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Precision dairy technology and its association with estrous expression and fertility outcomes in Holstein… Mesquita L. Madureira, Augusto 2020

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PRECISION DAIRY TECHNOLOGY AND ITS ASSOCIATION WITH ESTROUS EXPRESSION AND FERTILITY OUTCOMES IN HOLSTEIN CATTLE by Augusto Mesquita L. Madureira  B.Sc., São Paulo State University, 2011 M.Sc., São Paulo State University, 2016  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF  THE REQUIREMENTS FOR THE DEGREE OF Doctor of Philosophy in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Applied Animal Biology)  THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)   December 2020 ©Augusto Mesquita L. Madureira, 2020  ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled:  PRECISION DAIRY TECHNOLOGY AND ITS ASSOCIATION WITH ESTROUS EXPRESSION AND FERTILITY OUTCOMES IN HOLSTEIN CATTLE submitted by Augusto Mesquita L. Madureira in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Applied Animal Biology  Examining Committee: Dr. Ronaldo L.A. Cerri, Associate Professor, Applied Animal Biology, UBC Supervisor  Dr. Daniel Weary, Professor, Applied Animal Biology, UBC Supervisory Committee Member  Dr. Marina Von Keyserlingk, Professor, Applied Animal Biology, UBC University Examiner Dr. Raymond Ng, Professor, Computer Science, UBC University Examiner  Additional Supervisory Committee Members: Dr. Ky G. Pohler, Assistant Professor, Animal Science, Texas A&M University Supervisor Committee Member    iii Abstract Technologies developed to detect estrus have the potential to improve dairy cattle fertility; however, there is still need for better understanding of how the readers of automated activity monitors (AAM) are associated with fertility outcomes and reproductive physiology. The objectives of this thesis were to determine 1) if estrous expression, detected by AAM can be used within an ovulation synchronization program for timed artificial insemination (AI) and embryo transfer (ET), and 2) the relationship between estrous expression, ovulation rates, viability and quality of embryo, progesterone and estradiol concentrations, and fertility and pregnancy loss. In Chapter 2, it was demonstrated that following the use of a timed AI synchronization protocol, cows showed different intensities of estrus detected by an AAM and that greater intensity of estrous expression resulted in greater fertility and decreased pregnancy losses. In Chapter 3, I investigated the intensity of estrous expression at the end of a superovulation protocol, for embryo collection, in Holstein heifers and its association with production and viability of embryo. Heifers with greater intensity of estrus, detected by an AAM or a breeding indicator, had greater percentage and number of viable embryos compared with animals that had lower intensity of estrus. In Chapter 4, I examined the association between estrous expression and the success of ET, and found that the intensity of estrous expression, and the occurrence of estrus prior to ET, improved fertility. Finally, in Chapter 5, I summarized work that investigated if the concentrations of progesterone (P4) around estrus is related to the intensity of estrus and fertility of Holstein cows. Greater concentrations of P4 and lower concentrations of E2 at AI were associated with lower intensity estrous, while greater concentrations of P4 prior to AI were associated with greater estrous expression and fertility. Future research is needed to further understand the association of intensity estrous expression and fertility and pregnancy loss.  iv Lay Summary Automated activity monitors are used on dairy farms to help detect estrus in lactating cows. These new technologies have been shown to be efficient and, if correctly used, increase the efficiency of reproductive managements in dairy herds. This thesis set out to determine if estrous expression, detected by automated activity monitor, can be used within an ovulation synchronization program for timed artificial insemination (AI) and embryo transfer (ET), and the relationship between the intensity of estrus and fertility outcomes of dairy cows. Greater intensity of estrous expression was associated with higher ovulation rates, greater numbers of viable embryos, better fertility and reduced pregnancy loss. Finally, this thesis investigated if the intensity of estrus is modulated by concentration of progesterone around estrus. Concentrations of progesterone were associated with the intensity of estrus and fertility of lactating Holstein cows. Future research is needed to further understand the relationship between the intensity of estrous expression and fertility of lactating dairy cows.      v Preface A version of the materials in Chapters 2 and 3 have been accepted for publication: Chapter 2 – Madureira, A.M.L., L.B. Polsky, T.A. Burnett, B.F. Silper, S. Soriano, A.F. Sica, K.G. Pohler, J.L.M. Vasconcelos and R.L.A. Cerri. 2019. Intensity of estrus following an estradiol-progesterone-based ovulation synchronization protocol influences fertility outcome. J. Dairy Sci. 102(4):3598-3608. DOI: 10.3168/jds.2018-15129; Chapter 3 – Madureira, A.M.L., T.A. Burnett, K.G. Pohler, T.G. Guida, C.P. Sanches, J.L.M Vasconcelos and R.L.A. Cerri. 2020. Short Communication: Greater intensity of estrous expression is associated with improved embryo viability from supervoulated Holstein heifers. J. Dairy Sci. 103: 5641-5646. DOI: 10.3168/jds.2019-17772. Versions of the materials in Chapter 4 and 5 will be submitted for review: Chapter 4 -Madureira, A.M.L., T.A. Burnett, J.C.S. Marques, A.L. Moore, S. Borchardt, W. Heuwieser, T.G. Guida, J.L.M. Vasconcelos, and R.L.A. Cerri. Occurrence and intensity of estrus in recipient lactating dairy cows improve pregnancy per embryo transfer; Chapter 5 - Madureira, A.M.L., T.A. Burnett, S. Borchardt, W. Heuwieser, J.L.M. Vasconcelos, and R.L.A. Cerri. Concentrations of progesterone in plasma during the estrous cycle are associated with the intensity of estrus and fertility of lactating Holstein cows. For all chapters, A.M.L. Madureira was the lead investigator, and responsible for experimental design, data collection and processing, statistical analysis, material interpretation, and manuscript composition. R.L.A. Cerri acted in the supervisory role by helping in the idea formulation, statistical analysis and providing input and editing of manuscript drafts. The following authors were involved in data collection and processing: L.B. Polsky, B.F. Silper, S. Soriano, A.F. Sica, T.G. Guida, C. P. Sanches, J.C.S Marques and A.L. Moore. While the following authors were involved in data analysis, experimental design and reviewing manuscripts:  vi T.A Burnett, K.G. Pohler, J.L.M. Vasconcelos, S. Borchardt and H. Heuwieser. Three projects received UBC Animal Care approval as follows: Chapter 2 and Chapter 4- certificate number: #A14-0290; Chapter 5 - certificate number: # A18-0315.               vii Table of Contents   Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface ............................................................................................................................................ v Table of Contents ........................................................................................................................ vii List of Tables ............................................................................................................................... xii List of Figures ............................................................................................................................. xiii List of Abbreviations ................................................................................................................. xvi Acknowledgements ................................................................................................................... xvii 1 Chapter 1: Introduction ........................................................................................................ 1 1.1 Precision Dairy Farming ............................................................................................... 4 1.1.1 Technology to improve dairy management .............................................................. 4 1.1.2 Technology Available in the Dairy Industry ............................................................ 6 1.2 Automated Activity Monitors ....................................................................................... 7 1.2.1 Estrus Detection ........................................................................................................ 7 1.2.2 Diagnostics .............................................................................................................. 10 1.3 Fundamentals of Estrous Cycle .................................................................................. 13 1.3.1 Physiology of the estrous cycle............................................................................... 14 1.4 Importance of Progesterone pre-AI, at AI and post-AI ........................................... 19 1.4.1 Concentration of Progesterone pre-AI .................................................................... 19  viii 1.4.2 Concentration of Progesterone at AI....................................................................... 20 1.4.3 Concentration of Progesterone Post-AI .................................................................. 21 1.5 Insemination, Fertilization and Early Embryonic Development ............................. 23 1.5.1 Insemination and Fertilization ................................................................................ 23 1.5.2 Early Embryonic Development............................................................................... 24 1.5.3 Factors that Affect Fertilization .............................................................................. 25 1.6 Implantation and maternal recognition of pregnancy .............................................. 26 1.7 Factors associated with reduced estrous expression in dairy cattle ........................ 27 1.7.1 Social Interactions ................................................................................................... 30 1.7.2 Management ............................................................................................................ 31 1.8 Impact of estrous expression on fertility .................................................................... 32 1.9 Thesis Objective............................................................................................................ 35 2 Chapter 2: Intensity of estrus following an estradiol-progesterone based ovulation synchronization protocol influences fertility outcomes ........................................................... 37 2.1 Introduction .................................................................................................................. 37 2.2 Materials and methods................................................................................................. 39 2.2.1 Animals, Housing and Management ....................................................................... 39 2.2.2 Automated Activity Monitor................................................................................... 40 2.2.3 Synchronization Protocol, Blood Sampling and Analysis of Progesterone ............ 41 2.2.4 Statistical Analyses ................................................................................................. 42 2.3 Results ........................................................................................................................... 44 2.3.1 Animals and Number of Events .............................................................................. 44 2.3.2 Estrous Expression at Timed AI ............................................................................. 44  ix 2.3.3 Preovulatory Follicle Diameter ............................................................................... 45 2.3.4 Concentration of Progesterone in Serum ................................................................ 45 2.3.5 Ovulation Failure .................................................................................................... 46 2.3.6 Factors Impacting Pregnancy per AI and Pregnancy Loss ..................................... 46 2.4 Discussion ...................................................................................................................... 47 2.5 Conclusion ..................................................................................................................... 53 3 Chapter 3: Greater intensity of estrous expression is associated with improved embryo viability from superovulated Holstein heifers .......................................................................... 62 3.1 Introduction .................................................................................................................. 62 3.2 Materials and methods................................................................................................. 63 3.2.1 Animals and housing............................................................................................... 64 3.2.2 Superovulation protocol, estrus detection and embryo collection .......................... 64 3.2.3 Statistical Analyses ................................................................................................. 66 3.3 Results and Discussion ................................................................................................. 67 3.4 Conclusion ..................................................................................................................... 69 4 Chapter 4: Occurrence and higher intensity of estrus in recipient dairy cows improve pregnancy per embryo transfer ................................................................................................. 72 4.1 Introduction .................................................................................................................. 72 4.2 Materials and methods................................................................................................. 74 4.2.1 Animals, housing and management ........................................................................ 75 4.2.2 Ovulation Synchronization Protocol and Embryo Transfer.................................... 75 4.2.3 Detection of Estrus - Automated Activity Monitor and Tail Chalk........................ 77 4.2.4 Statistical Analyses ................................................................................................. 77  x 4.3 Results ........................................................................................................................... 79 4.3.1 Animals, Number of Events and Farm ................................................................... 79 4.3.2 Estrous Expression at the end of the timed AI protocol ......................................... 79 4.3.3 Pregnancy per ET and Pregnancy loss .................................................................... 80 4.4 Discussion ...................................................................................................................... 81 4.5 Conclusion ..................................................................................................................... 86 5 Chapter 5: Concentrations of progesterone in plasma during the estrous cycle are associated with the intensity of estrus and fertility of Holstein cows ..................................... 94 5.1 Introduction .................................................................................................................. 94 5.2 Materials and methods................................................................................................. 95 5.2.1 Animals, housing and management ........................................................................ 96 5.2.2 Automated Activity Monitors ................................................................................. 97 5.2.3 Synchronization Protocol, Artificial Insemination, Ultrasonography, and Pregnancy Diagnosis ............................................................................................................................... 98 5.2.4 Blood Sampling, Analyses of Estradiol and Progesterone Concentrations ............ 99 5.2.5 Statistical Analysis ................................................................................................ 100 5.3 Results ......................................................................................................................... 103 5.3.1 Animals and Number of Events ............................................................................ 103 5.3.2 Intensity of Estrous Expression at AI ................................................................... 103 5.3.3 Pre-ovulatory Follicle Diameter ........................................................................... 104 5.3.4 5.3.4 Concentration of Progesterone and Estradiol .............................................. 104 5.3.5 Pregnancy per AI (P/AI) ....................................................................................... 106 5.4 Discussion .................................................................................................................... 107  xi 5.5 Conclusion ................................................................................................................... 111 6 Chapter 6: General Discussion ......................................................................................... 125 6.1 Thesis findings ............................................................................................................ 125 6.2 Implications and future directions............................................................................ 128 6.3 Strengths and limitations ........................................................................................... 133 6.4 General conclusions.................................................................................................... 134 References .................................................................................................................................. 135        xii List of Tables Table 1.1: Comparison of automated activity monitor parameters during estrus and non-estrus in lactating dairy cows. ................................................................................................................ 9 Table 1.2: Equations used to determine the precision of the automated activity monitors. ......... 11 Table 1.3: Description of the main 6 hormones controlling the estrous cycle with their function and location of synthesis........................................................................................................ 15 Table 2.1: Relative increase in physical activity, ovulation rate, and pregnancy/AI according to BCS, parity and milk production. .......................................................................................... 54 Table 2.2: Means (± SE) for preovulatory follicle diameter at the moment of timed AI and progesterone concentration at d 7 post-AI according to BCS, parity, milk production, progesterone concentration at d 7 post-AI, relative increase and presence of estrus expression. ............................................................................................................................................... 56 Table 3.1: Number of viable embryos, percentage of viable embryos, number of follicles, and number of viable embryos per follicle according to breeding indicator score and automated activity monitor measures of estrous expression. .................................................................. 71 Table 4.1: Descriptive data on Experiment 1 according to Farm A (900 ET events) and Farm B (501 ET events). .................................................................................................................... 86 Table 4.2: Relative increase in activity at the end of the synchronization protocol and pregnancy per embryo transfer (ET) according to parity and milk production and embryo transfer method for Experiment 2, in Holstein cows. ...................................................................................... 88 Table 4.3: Pregnancy per embryo transfer (ET) according to the classification of the intensity of estrous expression detected by an automated activity monitor (AAM) and by the embryo transfer method for Experiment 2, in Holstein cows. ............................................................ 90 Table 4.4: Pregnancy per embryo transfer (ET) at 31 and 60 d post synchronization protocol, according to the stage of embryo transfer and grade quality on Experiment 1, in Holstein cows. ............................................................................................................................................... 91 Table 5.1: Intensity of estrous expression parameters, according to body condition score, parity and milk production. ............................................................................................................ 113 Table 5.2: Concentration of progesterone at AI and at 7 d post-AI, according to body condition score, parity and milk production on both Experiment 1 and Experiment 2. ...................... 115 Table 5.3: Pregnancy per AI, in both, Exp. 1 and Exp. 2 according to the interactions of estrus intensity and body condition score and the interaction of estrus intensity and parity. ........ 116  xiii List of Figures Figure 1.1: A historical summary of milk yield per cow, herd size, and number of dairy cows in the United States. Source: National Milk Producers Federation, 2016; (adapted from: Stevenson and Britt, 2017). ..................................................................................................... 6 Figure 1.2 : Percentage of cows standing to be mounted in Holstein dairy cattle reported on the literature (Hall et al., 1959; Esslemont and Bryant, 1976; Glencross et al., 1981; Stevenson et al., 1983; Fonseca et al., 1983; Hackett and McAllister, 1984; Britt et al., 1986; Pennington et al., 1986; López-Gatius and Camóón-Urgel, 1991; Nebel et al., 1994; Van Vliet and Van Eerdenburg, 1996; LeBlanc et al., 1998; Lyimo et al., 2000; Van Eerdenburg et al., 2002; Roelofs et al., 2005; Walker et al., 2008; Chebel et al., 2010; Denis-Robichaud et al., 2016; LeRoy et al., 2018). ................................................................................................................. 9 Figure 1.3: Sensitivity and positive predictive value (PPV) of the automated activity monitors (AAMs) in dairy cows kept in free-stall system and pasture using a neck mounted sensor and a pedometer............................................................................................................................ 13 Figure 2.1:  Experimental ovulation synchronization protocol as follows: EB (estradiol benzoate - 2 mg, Gonadiol, Zoetis, São Paulo, Brazil), GnRH (gonadorelin diacetate - 100 μg, Cystorelin, Merial, São Paulo, Brazil), PGF (dinoprost tromethamine - 25 mg, Lutalyse, Zoetis, São Paulo, Brazil), ECP (estradiol cypionate - 1 mg, E.C.P., Zoetis, São Paulo, Brazil), CIDR (intravaginal progesterone implant - 1.9 g progesterone; CIDR, Zoetis, São Paulo, Brazil), TAI (timed AI), US (examination of ovaries with ultrasonography), P4 (collection of blood sample for analysis of progesterone concentration). Automated detection of estrus was done with Afimilk Pedometer Plus Tags and AfiFarm software (Afimilk, Kibbutz Afikim, Israel). ............................................................................................................................................... 57 Figure 2.2 Distribution of ovulation rates (%) according to relative increase in activity at the moment of timed AI using an automated activity monitor. a-c Different letters indicate difference between variables within the bars (P < 0.05). ...................................................... 58 Figure 2.3: Distribution of pregnancy per AI (%) of all insemination events according to relative increase in activity at timed AI detected by an automated activity monitor (panel A) and considering only cows that had an ovulatory follicle (panel B). a-d Different letters indicate difference between variables within the bars (P < 0.05). ...................................................... 59 Figure 2.4: Pregnancy losses (%) according to categories of relative increase in physical activity at timed AI:No Estrus (< 100%), Moderate Intensity (100- 299 % relative increase) and Strong Intensity (≥ 300 % relative increase) as detected by an automated activity monitor (panel A; P = 0.03) and distribution of pregnancy losses (%) according to relative increase in physical activity at timed AI detected by an automated activity monitor (panel B). a-b Different letters indicate difference between variables within the bars (P < 0.05). ......................................... 61 Figure 3.1: The superovulation synchronization protocol used was as follows: an intravaginal progesterone implant of 1.9 g of progesterone previous used for 9 days (CIDR, Zoetis, Sao Paulo, Brazil), a 2.0 mg (i.m.) injection of estradiol benzoate (2.0 mL of RIC-BE®, Agener Uniao, Sao Paulo, Brazil) on pm at d0, on pm d4 a 2.0 mL (i.m.) injection of FSH  xiv (Folltropin®, Vetoquinol, X, Brazil), on am d5 and pm a 2.0 mL and 1.5 mL (i.m.; respectively) injection of FSH, on am d6 and pm a 1.5 mL and 1.0 mL (i.m.; respectively) injection of FSH and also 25 mg (i.m.) injection of dinoprost tromethamine (PGF; 5.0 mL ofLutalyse®, Zoetis, São Paulo, Brazil) at pm d6, on am d7 and pm a 1.0 mL and 0.5 mL (i.m.; respectively) injection of FSH and a PGF injection on am d7, on am d8 the last injection of FSH 0.5 mL (i.m.), cidr removal and estrus detection, on am d9 a 4 mg (i.m.) injection of Gonadorelin (GnRH; 4 mL ofFertagyl, MSD Animal Health, São Paulo, Brasil), a 1st AI at pm d9 and 2 nd AI at am d10, and on d16 oocyte-embryo collection. .................................. 70 Figure 4.1: Pregnancy per embryo transfer (ET) according to parity (primiparous and multiparous) and the intensity of estrous expression (No Estrus, Low Intensity and High Intensity). High Intensity – 41.6 ± 2.1 [68/166] vs. 36.5 ±  2.8 [151/407]; P = 0.37; Low Intensity - 13.6 ± 2.3 [9/68] vs. 24.1 ± 3.2 [72/286]; P = 0.03 and No Estrus - 6.3 ± 1.6 [4/52] vs. 5.1 ± 1.9 [6/168]; P = 0.41; for primiparous and multiparous, respectively. There was an interaction between parity and the intensity of estrous expression on pregnancy per ET (P < 0.01). ................... 92 Figure 4.2: Pregnancy per embryo transfer (ET) according to the stage of embryo development and the occurrence of estrus (Estrus) or not (No estrus). Pregnancy was performed at 31 and 60 d post end of the timed AI. ............................................................................................... 93 Figure 5.1: Schematic of the experimental design for Experiment 1 (Exp. 1; panel A) and Experiment 2 (Exp. 2; panel B). EB (estradiol benzoate; 2 mg, Gonadiol, Zoetis, São Paulo, Brazil), GnRH (gonadorelin diacetate; 100 μg, Cystorelin, Merial, São Paulo, Brazil), CIDR (intravaginal progesterone implant; 1.9 g progesterone; CIDR, Zoetis, São Paulo, Brazil), PGF (dinoprost tromethamine; 25 mg, Lutalyse, Zoetis, São Paulo, Brazil), ECP (estradiol cypionate; 1 mg, E.C.P., Zoetis, São Paulo, Brazil), Timed AI (artificial insemination), AI (artificial insemination, followed by spontaneous estrus using the am/pm rule; Exp. 2 only),US (examination of ovaries with ultrasonography), P4 (collection of blood sample for analysis of progesterone concentration), E2 (collection of blood sample of analysis of estradiol concentrations). Automated detection of estrus was done using a leg-mounted pedometer in Exp. 1 (Afimilk Pedometer Plus Tags; Afimilk, Kibbutz Afikim, Israel) and a neck-mounted accelerometer in Exp. 2 (Heatime®, SCR Engineers, Israel).............................................. 118 Figure 5.2: Distribution of increased estrous expression intensity (panel A) and duration (panel B) detected by a neck-mounted accelerometer at estrus and its association with the concentrations of progesterone and estradiol. .............................................................................................. 119 Figure 5.3: Proportion of cows displaying greater and lesser estrous expression according to the concentration of P4 at -4 d (Experiment 1, Panel A; P < 0.01), and the concentration of P4 at 0 d (Experiment 1 and Experiment 2, Panel B; P < 0.01). .................................................. 121 Figure 5.4: Concentrations of progesterone on the day of estrus alert (0 d; P < 0.01) and 7 d (P < 0.05), 14 d (P < 0.01), and 21 d (P < 0.01) post-AI relative to estrous expression intensity in Experiment 2. High intensity: estrous expression greater or equal to the median (80.5 index) of the automated activity monitor. Low intensity: estrous expression less than the median. ............................................................................................................................................. 123  xv Figure 5.5: Pregnancy per artificial insemination (%) according to the concentration of progesterone (P4) on days 7,14 and 21 post-AI (P = 0.10). Concentration of progesterone (P4) was classified as greater and lower concentration according to the median as follow: 7d post-AI = ≤ 2.65 and > 2.65 ng/mL; 14d post-AI = ≤ 3.12 and > 3.12 ng/mL; and 21d post-AI = ≤ 6.27ng/mL and > 6.27ng/mL).............................................................................................. 