schedule 1 86.019876 86.019876 114.78 <.0001* Mi_category*Schedule 2 1.613381 0.806690 1.08 0.3418 *:significant at a=0.05  4.2.7 Shape distortion 4.2.7.1 Bow  Table 4.49 lists the intensity of bow resulted from different drying schedules and Mi-categories. These statistics are actually the difference between the bow measured before and after drying. The overall mean for all the drying runs was 0.29 mm ranging from 0.21 to 0.34 mm and standard deviation of 0.26 to 0.38 mm. The bow distribution is also depicted in Fig. 4.23 individually for all the six runs. As can be seen, there are positive and some negative values for bow resulted from all the schedules. The negative values come from the specimens which deformed in the opposite direction of the original one measured before drying.   Table 4.49. Bow statistics for the six runs (mean values are the difference between measured bow before and after drying).   Schedule - Mi category Mean (mm) St. Dev. (mm) CV (%) Min  (mm) Max  (mm) IS - MiM 0.21 0.26 128.28 -0.30 1.24 MS - MiM 0.31 0.33 106.17 -0.30 1.06 IS - MiH 0.26 0.34 133.03 -0.30 1.42 MS - MiH 0.33 0.38 113.53 -0.35 1.47 IS - MiL 0.31 0.37 120.32 -0.31 1.42 MS - MiL 0.34 0.29 85.22 -0.09 1.27 74 Figure 4.23. Bow distribution in the six runs.  The statistical analysis showed a significant difference between the drying schedules applied in terms of intensity of bow (Table 4.50). Paired sample t-test indicated that the MS by providing a harsher drying condition resulted in significantly a larger bow than the IS. Moisture sorting, however, did not have a significant influence on the developed bow. It is reported in the literature that bow is associated with longitudinal shrinkage in juvenile wood near the pith, reaction wood, and spiral grain. Therefore, the cause, as already mentioned, is the difference in longitudinal shrinkage on opposite sides of a specimen. Moreover, this type of defect can also be the result of poor stacking; for example, stickers are not aligned and/or too far 020406080100120051015202530-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countBow (mm)CountCumulativeIndustrial schedule - Mix MDifference between initial and final bow 020406080100120051015202530-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countBow (mm)CountCumulativeModified schedule - Mix MDifference between initial and final bow 020406080100120051015202530-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countBow (mm)CountCumulativeIndustrial schedule - High MDifference between initial and final bow 020406080100120051015202530-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countBow (mm)CountCumulativeModified schedule - High MDifference between initial and final bow 020406080100120051015202530-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countBow (mm)CountCumulativeIndustrial schedule - Low MDifference between initial and final bow 020406080100120051015202530-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countBow (mm)CountCumulativeModified schedule - Low MDifference between initial and final bow 75 apart, stickers are not uniform in thickness, or foundations are uneven (Bendtsen 1978, Simpson 1991, Dening et al. 2000), though that was not the case in the current research.  Table 4.50. Analysis of variance for bow. Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 0.096232 0.048116 0.69 0.5003 Schedule 1 0.429048 0.429048 6.19 0.0133* Mi_category*Schedule 2 0.156265 0.078132 1.13 0.3253 *:significant at a=0.05 4.2.7.2 Crook Table 4.51 shows the intensity of crook resulted by different drying schedules and Mi-categories. These statistics are actually the differences between the crook before and after drying. The overall mean for all the runs was 0.39 mm ranging from 0.34 to 0.44 mm and standard deviation of 0.27 to 0.38 mm. The crook distribution is also depicted in Fig. 4.24 individually for all the six runs. Table 4.51. Crook statistics for the six runs (mean values are the difference between measured crook before and after drying).   Schedule - Mi category Mean (mm) St. Dev. (mm) CV (%) Min  (mm) Max  (mm) IS - MiM 0.37 0.38 102.72 0.01 1.45 MS - MiM 0.42 0.38 89.39 0.00 1.59 IS - MiH 0.44 0.38 86.93 0.01 1.70 MS - MiH 0.41 0.34 82.20 0.00 1.45 IS - MiL 0.36 0.27 73.48 0.00 1.10 MS - MiL 0.34 0.27 80.35 0.00 1.35 76 Figure 4.24. Crook distribution in the six runs.  