Animal Science Papers and Research

Permanent URI for this collection

https://hdl.handle.net/1813/40574

Browse

Now showing 1 - 10 of 24

Supplemental Material - Delaying induction of ovulation and timed AI in a Double-Ovsynch protocol increased expression of estrus and altered first service reproductive outcomes of lactating dairy cows
A. L. Laplacette, C. Rial, E. Sitko, M.M. Perez, S. Tompkins, M. L. Stangaferro, M. J. Thomas, J. O. Giordano (Elsevier, 2024-10-14)
The objective of this randomized controlled experiment was to evaluate the effect of delaying induction of ovulation and timed artificial insemination (TAI) on expression of estrus before AI and first service reproductive outcomes. A secondary objective was to evaluate the effects of delaying induction of ovulation in a Double-Ovsynch protocol on ovarian function. Lactating Holstein cows (n = 4,672) from 2 commercial dairy farms fitted with sensors for automated detection of estrus were synchronized with a Double-Ovsynch protocol up to the first PGF2α (PGF-L) of the Breeding-Ovsynch portion of the protocol (Pre-Ovsynch: GnRH, 7 d later PGF2α, 3 d later GnRH, 7 d later Breeding-Ovsynch: GnRH, 7 d later PGF2α, 1 d later PGF2α). At PGF-L, cows blocked by parity (primiparous vs. multiparous) and semen used for first service (sex-sorted dairy vs. conventional beef) were randomly assigned to the G56 (n = 2,338) or G80 (n = 2,334) treatments. Cows in G56 had 56 h whereas cows in G80 had 80 h from PGF-L to induction of ovulation with the last GnRH (GnRH2) before AI. For both treatments, TAI occurred ∼16 h after GnRH2. All cows with automated estrus alerts between PGF-L and TAI were inseminated at detected estrus (AIE) without GnRH. Ovarian function and responses to synchronization were monitored based on circulating concentrations of progesterone and examination of the ovaries by ultrasonography. Data for binary outcomes were analyzed by logistic and continuous outcomes with lineal regression. More cows in G80 received AIE and had estrus before AI. Overall, pregnancies per AI (P/AI) did not differ for the G80 and G56 treatments. Cows in G80 that received TAI and had no estrus had fewer P/AI than cows with estrus that received AIE or TAI in G80, and fewer P/AI than cows AIE and cows that received TAI and had or did not have estrus in the G56 treatment. No differences were observed between treatments or for cows with and without estrus for pregnancy loss. Unlike some minor differences between treatments for concentrations of progesterone at GnRH2, the most notable differences in ovarian function were for cows in both treatments with or without estrus that received TAI. Cows with estrus, were more likely to have follicles > 16 mm, had larger follicles before ovulation, and had a greater ovulation risk after AI. Likewise, within the G80 treatment only, cows with estrus that received AIE or TAI had larger follicles, were more likely to have complete luteal regression, had greater ovulation risk, were more likely to have a functional corpus luteum, and had more circulating progesterone after AI. We concluded that delaying induction of ovulation and TAI was effective for allowing more cows to express estrus before AI which had different ovarian function outcomes and greater P/AI than cows that did not express estrus. However, the greater P/AI of cows that expressed estrus was insufficient to compensate for the reduced P/AI of cows that did not express estrus, and thus increase overall P/AI compared with the treatment without delayed induction of ovulation. Detection of estrus before AI in cows undergoing synchronization of ovulation could help identify cows with different likelihoods of pregnancy after insemination.
SemenSolver: A tool to support dairy herd semen strategy under varying replacement needs
Adamchick, J.; Briggs, K. R.; Nydam, D. V. (2024-09-10)
Improved reproductive technologies and management have enabled dairy herds to produce more female calves than they need. One emerging strategy is to select a subset of superior animals to produce the next generation of herd replacements while breeding the others for off-farm value (often to beef semen). It is complex to anticipate how today’s breeding choices will impact herd inventory three years from now and it is costly to wind up with too few replacements to keep the dairy herd full with the most productive cows. We created the SemenSolver spreadsheet as a tool to guide week-by-week semen choices, customized for a specific farm, to capitalize on crossbred beef markets while maintaining the replacement supply to support herd size and performance.
SemenSolver spreadsheet
Adamchick, J.; Briggs, K. R.; Nydam, D. V. (2024-09-10)
Improved reproductive technologies and management have enabled dairy herds to produce more female calves than they need. One emerging strategy is to select a subset of superior animals to produce the next generation of herd replacements while breeding the others for off-farm value (often to beef semen). It is complex to anticipate how today’s breeding choices will impact herd inventory three years from now and it is costly to wind up with too few replacements to keep the dairy herd full with the most productive cows. We created the SemenSolver spreadsheet as a tool to guide week-by-week semen choices, customized for a specific farm, to capitalize on crossbred beef markets while maintaining the replacement supply to support herd size and performance. Factsheet can be found here.
A randomized controlled trial of the effect of automated health monitoring based on rumination, activity, and milk yield alerts versus visual observation on herd health monitoring and performance outcomes
C. Riala, M. L. Stangaferrob, M. J. Thomasb, and J. O. Giordanoa (Elsevier, 2024-09-24)