124                 xvi List of Abbreviations AAM – Automated activity monitor AI – Artificial insemination  BCS - Body condition score  CL – Corpus luteum DIM – Days in milk E2 - estradiol ECP – Estradiol-cypionate EM – Embryo mortality  ER – Estrogen receptor ET – Embryo Transfer FSH- Follicle-stimulating hormone  GnRH – Gonadotropin-releasing hormone  LH- Luteinizing hormone NPV – Negative Predictive Value P4 – Progesterone  PPV – Positive Predictive Value PGF2 - Prostaglandin F2 TMR – Total mixed ration VMH - Ventromedial nucleus    xvii Acknowledgements To my friend and advisor Ronaldo Cerri for giving me the opportunity to be part of his research group, supporting me and encouraging me during my graduate studies. To José Luis Moraes Vasconcelos (Zequinha) for all his advice, opportunities and friendship throughout the years. Always being a great example, as a person and as a researcher. I would also like to thank my supervisory committee members, Dan Weary and Ky Pohler, for helping throughout my PhD process. A special thanks to Doug Veira, Audrey Nadalin, Dan Weary and Nina von Keyserlingk for all their guidance and expertise during these years, all who inspired me and helped me to see things with different points of view. I would like to thank the farm staff of UBC Dairy Centre, especially for Nelson Dinn, Barry Thompson, Brad Duncan, Ted Toenders, Bill Kramer and Mary Ann and all the farmers that have passed through the Centre at some point over the years – they were very important in making for the amazing times that I have had in Agassiz.  To my mom and to my brother, for their support throughout my PhD, for everything that they made so that I could be where I am, always giving me support and encouragement.  To the Animal Welfare and the Repro Team members, both new and old. To Ruanito Daros, Janet Bauer, Heather Neave, Jane Stojkov, João Costa, and Hanna Eriksson for the amazing times together at Blue House, for our hours of discussions about different topics and different points of view, I learnt a lot with you. Particularly I want to thank Tracy Burnett for her support over the years (many years), both as a friend and colleague.  Thank you everyone that has helped me along through this process, I could never have done it without your motivation and encouragement.   1   1 Chapter 1: Introduction Annual total milk production has increased over the past decades. Canadian dairy herds were estimated to have a total of 1.4 million cows, producing 7.2 billion kg of milk annually in 1990. In contrast, in 2018, the dairy herd population in Canadian was estimated to total only 950 thousand cows, with an annual milk production of 9.3 billion kg (CDIC, 2020), where the number of animals per herd was shown to increase by 54.2 % (CDIC, 2020). This trend is reflected globally where the total annual milk per cow increased from 7717 kg to 9677 kg between 1991 and 2005 (LeBlanc, 2010). In the United States, the total number of cows decreased almost 36 %, from 1944 to 2007, with the total annual milk production increasing from 53.0 billion kg to 84.2 billion kg (Capper et al., 2009). If this trend is to continue, North America is predicted to maintain current production with 11.1% fewer animals by 2050 (Santos et al., 2010a). Increased individual milk production has been achieved in part due to improvements in management as well as intensive genetic selection (Lucy, 2001). However, this increase in milk production has also been shown to be associated with reduced reproductive performance (Nebel and McGilliard, 1993; Lucy, 2001; Butler, 2003). Dobson et al. (2008) reported that the intense genetic selection for high milk production has resulted in reduced fertility, primarily due to higher incidences of postpartum clinical problems, defective oocytes and embryos, uterine infections and poor expression of estrus.  Multiple reports have demonstrated embryonic mortality (EM) during the first third of gestation (Dalton et al., 2001; Sartori et al., 2002) can play a major role in reproductive inefficiency. Late embryonic mortality has been reported to range from 3.2 to 42.7 % (Cartmill et al., 2001b; a; Humblot, 2001), and can cause serious economic losses due to often being diagnosed  2   too late to re-inseminate the animal and maintain a timely calving interval. A cause for embryonic loss may be related with compromised placental function issues (Aires et al., 2014). Placental insufficiency is a potential cause of late EM since most of the pregnancy loss occurs around the time of placentation (days 25 to 40). Therefore, identification of a biomarker of placental function in the maternal circulation may be useful in predicting late EM.  Standing to be mounted has been considered the gold standard for visual detection of estrus, but the frequency of standing behaviour (Lopez et al., 2004; Roelofs et al., 2005) as well as the proportion of cows that display estrus (Dobson et al., 2008) has decreased over time. This trend has been particularly noted in high-producing dairy cows (Lopez et al., 2004; Rivera et al., 2010). Detection of estrus is the first step in getting a cow pregnant and is crucial for a successful reproductive program (Stevenson, 2001), thus the potential impacts of high milk production may be directly linked to the efficiency of reproductive management. However, the interpretation made from observed associations between greater milk yield and poor reproductive performance may require critical evaluation, as it is has been shown to be a complex relationship including many factors that can affect fertility (Santos et al., 2009). Additionally, LeBlanc (2010) suggests that inappropriate management practices of high producing dairy cows may be a significant contributor to the inability of dairy cows to conceive and maintain pregnancy, regardless the milk yield.  Dairy production depends on regular calving (Lucy et al., 1986). Ideal calving intervals are achieved with efficient detection of estrus, breeding and maintenance of pregnancy (Lucy et al., 1986; Ratnayake et al., 1998). At the animal level, milk production is strongly correlated to the dry matter intake (DMI) and energy intake, which is in-turn related to the metabolism of hormones important for reproduction, through increased blood flow through the portal vein and liver  3   (Wieghart et al., 1986; Parr et al., 1993; Sangsritavong et al., 2002). Progesterone (P4) and estradiol (E2) are mainly metabolized in the liver, thus with increased liver blood flow the metabolism of these steroid hormones is likely to increase (Sangsritavong et al., 2002; Vasconcelos et al., 2003). Reducing circulating concentration of P4 and E2 may generate lower duration and intensity estrous expression (Lopez et al., 2004; Rivera et al., 2010; Roelofs et al., 2010).  Problems in the transition period may also affect the intensity of estrus expression. After calving, cows go into a negative energy balance (NEB), and this has negative effects on fertility through altering metabolic and endocrine profiles in the liver, ovary, and uterus (Wathes et al., 2007). Cows that experience an intense NEB (lower insulin, glucose and IGF-I) have reduced LH pulse frequency, which may decrease the synthesis of E2 by the preovulatory follicle (Butler, 2003), impacting on the estrous cycle and sexual behaviour (Woelders et al., 2014). Not all studies have reported this same correlation between circulating E2 and milk production (van Eerdenburg, 2008; Madureira et al., 2015); some suggest that milk production may be actually be a function of health and thus related to high fertility in lactating dairy cows (López-Gatius et al., 2006; Santos et al., 2009; LeBlanc, 2010). Estrus detection has been greatly impaired due to shorter duration and lower intensity of estrous expression in high-producing lactating dairy cows (Lopez et al., 2004), increased herd sizes (Saint-Dizier and Chastant-Maillard, 2012), and housing conditions (Diskin and Sreenan, 2000). The need for more efficient and reliable technologies for estrus detection has led to the development of automated activity monitors (AAMs). Jónsson et al. (2011) suggests that the efficiency of technologies can be increased by focussing on secondary signs of estrus, such as walking behaviour, instead of relying on mounting behaviour. Increased physical activity is  4   considered a secondary feature of estrous expression in dairy cattle but has been used by AAMs to reliably identify cows in estrus (Roelofs et al., 2010). The technologies currently used on dairy farms vary in which feature of physical activity they measure (e.g. walking, lying, eating) as well as in the location on the animal and technology used (e.g. accelerometers, pedometers, neck-mounted, leg mounted, ear tags). Nevertheless, recent studies using activity monitors have shown estrus detection rates between 75 % and 90% (Dolecheck et al., 2015; Roelofs and Van Erp-Van Der Kooij, 2015), demonstrating the benefit of these technologies. In this review, I will first discuss the use of precision dairy farming, with specific emphasis on the use of AAM for the detection of estrus. Secondly, I will describe the basic physiology of the estrus cycle as well as fertilization and early embryonic development. I will then discuss the factors that affect estrus detection and the expression of estrus behaviour. Finally, I will conclude with a discussion on how automated activity monitors can improve estrus detection and improve reproductive management in dairy herds. Throughout this review I will note any relevant gaps in the literature. 1.1 Precision Dairy Farming  1.1.1  Technology to improve dairy management As dairy herd size has increased, (Figure 1.1; Schulze et al., 2007; Barkema et al., 2015; Stevenson and Britt, 2017) it has become more difficult for producers to provide attention at an individual level. Due these changes in the dynamic of herds size and production per animal, as well as the growing concern about animal welfare, has resulted in the dairy industry becoming a leader in the adoption of precision technology (Bewley, 2010).   5   Wathes et al. (2008) described precision livestock farming as “the management of livestock production using the principles and technology of process engineering.” Precision dairy farming (PDF) includes the use of wearable technologies that provide data on physiological, behavioural, and production-based measures that may allow for improvements in management and farm profitability (Boehlje and Schiek, 1998; Van Asseldonk et al., 1999). These sensors have the potential to detect diseases earlier and identify animals in estrus. Van Asseldonk et al. (1999) used the term “information technology”, defined as the “diverse class of applications which include all the hardware and software used by farmers to capture data, to transform data into information to help in decision making, to establish communication of data/information, internally as well as externally, and to perform production tasks.” There are many different PDF technologies to monitor cows. With the diverse technology on the market, and the enormous amount of information that these sensors can generate, producers are able to make decisions on almost a real-time basis. Sensor data will only be valuable if transformed into information that is useful for decision making (Spilke and Fahr, 2003).        6   Figure 1.1: A historical summary of milk yield per cow, herd size, and number of dairy cows in the United States. Source: National Milk Producers Federation, 2016; (adapted from: Stevenson and Britt, 2017).   1.1.2 Technology Available in the Dairy Industry There are a variety of sensors to monitor individual animals, their status relative to their herd mates, herd-level technologies and sensors used for better dairy farm management (El-Osta and Morehart, 2000). Sensors that are available to dairy producers include, daily milk yield recording, milk component monitoring (fat, protein, SCC, conductivity, P4), pedometers and accelerometers (health monitoring, estrus detection, lying behaviour and resting time), temperature devices, feeding behaviour, rumination, rumen pH, reticular contractions, and heart and respiratory rates.  When an animal exhibits the symptoms of clinical illness (change in body temperature and heart rate, for example) it is often is too late to intervene. Technologies that monitor physiological  7   parameters may give an opportunity for producers to carry out early interventions. These monitors can add information to current visual observation methods and may help identify the problems, improving the way some decisions are made by producers. Dairy consumers have become progressively concerned with food safety and quality as well as animal health and welfare (Berckmans, 2006); consumers want to know where the product they are consuming come from and how they are produced. The adoption of precision dairy monitoring can improve or maintain health on dairy herds and may help improve public perception. The increase in adoption of technologies is suggested to demonstrate that producers, and the dairy industry, are willing to develop strategies that help improve animal well-being (Laca, 2009). Because sensors can monitor individual animals, they have the potential to reduce the impact of livestock on environment, further improving public perception towards dairy industry.  1.2 Automated Activity Monitors  1.2.1 Estrus Detection Estrus detection, based on estrous behaviour, is used extensively to time breeding (Caraviello et al., 2006; Ferguson and Skidmore, 2013; Denis-Robichaud et al., 2016). In cattle, the primary sign of estrus is standing to be mounted (Williamson et al., 1972; Hurnik et al., 1975; Lyimo et al., 2000; Roelofs et al., 2010). However, there is evidence to show that this behaviour has changed over time (Figure 1.2) such that visual observation of this behaviour may be less practical. Pennington et al. (1986) reported that for a visual detection to be better than a pedometer it has to be carried out at least 4 to 6 times per day. In response to increasing difficulties in detecting estrus, various technological advances have been made to improve the ability to detect estrus (Firk et al., 2002). Among these technologies are automated activity monitors (AAMs) which rely on  8   the characteristic increase in physical activity observed in animals during estrus (Jónsson et al., 2011). The increase in activity associated with estrous expression was first observed in rats in 1923 (Wang, 1923), and in dairy cattle in 1954 (Farris, 1954). There are a number of different types of AAMs available for use in dairy cows including pedometers which attach to the leg and measure the number of steps as well as quantify lying and standing behaviours, and accelerometers which measure movements of cow’s head and neck during walking activities. Kiddy (1977) evaluated variation in physical activity of lactating cows using pedometers originally designed for humans and reported that during estrus the increase in steps was four times greater when compared with the non-estrual period, concluding that activity monitoring may be a useful tool for estrus detection. In a recent study, Dolecheck et al. (2015) reported changes in activity and lying time at estrus and in the non-estrual period (Table 1.1).  To define the increase in activity associated with estrus, the AAMs use a baseline (defined from a reference period) from each individual cow to detect a meaningful deviation from its own physical activity (Roelofs et al., 2005; Yániz et al., 2006). These baselines are defined differently by each manufacture, but generally account for the circadian pattern (i.e. that cow activity varies over the course of the day). The thresholds used for these AAMs also differ by company and device, and generally the algorithms used to define an estrus alert are proprietary.    9      Table 1.1: Comparison of automated activity monitor parameters during estrus and non-estrus in lactating dairy cows. Variable Monitor Estrus Non - Estrus     Activity HR tag activity neck (index/2h) 61.6 ± 2.0 28.2 ± 0.8  Iceqube number of steps (per h) 300.8 ± 10.9 79.1 ± 4.1  Cow Manager SensOor ear activity (min/h) 17.4 ± 0.7 4.3 ± 0.4 01020304050607080901001950 1960 1970 1980 1990 2000 2010 2020Standing to be mounted (%)YearsFigure 1.2 : Percentage of cows standing to be mounted in Holstein dairy cattle reported on the literature (Hall et al., 1959; Esslemont and Bryant, 1976; Glencross et al., 1981; Stevenson et al., 1983; Fonseca et al., 1983; Hackett and McAllister, 1984; Britt et al., 1986; Pennington et al., 1986; López-Gatius and Camóón-Urgel, 1991; Nebel et al., 1994; Van Vliet and Van Eerdenburg, 1996; LeBlanc et al., 1998; Lyimo et al., 2000; Van Eerdenburg et al., 2002; Roelofs et al., 2005; Walker et al., 2008; Chebel et al., 2010; Denis-Robichaud et al., 2016; LeRoy et al., 2018).  10       Lying time Iceqube lying times (min/h) 10.2 ± 2.0 24.8 ± 1.0  Track a cow lying time (min/h) 6.6 ± 2.6 18.2 ± 2.0 Source: adapted from Dolecheck et al. (2015). 1.2.2 Diagnostics  To determine the precision of sensors, common metrics used are positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity. These tests need to be carried out by comparing the detection of the monitor with a gold standard, which in this case is usually human detection via visual observation, ultrasonography, etc. Correctly identified estrus events, known as true positives, occur when the events occur and there is a correct alert from the AAMs. Non-alerted non-estrus events, a true negative, when the event does not occur and an alert is not generated from the AAMs (Hogeveen et al., 2010). False positive alerts are when there is an alert from the sensor, but the animal is not in estrus. Similarly, when an alert is not generated by the AAMs when the cow was in estrus, this is called a false negative (Firk et al., 2002). PPV is the proportion of true alerts divided by the total false and true positive alerts and, NPV is the proportion of true negative alerts divided by the total false and true negative alerts, as shown in Table 1.2. True events have a positive relationship with peak activity and duration of estrus (Aungier et al., 2012), while false positive events have been shown to have a shorter duration and intensity when compared to true estrus alerts (Burnett et al., 2018). Firk et al. (2002) suggested that the use of more than one measure obtained by AAMs to create an alert could help reduce false positives. A  11   false positive alert can cause economic losses, as cows may be inseminated although they are not truly in estrus. Sturman et al. (2000) reported that an insemination of a pregnant cow led to approximately 17% of induced embryonic death or abortion. However, false negative alerts may represent a bigger economic problem as cows that are not detected will remain un-bred until the next cycle, approximately 21 days later.  Estrus detection using AAM requires a balance of sensitivity and specificity. Sensitivity is the probability that a positive alert is a true indicator of estrus while specificity is the probability of an animal that is not in estrus not being alerted (Sherlock et al., 2008; Hogeveen et al., 2010), as shown in Table 1.2. A study performed by Roelofs et al. (2005) reported that the sensitivity of AAMs vary according to the thresholds used, where in general, more restrictive thresholds will decrease the number of false positives (thus increasing specificity) but increase the number of false negatives (thus decreasing sensitivity). Another measurement commonly used to measure the performance of sensors is accuracy, which considers both the sensitivity and specificity of the monitor (Table 1.2). Table 1.2: Equations used to determine the precision of the automated activity monitors.  Precision Equations Sensitivity TP1/(TP + FN) × 100    Specificity TN2/(TN + FP3) × 100    12   Accuracy [(TP + TN)/(TP + TN + FP + FN4) × 100]   Positive Predictive Value TP/(TP+FP) x 100   Negative Predictive Value TN/(TN+FN) x 100 1True Positive (TP) – alerted estrus events; 2True Negative (TN) – non-alerted non-estrus events; 3False Positive (FP) – alerted non-estrus events; 4False Negative (FN) – non-alerted estrus event.  Numerous studies have been conducted to evaluate the efficiency and reliability of AAMs to identify animals in estrus. The percentage of animals detected using AAMs varies between 51 and 90% both in the confinement and pasture-based systems (Lewis and Newman, 1984; Redden et al., 1993; Roelofs et al., 2005; Hockey et al., 2010; Kamphuis et al., 2012; Valenza et al., 2012; Aungier et al., 2014; Dolecheck et al., 2015). Generally, the estrus detection of AAMs are approximately 80%, depending on the threshold and reference period for each individuals baseline used (Saint-Dizier and Chastant-Maillard, 2012). Løvendahl and Chagunda (2010) reported that the use of AAMs had a 74.6% estrus detection rate with a 1.3% daily error rate, demonstrating an advantage over the use of visual observations which has been reported to have detection rates of roughly 50% (Denis-Robichaud et al., 2016; LeRoy et al., 2018). A combination of studies, shown in Figure 3, have shown sensitivity and PPV of varying monitors for cows kept in free-stall or pasture systems. A study conducted by Hockey et al. (2010) reported that the sensitivity of AAMs for detecting ovulatory periods ranged from 79.4 - 94.1%, while specificity ranged 90.0 - 98.2% and positive predictive value ranged from 35.8-75.8%. However, Roelofs and Van Erp-Van Der Kooij (2015) reported a wide range in sensitivity from 36-78%, which was higher than the  13   sensitivity of visual observations that ranged from 20-59%. These results show that AAMs are able to detect a great proportion of cows in estrus or near ovulation and have the potential to increase the reproductive efficiency of dairy farms.  Figure 1.3: Sensitivity and positive predictive value (PPV) of the automated activity monitors (AAMs) in dairy cows kept in free-stall system and pasture using a neck mounted sensor and a pedometer.   1.3 Fundamentals of Estrous Cycle  In mammals, estrus behaviour indicates that animals are sexually receptive to a mate (Forde et al., 2011). This behaviour starts occurring once the animals has reached puberty and is considered as a strategy to mate closer to the time of ovulation (Roelofs et al., 2010). The word estrus comes from the Greek word “oistros”, meaning Hornfly. It was originally believed that when 0 20 40 60 80 100Talukder et al. 2015Chanvallon et al. 2014Chanvallon et al. 2014Michaelis et al. 2014Kamphuis et al. 2012Aungier et al. 2012Holman et al. 2011Holman et al. 2011Jonsson et al. 2011Hockey et al. 2010Pasture SystemFree-stall System 14   cows were in estrus they had flies around them, causing the cows to show restless behaviour (Short, 1984). Estrous behaviour occurs due to a specific influence of ovarian steroid hormones in behavioural centers of the mammalian hypothalamus (Frandson et al., 2006). The hypothalamus is composed of nuclei where specific centers, such as the Ventromedial Nucleus and Medial Preoptic Area, are involved in female sexual behaviour (MPA; Simerly, 1998). There are neurons in these nuclei that respond to pheromones as well as sensory information, and also express E2 receptors, which increase their response to this hormone during estrus (Simerly, 1998).  1.3.1 Physiology of the estrous cycle The estrous cycle in bovines is the interval between two estrus phases, and is normally around 18 to 24 days in length (Forde et al., 2011) starting at 6 – 12 months of age. The estrous cycle consists of a luteal phase of 14 to 18 days (metaestrus and diestrus) of duration, during these phases the development of the corpus luteum (CL) occurs, followed by a follicular phase of 4 to 6 days (proestrus and estrus) where the final maturation and ovulation of the pre-ovulatory follicle occurs. Estradiol and P4 are the main hormones associated with estrus behaviour (Woelders et al., 2014), but there are 6 hormones in total that control the estrous cycle (Table 1.3).     15   Table 1.3: Description of the main 6 hormones controlling the estrous cycle with their function and location of synthesis. Hormone  Function  Synthesis Location   1. Estradiol (E2) Estrous behaviour and part of the cascade of ovulation  Theca interna of the ovarian follicle     2. Progesterone (P4) Acts together with E2 in promoting estrous behaviour and preparing the reproductive tract for implantation (early embryonic development and preparation of the endometrium for implantation and maintenance of pregnancy).     Corpus luteum and placenta    3. Gonadotropin-releasing Hormone (GnRH) Stimulates preovulatory surge of Luteinizing Hormone (LH) and stimulates tonic release of Follicle Simulating Hormone (FSH) and LH.    Hypothalamus   16    4. Luteinizing Hormone (LH)  Stimulates ovulation and luteinization of ovarian follicles to form the corpus luteum.          Anterior Pituitary Gland    5. Follicle Stimulating Hormone                    (FSH) Responsible for growth and maturation of the ovarian follicle (Graafian follicle).                                           Does not cause secretion of estrogen from the ovary by itself; instead, it needs the presence of LH to stimulate estrogen production.    Anterior Pituitary Gland    6. Prostaglandin (PGF)    Regression of the corpus luteum (luteolysis). Uterine contraction assisting in sperm transport and parturition.                                                                 Can be secreted by almost all body tissues, mainly produced by the endometrium of the uterus.     17   The increase in FSH, which promotes the growth and proliferation of follicular cells, starts two or three waves of follicular growth per estrous cycle (Adams et al., 1992; Sunderland et al., 1994). Each wave consists of the emergence of a group of follicles, with selection, dominance, and ovulation of the dominant follicle (Forde et al., 2011). Only a few follicles continue to grow, while the others suffer atresia. Generally, when the largest follicle reaches a diameter of 4 to 7 mm (Ginther et al., 1996), follicular deviation occurs, characterizing the selection of the dominant follicle. While the dominant follicle continues to develop, FSH induces the activation of other growth factors, increasing the concentration of IGF-1 available for cell growth and E2 synthesis (Rivera and Fortune, 2003). Estradiol is synthesized after LH binds to its receptor in the theca cell of the follicular membrane, where androgens will be synthesized from cholesterol and aromatase (aromatase enzyme P450arom, CYP19) and finally converted to E2 within the granulosa cells (Forde et al., 2011). The concentration of E2 in the follicular fluid of the dominant follicle is twice as high when compared with a subordinate follicle of the same diameter (Mihm et al., 2002). Unlike the smaller follicles, which regress, the dominant follicle may function independently of FSH due to the presence of LH receptors, which develop on granulosa cells, becoming responsive to LH (Xu et al., 1995). Ovulation occurs around 30 hours (Roelofs et al., 2005) after the onset of estrous behaviour, when E2 promotes positive feedback on the hypothalamus and anterior pituitary, stimulating the release of GnRH and LH and the maturation and ovulation of the dominant follicle (Roche, 1996). After ovulation, LH intercedes in the formation of the corpus luteum (CL) from the theca and the granulosa cells of the pre-ovulatory follicle (Forde et al., 2011).  18   Progesterone is secreted by the luteal cells of the CL and is fundamental for early embryonic development (Silva and Knight, 2000; Bisinotto et al., 2010b) and maintenance of pregnancy (Atkins et al., 2013). The high concentration of P4 during the luteal phase prevents the occurrence of frequent pulses of LH that would result in ovulation of a dominant follicle (Hatler et al., 2003). Dominant follicles that develop during this period enter atresia (Forde et al., 2011). If maternal recognition is not signaled, which occurs around the 16th day of the cycle, luteolysis will occur due to several PGF2α pulses released by a non-pregnant uterus (Niswender et al., 2000; Schams and Berisha, 2004).  Luteolysis of the CL occurs via the exchange of PGF2α in a countercurrent system between the uterine vein to the ovarian artery (Forde et al., 2011). There is great variability in the frequency and amplitude of PGF2α pulses associated with luteolysis in ruminants. At the beginning of proestrus a series of hormonal events and changes in the cells of the endometrium results in the release of pulses of PGF2α by the uterus. Usually 4-8 pulses occur at intervals of 6-14 hours (Silvia et al., 1991; Mann and Lamming, 2006). Mann and Lamming (2006) reported that there was complete luteolysis, in heifers, after fourth pulses of PGF2α in a period of approximately 30 hours. The mechanisms regulating the beginning of PGF2α release in ruminants involves changes in the expression of receptors in the endometrium for E2, P4 and oxytocin (Silvia et al., 1991). During the early phase of luteolysis, the expression of oxytocin and E2 receptors is suppressed due to the presence of P4 receptors in the uterus (Ivell et al., 2000). The decrease of P4 receptors in the late luteal phase results in an increase of E2 receptors in the uterus (Meyer et al., 1988), which stimulate the synthesis of endometrial oxytocin receptors, with subsequent oxytocin-induced secretion of PGF2α pulses from the uterus (Silvia et al., 1991). A natural luteolysis cascade (in the  19   absence of maternal recognition) normally occurs in the presence of a dominant follicle (Araujo et al., 2009) due to the activation of the estrogen receptor in the uterus by E2 secreted by the follicle.  The discovery of the luteolytic activity of PGF2α in ruminants (Baird et al., 1976) has allowed the commercial use of PGF2α as an inducer of CL regression (Lauderdale, 2009). Most estrus-ovulation synchronization protocols include at least one treatment with PGF2α for the regression of the CL. Studies have shown that CLs respond differently to PGF2α depending on their stage of development (Wiltbank et al., 1995; Mondal et al., 2011; Diaz et al., 2013).  