The statistical analysis showed that the neither drying schedule nor moisture presorting had a significant influence on the developed crook (Table 4.52). This type of defect is often a result of improper sawing patterns or crooked logs such that the rings, when viewed from the end of the piece of lumber, are off center edge to edge. Often the wood closer to the center of the tree shrinks more than does the wood closer to the bark. Although good stacking practices also help reducing 02040608010012005101520253035400 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countCrook (mm)CountCumulativeIndustrial schedule - Mix MDifference between initial and final crook02040608010012005101520253035400 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countCrook (mm)CountCumulativeModified schedule - Mix MDifference between initial and final crook02040608010012005101520253035400 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countCrook (mm)CountCumulativeIndustrial schedule - High MDifference between initial and final crook02040608010012005101520253035400 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countCrook (mm)CountCumulativeModified schedule - High MDifference between initial and final crook02040608010012005101520253035400 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countCrook (mm)CountCumulativeIndustrial schedule - Low MDifference between initial and final crook02040608010012005101520253035400 0.2 0.4 0.6 0.8 1 MoreCumulative frequency (%)Piece countCrook (mm)CountCumulativeModified schedule - Low MDifference between initial and final crook77 the crook, but they are not as effective against this type of warp as they are against cup, bow, and twist (Simpson 1991, Dening et al. 2000).  Table 4.52. Analysis of variance for crook. Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 0.184546 0.092273 1.18 0.3068 Schedule 1 0.001488 0.001488 0.02 0.8901 Mi_category*Schedule 2 0.081600 0.040800 0.52 0.5926  4.2.7.3 Cup  Table 4.53 shows the intensity of cup resulted by different drying schedules and Mi-categories. These statistics are actually the differences between the cup before and after drying. The overall mean for all the runs was 0.08 mm ranging from -0.40 to 1.86 mm and standard deviation of 0.09 to 0.34 mm. The average cup for the specimens dried by the IS within different Mi-categories ranged from 0.01 to 0.11 mm, though that was 0.01 to 0.22 mm where the MS was applied. In other words, IS by having a milder drying condition led to a lower amount of cup than the MS. The cup distribution is also depicted in Fig. 4.25 individually for all the six runs. As can be seen, there are positive and some negative values for cup resulted from all the schedules. The negative values come from the specimens which deformed in the opposite direction of the original one measured before drying.   Table 4.53. Cup statistics for the six runs (mean values are the difference between measured cup before and after drying).    Schedule - Mi category Mean (mm) St. Dev. (mm) CV (%) Min  (mm) Max  (mm) IS - MiM 0.02 0.10 467.28 -0.22 0.37 MS - MiM 0.09 0.15 169.90 -0.28 0.42 IS - MiH 0.11 0.18 163.21 -0.32 0.58 MS - MiH 0.00 0.11 79325.81 -0.40 0.26 IS - MiL 0.00 0.07 13180.45 -0.26 0.22 MS - MiL 0.16 0.22 135.43 -0.26 0.62  78 The statistical analysis showed that the neither drying schedules nor Mi-categories exclusively had a significant influence on the developed cup (Table 4.54). There was, however, a significant interaction between the two factors applied (Mi category and dying schedule). Paired sample t-test showed a significant difference between following runs:  MS - MiM had significantly a lower cup than that of MS - MiL.  IS - MiH had significantly a higher cup than that of IS - MiL.  IS - MiL had significantly a lower cup than that of MS - MiL.  Figure 4.25. Cup distribution in the six runs. 0204060801001200102030405060-0.4 -0.2 0 0.2 0.4 0.6 MoreCumulative frequency (%)Piece countCup (mm)CountCumulativeIndustrial schedule - Mix MDifference between initial and final cup0204060801001200102030405060-0.4 -0.2 0 0.2 0.4 0.6 MoreCumulative frequency (%)Piece countCup (mm)CountCumulativeModified schedule - Mix MDifference between initial and final cup0204060801001200102030405060-0.4 -0.2 0 0.2 0.4 0.6 MoreCumulative frequency (%)Piece countCup (mm)CountCumulativeIndustrial schedule - High MDifference between initial and final cup0204060801001200102030405060-0.4 -0.2 0 0.2 0.4 0.6 MoreCumulative frequency (%)Piece countCup (mm)CountCumulativeModified schedule - High MDifference between initial and final cup0204060801001200102030405060-0.4 -0.2 0 0.2 0.4 0.6 MoreCumulative frequency (%)Piece countCup (mm)CountCumulativeIndustrial schedule - Low MDifference between initial and final cup0204060801001200102030405060-0.4 -0.2 0 0.2 0.4 0.6 MoreCumulative frequency (%)Piece countCup (mm)CountCumulativeModified schedule - Low MDifference between initial and final cup79 Table 4.54. Analysis of variance for cup. Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 0.939302 0.469651 0.88 0.4170 Schedule 1 0.856912 0.856912 1.61 0.2072 Mi_category*Schedule 2 11.466072 5.733036 10.74 <.0001* *:significant at a=0.05 4.2.7.4 Twist Table 4.55 shows the intensity of twist resulted by different drying schedules and Mi-categories. These statistics are actually the differences between the twist before and after drying. The overall mean for all the drying runs was 0.12 mm ranging from 0.02 to 0.24 mm and standard deviation of 0.17 to 0.35 mm. The twist distribution is also depicted in Fig. 4.26 individually for all the six runs. As can be seen, there are positive and some negative values for twist resulted from all the schedules. The negative values come from the specimens which deformed in the opposite direction of the original one measured before drying.  Table 4.55. Twist statistics for the six runs (mean values are the difference between measured twist before and after drying). Schedule - Mi category Mean (mm) St. Dev. (mm) CV (%) Min  (mm) Max  (mm) IS - MiM 0.16 0.35 216.81 -0.40 1.10 MS - MiM 0.24 0.33 139.03 -0.23 1.10 IS - MiH 0.12 0.29 232.94 -0.44 0.98 MS - MiH 0.02 0.17 932.50 -0.45 0.70 IS - MiL 0.06 0.17 276.14 -0.15 0.67 MS - MiL 0.11 0.22 191.81 -0.24 0.94  The statistical analysis showed that the neither drying schedules nor Mi-categories had a significant influence on the developed twist (Table 4.56).  80 Table 4.56. Analysis of variance for twist. Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 4.044010 2.022005 2.23 0.1114 Schedule 1 0.342109 0.342109 0.38 0.5402 Mi_category*Schedule 2 0.303637 0.151818 0.17 0.8461 *:significant at a=0.05  Figure 4.26. Twist distribution in the six runs. 0204060801001200102030405060-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 MoreCumulative frequency (%)Piece countTwist (mm)CountCumulativeIndustrial schedule - Mix MDifference between initial and final twist0204060801001200102030405060-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 MoreCumulative frequency (%)Piece countTwist (mm)CountCumulativeModified schedule - Mix MDifference between initial and final twist0204060801001200102030405060-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 MoreCumulative frequency (%)Piece countTwist (mm)CountCumulativeIndustrial schedule - High MDifference between initial and final twist0204060801001200102030405060-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 MoreCumulative frequency (%)Piece countTwist (mm)CountCumulativeModified schedule - High MDifference between initial and final twist0204060801001200102030405060-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 MoreCumulative frequency (%)Piece countTwist (mm)CountCumulativeIndustrial schedule - Low MDifference between initial and final twist0204060801001200102030405060-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 MoreCumulative frequency (%)Piece countTwist (mm)CountCumulativeModified schedule - Low MDifference between initial and final twist81 4.2.8 Surface checks  Table 4.57 shows the total length of checks in mm which indicates the sum of the length of surface checks for each run before and after drying in all the corresponding kiln specimens. The percentage also represents the total length of surface checks in each run in relation to the total length of all of the specimens in the corresponding run. As can be seen in this table, only the MS - MiL category caused some surface checking which was 0.23% of the total length of all the specimens in this drying run.  Table 4.57. Total length and percentage of surface check in correlation to the total specimens’ length. Schedule - Mi category Total length of check (mm) Percentage (%) length before drying  length after drying   Difference (after - before)  length before drying  length after drying  Difference (after - before)  IS - MiM 0 0 0 0 0 0 MS - MiM 0 0 0 0 0 0 IS - MiH 0 0 0 0 0 0 MS - MiH 0 0 0 0 0 0 IS - MiL 0 0 0 0 0 0 MS - MiL 0 151 151 (out of 64800 mm) 0 0.23 0.23  Statistical analysis also showed that neither drying schedule nor presorting showed a significant influence on the developed surface checks (Table 4.58).   