Lauderdale (2009) reported that a dose of PGF2α was only effective when administered at least 6 days after estrus (Lauderdale, 2009). Administration of double doses of PGF2α in cows with a 5-day CL did not cause complete luteolysis (Santos et al., 2010b; Ribeiro et al., 2012), although it lead to a dramatic decrease in the concentration of P4, even in CLs at early stages (Nascimento et al., 2014). The absence of complete regression of a CL during the proestrus period has often been reported (Souza et al., 2007; Santos et al., 2010b; Giordano et al., 2013). In these studies, cows with a small P4 elevation close to AI, due to the absence of complete CL regression, had decreased fertility. In addition, studies conducted with cows that were inseminated after detection of estrus showed that even with small amounts of P4 AI fertility was impaired (De Silva et al., 1981; Waldmann et al., 2001; Ghanem et al., 2006, but see also Erb et al., 1976; Forshell et al., 1991). 1.4 Importance of Progesterone pre-AI, at AI and post-AI 1.4.1 Concentration of Progesterone pre-AI Progesterone concentration during diestrus may be associated with the occurrence of estrus and the intensity of estrous expression, as P4 primes the hypothalamus, making it  more responsive  20   to E2 and, thus the occurrence of estrous expression (Woelders et al., 2014).  Progesterone regulates the length of the estrous cycle, and should be greatest during diestrus, lower at proestrus, least at estrus and increasing slowly after ovulation occurs. Pereira et al. (2016) showed that cows that did not express estrus at the end of timed AI protocol were more likely to have higher concentrations of P4 compared with cows that expressed estrus. Higher concentrations of P4 at the moment of AI have been associated with lower fertility. It is known that P4 at estrus is required to be low, but there is limited research on how this hormone modulates the intensity of estrous expression.  1.4.2 Concentration of Progesterone at AI Proestrus is the phase where the regression of the CL begins and is characterized by an increase in E2 and decrease in P4. A number of studies have evaluated the timing of the regression of the CL until the moment of artificial insemination and its impacts on fertility in dairy cattle (Peters and Pursley, 2003; Ribeiro et al., 2012; Martins et al., 2017). Inadequate luteolysis can cause elevated concentrations of P4 close to the timing of AI, which may result in lower fertility (De Silva et al., 1981; Waldmann et al., 2001; Ghanem et al., 2006; Colazo et al., 2017). This problem has been reported in timed AI protocols (Souza et al., 2007; Brusveen et al., 2009; Pereira et al., 2013; Colazo et al., 2017) as well on spontaneous estrus detected by visual observation (De Silva et al., 1981; Waldmann et al., 2001; Ghanem et al., 2006).  A physiological mechanism that may reduce fertility when P4 is elevated at AI is that P4 may alter oocyte transport by altering uterine or oviductal contractility, thus reducing fertilization (Hunter, 2005). Another hypothesis to explain lower fertility is that the P4 could have an impact on embryo quality and development. When P4 was added to an in vitro fertilization protocol, it  21   reduced the blastocyst percentage, suggesting that P4 may have an effect on early embryonic development (Silva and Knight, 2000). A recent study that evaluated embryos from cows that had follicles grow during low or high concentrations of P4 did not find a difference on embryo quality (Cerri et al., 2011b). Reduced endometrial thickness with slight elevations in P4 (Silva and Knight, 2000) may suggest the effect of P4 on the uterus could result in reduced embryo development as well. Lower concentrations of P4 after AI may reduce embryonic development and survival rate (Mann and Lamming, 2001). Cerri et al. (2011a) indicated that cows with low P4 had increased basal LH concentrations, altering follicular dynamics that could in turn alter oocyte quality. In addition, concentrations of P4 at AI could alter gamete transport; a study in rats demonstrated that the facilitation of sperm migration into the oviduct is negatively affected by P4 (Orihuela et al., 1999).  1.4.3 Concentration of Progesterone Post-AI The concentration of P4 post-AI has an effect on fertility in lactating dairy cows (Lamming and Darwash, 1998; Lima et al., 2009; Pereira et al., 2014) and is a requirement for pregnancy maintenance (Inskeep, 2004). The positive effect on fertility may be due to the elongation of the conceptus (Garrett et al., 1988), early embryonic development (Bisinotto et al., 2010b), and increased secretion of interferon-tau (Mann and Lamming, 2001). Mann et al. (2006) observed that the insertion of an intravaginal P4 device between day 5 and 9 of the cycle caused an increase in embryo length 16 days after AI. However, P4 supplementation between days 12 and 16 post-AI did not increase the length of the embryo. A study by Herlihy et al. (2012) showed that lower  22   concentrations of P4 during diestrus was associated with lower fertility, as only a few cows with low P4 concentrations (< 2.00 ng/mL) at 11 days post-AI became pregnant (5.8%).  The diameter of the pre-ovulatory follicle during the estrus cycle may also be a factor that interferes with the concentration of P4 after AI, as follicles with larger diameters will generate larger CLs, which may result in higher endogenous production of P4 (Vasconcelos et al., 2001; Mussard et al., 2007; Cerri et al., 2009b; Pereira et al., 2014). However, other studies have not observed this positive relationship, since there was no difference in the concentration of P4 post-ovulation, even with differences in follicular diameter and the formation of CLs with larger diameters (Cerri et al., 2011a; b). Demetrio et al. (2007) observed that cows that were bred by embryo transfer were not influenced by the levels of P4 concentration, probably because the embryo is already developed when it is placed in the recipients.   Progesterone can block the estrus-inducing actions of E2 and plays an important role in priming the bovine brain for E2 functions. In dairy cows, the first postpartum ovulation normally occurs with low expression of estrus behaviour. Higher concentrations of E2 during late gestation can induce a refractory state early post-partum that will not respond to the action of the E2. Increased estrous expression in timed AI protocols that include P4 suggest that P4 may act as a primer for the responsiveness of the hypothalamus to E2 (Rhodes et al., 2002). As previously mentioned, there has been plenty of research showing the effect of P4 at AI and post-AI on fertility. However, the literature regarding the effect of circulating P4 prior to AI, at AI and post-AI on the intensity of estrous expression in cattle is limited. This topic was investigated within Chapter 5 of this thesis.  23    1.5 Insemination, Fertilization and Early Embryonic Development 1.5.1 Insemination and Fertilization After proestrus, the concentration of P4 decreases and the concentrations of E2 increases, as the cow comes into estrus. During this time the cow is ready to be inseminated, either by natural mating or AI resulting from either a timed AI program or spontaneous estrus. Inseminating cows at the correct time is important for an efficient reproductive program (Walker et al., 1996). Insemination too early reduces conception rates, which result from loss of sperm viability (30 - 48 hours) and the number of sperm at the site of fertilization, whereas loss of ovum viability (20 – 24 hours) can result from insemination after ovulation. Artificial insemination is recommended within 12-16 hours after the onset of estrus, as this has been shown to result in better conception rates (Dalton et al., 2001; Stevenson et al., 2014). After insemination, the spermatozoa take 6-8 hours to reach the oviduct (Saacke et al., 2000), and by approximately 12-24 hours few spermatozoa remain in the reproductive tract (Hawk, 1987). Spermatozoa can be lost from the female reproductive tract by retrograde transport and many are phagocytized by leukocytes (Hawk, 1987). Once the spermatozoa reach the oviduct, they undergo capacitation, which are the changes that occur to the spermatozoa that make them capable of fertilizing the oocyte (Saacke et al., 2000). Providing time for sperm capacitation is very important for the optimal timing of AI. Following insemination, viable spermatozoa must: transverse the cervix (in this case only for natural mating), be transported through the uterus to the oviduct, undergo capacitation, bind to the oocyte, undergo the acrosome reaction to penetrate the zona pellucida and fuse with the oocyte plasma membrane.  24   After fusion with the plasma membrane, the fertilizing spermatozoa enters the oocyte cytoplasm and its nucleus decondenses. This signifies successful fertilization.  1.5.2 Early Embryonic Development  Following fertilization (fusion of male and female pro nuclei), the zygote undergoes a series of mitotic divisions called cleavage divisions, forming blastomeres. After undergoing genome activation, the zygote develops into a morula by day 4 of development. After compaction, the morula enters the uterus by day 5 of development, where the outer cells of the morula develop into the trophectoderm, whereas the inner cells form the blastocyst. This process is the first embryonic cell differentiation. Other groups of cells will develop into the primary germ layers of the embryo (ectoderm, mesoderm, and endoderm). Differentiation of these specific groups of cell layers (trophoblast, the outside cell layer, and embryoblast) will contribute to the formation of the placenta and the embryo. Blastocyst formation is generally initiated shortly after entry into the uterus. The blastocyst then hatches from the zona pellucida on days 8 to 9, exposing the conceptus to the uterine environment. On day 13 post fertilization the blastocyst starts the elongation phase (hyperplasia of the trophoblast), where it transforms from a 3 mm spherical shape (day 13) to a 25 cm filamentous conceptus (day 17). By day 18 of gestation, the blastocyst has extended to the uterine horn and by day19 the fully elongated conceptus begins implantation and attachment of the trophectoderm to endometrial luminal epithelium.  25   1.5.3 Factors that Affect Fertilization Embryonic death (from fertilization until 42 days post-AI) or fetal death (more than 42 days after fertilization until parturition) reduce fertility and profitability in dairy herds. In addition, lactating cows are more susceptible to reproductive failures when comparted to non-lactating cows or heifers (Lucy, 2001; Sartori et al., 2002; Inskeep, 2004). However, fertilization failures only partly explain the low reproductive rates of lactating cows. Fertilization rates have been shown to be similar in lactating dairy cows (76.2%) or non-lactating (78.1%; Santos et al., 2004). Other studies have indicated that lactating dairy cows have approximately 83% of fertilization rates followed by a timed AI program (Sartori et al., 2002; Cerri et al., 2009a; b) and slightly higher (87.7%) in animals bred at the end of timed AI program where estrus occurred (Sartori et al., 2002; Cerri et al., 2009a).  But by 25-49 days of pregnancy the average conception rates is below 45% in dairy cows submitted to timed AI (Chebel et al., 2006; Pereira et al., 2014) or inseminated after visual observation of spontaneous estrus (Santos et al., 2004), showing embryonic death to be a major obstacle. Average calving rates of about 45% indicate an embryonic or a fetal mortality rate of about 35-40%. Out of these total losses, approximately 20% occur between days 8 and 16 post-AI, a further 10% between days 16 and 42 and a further 5-8% between day 42 and parturition (Diskin and Sreenan, 1980; Maurer and Chenault, 1983; Dunne et al., 2000). A study by Diskin and Sreenan (1980) reported that the rate of embryonic loss is very low due to gamete transportation and fertilization. Early pregnancy are influenced by ovarian steroid hormones (P4 and E2) and changes on its concentrations may affect oocyte quality and embryo viability (King et al., 1994). Mihm et al. (1994) reported a reduction in fertility on animals that had longer dominance of the ovulatory follicle exposed to low concentration of circulating P4.  26   Cerri et al. (2009) reported that embryo quality was compromised even when dominance of the ovulatory follicle was only extended by 1.5 days. Reduced fertility in cattle after ovulation of prolonged follicle dominance could be caused by increasing E2 secretion over an extended period. This may change intrafollicular, oviductal and uterine environments, causing early embryonic death (Leroy et al., 2008). Intrafollicular changes during prolonged growth possibly disrupts the oocyte in the persistent follicle and, after ovulation, may reduce the capability of fertilization or interrupt early embryonic development. Another possible explanation is that lower concentrations of P4 allow for increased pulse frequency of LH (Roberson et al., 1989), leading to ovulation of premature oocytes (Mattheij et al., 1994; Revah and Butler, 1996).  1.6 Implantation and maternal recognition of pregnancy  After hatching, the blastocyst is free-floating in the lumen of the uterus and is totally dependent on the uterine environment for survival. This allows for contact between the conceptus and the maternal uterine epithelium, which is essential for nutrient exchange and placental attachment. The elongated conceptus must cover a large portion of the maternal endometrium so it can regulate the release of prostaglandins to prevent luteolysis. Timing of implantation or placental attachment may be regulated by the length of time the uterine endometrium is exposed to P4. Progesterone concentrations increase around 24 hours after ovulation when the corpus luteum is forming (Dieleman et al., 1986). Over 8 to 10 days of exposure to P4, P4 receptors in the uterine epithelium down-regulate leading to a loss of the direct effect of P4 on this type of cell.  One crucial point for the maintainance of pregnancy is maternal recognition of pregnancy, occuring around the 16th day after AI, mediated by the action of interferon-tau (IFN-τ). Interferon-tau is produced by the trophoblastic cells of the blastocyst and acts on the endometrial cells of the  27   uterus to inhibit the production of oxytocin receptors such that oxytocin cannot stimulate prostaglandin synthesis, thus inhibiting luteolysis (Thatcher et al., 1994; Antoniazzi et al., 2013). In addition, IFN-τ causes production of proteins critical for embryonic survival pre-implantation, such as bovine trophoblastic protein 1 and bovine pregnancy associated glycoproteins (PAGs), from the uterine glands.  Bovine pregnancy associated glycoproteins are secreted by the ruminant placenta (Telugu et al., 2009) into the maternal circulation starting about day 24 of gestation and have been used to diagnose pregnancy in cattle (Zoli et al., 1992; Green et al., 2005). Pohler et al. (2016) identified that at day 31 circulating concentrations of PAGs below 1.4 ng/mL was 95% accurate in predicting pregnancy loss between day 31 and 59 of gestation in lactating dairy cows. Pregnancy-associated glycoproteins have the potential to be the first reliable hormonal pregnancy test for cattle and may serve as biomarker of placental function (Pohler et al., 2013).  1.7 Factors associated with reduced estrous expression in dairy cattle There are a number of factors that are associated with the expression of estrus (Britt et al., 1986; Lopez et al., 2004; Wiltbank et al., 2006; Palmer et al., 2012; Madureira et al., 2015). Milk production has been shown to be negatively correlated with the duration of estrus (Sangsritavong et al., 2002; Lopez et al., 2004; Wiltbank et al., 2006). Lopez et al. (2004) reported that the intensity of estrus was lower in high production cows. In the same study, lactating Holstein cows were divided into two groups based on milk production; mean duration and standing time of estrus in high yielding cows (6.2 ± 0.5 hours; 46.4 ± 0.4 kg/d) were shorter compared to low yielding cows (10.9 ± 0.7 hours; 33.5 ± 0.3 kg/d).  28   To meet the energy requirements of lactation, cows will often experience a negative energy balance (NEB) post-partum as the energy needs for milk production are higher than the available energy consumed through feed intake (Nebel and McGilliard, 1993).  Endocrine changes, such as decreased insulin and insulin-like growth factor (IGF-I), during this period have been reported (McGuire et al., 1992; Grummer et al., 2004). Insulin stimulates the synthesis and excretion of GnRH (Butler and Smith, 1989), thus changes in hormone profiles during this period may have negative effects on estrus through the suppression of pulsatile LH secretion, estrogen, and P4 (Butler and Smith, 1989; Spicer et al., 1991; Wathes et al., 2007), providing a potential explanation for the decrease in the duration and intensity of estrus. As mentioned earlier, lactating dairy cows have a higher metabolism of steroid hormones which is likely related to greater metabolic rate in cows with high milk production and high feed intake (Sangsritavong et al., 2002; Vasconcelos et al., 2003). As a result, these animals may experience a decrease in circulating concentrations of E2 and P4, which could generate lower expression and lower intensity of estrus (Lopez et al., 2004; Rivera et al., 2010; Roelofs et al., 2010). However, some studies (van Eerdenburg, 2008; Madureira et al., 2015) have reported no correlation between estrogen expression and milk production, showing that milk production may be related to high fertility in lactating dairy cows (López-Gatius et al., 2006; Santos et al., 2009; LeBlanc, 2010).  Some authors have reported that the duration of estrus is shorter in heifers and lactating primiparous cows compared with lactating multiparous cows (De Silva et al., 1981; Walker et al., 1996), but others have found no an association between parity and physical activity at estrus (Arney et al., 1994; Løvendahl and Chagunda, 2010). López-Gatius et al. (2005) found parity to be highly associated with increased physical activity at estrus, and reported that for each additional  29   lactation, physical activity was reduced by 21.4%. Other studies using different measures to detect cows in estrus (e.g. neck movements and mounting devices) have shown that as parity increases behaviours at estrus decrease (Peralta et al., 2005, Reith et al., 2014). Compared to nulliparous heifers, lactating cows have lower concentrations of circulating steroid hormones (Sartori et al., 2004a) which may explain the lower intensity of estrous expression. Methodological differences may also explain variation among different studies on the association between parity and estrous expression. Sensors have different algorithms and thresholds to create an alert for changes in physical activity, and these calibrations could influence the measurement of what is considered baseline and the relative increase in activity, such that there the same behaviour could be interpreted differently depending on the sensor that is being used. Another factor that may explain differences within studies is cattle breed. Orihuela et al. (2000) highlighted the importance of breed on the level of physical activity expressed at estrus, and these effects may be extrapolated to include parity.  Factors such as season, temperature and humidity have been shown to influence estrus behaviour in dairy cows (Wolff and Monty, 1974; Nebel et al., 1997; Orihuela, 2000; López-Gatius et al., 2005; Yániz et al., 2006; Sakatani et al., 2012). López-Gatius et al. (2005) reported lower increases in walking activity at estrus during the summer compared with the fall and spring. Only 19% of estrus episodes were detected by farm personnel in the summer in a study carried out in Florida (Thatcher and Collier, 1986). Yániz et al. (2006) found that an increase in humidity was associated with a decrease in walking activity during estrus. Increases in environmental temperature reduces the expression of mounting behaviours (Gwazdauskas et al., 1990). Heat stress has an effect on the period of dominance and follicle selection. The preovulatory luteinizing  30   hormone (LH) surge as well as E2 and inhibin are reduced in cows under heat stress (Gilad et al., 1993; Armengol-Gelonch et al., 2017). Additionally, an increase in number of large follicles on the ovary and prolonged ovulatory follicle dominance have been observed (Wilson et al., 1998; Roth et al., 2000). Together, these changes in dominance and hormone concentrations may also impact the intensity and duration of estrus episodes.   1.7.1 Social Interactions Social rank can influence the timing of estrous (Hurnik et al., 1975; Chicoteau et al., 1989; Van Vliet and Van Eerdenburg, 1996). Social (including agonistic) interactions are mainly affected by stocking density (Huzzey et al., 2006; Proudfoot et al., 2009). Social dominance may affect the duration and expression of estrus (Chicoteau et al., 1989; Galina et al., 1996). Some studies have shown an interaction between body weight and mounting behaviour (Allrich, 1993), where heavier animals (thought to be dominant),inhibited the mounting behaviour of smaller animals. The number of dominant animals expressing estrous behaviour may impact the total number of animals in estrus at any time within a group (Castellanos et al., 1997). However, other studies failed to find a correlation between dominance and mounting behaviour (Orihuela and Galina, 1997). The number of cows in estrus at the same time can also affect the expression of estrus behaviours (Hurnik et al., 1975; Helmer and Britt, 1985; Van Vliet and Van Eerdenburg, 1996; Roelofs et al., 2005). Van Vliet and Van Eerdenburg (1996) reported that when only one cow was in estrus, mounting activity and duration were reduced compared with when 2 or more cows were in estrus. Diskin and Sreenan (2000) reported that increasing stocking density increased the  31   number of cows interacting sexually; however, this also reduced signs of estrus signs as there was not sufficient space within the pen.   1.7.2 Management According to Diskin and Sreenan (2000), approximately 10% of the factors affecting low estrus detection rates can be attributed to cow-level factors and approximately 90% can be attributed to management. Concrete surfaces have been reported to decrease the frequency of mounting behaviours and the duration of estrous expression compared with dirt surfaces (Britt et al., 1986; Vailes and Britt, 1990). Slippery flooring may inhibit the expression of estrus. Palmer et al. (2010) reported that a number of cows slipped or fell when attempting to mount others. These authors also found that estrous expression was reduced in housed conditions (estrus detection rate - 52%) compared to cows on pasture (estrus detection rate - 91%), independent of the method used to detect estrus. Additionally, incidence of lameness was higher in housed cows compared to pastured cows which may also lead to a reduction in the intensity of estrus behaviour (Palmer et al., 2010). Lameness prevalence has been shown to be higher in barns with concrete floors (Zaffino Heyerhoff et al., 2014; Solano et al., 2015). Lameness is a painful condition and can be associated with reduced estrus intensity in dairy cows (Walker et al., 2008). Lameness may also have a negative impact on reproductive hormones from the hypothalamus-pituitary-ovarian axis (Dobson et al., 2003). Walker et al. (2008) reported that cows that were chronically lame had a lower intensity of estrous expression when exposed to a low P4 concentration before estrus.    32   1.8 Impact of estrous expression on fertility  Estrous expression and intensity have been positively associated with fertility. Increased estrous expression, based on a visual scoring system, has been associated with pregnancy in lactating dairy cows (Van Eerdenburg et al., 2002). Similarly, Reimers et al. (1985) reported that standing to be mounted and “riding other animals” were associated with 51.3% and 49.2% higher conception rates, respectively. Recent studies using AAMs has shown increased physical activity during estrus is associated with better fertility (López-Gatius et al., 2005; Madureira et al., 2015; Polsky et al., 2017). However, some studies have not found an association between fertility and strength of estrus as detected by AAMs (Yániz et al., 2006; Aungier et al., 2012). The differences among studies could be associated with diverse methodologies and calibration of AAMs. For instance, in a study by Yániz et al. (2006), the authors reported the average increase in physical activity for multiple alerts of estrus rather than considering the physical activity of a specific event (i.e. when the AI occurs). A recent study, that used two different AAM and evaluated fertility at spontaneous estrus, found that pregnancy per AI varied between 37.4% and 23.9% for animals with higher and lower intensity of estrus at the time of breeding, respectively (Madureira et al., 2015). Pereira et al. (2016) reported that animals that express estrus at the moment of AI had higher pregnancy per AI at timed AI (38.9% vs. 25.5%) and embryo transfer (ET; 46.7% vs. 32.7%) when compared to animals that did not express estrus. In the same study, gestational loss was also lower for animals that expressed estrus at timed AI (14.4% vs. 20.1%) and ET (18.6% versus 22.7%).  Synchronization protocols have been used as an alternative breeding strategy to achieve reproductive goals, and have been shown to increase pregnancy rates without depending on estrus  33   detection (Pursley et al., 1995). However, recent studies have not only reported the impact of estrous expression on fertility of spontaneous estrus events but also the occurrence of estrus at the end of timed AI and embryo transfer protocols. This question is particularly relevant for protocols using estrogens to induce ovulation as the majority of the cows will express estrus prior to AI (Cerri et al., 2004; Galvão et al., 2004; Pereira et al., 2015) as opposed to protocols using a GnRH (Stevenson and Phatak, 2005). A recent study by Pereira et al. (2016) reported that cows that express estrus at the moment of timed AI and embryo transfer, detected by tail chalk, had greater fertility and lower pregnancy losses when compared to cows that did not express estrus. Similarly, Hillegass et al. (2008), using a timed AI protocol with or without estradiol cypionate (ECP), showed that independent of the protocol used, cows that expressed estrous behaviour had an increase in fertility but no differences in gestational losses were found. Although the occurrence of estrus at the time of insemination has been shown to be beneficial with these types of protocols, there is a lack of research pertaining how the intensity of estrous expression may impact pregnancy outcomes at timed AI or the success of embryo transfer protocols.  The literature regarding the effects of the intensity of estrus expression on reproductive outcomes is limited. This topic was investigated within Chapter 2 and 4 of this thesis. However, there are a few factors that may help us understand this relationship. In cattle, P4 and E2 are the main hormones that control the estrous cycle and induce the behaviour of estrus. A positive relationship between the concentration of E2 and the intensity of estrus behaviour has been shown in several studies (Britt et al., 1986; Lyimo et al., 2000; Lopez et al., 2004). However, when comparing E2 concentrations at estrus with estrous expression measured using an AAM no relationship between estrous expression and E2 concentration was found (Madureira et al., 2015).  34   Estrus behaviour is induced once E2 concentrations reach a set threshold. The minimum concentration of circulating E2, and the duration of exposure to E2, necessary to trigger estrus are not known. Allrich (1994) reported that ovariectomized cows expressed estrus behaviour at similar levels with injections of different concentrations of E2. In a similar study, Reames et al. (2011), using various dosages of E2, reported individual cows differed in the amount of E2 needed to induce estrus. In the same study, the authors reported that all cows had a preovulatory surge of LH, but the magnitude of LH surge was less for lower doses of E2. The authors concluded that the hypothalamic centers responsible for regulating the expression of estrus and secretion of LH responded differently to E2. Estradiol has been reported to increase the responses of the granulosa cells to gonadotropins to synthesize estrogen, enhancing the ability of granulosa cells to respond to FSH and LH (Welsh et al., 1983). Thus, estrogens are important for granulosa cell differentiation and essential for the maintenance of the corpus luteum.  There is evidence that increased concentrations of E2 at the time of estrus may have a positive effect on fertility (Buhi, 2002; Jinks et al., 2013). Buhi (2002) reported that increased E2 concentration is associated with specific oviductal glycoproteins that increase capacitation and overall viability of sperm. A study by Jinks et al. (2013) reported that cows that had higher concentrations of E2 at estrus had a higher number of fertilized embryos, greater concentrations of P4 post-AI and greater conception rates than cows with lower E2 concentrations.  Progesterone is associated with estrous expression, embryonic development and fertility of dairy cattle. Decreased concentrations of P4 prior to estrus (diestrus) were associated with lower fertility (Bisinotto et al., 2010b). This relationship may be associated with follicular growth, and oocyte and embryo quality. Animals with follicles growing under high P4 concentrations have  35   been associated with high conception rate (Bisinotto et al., 2010b). Similarly, Rivera et al. (2011) reported that animals having higher concentrations of P4 during diestrus were more likely to have viable embryos. Additionally, P4 concentration in diestrus may be associated with estrous expression and intensity, as P4 primes the hypothalamus, making it more responsive to E2 and the occurrence of estrous expression (Woelders et al., 2014). As previous discussed, at the time of estrus, low concentrations of P4 are associated with greater fertility (Pereira et al., 2016) and are necessary for estrous expression. Negative impacts of P4 at estrus are believed to be associated with altered uterine or oviductal contractility impeding sperm and oocyte transport (Hunter, 2005). Pereira et al. (2016) showed that cows that did not express estrus at the end of timed AI protocol were more likely to have had higher concentration of P4 at estrus compared to cows that expressed estrus. It is known that P4 at estrus should be low; however, there is limited research on how this hormone modulates the intensity of estrous expression.   1.9 Thesis Objective  The overall objectives of this thesis were to determine if estrous expression, detected by AAM can be used within an ovulation synchronization program for timed artificial insemination (AI) and embryo transfer (ET), and to determine the relationship between estrous expression, ovulation rates, viability and quality of embryo, progesterone and estradiol concentrations, and fertility and pregnancy loss. The specific objectives of my thesis were: 1) investigate the association between the intensity of estrous expression, captured by an AAM, and outcomes  36   related to fertility such as ovulation rate, pregnancy per AI, and pregnancy loss, and concentration of progesterone 7 d after AI; 2) to evaluate the effect of the intensity of estrous expression on the viability of in vivo produced embryos in Holstein heifers; 3) to evaluate the occurrence and intensity of estrous expression detected by tail chalk or by an AAM on the fertility of recipient lactating dairy cows bred by ET; 4) to determine the association between the concentrations of P4 at different moments of the estrous cycle, the intensity of spontaneous or estrogen-induced estrous expression (detected by AAM), and pregnancy/AI.  I hypothesized that cows displaying more intense estrus would have increased pregnancy per AI, decreased pregnancy loss and ovulation failures, and greater progesterone concentration after AI (Chapter 2). In addition, heifers that displayed greater estrous expression would yield a greater number of embryos, of which, a greater proportion would be viable and freezable (Chapter 3). Additionally, I hypothesized that cows expressing estrus, receiving an embryo in a more advanced stage or greater quality and those with greater estrous expression intensity would have greater pregnancy per ET and reduced pregnancy loss (Chapter 4) and that greater concentrations of P4 at different moments of the diestrus coupled with lower concentrations of P4 at AI will be associated with greater estrous expression and improved pregnancy/AI in lactating dairy cows.     37   2 Chapter 2: Intensity of estrus following an estradiol-progesterone based ovulation synchronization protocol influences fertility outcomes 1 2.1 Introduction Detection of estrus is crucial for a successful reproductive program (Stevenson, 2001). Historically, standing to be mounted has been the gold standard for visual detection of estrus, but the frequency of standing behaviour (Lopez et al., 2004) as well as the proportion of cows that display estrus (Dobson et al., 2008) have decreased over the decades. This trend has been particularly noted in high-producing dairy cows (Lopez et al., 2004; Rivera et al., 2010). Increased physical activity is considered a secondary feature of estrous expression in dairy cattle but has been used by automated activity monitors (AAM) to reliably identify cows in estrus (Roelofs et al., 2010). Increases in physical activity have been associated with improvement in pregnancy per artificial insemination (AI) of dairy cows (Madureira et al., 2015; Polsky et al., 2017; Burnett et al., 2018). The intensity of estrous expression, as well as fertility, is impacted by body condition scores (BCS), parity, stage of lactation and health (Madureira et al., 2015; Burnett et al., 2017; Silper et al., 2017). Nonetheless, even when accounting for such factors, estrous detection and expression has consistently impacted pregnancy per AI (López-Gatius et al., 2005; Pereira et al.,  1 A version of this chapter has been accepted for publication: Madureira, A.M.L., L.B. Polsky, T.A. Burnett, B.F. Silper, S. Soriano, A.F. Sica, K.G. Pohler, J.L.M. Vasconcelos and R.L.A. Cerri. 2019. Intensity of estrus following an estradiol-progesterone-based ovulation synchronization protocol influences fertility outcome. J. Dairy Sci. 102(4):3598-3608. DOI: 10.3168/jds.2018-15129.  38   2016). Synchronization of ovulation protocols have been used as an alternative to achieve successful reproductive goals as they are able to increase pregnancy rates by improving submission rates to AI without depending on estrus detection (Pursley et al., 1995; Chebel et al., 2010). Recent studies have compared different combinations of timed AI protocols and estrus detection using AAM (Neves et al., 2012; Burnett et al., 2017; Denis-Robichaud et al., 2018a) and results suggested that in North American herds it is possible to maintain comparable reproductive efficiency between estrus detection-based reproductive programs and those that rely heavily on timed AI. Some recent studies have also reported the impact of estrous expression on fertility focused on spontaneous estrus events but did not test for the impact of estrous expression from timed AI protocols. This question is particularly important in protocols using estrogens to induce ovulation because the majority of the cows express estrus prior to AI (Cerri et al., 2004; Pereira et al., 2015) as opposed to protocols using a GnRH analog (Stevenson and Phatak, 2005). The occurrence of estrus at AI, using tail chalk and tail head patch, in a timed AI protocol was associated with reduction in pregnancy loss in dairy cows (Pereira et al., 2016). Furthermore, (Pereira et al., 2016) reported that the reduction in pregnancy loss in cows that expressed estrus at AI occurred regardless of the diameter of the pre-ovulatory follicle. Davoodi et al. (2016) reported that the occurrence of estrus at AI in beef cattle induced changes in gene expression in the endometrium and conceptus that are associated with pre-implantation success. It is unclear, however, if the intensity of estrus, and not only the expression of it, after such synchronization protocols also alters fertility outcomes as observed in spontaneous estrus events.  This study aimed at evaluating the association between the intensity of estrous expression, captured by an AAM, and outcomes related to fertility such as ovulation rate, pregnancy per AI,  39   and pregnancy loss, and concentration of progesterone 7 d after AI. Moreover, it was our objective to determine if BCS, parity, milk production and ovarian structures were associated with intensity of estrus and fertility. We hypothesized that cows displaying more intense estrus would have increased pregnancy per AI, decreased pregnancy loss and ovulation failures, and greater progesterone concentration after AI.   2.2 Materials and methods  This experiment was conducted at a commercial farm in São Paulo state, Brazil (latitude: 22°21’25” S; longitude: 47°23’03” W). The University of British Columbia’s Animal Care protocol related with the current study was A14-0290. The practices outlined in the Guide for the Care and Use of Agricultural Animals in Agricultural Research and Teaching (FASS, 1999) was also used for the approval of all experimental procedures as part of the local requirements.  2.2.1 Animals, Housing and Management Lactating Holstein cows (n = 1,040) were enrolled into the study during the first week post-partum with the placement of an AAM to the back limb of the animal. The experimental herd had an average 305-d mature equivalent milk yield of 11,438 kg/cow with an average of approximately 1,700 lactating dairy Holstein cows. This experiment was an observational cohort study. Cows were housed in a cross-ventilated free-stall barn in groups of 300 animals. The barn had grooved concrete floors and two rows of deep sand-bedded stalls. Milking was performed three times daily (at approximately 0500, 1300,  40   and 2100 h). Cows were fed a TMR thrice daily. The TMR was formulated to meet or exceed the requirements of a lactating Holstein cow producing 40 kg/day of 3.5% fat corrected milk (NRC, 2001). Water and TMR were available for ad libitum intake.  2.2.2 Automated Activity Monitor Cows were monitored continuously by one AAM, a leg-mounted pedometer (AfiPedometer Plus Tag; AfiMilk®, Israel). The pedometer sensor was attached to the right back limb above the distal expansion of the metacarpal bone of each cow on the day of their first calving and remained on the animals throughout their entire time within the herd.  The activity data (steps/h) were recorded in 2-h increments and were retrieved three times daily (every 8 h) by an electronic scanner at the entrance of the milking parlor. Using the data from the AAM, relative increase (RI) in walking activity was calculated by determining the change in activity on d-1 and d 0, relative to timed AI, in comparison to a baseline calculated specifically for each cow. The following formula was used: [(steps/h at estrus – steps/h at baseline) / steps/h at baseline] * 100]. The steps/h at estrus were defined as the greatest steps/h from the 8 h-session with the greatest number of steps among all sessions on d -1 or d 0 relative to timed AI. Baseline steps/h represented the average steps/h from the 7 d prior to AI. Cows were only considered to be in estrus if the RI on d -1 or d 0 exceeded 100%. Only animals that exceeded a RI of 100% were considered as expressing estrus at timed AI, thus not associated with an alert event from the AAM.  41   2.2.3 Synchronization Protocol, Blood Sampling and Analysis of Progesterone During the experimental period, cows were enrolled onto an ovulation synchronization protocol based on progesterone and estradiol for first AI postpartum, then again following a negative pregnancy diagnosis. Timed AI was performed using commercially frozen–thawed semen by the same two trained technicians. The synchronization protocol used was as follows: an intravaginal progesterone implant of 1.9 g of progesterone (CIDR, Zoetis, São Paulo, Brazil), a 2.0 mg (i.m.) injection of estradiol benzoate (EB; 2.0 mL of Gonadiol, Zoetis, São Paulo, Brazil) and a 100 μg (i.m.) injection of gonadorelin diacetate (GnRH; 2.0 mL of Cystorelin, Merial, São Paulo, Brazil) on d −11, on d-4 and d-2 a 25 mg (i.m.) injection of dinoprost tromethamine (PGF; 5.0 mL of Lutalyse, Zoetis, São Paulo, Brazil), on d-2 the CIDR was withdrawn and a 1.0 mg (i.m.) injection of estradiol cypionate (ECP; 0.5 mL of E.C.P., Zoetis, São Paulo, Brazil) was administrated, and timed AI occurred on d 0, as described by Pereira et al. (2015) and detailed in Figure 2.1.  Ovaries of all cows were examined by ultrasonography at d -11 (presence or absence of corpus luteum), and a subset of cows were examined on d 0 (assessment of two largest follicles; n = 588) and on d 7 (presence or absence of a corpus luteum to confirm ovulation; n = 819). Pregnancy diagnosis was carried out via ultrasonography on d 32 and 60 after timed AI and a cows considered pregnant when a viable embryo was found. Pregnancy per AI was calculated by dividing the number of cows that were pregnant on d 32 post-AI by the number of animals enrolled into the timed AI protocol. The pregnancy loss was calculated by dividing the number of animals that lost gestation between d 32 and 60 post-AI by the number of animals pregnant at d 32.  42    The BCS (1 to 5 scale at 0.25 increments; Edmonson et al., 1989) was recorded at timed AI. Milk production was recorded at each milking (AfiLite, Kibbutz Afikim, Israel). Milk production was measured daily between d -11 and d 0 of the experiment and the average daily milk production during this period was used for analysis. All cows examined at d 7 after AI had a blood sample collected, for progesterone analysis, from the coccygeal vein into commercial blood collection tubes (BD Vacutainer Serum Tubes, 10 mL; Becton Dickinson, Franklin Lakes, NJ), and were placed immediately on ice. Samples were then centrifuged at 3,000 × g at 4°C for 30 min for serum collection, and stored at -20°C. Serum progesterone concentrations were analyzed using a chemiluminescent enzyme immunoassay (Immulite 1000; Siemens Medical Solutions Diagnostics, Los Angeles, CA) as previous validated (Martin et al., 2007; Reis et al., 2015). The intra- and inter-assay CV were 5.1 and 5.2 %., respectively.The minimum detectable concentration was 0.1 ng/mL of progesterone.   2.2.4 Statistical Analyses Distributions and normality tests were obtained using the Univariate procedure in the SAS software, version 9.4 (SAS Institute Inc., Cary, NC). Normality was visually assessed and confirmed by the Kolmogorov-Smirnov method. Any variable found to not be normal were either transformed or categorized into class variables. Class variables used for analyses are described below. Parity was divided as cows in first lactation and second lactation or higher (primiparous vs. multiparous). The BCS categories were Low (< 2.75), Moderate (2.75 – 3.00), and High (> 3.25). Lactation stage at timed AI was classified as Early Lactation (≤ 72 DIM), Mid-lactation (73 to 170  43   DIM), and Late Lactation (> 171 DIM). Milk production was classified into quartiles (≤ 37.5 kg/d, 37.6 to 44.7 kg/d, 44.8 to 52.1 kg/d, and > 52.2 kg/d). Physical activity of estrus episodes from the AAM was categorized as No Estrus (< 100% RI), Moderate (100- 299 % RI), and Strong (> 300% RI). The receiver operating characteristic (ROC) analysis using MedCalc version 11.1.0.0 (MedCalc software, Mariakerke, Belgium) was performed to determine the critical value of RI that best predicted pregnancy per AI based on sensitivity and specificity, thus separating Moderate and Strong physical activity. The ROC curve analysis plots the sensitivity against the false positive fraction (1 - specificity) to detect the best combination of sensitivity and specificity for pregnancy per AI. The correlations between physiological measurements (BCS, diameter of pre-ovulatory follicle, serum progesterone concentration, DIM, and milk production) and automated activity measurements (RI in physical activity) were determined by Pearson’s correlation using the Corr procedure of SAS. Relative increase in physical activity was used as a continuous dependent variable assessed with ANOVA using the GLIMMIX procedure with AI event as the experimental unit and cow as a random effect. Parity, BCS, milk production, DIM, dominant follicle diameter and corpus luteum presence at d-11 were used as independent variables. Following the same model, dominant follicle diameter was tested as a continuous dependent variable against the fixed effects of parity, BCS, milk production, DIM, RI in physical activity, and corpus luteum presence at d-11. The pregnancy per AI, pregnancy loss and ovulation failure were binomial dependent variables assessed using the same model. The AI event was again used as the experimental unit and cow as the random effect. Only variables with a P-value < 0.15 were maintained in the final  44   model. Differences with P ≤ 0.05 were considered significant and those between 0.05 > P ≤ 0.10 were designated as a tendency.  2.3 Results 2.3.1 Animals and Number of Events A total of 1,411 timed AI events from 1,040 cows were recorded, resulting in 1.3 ± 0.6 events per animal. Cows were on average 137  93 DIM at the time of data collection. In total, 40.8% and 59.2% of cows enrolled were primiparous and multiparous, respectively. Of the total inseminations performed, 52% were first, 16% second, and 32% were third AI or greater.  2.3.2 Estrous Expression at Timed AI The mean RI at estrus was 328.29  132.08 %. Parity influenced estrous expression, as multiparous cows expressed lower RI at peak of estrus expression preceding the moment of AI (P < 0.01) when compared with primiparous cows (Table 2.1). Body condition score at timed AI tended to affect RI (P = 0.10; Table 2.1), as cows with Lower BCS tended to have lower estrous expression than those with Moderate or High BCS. There was an interaction between parity and BCS (P < 0.04), where multiparous cows with low BCS had lower RI than all other parity and BCS combinations (Multiparous: Low BCS = 263.1  19.7%, Moderate BCS = 316.4  13.7, High BCS = 323.3  12.2; Primiparous: Low BCS = 345.6  24.7, Moderate BCS = 320.7  14.7, High BCS = 326.7  14.1 % RI). Correlation between milk production and RI was weak (r = - 0.09; P < 0.01), however, when milk production at the day of timed AI was divided into quartiles, the quartile with the greatest milk production was associated with lower RI in comparison with all  45   other quartiles (P = 0.003; Table 2.1). Cows that had a corpus luteum at the beginning of the protocol tended to have greater RI at AI (334.5  5.2% vs. 320.8  5.8%; P = 0.07).  2.3.3 Preovulatory Follicle Diameter Preovulatory follicle diameter (mean: 13.4  2.8 mm) had no correlation with RI (r = 0.02; P = 0.61). The diameter of the preovulatory follicle did not differ among estrus events classified as Moderate or Strong RI or those that did not express estrus (P = 0.80). Follicle diameter was associated with BCS (P = 0.03), but not with parity (P = 0.41), milk production (P = 0.49) or expression of estrus (P = 0.26; Table 2.2). Cows with greater concentrations of progesterone at d 7 had larger pre-ovulatory follicles at the time of AI (14.1  0.2 vs. 12.3  0.6 mm; P < 0.001; Table 2.2).  2.3.4 Concentration of Progesterone in Serum Cows with Strong RI at timed AI had greater concentration of progesterone in serum at d 7 post-AI compared with those that expressed Moderate RI or those that did not show estrus (3.59  0.1 vs. 2.70  0. 1 vs. 1.25  0.2; P < 0.001). When the analysis was restricted to include only animals that had an ovulatory follicle, it was also observed that cows with Strong RI at AI had greater concentration of progesterone in serum on d 7 post-AI compared with Moderate RI and those that did not express estrus (3.48  0.1 vs. 3.18  0.1 vs. 2.13  0.2; P < 0.0001). Milk production was not correlated with concentration of progesterone at d 7 (r = - 0.01; P = 0.73).   46   2.3.5 Ovulation Failure The overall incidence of ovulation failure was 14.7% in this study. Cows with Strong RI at timed AI had greater ovulation rates when compared with Moderate RI and cows that did not express estrus (94.9% vs. 88.2% vs. 49.5%, P < 0.001). The distribution of ovulation rate according to RI in physical activity at timed AI is shown in Figure 2.2. Cows with a corpus luteum present at the beginning of the protocol had greater ovulation rates than those that did not have a corpus luteum (96.6% vs. 88.8%; P < 0.01). Ovulation rates were also increased with larger pre-ovulatory follicles (above median diameter) when compared with cows that had smaller pre-ovulatory follicles at timed AI (98.0 % vs. 87.4 %; P < 0.01).   2.3.6 Factors Impacting Pregnancy per AI and Pregnancy Loss Pregnancy per AI was influenced by estrous expression, parity, BCS, presence of a corpus luteum at the beginning of the timed AI protocol, and concentration of progesterone at d 7 post-AI, but not by milk production. Cows that expressed Strong RI had greater pregnancy per AI compared with those with Moderate RI or those that did not express estrus at timed AI (35.1 vs. 27.3 vs. 6.2 %; P < 0.01). When considering only cows that had an ovulatory follicle, cows that expressed Strong RI still had greater pregnancy per AI compared with those with Moderate RI and those that did not express estrus (45.1 vs. 34.8 vs. 5.5 %, P < 0.001). The distribution of pregnancy per AI according to RI at timed AI is shown on Figure 2.3. Furthermore, estrous expression also impacted pregnancy loss. Cows that did not express estrus or had Moderate RI at the moment of timed AI had greater pregnancy loss when compared with animals that had Strong RI (19.2 vs.  47   21.7 vs. 13.9%, P = 0.04). The distribution of pregnancy losses according to RI at timed AI is summarized in Figure 2.4. Parity and BCS were associated with pregnancy per AI. Multiparous cows had reduced pregnancy per AI compared with primiparous cows (28.8% vs. 38.9%; P < 0.01) and cows with High and Moderate BCS had greater pregnancy per AI than cows with Low BCS (38.8 % vs. 32.9 % vs. 22.4 %; P = 0.003). Cows bearing a corpus luteum at the beginning of the protocol (d-11) tended to have greater pregnancy per AI than those that did not (32.0 % vs 27.8%; P = 0.09). Cows with greater concentrations of progesterone at d 7 post-AI had greater pregnancy per AI compared with cows that had lower concentrations (> 3.0 ng/mL = 42.6% vs. ≥ 1.0 and ≤ 3.0 ng/mL = 37.2% vs. < 1.0 ng/mL = 19.6%; P < 0.01). Milk production had no effect on pregnancy per AI (P = 0.37).  2.4 Discussion   The goal of our study was to evaluate whether the expression of estrus, detected by AAM, at the moment of timed AI would impact pregnancy per AI, pregnancy loss and parameters of ovarian function associated with fertility. Cows categorized as Strong RI physical activity at timed AI had greater pregnancy per AI and decreased pregnancy loss compared with those cows expressing Moderate RI and those that did not express estrus at timed AI. This pattern remained the same when only cows that successfully ovulated after timed AI were included in the analysis. Estrous expression at the moment of timed AI could potentially be used as a reproduction strategy tool that adds predictive information about a specific breeding and assists in decision making  48   strategies at the farm level. Future studies might include the use of such information in breeding programs of greater risk or value, such as the use of sex-biased semen and embryo transfer.  The use of timed AI in this study allowed for the evaluation of potential mechanisms that may be producing estrus-induced differences in fertility that have previously been reported with spontaneous estrus events (Madureira et al., 2015; Polsky et al., 2017; Silper et al., 2017). We expected that 1) cows displaying estrus at the moment of AI would have greater pregnancy per AI than those that did not display estrus (Pereira et al., 2016), and 2) cows displaying a Strong RI in physical activity at timed AI would also have greater fertility (Madureira et al., 2015; Burnett et al., 2017; Polsky et al., 2017; Silper et al., 2017). Specifically, previous studies from our laboratory already demonstrated the significant impact of Strong RI of estrus on fertility, but those studies used mostly spontaneous estrus events. The limitation of using spontaneous estrus events to study possible mechanisms affecting fertility is the lack of control over the ovarian cycle preceding the estrus event, which could potentially impact subsequent estrous expression (Denis-Robichaud et al., 2018b). In agreement with the present study, (Pereira et al., 2016) reported that the display of estrus behaviour at timed AI was associated with a reduction in pregnancy loss, but the variation in intensity of estrous expression was not explored. To the best of our knowledge, this is the first report describing the impact of the intensity of estrous expression following a timed AI protocol on the ability of dairy cattle to sustain pregnancy, as opposed to using only spontaneous estrus events. The timed AI protocol aimed at synchronizing a follicular wave and corpus luteum function, producing an optimal endocrine environment with a pre-ovulatory follicle and synchronization of ovulation (Wiltbank et al., 2011). It has been suggested that timed AI can potentially improve fertility by modulating the pre-ovulatory follicle and oocyte quality (Cerri et  49   al., 2009b) as well as the uterine environment (Cerri et al., 2011a). This could have implications on how estrous behaviour intensity affects fertility compared with what has been observed in spontaneous estrus events.  The high concentrations and long exposure to estradiol during proestrus and estrus result in the expression of estrogen-dependent glycoproteins from the oviduct which have been implicated in changes in sperm transport, the uterine environment, and oocyte fertilization (Buhi, 2002). There is evidence that the circulating concentration of estradiol has a positive correlation with intensity of behavioural estrus, assessed by standing to be mounted behaviour (Lopez et al., 2004). Plasma concentration of estradiol, however, has been reported to be not correlated (Aungier et al., 2015) or weakly correlated (Madureira et al., 2015; Silper et al., 2015) with walking activity detected by AAM. Reames et al. (2011) evaluated the relationship between infused estradiol, the occurrence of behavioural estrus and the LH surge in ovariectomized cows. The authors reported that with low doses of estradiol infusions some cows did not display estrus, but still had an LH surge, suggesting that the center responsible for estrous behaviour might have a different center activation threshold of circulating estradiol compared with the center responsible for the LH surge. Thus, cows that ovulated but did not express estrus may have achieved the threshold of circulating concentrations of estradiol that are needed to induce the GnRH surge and subsequently the LH surge, but insufficient to induce estrous behaviours. In this study cows that displayed estrus, induced by estradiol cypionate, indeed had significantly better fertility than those that did not show estrus. This result agrees with a previous study (42.6% vs. 21.1%; Cerri et al., 2004) using a different ovulation synchronization (Heatsynch), but that also used estradiol cypionate to induce  50   ovulation. Reasons for this large difference was tightly correlated with ovulation rates, which are much lower for cows that did not display estrus.  In spite of the clear differences in fertility and ovarian function expected between cows that displayed estrus compared with those that did not, it was unclear if the same tendency would be observed in cows displaying different intensity of estrus (Strong RI vs. Moderate RI) in estradiol cypionate induced events. The pre-ovulatory follicle diameter was not correlated with RI and did not differ between estrus events classified as having Strong or Moderate RI in physical activity. Concentrations of estradiol-17β produced by the pre-ovulatory follicle and preceding diestrus’ concentrations of progesterone are involved in triggering the expression of estrous behaviour (Allrich, 1994; Forde et al., 2011; Reames et al., 2011). Some studies have shown that there is no correlation between pre-ovulatory follicle diameter and plasma estradiol in lactating dairy cattle (Sartori et al., 2004a; Madureira et al., 2015). Although estradiol concentration at onset of estrus has been observed to be approximately 1 pg/mL greater in cows expressing high intensity estrus (Madureira et al., 2015), correlation between estradiol concentration in serum and estrus activity levels are surprisingly weak (Aungier et al., 2015). Progesterone concentration in serum was not measured at the beginning of the timed AI protocol in this experiment, but cows that had a corpus luteum at the start of the timed AI protocol were more likely to have a high intensity estrus at the moment of AI and also more likely to ovulate. In addition, concentrations of progesterone 7 d after AI were greater in cows displaying Strong RI estrus at AI than those that displayed estrus of lower intensity. Collectively, the results from the ovarian function suggests that progesterone is a key modulator that led to estrous expression of higher intensity and greater fertility. Increases in progesterone concentration post-AI have been reported to sustain embryo and fetal development  51   (Bisinotto et al., 2010b), which may be caused by the changes in the progesterone receptor profile within the endometrium (Lonergan, 2011). This relationship could have contributed to the increase in pregnancy per AI and reduction in pregnancy loss found in cows with Strong RI in this study. Along with the same rationale of progesterone as the main driver for Strong RI estrus events and greater fertility, the concentration of progesterone at AI, which was not evaluated in this study, could be another possible factor associating estrous expression and fertility. Increases in circulating progesterone concentration at AI has been related with inadequate luteolysis and reductions in fertility in dairy cattle (Wiltbank et al., 2012). Souza et al. (2007) reported that progesterone concentration 48 h after PGF2α treatment above 0.5 ng/mL reduced pregnancy per AI by 50% (Souza et al., 2007). Similarly, Pereira et al. (2015) used the same synchronization protocol as the current study and found that concentrations of progesterone near AI above 0.1 ng/mL resulted in decreased in fertility (≤ 0.09 ng/mL = 34.1% vs. ≥ 0.1 ng/mL = 20.8%). Progesterone can potentially alter oocyte transport in the oviduct, by impacting contractility (Hunter, 2005), as well as reduce embryo development (Silva et al., 1999), which can lead to decreased fertility.  