Table 4.58. Analysis of variance for surface checks. Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 105.56018 52.78009 2.01 0.1348 Schedule 1 52.78009 52.78009 2.01 0.1567 Mi_category*Schedule 2 105.56018 52.78009 2.01 0.1348    82 4.2.9 Internal checks The results showed that none of the drying schedules and Mi-categories led to occurrence of honeycomb in this study. This means that even the MS has still shown a promising result in terms of honeycomb and that can be used (along with different Mi-categories) to dry PCH without any concerns.   4.2.10 Casehardening Table 4.59 shows the intensity of casehardening resulted from different drying schedules and Mi-categories. The overall mean for all the runs was 0.71×10-3 mm-1 and standard deviation of 0.22×10-3 mm-1 ranging from 0.01×10-3 mm-1 to 1.55×10-3 mm-1. The average casehardening for the specimens dried by the IS within different Mi-categories ranged from 0.47 to 0.58×10-3 mm-1, though that was 0.73 to 1.01×10-3 mm-1 where the MS was applied. In other words, IS by having a milder drying condition led to a lower amount of casehardening than the MS. The casehardening distribution is also depicted in Fig. 4.27 individually for all the six runs. There is a tendency for the casehardening values resulted from the MS to be in the upper range of the plots with larger intensities when compared to the IS.  Table 4.59. Casehardening statistics for the six runs. Schedule - Mi category  Mean (10-3 mm-1) SD (10-3 mm-1) CV (%) Min (10-3 mm-1) Max (10-3 mm-1) IS - MiM 0.47 0.17 35.45 0.10 0.75 MS - MiM 0.89 0.22 24.50 0.49 1.55 IS - MiH 0.58 0.28 48.71 0.01 1.13 MS - MiH 1.01 0.23 22.93 0.62 1.48 IS - MiL 0.57 0.19 34.38 0.01 1.02 MS - MiL 0.73 0.24 32.89 0.39 1.29          83 Figure 4.27. Casehardening distribution in the six runs.  The statistical analysis showed that the drying schedule had a significant influence on the intensity of residual stresses (Table 4.60). Paired sample t-test indicated that MS resulted in a significantly higher casehardening than the IS. In addition, there was also a significant difference in terms of Mi-sorting between the drying runs. The corresponding paired sample t-test revealed that the MiH category had a higher amount of casehardening than either of MiM and MiL categories, though the last two Mi categories were the same in this regard. 0204060801001200246810120 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 MoreCumulative frequency (%)Piece countCasehardening (10- 3 mm-1)CountCumulativeIndustrial schedule - Mix M0204060801001200246810120 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 MoreCumulative frequency (%)Piece countCasehardening (10- 3 mm-1)CountCumulativeModified schedule - Mix M0204060801001200246810120 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 MoreCumulative frequency (%)Piece countCasehardening (10- 3 mm-1)CountCumulativeIndustrial schedule - High M0204060801001200246810120 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 MoreCumulative frequency (%)Piece countCasehardening (10- 3 mm-1)CountCumulativeModified schedule - High M0204060801001200246810120 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 MoreCumulative frequency (%)Piece countCasehardening (10- 3 mm-1)CountCumulativeIndustrial schedule - Low M0204060801001200246810120 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 MoreCumulative frequency (%)Piece countCasehardening (10- 3 mm-1)CountCumulativeModified schedule - Low M84 There was also a significant interaction between the two factors applied (Mi-category and dying schedule). Paired sample t-test showed a significant difference between following runs:   IS - MiM had significantly a lesser casehardening than that of MS -MiM, MS - MiH, and MS - MiL.  MS -MiM had significantly a greater casehardening than that of IS - MiH, though lesser than IS-MiL.  IS-MiH had significantly a lesser casehardening than that of MS -MiH.  MS - MiH had significantly a greater casehardening than that of IS-MiL and MS - MiL. Application of MS with harsher drying conditions (higher temperature and lower relative humidity) resulted in significantly a higher casehardening. The MS, as already mentioned, followed by a larger amount of shrinkage than that of IS, which can be considered as another underlying causes of casehardening. Moreover, MiH category also led to a greater casehardening than its corresponding Mi -categories.   Table 4.60. Analysis of variance for casehardening.  