The differences in ovulation rates between Strong and Moderate RI, although significantly different, are more modest (94.9 vs 88.2%). The differences in ovulation rate found in this study do agree with the findings from Burnett et al. (2018), who used only spontaneous estrus events, and may at least partially explain the fertility outcomes. Nevertheless, when only cows had an ovulatory follicle were analyzed, the same association of Strong RI resulting in higher pregnancy per AI was found. The fact that estradiol cypionate was used to induce ovulation and that concentration of estradiol was likely elevated in both groups, raises the possibility that estrogen receptor might also be key to explain the differences in fertility between Strong and Moderate RI  52   groups found in this study. Cows might have a large individual variation in the ability to express estrogen receptors in the endometrium and in the hypothalamus. Probably some cows or some estrus events are more likely to translate circulating estradiol concentrations into optimal expression of estrus and adequate uterine environment for embryo development. To some extent, the LH surge is another possible factor to explain the results in fertility found herein between cows that displayed Strong and Moderate RI estruses, but further studies are necessary to confirm this hypothesis. Parity influenced estrus intensity, as multiparous cows expressed lower RI at the moment of AI. This is in agreement with other studies (López-Gatius et al., 2005; Madureira et al., 2015) using spontaneous estrus and different AAM systems. López-Gatius et al. (2005b) reported that for each additional lactation, walking activity at estrus was reduced by 21.4%. Contrary to these results, (Walker et al., 1996) described that duration of estrus was shorter for primiparous than for multiparous lactating dairy cows. Additionally, BCS at estrus tended to affect RI, as cows with lower BCS tended to have lower estrus intensity. The BCS has been consistently shown to be one of the strongest factors associated with a RI in physical activity and duration at estrus detected by AAM (Løvendahl and Chagunda, 2010; Madureira et al., 2015; Silper et al., 2017). Poor BCS has been associated with delayed display of estrus post-calving, longer interval to first service and to conception, and reduced pregnancy to first AI (Roche et al., 2009). The transition period in dairy cows has an important role in reproductive success and likely affect the intensity of estrous expression. After calving, cows experience negative energy balance, which has negative effects on fertility through metabolic and endocrine modulations in the liver, ovary, and functioning of the uterus (Wathes et al., 2007). Cows that experience an intense negative energy balance (lower  53   insulin, glucose and IGF-I) have reduced LH pulse frequency, which decreases the synthesis of estradiol by the preovulatory follicle (Butler, 2003). The IGF-1 in particular is a growth factor essential to follicular growth and estradiol synthesis (Garnsworthy et al., 2008) and has functional interactions with estrous cycles and sexual behaviour (Woelders et al., 2014).   There was no correlation between milk production and RI of activity, however, when categorized by quartiles, greater milk production was associated with lower RI. The increased individual milk production has been negatively associated with standing to be mounted at estrus (Lopez et al., 2004; Rivera et al., 2010), which overall agrees with the findings from this study. A possible cause for the decrease in estrus-related behaviours might be the decrease in ovarian steroid concentrations, mainly progesterone, which occurs in response to increased hepatic blood flow and steroid clearance in lactating dairy cattle (Sangsritavong et al., 2002; Vasconcelos et al., 2003).   2.5 Conclusion In conclusion, greater estrous expression at timed AI improved ovulation rates, pregnancy per AI and reduced pregnancy loss. These results provide further evidence that measurements of estrous expression, even in timed AI programs, might be a reliable predictor of fertility and could be used as a tool to assist in the decision making of reproduction strategies at the farm level. Cows that had greater estrous expression also had greater circulating concentration of progesterone 7 d post-AI, providing evidence of improved ovarian function following those high intensity estrus events. The improvement in fertility with increased estrous expression was also linked with  54   reduced pregnancy loss, which further supports the notion that the endometrium environment is significantly affected by the mechanisms that cause greater intensity of estrus.  Table 2.1: Relative increase in physical activity, ovulation rate, and pregnancy/AI according to BCS, parity and milk production. Variables Relative Increase1 Mean % ± SEM [n] Ovulation rate2 (%, [n/n]) Pregnancy/AI3 (%, [n/n])     BCS    <2.75 300.2 ± 14.8a[243] 82.2 [88/107] 27.5a [52/243] ≥ 2.75 - 3.0 332.1 ± 9.4b[523] 85.5 [248/290] 35.4b [159/523] ≥ 3.0 332.1 ± 9.6b[640] 87.6 [323/372] 38.8b [211/640]     Parity    Primiparous 331.1 ± 12.6a[576] 87.9 [291/331] 38.9a [209/576] Multiparous 300.9 ± 11.1b[835] 84.3 [372/442] 28.8b [214/835]     Milk Production (kg/d)    ≤ 37.5 339.3 ± 6.4a[354] 81.5 [141/173] 27.1 [96/354] 37.6 - 44.7 334.9 ± 7.9a[353] 87.0 [188/216] 33.1 [117/353]  55   44.8-52.1 325.7 ± 8.0a[353] 87.6 [170/191] 29.9 [106/353] > 52.2 298.7 ± 9.49b[351] 86.7 [164/193] 29.8 [104/351] a-cDifferent letters indicate differences between variables within the columns (P < 0.05). 1 Relative increase in activity was calculated as the percentage increase in activity at estrus in relation to each cow’s own basal activity. 2 Cows that had a corpus luteum at d 7 after AI. 3 Number of cows pregnant at d 31 divided by the number of cows inseminated.   56   Table 2.2: Means (± SE) for preovulatory follicle diameter at the moment of timed AI and progesterone concentration at d 7 post-AI according to BCS, parity, milk production, progesterone concentration at d 7 post-AI, relative increase and presence of estrus expression. Variables   Follicle Diameter (mm) [P4] d7 post AI   (Mean ng/mL ± SEM) BCS   <2.75 12.6 ± 0.2a [79] 2.5 ± 0.2a [115] ≥ 2.75 - 3.0 13.6 ± 0.3b [201] 3.2 ± 0.1b [313] ≥ 3.0 13.1 ± 0.2b [274] 3.2 ± 0.1b [387]    Parity   Primiparous 13.3 ± 0.4 [243] 3.41 ± 0.1a [357] Multiparous 13.5 ± 0.4 [315] 2.91 ± 0.1b [462]    Milk Production (kg)   ≤ 37.5 13.2 ± 0.2 [155] 3.18 ± 0.1 [245] 37.6 - 44.7 13.4 ± 0.3 [136] 3.11 ± 0.1 [186] 44.8-52.1 13.3 ± 0.3 [124] 3.25 ± 0.1 [186] > 52.2 13.8 ± 0.3 [143] 2.92 ± 0.2 [163]    Progesterone concentration at d 7 post-AI (ng/ml)   <1.0 12.3 ± 0.6a [111] - 1.0 – 3.0 12.8 ± 0.2a [254] - > 3.0 14.1 ± 0.2b [276] -  57      Automated Activity Monitor Relative increase (%)   Moderate Intensity 13.4 ± 0.2 [188] 2.70 ± 0.1a [275] Strong Intensity 13.3 ± 0.1 [301] 3.59 ± 0.2b [403]    Estrus   No Estrus 12.7 ± 0.6 [49] 1.25 ± 0.3a [102] Estrus 13.4 ± 0.1 [489] 3.42 ± 0.2b [678] a-c Different letters indicate difference between variables within the columns (P < 0.05).  Figure 2.1:  Experimental ovulation synchronization protocol as follows: EB (estradiol benzoate - 2 mg, Gonadiol, Zoetis, São Paulo, Brazil), GnRH (gonadorelin diacetate - 100 μg, Cystorelin, Merial, São Paulo, Brazil), PGF (dinoprost tromethamine - 25 mg, Lutalyse, Zoetis, São Paulo, Brazil), ECP (estradiol cypionate - 1 mg, E.C.P., Zoetis, São Paulo, Brazil), CIDR (intravaginal progesterone implant - 1.9 g progesterone; CIDR, Zoetis, São Paulo, Brazil), TAI (timed AI), US (examination of ovaries with ultrasonography), P4 (collection of blood sample for analysis of progesterone concentration). Automated detection of estrus was done with Afimilk Pedometer Plus Tags and AfiFarm software (Afimilk, Kibbutz Afikim, Israel).          58   Figure 2.2 Distribution of ovulation rates (%) according to relative increase in activity at the moment of timed AI using an automated activity monitor. a-c Different letters indicate difference between variables within the bars (P < 0.05).             41.983.689.794.6 95.40102030405060708090100< 100 100-199 200-299 300-399 ≥ 400Ovulation Rates (%)Relative Increase in Activity (%)a39/95 64/76 160/178 162/176 195/205 b b bc c  59   Figure 2.3: Distribution of pregnancy per AI (%) of all insemination events according to relative increase in activity at timed AI detected by an automated activity monitor (panel A) and considering only cows that had an ovulatory follicle (panel B). a-d Different letters indicate difference between variables within the bars (P < 0.05). A)  6.222.630.332.438.3051015202530354045< 100 100-199 200-299 300-399 ≥ 400Pregnancy per AI (%)Relative Increase in Activity (%)107/310 125/314a b c cd d 10/181 43/185 111/349  60   B)             5.537.034.740.548.80102030405060< 100 100-199 200-299 300-399 ≥ 400Pregnancy per AI (%)Relative Increase in Activity (%)24/64a57/160 69/162 97/195 2/39 b b bc c  61   Figure 2.4: Pregnancy losses (%) according to categories of relative increase in physical activity at timed AI:No Estrus (< 100%), Moderate Intensity (100- 299 % relative increase) and Strong Intensity (≥ 300 % relative increase) as detected by an automated activity monitor (panel A; P = 0.03) and distribution of pregnancy losses (%) according to relative increase in physical activity at timed AI detected by an automated activity monitor (panel B). a-b Different letters indicate difference between variables within the bars (P < 0.05). A)  B)  19.221.713.90510152025No Estrus Moderate Intensity Strong IntensityPregnancy Losses (%)Classification of Peak of Activity (% relative increase)27/151 25/2292/10a19.2 20.122.115.28.20510152025< 100 100-199 200-299 300-399 400-499Pregnancy Losses (%)Relative Increase in Activity (%)2/10 7/42 20/109 16/107 9/122 a a a b a b a  62   3 Chapter 3: Greater intensity of estrous expression is associated with improved embryo viability from superovulated Holstein heifers 2  3.1 Introduction Superovulation was developed in the 1970s (Hasler, 2014) and can be used to accelerate gains in genetic progress (Jaton et al., 2016). The procedure involves providing a combination of hormones to super-stimulate the ovarian follicles, leading to multiple ovulations (Peippo et al., 2011). Successful multiple ovulations are influenced by factors related to the donor (including parity, age and breed) and to management (including the superovulation protocol, climate, and nutrition; Chebel et al., 2008). Factors that contribute to fertilization rates in superovulated animals include semen fertility, type of semen and AI technician skills (Sartori et al., 2004b; Schenk et al., 2006). All together these factors can impact fertilization rates and embryo production; the efficiency of superovulation methods has remained fairly stable in recent years, with an average yield of 6.2 embryos per superovulation event (IETS, 2013).  The intensity of estrous expression is related to cow fertility, both when spontaneous estruses are detected by automated activity monitors (Madureira et al., 2015) and when following a timed AI program (Pereira et al., 2016; Madureira et al., 2019). Similarly, the occurrence of estrus in recipient cows appears to increase pregnancy rates following embryo transfer in estradiol-based (Pereira et al., 2016) or GnRH-based protocols (Jinks et al., 2013). Furthermore, stronger  2 A version of this chapter has been accepted for publication: Madureira, A.M.L., T.A. Burnett, K.G. Pohler, T.G. Guida, C.P. Sanches, J.L.M Vasconcelos and R.L.A. Cerri. 2020. Short Communication: Greater intensity of estrous expression is associated with improved embryo viability from supervoulated Holstein heifers. J. Dairy Sci. 103: 5641-5646. DOI: 10.3168/jds.2019-17772.  63   displays of estrus are associated with decreased pregnancy losses after embryo transfer (Pereira et al., 2016). The reasons for this link between estrous expression and fertility are not well understood, but may be associated with the hormonal milieu surrounding estrus, as both progesterone and estradiol play important roles for the final maturation of the oocyte, embryo development and the receptivity of the uterus while also associated with differences in the occurrence and expression of estrus (Denis-Robichaud et al., 2018b; Madureira et al., 2018). To date, there is limited literature about the effect of estrous expression on the superovulatory response and viability of embryos (Jinks et al., 2013; Larimore et al., 2015).  The main objective of this study was to evaluate the effect of the intensity of estrous expression on the viability of in vivo produced embryos. We hypothesized that heifers that displayed greater estrous expression would yield a greater number of embryos, of which, a greater proportion would be viable and freezable.   3.2 Materials and methods This study was conducted at a commercial farm in Minas Gerais State, Brazil (latitude: 19°18’40” S; longitude: 46°02’56” W). The practices outlined in the Guide for the Care and Use of Agricultural Animals in Agricultural Research and Teaching (FASS, 1999) were used for all procedures as part of the local requirements.   64   3.2.1 Animals and housing A total of 51 nulliparous Holstein heifers (n = 69 events; 10.5 to 14.5 mo and 325.0 ± 21.1 kg of body weight) were enrolled in the study one week before the superovulation protocol. Heifers were housed in an open pack compost barn. Animals were fed a TMR thrice daily and pushed up three times daily. Water and TMR were available for ad libitum intake. At the time of enrollment, BCS was recorded (1 to 5 scale at 0.25 increments; Edmonson et al., 1989). Heifers were monitored continuously by a collar-mounted sensor (CowScout™ Activity Monitoring System, GEA, Dusseldorf, Germany) starting one week before the superovulation protocol until the moment of timed AI, allowing for sufficient time for the AAM to create a baseline prior to the initiation of the protocol.   3.2.2 Superovulation protocol, estrus detection and embryo collection Heifers were submitted to a superovulation protocol based on FSH and progesterone, as described in Figure 3.1. Timed AI was performed twice, first at the moment of GnRH (d 9) then 12 h (d 10) later using thawed, sexed semen delivered by a trained technician. All heifers were bred despite estrous expression. At the time of the progesterone insert removal (d 8), all heifers received an breeding indicator for detection of estrus (Estrotect, Rockway Inc., Spring Valley, WI) placed on the spine, halfway between the hip and the tail head; all heifers received both the AAM and the breeding indicator. At the day of first AI a score was given to the breeding indicator based on the proportion of the original color that remained on it (score 1: 100% of the indicator was intact and animals were classified as not being in estrus; score 2 - 50% of the indicator was rubbed  65   off and animals were classified as having displayed a moderately intense estrus; and score 3 - greater than 50 % of the indicator was rubbed off and the animals were classified as having displayed a high intensity of estrous expression). The AAM system was equipped with a wireless antenna-receiver located in the open pack barn that sent data to a processing unit for recording and analysis. The estrus event alarm was triggered when at least three consecutive data block-intervals of 2 h were above a set threshold recommended by the manufacturer. Two traits of estrous expression were calculated from the AAM: intensity of activity (maximum activity during an estrus episode) and duration (total of time the animal spent with activity above the threshold) to describe the expression of estrus (see also Madureira et al., 2015)). Ovulatory response was calculated by the number of follicles on the day of AI (> 10 mm) divided by the number of CL on the day of collection. Heifers were flushed 7 d after the first AI by a transcervical procedure using a silicone Foley catheter (number 18; Solidor®, Well Lead Medical Instruments, China). The balloon of the Foley catheter was placed into the uterine horn ipsilateral to the CL. Approximately 500 mL of flushing solution (DM-PBS, Biodux®, SP, Brazil) was used to recover structures into a sterile filter (WTA®, SP, Brazil). For heifers with CL on both ovaries, both horns were flushed as described previously. Oocytes/embryos collected were evaluated for fertilization and grade quality (G1 = excellent or good, G2 = fair, G3 = poor, and G4 = degenerated) as described by the International Embryo Transfer Society (IETS, 2013). Also, each embryo was classified by its stage of development, as follows: morula (Mo), initial blastocyst (Bi), blastocyst (Bl) and as expanded blastocyst (Bx; Robertson and Nelson, 1998). Initial blastocyst and blastocyst groups were later combined due to low number of embryos in these stages, and no embryos were found in the  66   expanded blastocyst category. After the classification, embryos were placed into a straw (0.25 mm) with ethylene-glycol solution (Holding, Biodux®, SP, Brazil) for a fresh or frozen-thawed transfer to a recipient cow.  3.2.3 Statistical Analyses Distributions and normality tests were obtained using the Univariate procedure of the SAS software, version 9.4 (SAS Institute Inc., Cary, NC). Class variables used for analyses are described below. BCS categories were average (< 3.0) and moderate (> 3.0). Duration of estrus was calculated as the number of hours above the alert threshold detected by the AAM and was categorized as shorter or longer using the median. Intensity of activity from the AAM was defined as the maximum activity value recorded during the estrus event and was also categorized using the median into moderate and greater estrous expression groups. Percentage and number of viable embryos, number of follicles, ovulatory response, and percentage of morula and blastocysts were used as continuous dependent variables and assessed with ANOVA using the MIXED procedure with AI event as the experimental unit and heifer as a random effect. Age was used as continuous independent variable. Breeding indicator score, BCS, and intensity and duration of estrous expression (AAM) were used as categorical independent variables; breeding indicator score, estrous expression intensity and duration were considered colinear variables and thus not included within the same models. Only variables with a P-value < 0.15 were maintained in the final model. Differences with P ≤ 0.05 were considered significant and those between 0.05 > P ≤ 0.10 were designated as a tendency.   67   3.3 Results and Discussion The main objective of our study was to evaluate the association between estrous expression measured by a breeding indicator and AAM, on the viability of in vivo produced embryos. Increased estrous expression was associated with increased embryo production. Heifers that had a score 3 on the breeding indicator had a greater number and percentage of viable embryos when compared with animals that had a score 1 or 2 (Table 3.1; P < 0.05). Similarly, greater intensity of estrous expression detected by the AAM was also associated with heifers having a greater number (P = 0.01) and percentage of viable embryos (P < 0.01) when compared with heifers expressing a moderate intensity of activity. Moreover, heifers that had a longer duration of estrus, as measured using the AAM, tended to have more viable embryos (P = 0.10) and a greater percentage of viable embryos (P < 0.01) than heifers that had shorter duration of estrus. Although the viability of embryos was increased with increased estrous expression, the stage and quality of the embryos were unaffected. The total percentage of embryos at the morula, initial blastocyst and blastocyst stages in this study were 78.9%, 18.6% and 2.5%, respectively.  Estradiol and progesterone are the main hormones acting on the hypothalamus to trigger estrous behaviour (Woelders et al., 2014). Standing to be mounted has been the gold standard for estrus detection (Roelofs et al., 2010), but this behaviour in lactating dairy cows is well known to be reduced (Rivera et al., 2010). In our study, a total of 34.8 % of heifers did not stand to be mounted (score 1 on the breeding indicator) but had an increase in physical activity detected by the AAM. Recent studies have shown that the intensity and duration of the estrus event is associated with ovulation rates and timing, pregnancy per AI, and pregnancy loss (Madureira et  68   al., 2015, 2019; Burnett et al., 2017, 2018; Polsky et al., 2017; Silper et al., 2017), but physiological mechanisms that explain this link are still unclear.  One possible explanation for decreased estrous behaviour close to ovulation may be the abnormal pattern of concentrations of progesterone at and post AI (Madureira et al., 2018). Increased progesterone decreases LH pulses from the anterior pituitary resulting in lower circulating estradiol concentrations (Stevenson and Pulley, 2016), thus inhibiting or decreasing its effects in the hypothalamic nuclei that trigger modifications in behaviour (Lyimo et al., 2000). However, estradiol concentrations do not seem to be highly correlated with increased physical activity as detected by AAMs (Lyimo et al., 2000; Madureira et al., 2015). Increased estradiol concentration increases duration and frequency of standing behaviour (Lyimo et al., 2000), but perhaps increased physical activity is dependent on estradiol for its initiation, but not for its intensity. Nonetheless, it is remarkable that animals enrolled and responding to a multiple ovulation protocol do not express estrous behaviour, considering the elevated pre-ovulatory plasma concentrations of estradiol (Soumano et al., 1996). In our study, heifers displaying greater intensity of estrus had a greater proportion of viable embryos. Studies have shown the importance of progesterone in the first week after conception to support embryo and fetal development (Bisinotto et al., 2010b; Spencer et al., 2016). In a recent study, (Madureira et al., 2019) showed that cows with greater estrous expression had lower concentrations of progesterone at AI and greater concentrations of progesterone 7 d post-AI. In addition, Pereira et al. (2016) reported that cows that expressed estrus had lower concentrations of progesterone compared with cows that did not express estrus near timed AI. Thus, suggesting that  69   the circulating progesterone profile around the time of AI affected both estrous behaviour, and fertilization and early embryo development. Total number of follicles was associated with estrous expression detected by the breeding indicator, but not by the AAM. Response to a superovulation protocol is important to optimize the number of fertilized and ideally transferable embryos. The total mean ± SD ovulatory response in this study was 67.5 ± 26.3 %. Heifers with a breeding indicator score of 1 had a lower ovulatory response (42.1 ± 8.0 %) than those that had some or all of the indicator rubbed off (i.e. score 3; 74.0 ± 4.9 %; P < 0.01). Variability in superovulation responses have been reported previously (Keller and Teepker, 1990; Kafi and McGowan, 1997; Bó and Mapletoft, 2014), and this variability may be related to the superovulation protocol itself as well as other factors related to the animal and environment (Kakar et al., 2005; Chebel et al., 2008).  3.4 Conclusion In conclusion, greater estrous expression was associated with a greater number of embryos collected and a greater percentage of viable embryos. The strength of estrous expression was not associated with the number of follicles present at AI but was associated with a greater ovulatory response.       70   Figure 3.1: The superovulation synchronization protocol used was as follows: an intravaginal progesterone implant of 1.9 g of progesterone previous used for 9 days (CIDR, Zoetis, Sao Paulo, Brazil), a 2.0 mg (i.m.) injection of estradiol benzoate (2.0 mL of RIC-BE®, Agener Uniao, Sao Paulo, Brazil) on pm at d0, on pm d4 a 2.0 mL (i.m.) injection of FSH (Folltropin®, Vetoquinol, X, Brazil), on am d5 and pm a 2.0 mL and 1.5 mL (i.m.; respectively) injection of FSH, on am d6 and pm a 1.5 mL and 1.0 mL (i.m.; respectively) injection of FSH and also 25 mg (i.m.) injection of dinoprost tromethamine (PGF; 5.0 mL ofLutalyse®, Zoetis, São Paulo, Brazil) at pm d6, on am d7 and pm a 1.0 mL and 0.5 mL (i.m.; respectively) injection of FSH and a PGF injection on am d7, on am d8 the last injection of FSH 0.5 mL (i.m.), cidr removal and estrus detection, on am d9 a 4 mg (i.m.) injection of Gonadorelin (GnRH; 4 mL ofFertagyl, MSD Animal Health, São Paulo, Brasil), a 1st AI at pm d9 and 2 nd AI at am d10, and on d16 oocyte-embryo collection.     71   Table 3.1: Number of viable embryos, percentage of viable embryos, number of follicles, and number of viable embryos per follicle according to breeding indicator score and automated activity monitor measures of estrous expression. Variables Number of viable embryos1[n]  Viable embryos1 (%) Number of follicles [n] Viable embryos per follicle1 (%) Breeding indicator            Score 1 1.2 ± 1.0a 35.5 ± 0.1a 7.7 ± 1.9a 15.6a        Score 2 1.8 ± 1.0a 34.3 ± 0.1a 10.3 ± 1.9a 17.8a       Score 3 4.1 ± 0.5b 43.1 ± 0.05b 13.9 ± 0.9b 29.5b AAM Device – Intensity2       Moderate 2.0 ± 0.6a 23.4 ± 0.05a 12.1 ± 1.3 16.5a      Greater 4.6 ± 0.6b 53.1 ± 0.05b 13.6 ± 1.3 33.8b AAM Device – Duration3       Longer 4.1 ± 0.6a 51.2 ± 0.05a      13.8 ± 1.5 29.7      Shorter  2.7 ± 0.6b 25.3 ± 0.05b      11.8 ± 1.3 22.8 1 Embryos were considered viable if they were fertilized and of excellent or good quality. 2 Intensity of estrous expression using the AAM was determined as the maximum activity during an estrus episode and categorized as moderate or greater using the median.  3 Duration of estrous expression using the AAM was determined as the total time the heifer spent with activity above the threshold and categorized as longer or shorter using the median.   a-cDifferent letters indicate differences between variables within the columns (P < 0.05).   72   4 Chapter 4: Occurrence and higher intensity of estrus in recipient dairy cows improve pregnancy per embryo transfer3 4.1 Introduction  Embryo transfer was developed in the 1970s (Hasler, 2014) and has become an important breeding technology for the dairy industry associated with accelerated gains in genetic progress (Nicholas, 1996; Jaton et al., 2016). Studies have shown that embryo transfer can be applied to dairy herds to improve fertility compared with artificial insemination (Chebel et al., 2008; Vasconcelos et al., 2011). Embryo transfer can minimize problems of poor quality oocytes and embryos that result from extended follicular dominance (Cerri et al., 2009b; Santos et al., 2010b), lower concentrations of progesterone during the growth of the pre-ovulatory follicle (Wiltbank et al., 2012), as well as minimize issues during early embryonic development (Mann et al., 2006). Embryo transfer reduces the negative effects of heat stress (Hansen, 2007) on fertility (Drost et al., 1999; Al-Katanani et al., 2002; Vasconcelos et al., 2006) as embryos are placed in the uterus at a developmental stage less susceptible to the harmful effects of heat stress. In addition, embryo transfer yields satisfactory fertility, especially in females classified as repeat breeders. Overall, factors affecting pregnancy outcomes after embryo transfer in dairy cattle have been extensively studied. However, few studies have focused on the effect of the occurrence and intensity of estrous  3 A version of this chapter has been submitted for publication: Madureira, A.M.L., T.A. Burnett, J.C.S. Marques, A.L. Moore, S. Borchardt, W. Heuwieser, T.G. Guida, J.L.M. Vasconcelos, and R.L.A. Cerri. Occurrence and intensity of estrus in recipient lactating dairy cows improve pregnancy per embryo transfer.    73   expression in recipient lactating dairy cows and its association with the pregnancy outcomes from ET. Manifestation of estrus, as well as the intensity of estrous expression, has been shown to have positive impacts on fertility from spontaneous estrus detected by automated activity monitors (Madureira et al., 2015; Polsky et al., 2017; Silper et al., 2017; Burnett et al., 2018) and timed AI programs (Pereira et al., 2016; Madureira et al., 2019). Similarly, the occurrence of estrus in recipient cows appears to increase pregnancy per ET when using either estradiol-based (Pereira et al., 2016) or GnRH-based protocols (Jinks et al., 2013) and has been associated with decreased pregnancy losses after embryo transfer (Pereira et al., 2016).  Previous study (see Chapter 2) reported that cows with higher intensity estrous expression have higher concentration of P4 post-AI and greater pregnancy per AI. Higher conception rates are associated when embryo transfer occurs with excellent and good quality embryos (Ferraz et al., 2016) and embryos in later stages embryonic development (Erdem et al., 2020). However, the association of stage of embryo development and the quality of the transferred embryo with the occurrence and intensity of estrous behaviour has yet to be studied. Overall, the biological mechanism linking estrous expression and fertility is unclear, but likely associated with the hormonal milieu during diestrus and proestrus, as both progesterone and estradiol play important roles in the development of the oocyte and the environment of the uterus while also being associated with differences in the occurrence and expression of estrus (Denis-Robichaud et al., 2018b; Madureira et al., 2018).   74   The main objective of this study was to evaluate the occurrence and intensity of estrous expression on the fertility of recipient lactating dairy cows bred using embryo transfer technology. We hypothesized that cows expressing estrus, receiving an embryo in a more advanced stage or of higher quality, and those with greater estrous expression intensity, would have higher pregnancy rates (per ET) and reduced pregnancy loss.  4.2 Materials and methods  Two observational cohort studies were conducted on two separate farms; Farm A: a commercial farm in São Paulo state, Brazil (22°21′25″ S, 47°23′03″ W) and Farm B: a commercial farm in Minas Gerais State, Brazil (latitude: 19°18’40” S; longitude: 46°02’56” W). Experiment 1 (Exp. 1) contained a subgroup of cows both from Farm A and B, while Experiment 2 (Exp. 2) was conducted only on Farm A. Farm A had an average 305-d mature equivalent milk yield of 11,438 kg/cow with the average herd size of approximately 1,700 lactating Holstein cows. Farm B had an average 305-d mature equivalent milk yield of 10,533 kg/cow with an average herd size of approximately 1,300 lactating Holstein cows. The practices outlined in the Guide for the Care and Use of Agricultural Animals in Agricultural Research and Teaching (FASS, 1999) was used for the approval of all experimental procedures as part of the local requirements. The study was approved by the University of British Columbia’s Animal Care Committee (protocol A14-0290).   75   4.2.1 Animals, housing and management Cows from Exp. 1 and Exp. 2 were enrolled at the beginning of an ovulation synchronization protocol. Cows enrolled from Farm A (Exp. 1 and 2) were housed in a cross-ventilated free-stall barn system. Milking was performed in a 72-stall rotary parlour three times daily (at approximately 0500, 1300, and 2100 h), and cows were fed a fresh TMR twice daily. Cows enrolled from Farm B (subgroup of Exp. 1) were housed in a free-stall barn with fans for cooling. Milking was performed in a double 24-stall conventional parlour three times daily (0400, 1200 and 1900 h) and cows were fed fresh TMR three times daily. The TMR was pushed up three time daily on both farms and formulated to meet or exceed the requirements of a lactating Holstein cow producing 40 kg/day of 3.5% fat corrected milk (NRC, 2001). Water and TMR were available for ad libitum intake on both farms. Cows in Exp. 1 were assessed for BCS at enrollment (1 to 5 scale at 0.25 increments; Edmonson et al., 1989). Daily milk production was recorded for the cows in both experiments.  4.2.2 Ovulation Synchronization Protocol and Embryo Transfer  In both experiments, cows were enrolled onto an ovulation synchronization protocol based on P4 and E2, as described by Pereira et al. (2015); in the case of a negative pregnancy diagnosis, cows were re-enrolled on the same protocol. The synchronization protocol consisted of an intravaginal progesterone implant of 1.9 g of progesterone (CIDR, Zoetis, São Paulo, Brazil), a 2.0 mg i.m. injection of estradiol benzoate (EB; 2.0 mL of Gonadiol, Zoetis, São Paulo, Brazil), and a 100 μg i.m. injection of gonadorelin diacetate (GnRH; 2.0 mL of Cystorelin, Merial, São Paulo, Brazil) on -11 d relative to the end of the protocol ; then, on -4 d and -2 d, a 25 mg i.m.  76   injection of dinoprost tromethamine (PGF; 5.0 mL of Lutalyse, Zoetis, São Paulo, Brazil) was given, and on -2d the CIDR was withdrawn and a 1.0 mg i.m. injection of estradiol cypionate (ECP; 0.5 mL of E.C.P., Zoetis, São Paulo, Brazil) was administrated. Embryo transfer was performed 7 d after the end of the protocol and cows received one single embryo, placed into the uterine horn ipsilateral to the CL. The embryos were transferred by an experienced veterinarian in both experiments. The embryos used in Exp.1 were fresh in vitro-produced embryos of excellent and fair quality (grades 1 and 2) in the stages of morula, initial blastocyst, and blastocyst according to the International Embryo Technology Society guidelines (Stringfellow and Givens, 2010). A description of the embryos used for Exp. 1 is available in Table 4.1. The embryos used in Exp. 2 were fresh and frozen in vivo-produced and frozen in vitro-produced. The criteria for the choice of embryos used was identical to Exp. 1.  Ovaries were examined by ultrasonography (Honda HS 101V with a 5.0 MHz linear probe, Honda, Japan) on the day of embryo transfer (7d) to check for the presence of a CL as a confirmation of ovulation. Absence of a CL was classified as ovulation failure, and cows did not receive an embryo and were not enrolled in the study.  Pregnancy diagnosis was carried out via ultrasonography, as described above, on 31d (Exp. 1 and 2) and 60d (Exp. 1) after the end of the ovulation synchronization protocol. Cows were considered pregnant when a viable embryo with a heartbeat was detected. Pregnancy per ET was calculated by dividing the number of cows that were pregnant on 31 d (Exp. 1 and Exp. 2) and 60 d (Exp. 1) after the end of the protocol by the total number of cows that received an embryo on 7 d. Pregnancy loss was calculated by dividing the number of cows found non-pregnant on 60 d by the total number of pregnant cows on 31 d after the end of the synchronization protocol.   77   4.2.3 Detection of Estrus - Automated Activity Monitor and Tail Chalk To assess the occurrence of estrus in Exp. 1 (Farm A and Farm B), tail chalk was applied on the tail head of the cows on the day of CIDR removal (-2 d) and at 0 d (end of the ovulation synchronization protocol) and cows were later (at 0 d) evaluated for chalk presence or removal. Cowes were then classified as having no Estrus if all the chalk was still visible and were considered to having showed Estrus if < 50 % of chalk still visible.  In Exp. 2, AAM were used to determine both the occurrence of estrus as well as the intensity of estrous expression. Cows were monitored continuously with a leg-mounted pedometer (AfiPedometer Plus Tag; AfiMilk®, Israel) attached to the right back limb of each cow on the day of their first calving. The steps/h were recorded in 2-hour blocks and retrieved by a computer system. Relative increase (RI) in steps/h was calculated by determining the change in steps on -1d and 0d, relative to the end of the ovulation synchronization protocol, in comparison to a baseline calculated for each cow. Baseline steps/h represented the average steps/h from the 7 d prior to the end of the timed AI protocol. The following formula was used: [(steps/h at estrus – steps/h at baseline) / steps/h at baseline] * 100]. The steps/h at estrus was defined as the greatest number of steps on -1d or 0d relative to timed AI. Cows were only considered to be in estrus if the RI on -1d or 0d exceeded 100 % at the end of the timed AI protocol.  4.2.4 Statistical Analyses In Exp. 1 and Exp. 2, the sample size (n = 250 per group) was calculated to identify a difference of 15 % in pregnancy per ET, between cows expressing estrus or not (Exp. 1) and between low or high intensity of estrus expression (Exp. 2) at the end of the timed AI protocol, with 95 % confidence and 80 % power.   78   Distributions and normality tests were obtained using the Univariate procedure in the SAS software, version 9.4 (SAS Institute Inc., Cary, NC). Class variables used for the analyses are described below. Parity was divided into primiparous (cows in first lactation) and multiparous (cows in second lactation or higher for both experiments. For Exp. 1, BCS was categorized as Low (< 2.75), Moderate (2.75 – 3.00), and High (≥ 3.25) using the 33rd percentiles. Milk production was classified into quartiles of each experiment, Exp. 1: 1st quartile: ≤ 31.9 kg/d; 2nd quartile: 32.0 – 39.2 kg/d; 3rd quartile: 39.3 – 46.1 kg/d; and 4th quartile: ≥ 46.2 kg/d; and for Exp. 2: 1st quartile: ≤ 28.8 kg/d; 2nd quartile: 28.9 – 37.8 kg/d; 3rd quartile: 37.9 – 45.8 kg/d; and 4th quartile: ≥ 45.9 kg/d. Physical activity of estrus episodes on Exp. 2 was categorized as No Estrus (< 100% relative increase in activity [RI]), Low intensity (100-299 % RI), and High intensity (≥ 300% RI), as described by Madureira et al. (2019).  Correlations between physiological measures (e.g. BCS, DIM, milk production, embryo development and quality) and the intensity of estrus expression (increase in physical activity using the AAM) were determined by Pearson’s correlation. Pregnancy per ET was used as a binomial dependent variable and tested for the effects of parity, BCS, DIM, milk production, embryo development and quality, and the occurrence (Exp. 1) and intensity (Exp. 2) of estrous expression using ANOVA with ET event as the experimental unit and the cow as a random effect using the GLIMMIX procedure in SAS. Only variables with a P-value < 0.15 were maintained in the final model. Differences with P ≤ 0.05 were considered significant and those between 0.05 > P ≤ 0.10 were designated as a tendency.   79   4.3 Results 4.3.1 Animals, Number of Events and Farm In Exp. 1, a total of 1,401 ET events from 1,045 cows were recorded (Farm A, n = 664 cows; and Farm B, n = 381 cows). The descriptive data for each farm on Exp. 1 is described on Table 4.1. A total of 1,147 ET events from 657 cows were recorded for Exp. 2 with an average milk production during the data collection of 37.8 ± 12.1 kg/d averaging 226.1  139.4 DIM. In Exp. 2, 24.9% and 75.1% of cows enrolled were primiparous and multiparous, respectively, and 60% [689/1,147], 22.8 % [261/1,147], 17.2 % [197/1,147] of the embryos transferred were in vitro fertilization, in vivo frozen and, in vivo fresh, respectively.  4.3.2 Estrous Expression at the end of the timed AI protocol A total of 65.2% (914/1,401) and 89.7% (1,019/1,142) of cows from Exp. 1 and Exp. 2, respectively, displayed estrus at the end of the ovulation synchronization protocol. The mean RI at estrus, in Exp. 2, was 281.3  180.9%. Parity influenced the expression of estrus, as multiparous were more likely to be classified as in estrus using tail chalk than primiparous (67.4% [652/968] vs. 60.5% [262/433]; P = 0.01, respectively), in Exp. 1. In Exp. 2, multiparous cows expressed lower RI at the end of the timed AI protocol (P < 0.01; Table 4.2) when compared with primiparous cows. The proportion of cows showing no estrous expression, low and high intensity estrous expression, by parity and milk production, is shown in Table 4.2. There was an interaction between parity and the intensity of estrous expression on pregnancy per ET (P < 0.01), as shown in Figure 2.1. In Exp. 1, there was no difference in the proportion of cows expressing estrus when milk production was classified into quartiles (1st quartile: 60.9 [208/330]; 2nd quartile: 67.5 [221/323]; 3rd quartile: 65.6 [216/325]; and 4th quartile: 61.4% [209/327], P = 0.21). In Exp.2, there was a  80   negative correlation between milk production and RI (r = - 0.15; P < 0.01). Greater milk production was associated with lower RI (Table 4.2) when milk production was classified into quartiles. There was a greater proportion of cows with high BCS which displayed estrus compared with cows having lower or moderate BCS (76.7 [195/254] vs. 67.4 [122/181] vs. 64.8% [155/239]; P < 0.05; respectively) in Exp. 1.   4.3.3 Pregnancy per ET and Pregnancy loss Pregnancy per ET was influenced by the occurrence and intensity of estrous expression, embryo transfer method, milk production, but not by parity, BCS and days in milk. In Exp. 1, cows that expressed estrus had greater pregnancy per ET compared with cows that did not display estrus (41.0 ± 2.3 [381/914] vs. 31.5 ± 2.9 [151/487]; P < 0.01, respectively). Similarly, in Exp. 2, cows that had greater estrous expression at the end of the ovulation synchronization protocol, as determined using the AAM, had greater pregnancy per ET (P < 0.01; Table 4.3). In Exp. 1, there was no effect of embryo transfer method on pregnancy per ET (P = 0.42). However, in Exp. 2, cows that received an in vivo embryo, either fresh or frozen, had greater pregnancy per ET compared with cows that received an in vitro fertilized embryo (P < 0.01; Table 4.3). Pregnancy per ET was affected by the stage of embryo development in Exp.1, as cows receiving embryos in the blastocyst and initial blastocyst stage had greater fertility on 31 d and 60 d post-AI when compared with cows receiving embryos in the morula stage (Table 4.4). There was no interaction between estrous expression (Low and High intensity) and stage of embryo development on pregnancy per ET (P = 0.44) in Exp. 1. There was, however, an effect of estrus detection (estrus  81   and no estrus) and embryo stage; cows that received a morula or initial blastocyst had greater pregnancy per ET as did cows that displayed estrus (Figure 4.2).  There was no interaction between estrous expression and quality of embryo on pregnancy per ET (P = 0.67). Milk production had a tendency to affect pregnancy per ET in Exp. 1 (P = 0.06). Similarly, milk production was associated with pregnancy per ET (P = 0.01) in Exp. 2 (Table 4.2), independent of embryo transfer method (P = 0.22). Pregnancy per ET tended to be influenced by parity (P = 0.07) in Exp. 1 but not in Exp. 2 (P = 0.78). There was no interaction between parity and embryo transfer method on pregnancy/ET. Days in milk did not influence pregnancy per ET in either experiment. Pregnancy loss was not influenced by the quality of the embryo (P = 0.61), by embryo transfer method (P = 0.46) or stage of the embryo (P = 0.19). Also, pregnancy loss was not associated with milk production (P = 0.99), BCS (P = 0.44) or the occurrence of estrus detected by tail chalk (P = 0.26). The current data set does not allow an assessment of whether pregnancy loss is associated with estrous expression as measured by an AAM. Pregnancy loss tended to be higher in primiparous compared to multiparous cows (20.7 ± 2.7 [39/187] vs. 14.7 ± 2.2 [51/345] %, P = 0.08; respectively). There was no farm effect on pregnancy loss (P = 0.36) in Exp. 1.  4.4 Discussion The aim of this study was to determine the association between the occurrence and intensity of estrus events and pregnancy success in recipient cows subjected to embryo transfer. The occurrence (Exp. 1 and Exp. 2) and intensity of estrus events (Exp. 2) influenced pregnancy per ET. Pregnancy per ET was affected by the stage of embryo development, but not grade quality, as  82   demonstrated by greater fertility observed in cows receiving embryos in the initial blastocyst and blastocyst stage compared with cows receiving embryos in the morula stage. Furthermore, cows that displayed estrus and received an embryo in a morula or initial blastocyst had greater pregnancy per ET than cows which did not display estrus. Previous studies have shown that expression of estrus detected by a breeding indicator (Pereira et al., 2016) or the intensity of estrous expression at spontaneous estrus or timed AI, measured using automated activity monitors, were associated with improvements in fertility (Madureira et al., 2015, 2019), lower ovulation failure (Burnett et al., 2018), and lower pregnancy losses (Pereira et al., 2016).  In cattle, P4 and E2 are the main hormones that control the estrous cycle and induce behavioural estrus. Progesterone is associated with estrous expression, embryonic development (Rivera et al., 2011), and fertility of dairy cattle (Bisinotto et al., 2010b). Pereira et al. (2016) showed that cows that did not express estrus at the end of a timed AI protocol were more likely to have higher concentration of P4 at estrus when compared to cows that expressed estrus. Additionally, P4 concentration during proestrus may be associated with estrous expression and intensity, as P4 primes the hypothalamus, making it more responsive to E2 and the occurrence of estrous expression (Woelders et al., 2014). A positive relationship between the concentration of E2 and the intensity of estrus behaviour has been shown in several studies (Britt et al., 1986; Lyimo et al., 2000; Lopez et al., 2004), although no relationship was found between E2 concentrations at estrus and estrous expression measured using an AAM (Madureira et al., 2015). Nevertheless, there is evidence that increased concentrations of E2 at the time of estrus has a positive effect on fertility (Buhi, 2002; Jinks et al., 2013). A study by Jinks et al. (2013) reported that cows that had higher concentrations of E2 at estrus had a higher number of fertilized embryos, greater  83   concentrations of P4 post-AI, and greater conception rates than cows with lower E2 concentrations. Progesterone and or E2 may be the key to these results. However, in the current study we did not measure these steroidal hormones. Cows that received an in vivo embryo, either frozen or fresh, had greater pregnancy/ET compared with cows that received an IVF embryo. Previous studies have shown slightly lower conception rates resulting from embryo transfers of in vitro compared with in vivo produced embryos (Wright and Ellington, 1995; Hasler, 2001). The processes of IVF results in darker and lower density cytoplasms (Pollard and Leibo, 1994), swollen blastomeres (Van Soom et al., 1992), more fragile zona pellucida (Duby et al., 1997), differences in intercellular communication (Boni et al., 1999), a higher incidence of chromosomal abnormalities (Viuff et al., 1999; Slimane et al., 2000), slower growth rates and higher thermal sensitivity (Leibo and Loskutoff, 1993). These differences may lead in vitro embryos to be less able to establish pregnancy.  Pregnancy/ET was also affected by the stage of embryo development. Cows receiving embryos in the initial blastocyst and blastocyst stage had greater fertility compared with embryos of morula stage. These results support conclusions from previous studies (Ferraz et al., 2016; Erdem et al., 2020). However, previous studies have reported no effect of embryo stage on the success of ET (Spell et al., 2001; Demetrio et al., 2007), and in the current study an association between estrous expression and developmental stage of the embryo was observed. Cows receiving less advanced embryos (morula and initial blastocyst) benefited from the occurrence of estrus, perhaps because of a more receptive uterine environment. More advanced embryos (blastocyst) might be mature enough to maintain pregnancy even in less ideal situations. Previous research, described in this thesis, has reported that cows with greater estrous expression have higher  84   concentration of P4 post-AI (Madureira et al., 2019). The ability of the embryo to produce interferon tau (IFNT) has been correlated with circulating progesterone concentrations during the luteal phase. Poor progesterone secretion during the luteal phase may result in the development of poor embryos unable to produce, or producing lower amounts of IFNT (Mann et al., 2006), thus decreasing its ability to maintain pregnancy. (Bauersachs et al., 2012; Mann et al., 2006).  In this study, a total of 89.7 % of estrus detection was recorded by the AAM and a total of 65.2 % were detected by the tail chalk. The detection rates for cows that received tail chalk were much lower than the detection rates for the cows that were fitted with an AAM. Standing to be mounted has been the gold standard for detection of estrus (Roelofs et al., 2010). However, this behaviour in lactating dairy cows is reduced (Rivera et al., 2010). The decrease in this behaviour has been associated with high milk production (Lopez et al., 2004), free-stall systems and the size of the herd (Britt et al., 1986; Palmer et al., 2012; Stevenson and Britt, 2017). Estrus behaviour is induced once E2 concentrations reach a set individual threshold. The minimum concentration of circulating E2 or the duration of exposure to E2 necessary to trigger estrus is likely dependent on several factors that are probably not uniform among cows, perhaps leading to variation in sexual behaviours displayed during estrus and perhaps having a more negative effect on mounting and standing to be mounted than on secondary signs of estrus.  Multiparous cows in this study displayed lower intensity of estrous expression at the end of a timed AI protocol. In López-Gatius et al. (2005), walking activity during estrus decreased by 21.4% for each increase in parity number, but some other studies have found that walking activity was not associated with parity (Arney et al., 1994; Løvendahl and Chagunda, 2010). Interestingly, in Exp. 1 multiparous cows were more likely to display estrus than primiparous cows. However,  85   it is noteworthy that the estrus detection in Exp. 1 was by tail chalk, a tool characterized by detection of standing estrus in contrast to walking behaviour. A shorter and less intense estrous has also been reported for primiparous cows when data were collected via visual scoring (Van Vliet and Van Eerdenburg, 1996). Demonstrating the vast differences in physical activity, Roelofs et al. (2005) observed that mounting occurred in 90% of estrous events, while standing to be mounted occurred in only 56% of estrous events; however, no impacts of parity were found on standing to be mounted. The difference in methods used to evaluate estrous expression, by measuring different behaviours, may explain the different results for parity in Experiments 1 and 2.  There was no correlation between milk production and the occurrence and intensity of estrus detected by AAM. However, when data was divided in quartiles, animals in the highest quartile had lower estrous expression (Exp. 2). The association between milk production and the intensity of estrus found in Exp. 2 is consistent with other studies (Lopez et al., 2004; Rivera et al., 2010; Madureira et al., 2015). This relationship is often explained by the elevated rate of metabolic clearance of steroidal hormones in animals with high energy intake and expenditure (Sangsritavong et al., 2002). Reduced levels of circulating reproductive hormones may lead to compromised reproductive processes including higher multiple ovulation rates and more luteal tissue in spite of the decreased hormone present in the bloodstream (Wiltbank et al., 2006).    86   4.5 Conclusion In conclusion, the occurrence and the intensity of estrous expression at end of an ovulation synchronization protocol improved pregnancy per ET. Pregnancy per ET was affected by the stage of embryo development, as cows receiving embryos in the blastocyst and initial blastocyst stage had greater fertility compared with cows receiving embryos in the morula stage. Cows that displayed estrus and received an embryo in a morula or initial blastocyst had greater pregnancy/ ET than cows which did not display estrus. These results provide evidence that the occurrence and intensity of estrous expression can predict fertility in lactating dairy cows and could be used as a tool to assist decision making in reproduction management. Table 4.1: Descriptive data on Experiment 1 according to Farm A (900 ET events) and Farm B (501 ET events). Variables Farm A Farm B Number of Events 900 501 Milk production (kg/d) 37.1 ± 11.6 41.4 ± 8.4 Days in milk (d) 212.1 ± 87.6 150.4 ± 93.4 Embryo Transfer Stage (%, [n])                Blastocyst 11.8 [106] 13.2 [66] Initial Blastocyst 34.0 [306] 29.1 [146]                Morula 54.2 [488] 57.7 [289]  87   Grade Quality (%, [n])   Excellent or Good 76.4 [688] 75.8 [380]              Fair 23.6 [212] 24.2 [121] Parity (%, [n])   Primiparous 40.6 [365] 13.6 [68] Multiparous 59.4 [535] 86.4 [433] Pregnancy/ET1 at 31 d (%, [n]) 39.5 [356] 35.1 [176] Pregnancy/ET at 60 d (%, [n]) 32.2 [290] 26.2 [131] 1 Pregnancy/ET – pregnancy was carried out via ultrasonography on 31 and 60 d after the end of the timed AI protocol and cows were considered pregnant when a heartbeat of the embryo was present.   88   Table 4.2: Relative increase in activity at the end of the synchronization protocol and pregnancy per embryo transfer (ET) according to parity and milk production and embryo transfer method for Experiment 2, in Holstein cows.       Variables Relative Increase1 Mean % ± SEM [n] Pregnancy/ET2 (%, [n/n]) Classification of Estrous Expression3 (%, [n/n])  No Estrus  Low Intensity  High Intensity       Parity       Primiparous 306.2 ± 12.6a [286] 32.9 ± 2.9 [90/286]  18.2 [52/286] 23.8a [68/286] 58.0a [166/286]  Multiparous 275.1 ± 6.8b [861] 31.1 ± 1.7 [265/861] 19.5 [168/861] 33.2b [286/861] 47.3b [407/861]  Milk Production (kg/d)         ≤ 28.8 324.7 ± 10.9a [287] 37.5 ± 3.2a [99/287] 14.5a [55/379] 26.4a [100/379] 59.1a [224/379]  28.9 – 37.8 300.9 ± 10.7a [285] 36.6 ± 2.9a [99/285] 25.4b [63/248] 28.6a [71/248] 46.0b [114/248]   89   37.9 - 45.8 306.3 ± 10.8a [286] 32.0 ± 2.9ab [86/286] 15.4ax [37/241] 36.9b [89/241] 47.7b [115/241]       ≥ 45.9 243.2 ± 11.3b [279] 25.8 ± 3.0b [69/279] 20.8by [58/279] 46.9c [131/279] 32.3c [90/279] a-c Different letters indicate differences between variables within the columns (P < 0.05). 1 Relative increase in activity was calculated as the percentage increase in activity at estrus in relation to each cow’s own basal activity. 2 Pregnancy/ET – pregnancy was carried out via ultrasonography on 31 d after the end of the timed AI protocol and cows were considered pregnant when a heartbeat of the embryo was present. 3 Classification of estrous expression - No Estrus - < 100 % relative increase (RI) in activity detected by the automated activity monitor (AAM); Low Intensity – 100 – 299 % RI in activity detected by the AAM; High Intensity - ≥ 300 % RI in activity detected by AAM 90   Table 4.3: Pregnancy per embryo transfer (ET) according to the classification of the intensity of estrous expression detected by an automated activity monitor (AAM) and by the embryo transfer method for Experiment 2, in Holstein cows. a-c Different letters indicate differences between variables within the columns (P < 0.05). 1 Pregnancy/ET – pregnancy was carried out via ultrasonography on 31 d after the end of the timed AI protocol and cows were considered pregnant when a heartbeat of the embryo was present. 2 Estrous expression was quantified using the relative increase at estrus, and an estrus episode on was classified as No Estrus (< 100% relative increase in activity [RI]), Low intensity (100-299 % RI), and High intensity (≥ 300% RI).     Variables Pregnancy/ ET1 (%, [n/n]) Automated Activity Monitor2               High Intensity 41.3 ± 2.2a [213/571]              Low Intensity 32.7 ± 2.7b [115/353]              No Estrus 11.3 ± 3.5c [26/218] Embryo Transfer Methods  In vivo Fresh  35.2 ± 2.9a [93/261] In vivo Frozen 35.6 ± 3.5a [65/197] In vitro Fertilization 28.1 ± 1.9b [197/689]  91   Table 4.4: Pregnancy per embryo transfer (ET) at 31 and 60 d post synchronization protocol, according to the stage of embryo transfer and grade quality on Experiment 1, in Holstein cows.  a-c Different letters indicate differences between variables within the columns (P < 0.05). 1 Pregnancy/ET – pregnancy was carried out via ultrasonography on 31 and 60 d after the end of the timed AI protocol and cows were considered pregnant when a heartbeat of the embryo was present.          Variables Pregnancy/ ET1 at 31 days (%, [n/n]) Pregnancy/ET at 60 days (%, [n/n])    Embryo Transfer Stage   Blastocyst 46.5 ± 3.8a [79/172] 31.3 ± 4.0a [63/172] Initial Blastocyst 42.1 ± 2.4a [184/452] 28.4 ± 2.6ax [148/452] Morula 35.3 ± 1.8b [269/777] 23.4 ± 1.9by [210/777] Grade Quality    Excellent and Good   39.2 ± 1.9a [430/1,068] 31.6 ± 1.9a [344/261] Fair 32.5 ± 3.3b [102/333] 23.8 ± 3.1b [65/197]  92   Figure 4.1: Pregnancy per embryo transfer (ET) according to parity (primiparous and multiparous) and the intensity of estrous expression (No Estrus, Low Intensity and High Intensity). High Intensity – 41.6 ± 2.1 [68/166] vs. 36.5 ±  2.8 [151/407]; P = 0.37; Low Intensity - 13.6 ± 2.3 [9/68] vs. 24.1 ± 3.2 [72/286]; P = 0.03 and No Estrus - 6.3 ± 1.6 [4/52] vs. 5.1 ± 1.9 [6/168]; P = 0.41; for primiparous and multiparous, respectively. There was an interaction between parity and the intensity of estrous expression on pregnancy per ET (P < 0.01).        41.613.66.336.524.15.105101520253035404550High Intensity Low Intensity No EstrusClassification of Estrous ExpressionPregnancy per ET (%)PrimiparousMultiparous 93   Figure 4.2: Pregnancy per embryo transfer (ET) according to the stage of embryo development and the occurrence of estrus (Estrus) or not (No estrus). Pregnancy was performed at 31 and 60 d post end of the timed AI.         0102030405060Morula InitialBlastocystBlastocyst Morula InitialBlastocystBlastocystPregnancy at 31d Pregnancy at 60dPregnancy per ET (%)No estrus Estrus 94   5 Chapter 5: Concentrations of progesterone in plasma during the estrous cycle are associated with the intensity of estrus and fertility of Holstein cows4 5.1 Introduction Visual estrus detection has been impaired due to the shorter duration and lower intensity of estrous expression (Diskin and Sreenan, 2000; Lopez et al., 2004; Saint-Dizier and Chastant-Maillard, 2012) in modern dairy cows. However, AAM have proven to be efficient and reliable technologies as an alternative estrus detection strategy over visual detection (Dolecheck et al., 2015). In a series of studies using different AAM systems, pregnancy per artificial insemination (P/AI) was reported to be greater for cows with more intense estrus (Polsky et al., 2017; Silper et al., 2017; Burnett et al., 2018). Pereira et al. (2016) reported that cows expressing estrus at the end of a synchronization of ovulation protocol had improved P/AI after using timed AI (38.9% vs. 25.5%) and embryo transfer (46.7% vs. 32.7%) technologies compared with animals that did not express estrus. Furthermore, gestational loss was lower for cows that expressed estrus at timed AI (14.4% vs. 20.1%) and prior to ET (18.6% vs. 22.7%; Pereira et al., 2016).   