Source DF Type III SS Mean Square F Value Pr > F Mi_category 2 0.541220 0.270610 5.31 0.0061* Schedule 1 3.862666 3.862666 75.73 <.0001* Mi_category*Schedule 2 0.499647 0.249823 4.90 0.0089* *:significant at a=0.05 85 5. Conclusions The objective of this study was to investigate the possibility of reducing the final moisture content variation of conventionally dried PCH lumber using moisture pre-sorting coupled with a modified drying schedule. The conclusions are as follows: 1. Moisture sorting statistically improved the final moisture content (Mf) variation exclusively when there was a high-Mi (MiH) sorting. Within this moisture sorting, Modified schedule (MS) statistically helped to reduce the Mf variation than the corresponding industrial schedule (IS). Modified schedule, however, did not significantly affect the Mf variation in either of Mixed-Mi (MiM) or Low-Mi (MiL) sortings. 2. Since the drying runs started with specimens of different initial moisture contents, the drying terminated at different times for different drying schedules and Mi combinations. The runs with a higher initial moisture contents (MiH) took longer to dry. According to the adjusted drying times, however, the runs dried by MS took less time to reach the same final moisture content than the IS. As regards the drying rate, MS (applied with different Mi categories) resulted in a higher drying rate throughout the drying process.  3. The MS led to significantly a higher difference between shell-and-core moisture content than the IS. As regards the Mi sorting, MiH category also resulted in a higher difference between shell-and-core M than both the MiM and MiL categories. 4. The MS resulted in a larger shrinkage percentage (all drying runs terminated at lower final moisture contents where the MS was used). Moisture sorting, however, did not statistically influence the shrinkage percentage. 5. MS resulted in significantly a larger bow than the IS. Moisture sorting, however, did not have a significant influence on the developed bow. The statistical analysis also showed that the neither drying schedule nor moisture presorting had a significant influence on the crook, cup, and twist. 6. The statistical analysis also showed that neither drying schedule nor presorting showed a significant influence on the occurrence of surface checks and honeycomb. 86 7. MS resulted in a significantly higher casehardening than the IS. MiH category, on the other hand, led to a higher amount of casehardening than either of MiM and MiL categories. In conclusion, moisture sorting statistically improved the Mf variation exclusively when there was a MiH sorting. Within this Mi sorting, MS statistically helped to decrease the Mf variation than the corresponding IS. Neither sorting nor drying schedule affected the Mf variation in MiL and MiM sorting, which could be because of the type of drying schedule applied. This can be because of the EMC-based drying schedule that was applied which has already helped to get a better Mf variation below the Mfsp when compared to the temperature-based schedule. Even though the MS was not successful in some cases, but that could reduce the drying time through all the Mi categories in comparison to the IS. So the moisture sorting is suggested to be used when there are specimens with high green moisture contents (which are more likely to carry sapwood). In such cases, the MS is recommended to be used to reduce the final moisture content variation in the dried specimens. The MS, however, can also be considered when the kiln drying time matters.  5.1 Recommendations 1. Application of equalization and conditioning treatments at the end of drying process need to be evaluated to figure out if they can improve Mf variability. 2. Application of faster drying schedule can be investigated.  3. Temperature-driven drying schedule can also be developed and assessed. 4. Industrial-size specimens can be used, specially, if the shape distortion is also of interest. 5. Sorting PCH based on the species should also be studied.          87 References Abner, T. L. 1964. Dry west coast hemlock and Douglas-fir 1 1/2 inch dimension to the new moisture specification with a minimum amount of degrade. Western Dry Kiln Clubs Conference, Coeur d'Alene, US, 4-7pp. Alden, H. 1995. Softwoods of North America, FPL-GTR-102. Madison, WI. U.S. Dept. of Agriculture, Forest Service, Forest Products Laboratory, 151pp. Anonymous 1997. Hem-Fir Species Facts, Western Wood Products Association, 10pp. Anonymous 2003. 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