4 A version of this chapter has been submitted for publication: Madureira, A.M.L., T.A. Burnett, S. Borchardt, W. Heuwieser, J.L.M. Vasconcelos, and R.L.A. Cerri. Concentrations of progesterone in plasma during the estrous cycle are associated with the intensity of estrus and fertility of lactating Holstein cows.   95   Pereira et al. (2016) reported that cows that did not express estrus at the end of a timed AI protocol were more likely to have had higher concentrations of P4 at AI compared with cows that expressed estrus. The absence of complete regression of the CL during the proestrus period has often been reported (Souza et al., 2007; Santos et al., 2010b; Giordano et al., 2013). In these studies, cows with slightly higher plasma concentrations of P4 at AI, possibly caused by the absence of complete CL regression, had decreased fertility. Moreover, P4 concentrations after AI have also been reported to be important; Madureira et al. (2019) noted that the concentration of P4 at 7 d post-AI was greater in cows that expressed greater intensity estrous expression. Numerous studies have demonstrated the effects of P4 at AI, and immediately after AI, on fertility. However, the literature regarding the association between circulating P4 pre-luteolysis, at AI and post-AI and the intensity of estrous expression in cattle is limited. The aim of this study was to determine the association between the concentrations of P4 at different phases of the estrous cycle and the intensity of spontaneous or estrogen-induced estrous expression (detected by AAM), and on P/AI. We hypothesized that higher concentrations of P4 at different phases of diestrus, coupled with lower concentrations of P4 at AI, would be associated with greater estrous expression and improved P/AI.  5.2 Materials and methods This study was conducted at two locations. Experiment 1 (Exp. 1) was conducted on a commercial farm in São Paulo, Brazil (latitude: 22°21’25” S; longitude: 47°23’03” W) while Experiment 2 (Exp. 2) was conducted at the University of British Columbia’s Dairy Education and  96   Research Centre in Agassiz, Canada (49°13’59”N, 121°46’01”W). The University of British Columbia’s Animal Care protocol related with the current study was A18-0315. The practices outlined in the Guide for the Care and Use of Agricultural Animals in Agricultural Research and Teaching (FASS, 1999) and the Canadian Council on Animal Care (CCAC, 2009) was used for the approval of all experimental procedures as part of the local requirements.  5.2.1 Animals, housing and management  A total of 1,953 events from lactating Holstein cows were enrolled, consisting of 1,289 timed AI events from Exp. 1 and 664 AI events from Exp. 2. Cows from Exp. 1 were enrolled at the beginning of a timed AI protocol (Figure 1A) from a commercial herd with an average 305-d mature equivalent milk yield of 11,438 kg/cow and approximately 1,700 lactating Holstein dairy cows. Cows from Exp. 2 were enrolled upon the detection of spontaneous estrus (Figure 1B) from an experimental herd with an average 305-d mature equivalent milk yield of 12,799 kg/cow and approximately 270 lactating Holstein dairy cows. At the time of enrollment, BCS was assessed (1 to 5 scale at 0.25 increments; Edmonson et al., 1989) in both experiments. Milk production was measured daily at each milking (AfiLite, Kibbutz, Afikim, Israel) in Exp.1 between -11d and 0d (AI) of the experiment and the average daily milk production during this period was used for analysis. In Exp.2, milk production was recorded daily and averaged over 2 days before until 2 days after of detection of estrus.  In Exp. 1 cows were housed in a cross-ventilated free-stall barn, while cows in Exp. 2 were housed in a naturally ventilated free-stall barn. Milking was performed three times daily (at approximately 0500, 1300, and 2100 h) in Exp. 1, while milking was performed twice daily (at approximately 0500 and 1500 h) in Exp. 2. Cows were fed a TMR three times daily in Exp. 1 and  97   twice daily in Exp. 2. The TMR was formulated to meet or exceed the requirements of a lactating Holstein cow producing 40 kg/day of 3.5% fat corrected milk (NRC, 2001) and pushed up three times daily on both locations. Water and TMR were available for ad libitum intake.  5.2.2 Automated Activity Monitors Cows were continuously monitored by a leg-mounted pedometer (AfiPedometer Plus Tag; AfiMilk®, Israel) in Exp. 1. The pedometer was attached to the right back leg of each cow on the day of calving where it remained throughout the entire experimental period. The data from the AAM were used to calculate the relative increase in physical activity. To determine the relative increase the following formula was used: [(steps/h at estrus - steps/h at baseline)/steps/h at baseline] * 100]. Maximum steps/h at estrus was considered as the greatest steps/h count of the entire estrus event and the baseline was defined as the average steps/h for the 7d prior to AI.  Cows that exceeded a relative increase of 100% on either -1d or 0d relative to timed AI were considered to be in estrus at the moment of AI, whereas those with a relative increase < 100% were classified as not having an alert from the AAM, as described by Madureira et al. (2019). In Exp. 2 a neck-mounted accelerometer (Heatime®, SCR Engineers, Netanya, Israel) was placed on the upper left side at the cranial portion of the cow’s neck using a collar on the day of calving and it was removed if a positive pregnancy diagnosis was detected. The activity data from each cow were computed into an index value that ranged from 0 to 100 through the system’s propriety algorithm and a threshold of 35 was set to alert for an estrus event. The maximum increase in physical activity index and the interval from the onset to the end of the alert (h above  98   threshold) was calculated using an Excel macro (Excel; Microsoft Corporation, Redmond, WA) to identify estrus events from the exported backup files.  In order to simplify the description of estrus intensity categories, the median value of the maximum activity value from the two AAM systems in Exp. 1 and Exp. 2, as well as the total duration of the estrus episodes in Exp. 2 were used. Estrus events were classified as High Intensity and Low Intensity using the threshold of 300 % relative increase in Exp. 1, and 80.5 Index in Exp.2. The duration of estrus was classified as Long and Short using the threshold of 8 h.  5.2.3 Synchronization Protocol, Artificial Insemination, Ultrasonography, and Pregnancy Diagnosis 5.2.3.1 Experiment 1 All cows were enrolled onto a synchronization protocol based on progesterone and estradiol. Timed AI was performed using commercially frozen–thawed semen by the same two trained technicians. The synchronization protocol used is described by Pereira et al. (2015) and detailed in Figure 1. Ovaries of a subset of cows were examined by ultrasonography (Honda Electronics, Toyohashi, Japan) using a 7.5 MHz linear-array rectal transducer at 0d (assessment of two largest follicles; n = 541 cows) and on 7d (presence or absence of a corpus luteum to confirm ovulation; n = 741 cows). Pregnancy diagnosis was performed via ultrasonography on 31d after timed AI for all cows. A cow was considered pregnant if an embryo with heartbeat was present. Pregnancy per AI was calculated by dividing the number of cows that were pregnant on d 31 post-AI by the number of animals inseminated into the timed AI protocol.   99   5.2.3.2 Experiment 2  All cows had their ovaries examined by ultrasonography (Aloka SSD-500, Aloka Co. Ltd, Wallingford, CT, USA) using a 7.5 MHz linear rectal transducer at the time of an estrus alert identified by the neck mounted accelerometer as well as at 7 d, 14 d and 21 d post-AI. Presence of a CL and/or diameter of the largest follicles were measured and recorded at each assessment. Cows were artificially inseminated upon estrus detected by an AAM using the a.m./p.m. rule. True events from the AAM alerts were considered based on the presence of a pre-ovulatory follicle larger than 15 mm in diameter and absence of an active CL (greater than 25 mm in diameter). All cows were examined with an ultrasound at 35 ± 7 d post-AI for pregnancy diagnosis, cows that had an embryo with a heartbeat were considered positive for pregnancy. 5.2.4 Blood Sampling, Analyses of Estradiol and Progesterone Concentrations  5.2.4.1 Experiment 1 Blood samples were harvested from the coccygeal vein or artery into commercial blood collection tubes (BD Vacutainer Serum Tubes, 10 mL; Becton Dickinson, Franklin Lakes, NJ). Blood samples were collected on -4 d (n = 312 cows), 0 d (n = 923 cows) and 7 d (n = 780 cows) relative to timed AI. All samples were placed immediately on ice and then centrifuged at 3,000 × g at 4°C for 30 min for serum collection and stored at -20°C until analyzed for P4 concentration. Serum P4 concentrations were analyzed using a chemiluminescent enzyme immunoassay (Immulite 1000; Siemens Medical Solutions Diagnostics, Los Angeles, CA) as previous validated (Martin et al., 2007; Reis et al., 2015). The intra- and inter-assay CV were 5.1 and 5.2 %, respectively.  The minimum detectable concentration was 0.1 ng/mL of P4.   100   5.2.4.2 Experiment 2 Blood samples were harvested from the median coccygeal vein or artery utilizing Vacutainer tubes (10 mL; Becton & Dickinson Vacutainer systems, Rutherford, NJ) with K2EDTA. Blood samples were collected immediately following a detected estrus alert (0 d; n = 553) by the AAM system and at 7 d (n = 142 cows), 14 d (n = 148 cows) and 21 d (n = 138 cows) post-AI for P4 analysis. Only samples collected at the estrus alert (0 d; n = 617 cows) were analyzed for E2. All samples were placed immediately on ice, transported to the laboratory and centrifuged at 2,700 x g for 15 min for separation of plasma. Plasma samples were then stored at -80 °C to be analyzed for E2 and P4 concentrations. Plasma concentrations of E2 were determined using a double-antibody I125-based assay developed as described by Burke et al. (2003) with modifications. Average intra-assay coefficient of variation (CV) was 4.2%, and inter-assay CV for pooled plasma samples containing 2.7, 5.8, and 12.3 pg/mL of estradiol were 6.3%, 5.2% and 4.1%, respectively. The average sensitivity of the estradiol assay was 1.1 pg/mL, as described by Madureira et al. (2015). Plasma P4 concentrations were measured using a commercial ELISA kit (Ovucheck Plasma; Biovet, St-Hyacinthe, Quebec; Broes and LeBlanc, 2014). The range of quantification of the test is 0.55 – 10.45 ng/mL, and the intra-assay CV in the present study was 10.8%.  5.2.5 Statistical Analysis  In Experiment 1, the sample size (n = 281 per group) was calculated to identify a difference of 15 % in pregnancy per AI, between cows expressing high and low intensity of estrus at AI with 95 % confidence and 80 % power. This samples size was also sufficient to identify an increase of  101   25% in activity, expecting a SD of 130 steps/h between cows with different P4 concentrations prior to AI (-4 d) and at AI (0 d), and also sufficient to identify a difference of 1.0 ng/mL in P4 concentration at 7 d post-AI, expecting a SD of 2.0 ng/mL between cows expressing high and low intensity of estrus at AI.  In Experiment 2, the sample size (n = 80 per group) was calculated to identify a difference of 11 index points, expecting a SD of 18.9 index points between cows with different P4 concentrations at estrus with 95% confidence and 80% power.  The sample size (n = 109 per group) was calculated to identify a difference of 1.0 ng/mL in P4 concentration at 7 d, 14 d and 21d post-AI, expecting a SD of 2.0 ng/mL between cows expressing high and low intensity of estrus at AI. Distributions and normality tests were obtained using the Univariate procedure of SAS software, version 9.4 (SAS Institute Inc., Cary, NC). Class variables used for analyses are described below. Parity was divided as cows in first lactation and second lactation or higher (primiparous vs. multiparous), in both experiments. For Exp. 1 and Exp. 2, BCS was categorized as Low (< 2.75), Moderate (2.75 – 3.00), and High (> 3.00). Physical activity of estrus episodes in Exp. 1 was categorized as No Estrus (< 100% relative increase in activity), Low intensity (100- 299 % relative increase in activity), and High intensity (> 300% relative increase in activity). In Exp.2, the activity at time of alert was categorized relative to the median as High intensity (≥ 80.5 index) and Low intensity (< 80.5 index). Duration of the estrus event was also categorized using the median as Long duration (≥ 8 h) and Short duration (< 8 h). A total of 67 cows had missing estrus intensity data from Exp. 1. In Exp. 1, concentrations of P4 were classified as lesser or equal to the median and greater than the median at each sampling time using the following values:  - 4 d prior to timed AI (3.04 ng/mL); 0 d (at the moment of timed AI; 0.1 ng/mL) and at 7 d post-AI  102   (2.96 ng/mL). Concentrations of P4 were categorized by the median in Exp. 2 as having greater or lower concentration as: on 0 d (at the moment of AI; 0.26 ng/mL); on 7 d post-AI (2.65 ng/mL); on 14 d post-AI (3.12 ng/mL); and on 21 d post-AI (6.27 ng/mL). To evaluate the cumulative effect of both the concentration of P4 at -4 d and 0 d on estrous expression and P/AI in Exp. 1, a classification was created according to the median as described above – HL = high concentration of P4 at -4d and low concentration of P4 at 0 d; LH = low concentrations of P4 at -4 d and high concentration of P4 at 0 d; HH = high concentration of P4 at -4 d and high concentration of P4 at 0 d; and LL = low concentration of P4 at -4 d and low concentration of P4 at 0 d. Correlations between physiological measurements (e.g. diameter of pre-ovulatory follicle, progesterone concentration, estradiol concentration, DIM, and milk production) and automated activity measurements (e.g. high and low intensity and long and short duration) were determined by Pearson’s correlation. Relative increase in physical activity (Exp. 1), maximum increase in activity (Exp. 2), and total duration were used as a continuous dependent variable and assessed by ANOVA using the GLIMMIX in SAS with artificial insemination event as the experimental unit and cow as a random effect. Parity, BCS, milk production, DIM, pre-ovulatory follicle diameter and corpus luteum size were used as independent variables. For the analysis of pregnancy per AI associated with the concentration of P4 at 7 d, 14 d and 21 d post-AI only animals that ovulated were included. Diameter of the pre-ovulatory follicle was tested as a continuous dependent variable against the fixed effects of parity, BCS, milk production, relative increase (Exp. 1), activity index (Exp. 2), and duration (Exp. 2), and size of the corpus luteum.  Pregnancy per AI was used as a binomial dependent variable assessed using the same model, where AI event was again used as the experimental unit and cow as the random effect. Only variables with a P-value  103   < 0.15 were maintained in the final model. Differences with P ≤ 0.05 were considered significant and those between 0.05 > P ≤ 0.10 were designated as a tendency.  5.3 Results 5.3.1 Animals and Number of Events A total of 1,289 timed AI events from 984 cows were recorded for Exp. 1 with an average milk production of 45.5 ± 10.7 kg/d with approximately 3.5% fat, averaging 117.2 ± 58.2 DIM. In total, 44.2% and 55.8% of cows enrolled were primiparous and multiparous, respectively. In Exp. 2, a total of 664 events from 291 cows were recorded, with an average milk production of 38.4 ± 8.2 kg/d with approximately 4.7% fat, averaging 118.4 ± 52.9 DIM. In Exp. 2, a total of 39.2 % and 60.8% of cows enrolled were primiparous and multiparous, respectively.  5.3.2 Intensity of Estrous Expression at AI The mean relative increase in activity at estrus was 328.7 ± 132.7 % in Exp. 1 and the mean activity index and duration at estrus was 76.6 ± 18.9 index and 12.6 ± 9.7 h, respectively, in Exp. 2. In Exp. 1, 13.7 % (167/1222) of the cows did not display estrus at timed AI. Parity influenced estrous expression, in both Exp. 1 and Exp. 2, as multiparous cows expressed lower relative increase, activity index, and duration at the moment of AI (P < 0.01; Table 1) when compared with primiparous cows. In Exp. 1, BCS at timed AI, tended to affect relative increase (P = 0.10; Table 1), as cows with lower BCS tended to have lower estrous expression than those with Moderate or High BCS. In Exp. 2, BCS was associated with maximum activity index and duration (P = 0.01; Table 1). There was no correlation between milk production and relative increase in Exp. 1 (r = - 0.02; P = 0.37), but there was a weak negative correlation for both estrous expression  104   measurements in Exp. 2 (maximum activity index: r = - 0.20; P < 0.01; duration: r = - 0.18; P < 0.01).  5.3.3 Pre-ovulatory Follicle Diameter   Mean pre-ovulatory follicle diameter was 13.4 ± 3.3 mm and 18.7 ± 4.7 mm for Exp. 1 and Exp. 2, respectively. There was no correlation between follicle diameter and relative increase in Exp. 1 (r = -0.01; P = 0.89), maximum activity index (r = -0.04; P = 0.31), or duration (r = - 0.03; P = 0.52) in Exp. 2.   In Exp. 1, cows that had higher concentration of P4 at -4 d had larger pre-ovulatory follicles (14.8 ± 0.2 vs. 12.3 ± 0.3 mm; P < 0.001). There was no association of concentration of P4 at AI and the size of the pre-ovulatory follicle size within either study (Exp. 1: 12.9 ± 0.7 vs. 13.0 ± 0.6; P = 0.91; Exp. 2: 17.7 ± 0.5 vs. 18.6 ± 0.5, P = 0.20). Cows with greater concentrations of P4 at 7 d post-AI had larger pre-ovulatory follicles at the time of AI within both experiments (Exp. 1: 13.7 ± 0.3 vs. 12.6 ± 0.3 mm; P < 0.001; Exp. 2: 19.1 ± 0.5 vs. 17.2 ± 0.5 mm; P < 0.001). However, no associations were found between concentrations of P4 at 14 d (P = 0.88) or 21 d (P = 0.73) post-AI and pre-ovulatory follicle diameter. In Exp. 2, cows that had greater concentrations of E2 at the moment of estrus alert had larger pre-ovulatory follicles compared with cows that had lower concentrations of E2 (19.5 ± 0.4 vs. 18.2 ± 0.3 mm; P < 0.001). 5.3.4 5.3.4 Concentration of Progesterone and Estradiol  Concentrations of P4 at -4, 0 d and 7 d post-AI were all associated with the intensity of estrous expression within the current study. Cows with greater concentrations of P4 at -4 d had greater estrous expression compared with cows that had lower concentrations of P4 (318.2 ± 10.5  105   vs. 289.4 ± 10.6 % relative increase; P = 0.05). While lower concentrations of P4 on 0 d were associated with increased intensity and duration of estrous expression (Exp. 1- 363.6 ± 5.2 vs. 275.9 ± 8.0 % relative increase; P < 0.001; Exp 2 - 76.7 ± 1.9 vs. 67.4 ± 4.7 index; P < 0.05; Exp. 2 - 12.5 ± 0.5 vs. 9.3 ± 1.8 h; P < 0.001). Similarly, cows that had lower intensity and shorter duration of estrous expression not only had higher concentrations of P4 but also lower concentrations of E2 at estrus compared with cows with greater activity and longer duration estrous behaviour (Figure 2A and Figure 2B; P < 0.01). The proportion of cows displaying greater and lesser estrous intensity was shifted between cows with higher or lower concentrations of P4 at -4 d in Exp. 1 (Figure 3A) and 0 d in both, Exp. 1 and Exp. 2 (Figure 3B). Moreover, a total of 66.7% of the cows with greater concentration of P4 at -4 d had lower concentration of P4 at 0 d. Together, cows classified as HL had greater estrous intensity when compared with cows classified as LH, HH and LL (356.6 ± 5.5 vs. 272.4 ± 7.4 vs. 293.8 ± 4.8 vs. 267.2 ± 14.6 % relative increase; P < 0.001), whereas the latter three categories did not differ.  Cows with higher intensity of estrus at timed AI had higher concentrations of P4 at 7 d post-AI compared with those that had lower intensity or those that did not express estrus (3.45  0.1 vs. 3.19  0.1 vs. 2.16  0.2 ng/mL; P < 0.001). Greater concentrations of P4 on 7 d (P < 0.05), 14 d (P < 0.01) and 21 d (P < 0.01) post-AI were found in cows that had higher intensity of estrus detected at the time of AI (Figure 3). Size of the corpus luteum on 7 d (P = 0.83), 14 d (P = 0.67) and at 21 d (P = 0.58) post-AI did not differ between cows that expressed higher or lower intensity of estrus.  Milk production was not correlated with concentrations of P4 at -4 d (r = 0.01; P = 0.75),0 d (Exp. 1: r = 0.02; P = 0.51; Exp. 2: r = - 0.01; P = 0.91),7 d (Exp. 1: r = 0.05; P = 0.12; Exp. 2:  106   r = - 0.05; P = 0.50 ), 14 d (r = 0.006; P = 0.94) and 21 d post-AI (r = 0.004; P = 0.95) or with the concentration of E2 on 0 d (r = - 0.09; P = 0.31). Concentrations of P4 at AI and 7 d post-AI, relative to BCS, parity and milk production, are summarized in Table 2 for both Exp. 1 and 2.  5.3.5 Pregnancy per AI (P/AI) In Exp. 1, P/AI was influenced by estrous expression, parity, BCS, concentration of progesterone at -4 d, at 0 d and 7 d post-AI, but not by milk production. Cows that expressed greater intensity of estrus had greater P/AI compared with those with lower intensity or those that did not express estrus at timed AI (46.15 ± 3.0 % [2/36] vs. 33.6 ± 3.6 % [69/193] vs. 5.4 ± 8.1 % [174/370]; P < 0.01).Cows with greater concentrations of P4 at -4 d (> 3.04 ng/mL) had greater P/AI compared with cows with lower concentrations of P4 at -4 d (32.8 ± 4.4 % [53/153] vs. 22.4 ± 4.5 % [34/151]; P < 0.01). Cows with lower concentrations of P4 at the moment of timed AI (≤ 0.1 ng/mL) were more likely to become pregnant compared with cows that had greater concentrations of P4 at AI (35.2 ± 3.4 % [214/467] vs. 19.6 ± 4.6 % [40/143]; P < 0.001). Cows with greater concentration of P4 7 d post-AI (> 2.96 ng/mL) had greater P/AI compared with cows that had lower concentration of P4 7 d post-AI (39.1 ± 2.9 % [169/390] vs. 24.7 ± 2.6 % [108/387]; P < 0.001). Altogether, cows classified as HL had higher P/AI when compared with cows classified as LH, LL and HH (31.2 ± 2.1 [47/121] vs. 18.1 ± 2.8 [40/183] vs. 20.5 ± 4.1 [31/126] vs. 9.7 ± 4.9 [6/32]; P < 0.001). Parity and BCS were associated with pregnancy per AI. Multiparous cows had reduced P/AI compared with primiparous cows (32.2 ± 3.6% [133/280] vs. 46.5 ± 4.1% [131/361]; P < 0.01) and cows with high and moderate BCS had greater P/AI than cows with Low BCS (36.1 ± 1.9 % [136/309] vs. 31.7 ± 2.0 % [97/241] vs. 22.1 ± 3.0 % [30/87]; P < 0.001). No interaction between estrus intensity and parity was found on P/AI (P = 0.37); however, there was  107   an interaction between estrus intensity and BCS on P/AI (P = 0.05). Milk production had no effect on P/AI (P = 0.44). In Exp. 2, P/AI was influenced by estrous expression, BCS, and concentration of P4 at 0 d and tended to be influenced by concentrations of P4 at 7 d, 14 d and 21 d post-AI, but not by milk production or parity. Cows that expressed higher intensity or longer duration estrous expression had greater P/AI compared with those with lower intensity or shorter duration estrous expression at AI (High intensity: 39.9 ± 3.6 % [125/362] vs. Low intensity: 26.8 ± 2.6% [70/277]; P < 0.001; Long duration: 31.2 ± 2.5 % [126/412] vs. Short duration: 23.1 ± 3.2 % [56/227]; P < 0.001). Cows with lesser concentrations of P4 at 0d (≤ 0.26 ng/mL) had greater P/AI compared with cow with greater concentrations (31.8 ± 2.8 % [116/386] vs. 23.4 ± 3.2 % [71/278]; P < 0.01). Cows that had lower concentration of P4 at 7 d, 14 d and 21 d post-AI tended to have lower P/AI when compared to cows with greater concentrations of P4 (P = 0.10; Figure 4). Parity was not associated with pregnancy (P = 0.83) in Exp. 2. Body condition score was associated with P/AI (P < 0.001), as cows with High and Moderate BCS had greater P/AI than cows with Low BCS (32.9 ± 2.9 % [72/203] vs. 42.3 ± 4.6 % [102/234] vs. 19.5 ± 4.7 % [45/199]; P < 0.001). An interaction between estrus intensity and parity on P/AI was found (P < 0.001), as well as a tendency for an interaction between estrus intensity and BCS on P/AI (P = 0.10), as shown in Table 3. Milk production had no association with P/AI (P = 0.80).  5.4 Discussion  The aim of this study was to evaluate whether the concentration of P4 at different moments of the estrous cycle was associated the intensity of estrous expression at the end of a timed AI synchronization protocol or at spontaneous estrus and consequent association with P/AI. Overall,  108   we found that cows with a more ideal hormonal milieu had higher intensity of estrous expression and greater P/AI. Cows with greater concentrations of P4 just before luteolysis and on 7 d post-AI were more likely to have had greater intensity estrous expression at AI. Greater concentrations of P4 (Exp. 1 and 2) and lower concentrations of E2 (Exp. 2) at AI were associated with lower intensity estrous expression, detected by AAM. Altogether, the findings from the current study suggest that greater concentrations of P4 during the growth of the pre-ovulatory follicle, and a faster rise of P4 during the early stages of embryo development are in close association with the intensity of induced and spontaneous estrous expression. In addition, very low concentrations of P4 at AI, even in induced estrous events, was linked with estrous expression and fertility, suggesting an association between complete CL regression and the behavioural trigger of estrus in the hypothalamus.  Greater concentrations of P4 at -4 d were associated with a greater intensity of estrous expression and increased fertility. Progesterone concentrations during diestrus may be associated with the occurrence and the intensity of estrous expression, as P4 is known to prime the hypothalamus to be more responsive to E2 (Woelders et al., 2014), due to increased expression of estradiol receptors in the hypothalamus (Van Eerdenburg et al., 2000; Gümen and Wiltbank, 2002). Walker et al. (2008) reported that low P4 exposure before estrus, in chronically stressed lame cows, was asssociated with low intensity sexual behaviours during estrus. Exposure to P4 prior to estrus has also been shown to be crucial to the intensity of estrous expression in ewes (Fabre-Nys and Martin, 1991). Progesterone may cause up - or downregulation in the hypothalamus of a number of genes that are involved in the estrous behaviour, as E2 receptors. A study by Herlihy et al. (2012) demonstrated that lower concentrations of P4 during diestrus was associated with lower  109   fertility, as only a few cows (5.8%) with low P4 concentrations (< 2.0 ng/mL) at 11 d post-AI became pregnant. Progesterone can block the estrus-inducing actions of E2 and plays an important role in priming the bovine brain for E2 functions (Caraty et al., 2002; Boer et al., 2010). For example, in dairy cows, the first postpartum ovulation normally occurs with low expression of estrus behaviour partly due to higher concentrations of E2 during late gestation inducing a refractory state early post-partum that will not respond to the action of the E2, yet these refractory states have been shown to be alleviated by inducing increased P4 concentrations (Júnior et al., 2010). Increased estrous expression in timed AI protocols that include P4 also suggests that P4 may act as a primer for the responsiveness of the hypothalamus to E2 (Rhodes et al., 2002). Bisinotto et al. (2015) compared different timed AI protocols and reported that an addition of an intravaginal progesterone device in the first wave of follicle development increased the proportion of cows inseminated in estrus at the end of the timed AI. In both, Exp. 1 and Exp. 2, greater concentrations of P4 at AI were associated with lower intensity and duration of estrus and lower fertility. Pereira et al. (2016) reported that cows that did not express estrus at the end of a timed AI protocol were more likely to have higher concentrations of P4 compared with cows that expressed estrus. Higher concentrations of P4 at the moment of AI have also been associated with lower fertility (Pereira et al., 2016). It is known that P4 at estrus is required to be low, but there is limited research on how this hormone modulates the intensity of estrous expression at such low levels. A physiological mechanism that may reduce fertility when P4 is elevated at AI is that P4 may alter oocyte transport by altering uterine or oviductal contractility, thus reducing fertilization (Hunter, 2005). In addition, concentrations of P4 at AI could alter gamete transport; a study in rats demonstrated that the facilitation of sperm migration  110   into the oviduct is negatively affected by P4 (Orihuela et al., 1999). Cerri et al. (2011a) suggested that cows with low P4 prior to AI had increased basal LH concentrations, altering follicular dynamics that could in turn alter oocyte quality. Another hypothesis to explain lower fertility is that P4 could have detrimental impacts on embryo quality and development. When P4 was added to an in vitro fertilization protocol, it reduced the blastocyst percentage, suggesting that P4 may have a direct effect on early embryonic development (Silva and Knight, 2000). In addition, slight elevations in P4 are associated with reduced endometrial thickness (Silva and Knight, 2000), suggesting that the effects of P4 on the uterus could also reduce embryo development. In the present study, cows with a higher increase in estrous expression had higher concentrations of P4 post-AI (Exp. 1 – 7 d post-AI and Exp. 2 – 7 d, 14 d and 21 d post-AI) and greater P/AI. The concentration of P4 post-AI has been shown to affect fertility in lactating dairy cows (Lamming and Darwash, 1998; Lima et al., 2009; Pereira et al., 2014) and is a requirement for pregnancy maintenance (Inskeep, 2004). This positive effect of P4 post-AI on fertility may be due to impacts on the elongation of the conceptus (Garrett et al., 1988), early embryonic development (Bisinotto et al., 2010b), and increased secretion of interferon-tau (Mann and Lamming, 2001). Mann et al. (2006) observed that the insertion of an intravaginal P4 device between day 5 and 9 of the cycle caused an increase in embryo length 16 days after AI. However, P4 supplementation between days 12 and 16 post-AI did not increase the length of the embryo. Additionally, Demetrio et al. (2007) observed that cows that were bred by embryo transfer were not influenced by P4 concentrations, probably because the embryo is already developed when it is placed into the recipients. Together, this may suggest the critical period to benefit from greater concentrations of progesterone post-AI might be early within the estrous cycle.   111   The diameter of the pre-ovulatory follicle during the estrous cycle may also be a factor that contributes to concentrations of P4 after AI, as follicles with larger diameters have been shown to generate larger CLs, resulting in higher endogenous production of P4 (Vasconcelos et al., 2001; Mussard et al., 2007; Cerri et al., 2009b; Pereira et al., 2014). However, other studies have not always observed this relationship, as some have reported no difference in the concentration of P4 post-ovulation, even with differences in follicular diameter and the formation of CLs with larger diameters (Cerri et al., 2011a; b).  One important point from the current study is that the combination of P4 concentrations at different times of the estrous cycle is likely more important than just one measurement alone. For example, it was observed that combining different categories of -4 d and 0 d P4 concentrations can be associated with estrous expression and fertility outcomes. There is still need for more randomized trials to properly suggest cause-effect, but there is increasing evidence of the effect of P4 on the trigger and intensity of estrus. One study (Denis-Robichaud et al., 2018b), using long or short exposure times of P4 during the follicular growth phase, demonstrated that longer exposure to P4 was associated with numerically higher estrous expression. Animal related factors such as parity, BCS, and milk production have been consistently associated with estrous expression. In all cases, primiparous cows with higher BCS were more likely to express high intensity estrus; these cows are also more likely to have greater concentrations of circulating P4 and improved fertility (Sartori et al., 2004a). 5.5 Conclusion  The literature regarding the effect of circulating P4 prior to AI, at AI and post-AI on the intensity of estrous expression in cattle is limited. This research demonstrates that P4  112   concentrations around the time of AI are important for the expression of estrus for both timed AI and spontaneous estrus. As the intensity of estrus is associated with greater P/AI, future studies should determine if cows can be selected for their ability to maintain hormonal milieus (i.e. high concentration of P4 prior to AI, low concentration of P4 at AI and high concentration of P4 post-AI) associated with increased estrous expression and fertility.            113   Table 5.1: Intensity of estrous expression parameters, according to body condition score, parity and milk production. Variables Relative Increase1 Mean % ± SEM   [n] Maximum Activity Change2 (index) ± SEM [n]  Duration3 (h) ± SEM [n]     Body Condition Score4    <2.75 312.9 ± 9.8a[238] 72.1 ± 1.9a [199] 11.3 ± 0.5a [199]  ≥ 2.75 - 3.0 329.5 ± 6.4b[432] 77.9 ± 0.9ab [234] 12.9 ± 0.3b [234]  > 3.0 335.7 ± 6.2b[552] 36.7 ± 1.9b [203] 12.8 ± 0.5b [203]      Parity    Primiparous 332.5 ± 6.9a[527] 80.8 ± 1.3a [211] 13.5 ± 0.3a [211]  Multiparous 301.6 ± 5.5b[762] 73.8 ± 0.9b [404] 12.0 ± 0.2b [404]  Milk Production (kg/day)5     1st Quartile 280.6 ± 10.4ab [279] 80.9 ± 1.7a [141] 13.4 ± 0.7a [141] 2nd Quartile 300.4 ± 9.3a [324] 78.9 ± 1.5ax [163] 13.1 ± 0.5a [163] 3rd Quartile 295.3 ± 8.9ab [342] 75.4 ± 1.3by [221] 12.7 ± 0.3a [221]  114   a-cDifferent letters indicate differences between variables within the columns (P < 0.05). 1Relative increase in activity was calculated as the percentage increase in activity at estrus in relation to each cow’s own basal activity. 2Maximum activity change given by the neck-mounted accelerometer. 3Duration was calculate as the total time above the threshold for an alert of activity. 4Body Condition Score measure - 1 to 5 scale at 0.25 increments. 5 Milk production (kg/day) was classified according to the quartiles in Exp.1 (1st Quartile - ≤ 37.5; 2nd Quartile – 37.6 - 44.5; 3rd Quartile – 44.8 – 52.1; 4th Quartile - ≥ 52.2 kg/day) and in Exp.2 (1st Quartile - ≤ 28.3; 2nd Quartile – 28.3 - 35.9; 3rd Quartile – 36.0 – 44.8; 4th Quartile - ≥ 44.9 kg/day).   4th Quartile 276.9 ± 9.1b [344] 70.5 ± 1.7c [139] 11.1 ± 0.5b [139]  115   Table 5.2: Concentration of progesterone at AI and at 7 d post-AI, according to body condition score, parity and milk production on both Experiment 1 and Experiment 2.     Variables Concentration of P4 at AI (ng/mL) Concentration of P4 at 7d post-AI (ng/mL)  Experiment 1 Experiment 2 Experiment 1 Experiment 2 Body Condition Score1     < 2.75 0.27 ± 0.02a 0.26 ± 0.11a 2.53 ± 0.20a 3.22 ± 0.36x ≥ 2.75 - 3.0 0.19 ± 0.01bx 0.38 ± 0.06b 3.24 ± 0.10b 3.03 ± 0.21x > 3.0 0.23 ± 0.01ay 0.63 ± 0.10c 3.25 ± 0.10b 2.11 ± 0.21y Parity     Primiparous 0.20 ± 0.01x 0.32 ± 0.10x 3.24 ± 0.10a 3.32 ± 0.18a Multiparous 0.24 ± 0.01y 0.44 ± 0.04y 2.94 ± 0.10b 2.76 ± 0.19b Milk Production (kg/day)2     1st Quartile 0.23 ± 0.02 0.45 ± 0.10 2.83 ± 0.20 2.68 ± 1.31 2nd Quartile 0.22 ± 0.02 0.34 ± 0.09 3.06 ± 0.10 3.47 ± 0.33 3rd Quartile 0.21 ± 0.02 0.48 ± 0.06 3.07 ± 0.20 3.25 ± 0.45 4th Quartile 0.26 ± 0.02 0.45 ± 0.10 3.05 ± 0.20 4.05 ± 0.58 a-d Different letters indicate differences between variables within the columns (P < 0.05). x-y Different letters indicate a tendency between variables within the columns (P = 0.10). 1 Body Condition Score measure - 1 to 5 scale at 0.25 increments 2 Milk production (kg/day) was classified according to the quartiles in Exp.1 (1st Quartile - ≤ 37.5; 2nd Quartile – 37.6 - 44.5; 3rd Quartile – 44.8 – 52.1; 4th Quartile - ≥ 52.2 kg/day) and in Exp.2 (1st Quartile - ≤ 28.3; 2nd Quartile – 28.3 - 35.9; 3rd Quartile – 36.0 – 44.8; 4th Quartile - ≥ 44.9 kg/day).    116   Table 5.3: Pregnancy per AI, in both, Exp. 1 and Exp. 2 according to the interactions of estrus intensity and body condition score and the interaction of estrus intensity and parity. Variables Pregnancy per AI (%) ± SEM [n/n] Experiment 1 Pregnancy per AI (%) ± SEM [n/n] Experiment 2 Estrus intensity1 x BCS2   No Estrus   < 2.75 7.8 ± 6.2a [3/51] - ≥ 2.75 - 3.0 8.4 ± 5.9a [4/57] - > 3.0 5.6 ± 4.7a [3/59] - Low Estrus Intensity   < 2.75 17.5 ± 4.8a [13/87] 19.2 ± 6.4a [9/49] ≥ 2.75 - 3.0 30.1 ± 3.4bd [49/171] 24.4 ± 3.5a [39/168] > 3.0 36.9 ± 3.3cd [66/182] 35.6 ± 6.7b [18/46] High Estrus Intensity   < 2.75 36.2 ± 4.7bc [31/90] 19.9 ± 6.9a [8/43] ≥ 2.75 - 3.0 39.0 ± 2.9c [95/246] 34.1 ± 2.9b [80/256] > 3.0 42.2 ± 2.7c [114/274] 47.5 ± 7.8b [22/51] Estrus intensity x Parity    117    a-d Different letters indicate differences between variables within the columns (P < 0.05). 1 Intensity of estrous expression was quantified using the relative increase at estrus, and an estrus episode on was classified as No Estrus (< 100% relative increase in activity [RI]), Low intensity (100-299 % RI), and High intensity (≥ 300% RI). 2 Body Condition Score measure - 1 to 5 scale at 0.25 increments.          No Estrus   Primiparous 5.6 ± 4.7a [4/61] - Multiparous 6.1 ± 4.3a [6/106] - Low Estrus Intensity     Primiparous 32.6 ± 3.5c [56/164] 17.5 ± 5.7a [12/73] Multiparous 25.5 ± 2.6b [73/279] 26.2 ± 2.7a [49/183] High Estrus Intensity   Primiparous 44.3 ± 2.7d [125/272] 39.1 ± 4.5b [47/136] Multiparous 32.9 ± 2.4c [115/340] 33.0 ± 2.8b [56/199]  118   Figure 5.1: Schematic of the experimental design for Experiment 1 (Exp. 1; panel A) and Experiment 2 (Exp. 2; panel B). EB (estradiol benzoate; 2 mg, Gonadiol, Zoetis, São Paulo, Brazil), GnRH (gonadorelin diacetate; 100 μg, Cystorelin, Merial, São Paulo, Brazil), CIDR (intravaginal progesterone implant; 1.9 g progesterone; CIDR, Zoetis, São Paulo, Brazil), PGF (dinoprost tromethamine; 25 mg, Lutalyse, Zoetis, São Paulo, Brazil), ECP (estradiol cypionate; 1 mg, E.C.P., Zoetis, São Paulo, Brazil), Timed AI (artificial insemination), AI (artificial insemination, followed by spontaneous estrus using the am/pm rule; Exp. 2 only),US (examination of ovaries with ultrasonography), P4 (collection of blood sample for analysis of progesterone concentration), E2 (collection of blood sample of analysis of estradiol concentrations). Automated detection of estrus was done using a leg-mounted pedometer in Exp. 1 (Afimilk Pedometer Plus Tags; Afimilk, Kibbutz Afikim, Israel) and a neck-mounted accelerometer in Exp. 2 (Heatime®, SCR Engineers, Israel).         119    00.10.20.30.40.50.60.70.80.901234567835-40 41-50 51-60 61-70 71-80 81-90 91-100Concentration of Progesterone (ng/mL)Concentration of Estradiol (pg/mL)Index Activity E2 P4A)Figure 5.2: Distribution of increased estrous expression intensity (panel A) and duration (panel B) detected by a neck-mounted accelerometer at estrus and its association with the concentrations of progesterone and estradiol.  120             00.20.40.60.811.21.41.601234567892h 2 - 4h 4 - 6h 6 - 8h 8 - 10h 10 - 12h 12 - 14h 14 - 16h 16 - 30hConcentration of Progesterone (ng/mL)Concentration of Estradiol (pg/mL)Duration of acitivty E2 P4B) 121   Figure 5.3: Proportion of cows displaying greater and lesser estrous expression according to the concentration of P4 at -4 d (Experiment 1, Panel A; P < 0.01), and the concentration of P4 at 0 d (Experiment 1 and Experiment 2, Panel B; P < 0.01). A)          010203040506070No Estrus Low Intensity High IntensityFrequency of estrus events (%)Classification of Intensity of Estrous ExpressionGreater Concentration of P4 at -4dLower Concentration of P4 at -4d* * 122            0102030405060708090No Estrus LowIntensityHighIntensityLowIntensityHighIntensityShortDurationLongDurationRelative Increase - Experiment 1  Index - Experiment 2 Duration - Experiment 2Frequency of estrus events (%)Greater Concentration of P4 at AILower Concentration of P4 at AI** * ***B)  123   Figure 5.4: Concentrations of progesterone on the day of estrus alert (0 d; P < 0.01) and 7 d (P < 0.05), 14 d (P < 0.01), and 21 d (P < 0.01) post-AI relative to estrous expression intensity in Experiment 2. High intensity: estrous expression greater or equal to the median (80.5 index) of the automated activity monitor. Low intensity: estrous expression less than the median. 012345678Day of Alert 7d post-AI 14d  post-AI 21d post-AIConcentration of  Progesterone (ng/mL)High IntensityLow Intensity 124   Figure 5.5: Pregnancy per artificial insemination (%) according to the concentration of progesterone (P4) on days 7,14 and 21 post-AI (P = 0.10). Concentration of progesterone (P4) was classified as greater and lower concentration according to the median as follow: 7d post-AI = ≤ 2.65 and > 2.65 ng/mL; 14d post-AI = ≤ 3.12 and > 3.12 ng/mL; and 21d post-AI = ≤ 6.27ng/mL and > 6.27ng/mL).     0510152025303540LowerConcentrationGreaterConcentrationLowerConcentrationGreaterConcentrationLowerConcentrationGreaterConcentration[P4] 7d post-AI [P4] 14d post-AI [P4] 21d post-AIPregnancy per AI (%)8/52 17/60 8/56 20/61 9/50 19/61  125   6 Chapter 6: General Discussion 6.1 Thesis findings The overarching objective of this thesis was to investigate the association between estrous expression intensity as detected by automated activity monitors (AAM) and fertility outcomes in dairy cattle. The intensity of estrous expression could be used to predict fertility and assist in the decision making regarding reproductive management. Precision dairy farming and the usage of AAM in dairy industry were reviewed in Chapter 1. The fundamentals of estrous cycle and the base physiology of the cycle, including from breeding to early embryonic development to maternal recognition was also reviewed in the same Chapter. It is known that AAM are able to detect cows in estrus, and overall detection rates are about 75 to 90 % (Roelofs et al., 2005; Kamphuis et al., 2012; Dolecheck et al., 2015). However, the association of the occurrence and intensity of estrous expression with fertility outcomes in timed AI, super-ovulation and embryo transfer programs was limited. Previous studies have demonstrated that the occurrence of estrus on timed AI programs (Pereira et al., 2016) and intensity of estrous expression, in spontaneous estrus (Madureira et al., 2015) is associated with fertility in dairy cows. In Chapter 2, I reported that when using a timed AI synchronization protocol based on estradiol and progesterone with administration of estradiol cypionate, cows showed different intensities of estrus (as detected by an AAM) resulting in different ovulation rates, different fertility outcomes and different pregnancy losses. Cows demonstrating a greater intensity of estrous expression had greater ovulation rates, greater fertility and lower pregnancy losses compared with cows that had lower intensity or did not demonstrate  126   estrus at the end of the timed AI protocol. Furthermore, the intensity of estrus was associated with concentrations of progesterone 7 d post-AI, as cows with greater intensity of estrous expression had greater concentrations of P4, which may attribute to why they were also more likely to become pregnant. Thus, the use of AAM has the potential to identify the intensity of estrus associated with fertility outcomes. Interestingly, cows that had a lower intensity estrus were more likely to lose the pregnancy, which also may be partially explained by the lower concentrations of progesterone 7 d post-AI in cows with lower estrous expression. In conclusion, Chapter 2 demonstrated that occurrence and intensity of estrous expression at the end of a timed AI improved ovulation rates, pregnancy per AI and reduced pregnancy losses in cows. The improvement in fertility with increased estrous expression linked with reduced pregnancy loss suggest that the endometrium environment is affected by the same mechanisms related to intensity of estrus. Also, it was interesting that although all cows received the same dose of estradiol cypionate, there was a large variation in the intensity of estrous expression, showing that there may be variation in the receptors for estradiol in the brain.  Protocols used for stimulating multiple ovulations have been important breeding technologies for the dairy industry, accelerating gains in genetic progress. Although the intensity of estrus measured by automated activity sensors has been associated with improvements in fertility of dairy cows submitted to AI using both synchronization protocols and at spontaneous estrus, little research has been carried out on the association between estrous expression and the success of embryo process, either for the production of embryos (donors) or for recipient cows. Thus, the objectives of Chapter 3 and 4 were to determine the association between estrous expression and success of embryo collection from super-ovulated Holstein heifers (Chapter 3) and  127   the success of embryo transfer within recipient cows (Chapter 4). Chapter 3 showed that heifers with higher intensity of estrus produced a greater percentage and number of viable embryos compared. It is unknown from this study if these effects are due to the impacts of estrous expression prior to or after ovulation. Chapter 4 showed that both the intensity of estrous expression, and the occurrence of estrus prior to embryo transfer, improved fertility. These results could be used to improve reproductive management, providing a relatively low-cost strategy to improve efficiencies of a high-cost technology. As expected, cows that received an in vitro fertilized embryo had lower fertility compared with in vivo embryo, either fresh or frozen. However, we found no evidence of an interaction between estrous expression and embryo transfer method on pregnancy. Additionally, we found that cows receiving embryos at the blastocyst and initial blastocyst stages had greater fertility compared with cows receiving embryos at the morula stage. Although there was no interaction between estrous expression and the stage of embryo development on pregnancy, cows that displayed estrus and received an embryo which was a morula or initial blastocyst had greater pregnancy rates than cows which did not display estrus. Overall, Chapter 4, demonstrated that the occurrence and the intensity of estrous expression at end of a timed AI protocol improved pregnancy per ET.  Chapter 5 demonstrated that concentrations of progesterone surrounding estrus were associated with the intensity of estrus and fertility. Progesterone is required for pregnancy maintenance. This study aimed to evaluate the association between the concentration of P4 around the time of estrus and the intensity of estrus (as measured by AAM), and fertility. Greater concentrations of P4 and lower concentrations of E2 at AI were associated with lower intensity estrous, and higher concentrations of P4 prior to AI were associated with greater estrous expression  128   and fertility. Progesterone concentration at 7d post-AI was impacted by the intensity of estrus and was also positively associated with pregnancy per AI. We therefore concluded that the improvement in fertility associated with the intensity of estrous behaviour may be explained by the changes in P4 and E2 found around estrus. 6.2 Implications and future directions Technologies have been developed to help detect estrus in cattle and are now considered a useful tool for dairy farms. Together the results reported in this thesis indicate that AAM can be used for reproductive management and breeding decisions, as the likelihood of cows becoming pregnant when they do not express estrus or have reduced estrous expression at the end of a timed AI protocol, is very low. Chapters 2 and 4 showed that the occurrence and the intensity of estrous expression, detected by the sensors, was associated with fertility; specifically, cows with greater intensity of estrus had greater fertility. Timed AI protocols were developed with the intention of helping cows get pregnant, and these also helped researchers understand the basic physiology of the estrus cycle. A variety of ovulation synchronization protocols have been developed which minimize time and labor and have positive results in terms of fertility. One of the main selling points of a synchronization protocol is that there is no longer a need to detect estrus, a process that can be time consuming and thus costly. The results presented in Chapter 2 and 4 suggest that this point should be reconsidered, as cows that did not express estrus at the end of a timed AI protocol had a very low pregnancy per AI (6.2 % [10/181]) and pregnancy per ET (11.3 % [26/218]). I thus conclude that it is important to monitor estrus even when using timed AI protocols.   129   Chapter 3 reported that, under a superovulation protocol for embryo collection, heifers (showing greater estrous expression were more likely to have viable embryos suitable for embryo transfer. Superovulation protocols were established in the dairy industry in the early 1970s and have been an efficient way to increase the number of offspring from genetically superior females. The efficiency of this process has not improved over the years; the average number of transferable embryos, in a single embryo collection, has remained constant at approximately 6 embryos per donor (Bó et al., 2019). There are many factors that may impact success, such as animal related factors, the environment and management. However, the effect of the occurrence and intensity of estrous expression has not been previously examined. The results from the current study provide evidence that the occurrence and intensity of estrous expression, could be a tool to predict super-ovulatory responses as well as embryo quality in Holstein heifers and could be used to assist in decision making of reproduction management. In Chapter 4, the intensity and the occurrence of estrus prior at end of an ovulation synchronization protocol improved pregnancy per ET. Pregnancy per ET was affected by the stage of embryo development, as cows receiving embryos in the blastocyst and initial blastocyst stage had greater fertility compared with cows receiving embryos in the morula stage. Cows that displayed estrus and received an embryo in a morula or initial blastocyst had greater pregnancy/ ET than cows which did not display estrus. Studies have shown that embryo transfer can be applied to dairy herds to improve fertility, as it can minimize problems during early embryonic development and problems associated with quality of the oocyte and follicular dominance. There is extensive literature on the factors that affect pregnancy outcomes after an embryo transfer in dairy cattle. However, very few studies have focused on the effect of the occurrence and the  130   intensity of estrous expression in recipient lactating dairy cows and its association with fertility outcomes. Future studies are needed to understand if an embryo that comes from a donor that had higher intensity estrous is more likely to survive in the recipient cow, independent of her estrus intensity. Together, Chapters 2, 3 and 4 provide evidence that AAM can contribute to improve reproductive management, as sensors are able to give important information related to the occurrence of estrus (at the end of a timed AI, super-ovulation and embryo transfer protocols), and can inform reproductive management decisions. Specific breeding decisions that producers can apply relative to the information collected from the monitors still need to be studied. To date there is no research describing the economic viability of inseminating a cow that has reduced estrous expression, knowing that the likelihood of pregnancy is low and that there are greater chances of pregnancy loss. Greater economic losses occur in cows that have greater calving to conception intervals. Different strategies could be used to inseminate cattle at spontaneous estrus, in a synchronization protocol, and or within a synchronization protocol for embryo collection (for both the donor and recipient stage). A strategy at the moment of AI, for cows that have lower intensity of estrous expression, could be the use of a single administration of GnRH at AI (as an inducer of ovulation). A recent study from our laboratory showed that GnRH can benefit cows that have lower intensity of activity at the moment of AI by increasing pregnancy per AI. Another strategy that could be implemented is the use of beef semen for those cows with reduced estrous expression. Using beef semen in dairy herds allows farmers to produce crossbred calves whose carcasses are more valuable than those of purebred calves (Wolfová et al., 2007). Beef semen has different quality and fertility compared to dairy semen (Borges-Silva et al., 2016; Morrell et al., 2018) and  131   lately has been used in dairy herds for cows that are repeat breeders. In addition to these options, there are many other applicable strategies that could be used at the moment of AI (e.g. enroll the cow into a synchronization protocol; use a poor-quality semen [unproved sires and cheaper semen], etc.). The same thought process would also work for cows showing greater estrous expression, as cows having a greater intensity of estrus are more likely to become pregnant and retain the pregnancy, reducing the risk associated with expensive technologies such as embryo transfer, super-ovulation protocols and sires with better genetics. These strategies could be used as individualized management, reducing blanket treatments and using hormonal protocols more efficiently. However, there is currently no research on the effect of these strategies and the long-term economic impact of introducing these strategies into the herd. Resumption of early post-partum cyclicity within the voluntary waiting period is associated with improved reproductive performance (Santos et al., 2009; Dubuc et al., 2011). A delayed resumption of cyclicity reduces fertility and is associated with an increased risk of pregnancy loss (Gümen and Seguin, 2003). Even though resumption of cyclicity has been shown to impact fertility and overall farm profitability, cows are not routinely diagnosed for anestrous. Assessing cyclicity is time consuming, as circulating concentrations of P4 need to be analyzed or the visualization of a CL using ultrasound needs to be performed.  In addition to resumption of cyclicity early in the postpartum period, a closely monitored estrous cycle is important in determining time for AI. Lopez et al. (2004) reported that cows in the first postpartum preovulatory follicular phase (estrus) stood to be mounted for a shorter time and mounted others less often than did cows in subsequent phases. In the study by Aungier et al. (2012), progesterone concentrations were used to detect the resumption of postpartum reproductive  132   activity and occurrence of estrus. These authors reported that an AAM worked better for detecting second or subsequent preovulatory follicular phases postpartum, but the first preovulatory follicular phase postpartum was rarely detected. However, these authors also report that those first preovulatory follicular phases that were detected tended to have a shorter duration and a lower peak activity than second or subsequent preovulatory follicular phase. Thus, future research could investigate the use of varying thresholds depending on the stage of lactation, with the objective of detecting estrus events early postpartum that currently may be missed.  The association between the concentrations of P4 at different moments of the estrous cycle and the intensity of spontaneous or estrogen-induced estrous expression, was described in Chapter 2 and Chapter 5. Concentrations of P4 prior to and at AI were associated with greater estrous intensity and fertility. Studies have reported that cows that did not express estrus at the end of a timed AI protocol were more likely to have had higher concentrations of P4 at AI compared with cows that expressed estrus (Pereira et al., 2016). Progesterone concentrations at 7 d post-AI were associated by the intensity of estrus and was also positively associated with pregnancy per AI, in spontaneous estrus (no hormonal intervention) and at the end of timed AI protocols. Overall, the biological mechanism linking estrous expression and fertility is unclear but is likely associated with the hormonal milieu during diestrus and proestrus, as both progesterone and estradiol play important roles in the development of the oocyte and the receptivity of the uterus and are associated with differences in the occurrence and expression of estrus. Numerous studies have demonstrated the effects of P4 at AI, and immediately after AI, on fertility. However, the literature regarding the association between circulating P4 pre-luteolysis, at AI and post-AI, and the intensity of estrous expression in cattle is limited.   133   As previously discussed in Chapter 5, P4 concentration during diestrus may be associated with the occurrence of estrus and the intensity of estrous expression, as P4 primes the hypothalamus, making it more responsive to E2 and the occurrence of estrous expression (Woelders et al., 2014). Timed AI protocols synchronize ovulation and not necessarily estrus or estrus intensity. Estrous expression may be enhanced by altering the hormone milieu during the diestrus. Cows that had greater P4 concentrations at the beginning of an ovulation-synchronization program (i.e. during diestrus) had more pregnancy per AI compared with cows with lesser concentrations (Bisinotto et al., 2010a; Stevenson and Pulley, 2016). Future studies should assess the effect of different concentrations of P4 during a synchronization protocol on the occurrence and on the intensity of estrous expression. This will give us a better understanding of why some cows have different intensities of estrus for both spontaneous and synchronized events.  6.3 Strengths and limitations This thesis provides some of the first evidence of an association between estrous expression and ovulation, pregnancy losses, the viability of embryos and fertility. These results provide further evidence that measures of estrous expression (including at spontaneous estrus, timed AI and superovulation programs) may provide a useful predictor of fertility. This thesis contributes to the literature regarding the association between estrous expression and fertility, and the integration of AAM into synchronization programs. The associations found in this thesis, also contribute to our understanding of the use of AAM data to improve reproductive management in dairy herds.  One limitation is that the studies conducted were all observational rather than randomized, controlled experiments. The research of Chapter 2 and 4 required a large number of inseminations  134   and embryo transfers to reliably assess ovulation rates and fertility outcomes; this sample size would be difficult to achieve in a randomized controlled experiment. Another limitation is that due to the experimental design of both Chapter 3, in which we were not able to conclude the stage of embryo development for which estrous expression is most relevant. Specifically, we were not able to determine if estrous expression was beneficial for oocyte quality prior to ovulation, fertilization post ovulation, or embryo development until 7 d post AI. Another limitation is that for some of the studies presented in this thesis we were not able to collect blood samples for analysis of steroidal hormones that are important for estrous expression, pregnancy and pregnancy loss. 6.4 General conclusions In conclusion, automated activity monitors are helpful tools that can be easily implemented in dairy herds. The use of these technology can be incorporated in reproductive management, for spontaneous estrus, timed AI, super-ovulation and embryo transfer programs. The intensity of estrous expression, detected by the monitors, can be used to predict ovulation failure, quality and viability of embryos, fertility and pregnancy losses. Further research is needed to incorporate individual cow-factors into the AAM algorithms to better predict the intensity of estrous expression.      135   References Adams, G.P., R.L. Matteri, J.P. Kastelic, J.C.H. Ko, and O.J. Ginther. 1992. 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