A primary objective of this randomized trial was to compare the percentage of cows that underwent clinical examination and were diagnosed with clinical health disorders (CHD) with a health monitoring program that relied only on automated monitoring system alerts vs a program that relied only on visual observation of clinical signs of disease to select cows for clinical examination. Another objective was to compare the effects of these health monitoring programs on milk yield, the herd exit dynamics (i.e., cows sold and dead), and first service reproductive outcomes. Lactating Holstein cows (n = 1,204) enrolled in the experiment were fitted with a neck-attached sensor of an automated monitoring system (HR Tags; Merck & Co., Inc) that generated health alerts based on rumination time and activity. Milk yield was monitored three times per day by automated milk meters (MM27BC, DeLaval). Cows were blocked by parity, close-up period diet, and stratified by previous lactation milk yield, and then were randomly assigned within block to different programs for monitoring health from 3 to 21 d in milk (DIM). Cows in the visual observation group (VO; n = 597) were selected for clinical examination exclusively based on visual observation of clinical signs of disease, whereas cows in the automated health monitoring group (AHM; n = 607) were selected for clinical examination based on health alerts consisting of the following: a Health Index Score <86 arbitrary units, daily rumination <250 min, or a reduction of >20% in daily milk yield. Once selected for examination, the clinical exam was the same for both treatment groups. Binary data such as the occurrence of CHD, herd exit, and pregnancies per AI were analyzed with logistic regression. Daily and weekly milk yield were analyzed using ANOVA with repeated measurements. More cows underwent a clinical examination, more cows were diagnosed with at least one CHD, and more cows received treatment in the AHM than the VO treatment group. Cows in the AHM treatment had more accumulated milk than cows in the VO treatment from 2 to 21 DIM. Cows in the AHM treatment diagnosed with at least one CHD produced more milk from 3 to 18 and 20 to 21 DIM than cows diagnosed with a CHD in the VO treatment. Fewer cows left the herd up to 21 DIM for the AHM than the VO treatment. Pregnancies per AI at first service were greater for the VO than the AHM treatment at 30 d but not at 50 d after AI and no difference in pregnancy loss was detected. In conclusion, a health monitoring strategy that used automated health alerts increased the risk of undergoing clinical examination and having CHD diagnosed compared with a program that selected cows for clinical examination based exclusively on visual observation. Cows monitored with the program that relied on automated alerts also had greater milk yield in the first 21 DIM. Thus, monitoring cow health based on automated behavior and milk yield alerts might be a more effective alternative for health monitoring than exclusive use of visual observation of clinical signs of disease.
Comparison of Social Behavior and Housing Condition Effects on Sociability Scores in LEWES and NY3 Mouse Lines Using a Three-Chamber Paradigm Test
Bayrakdarian, Sylvia (2023-05)
Studying social behavior in mice is a crucial area of research in neuroscience, providing insights into information transmission between conspecifics and modulators of their behavior in addition to identifying what these social signals may control. However, little research has been done to compare social behaviors amongst strains of wild-derived mice such as NY3 and LEWES, which have been bred from mice caught in the wild compared to the typically utilized laboratory strains bred for generations within the laboratory. The objective of this research project is to differentiate between social behaviors, as measured by sociability scores, in these mouse lines using a three-chamber paradigm test (3CT). The study also aims to assess the effects of housing conditions, specifically between single-housing and pair-housing, on sociability given the implications of isolation as a social stressor, and thus making it important to understand the impact of housing conditions on social behavior in these mouse lines. The three-chamber paradigm test is a commonly used technique used for studying social behavior in mice which involves placing a test mouse in a chamber with three compartments and giving it the opportunity to interact with either a stranger mouse, the social stimulus, or an inanimate object, the non-social stimulus. The subsequently derived sociability score is a measure of how much time the test mouse spends in the compartment with the social stimulus compared to the time spent with the non-social stimulus, and is ultimately used as a measure of social behavior in mice. The outcomes of this study may be of significant value in future behavioral studies involving these or genetically similar mouse strains, as they may provide insight into the determinants of sociability and the ways in which housing conditions may affect such social behaviors.
Supplementary figures for Reproductive physiological outcomes of dairy cows with different genomic merit for fertility: biomarkers, uterine health, endocrine status, estrus features, and response to ovarian synchronization
Sitko, Emily; Laplacette, Ana; Duhatschek, Douglas; Rial, Clara; Perez, Martin M.; Tompkins, Sheridan; Kerwin, Allison L.; Giordano, Julio O. (Journal Dairy Science, 2024-06-07)
Our overarching objective was to characterize associations between genomic merit for fertility and the reproductive function of lactating dairy cows in a prospective cohort study. In this manuscript, we present results of the association between genomic merit for fertility and indicators of metabolic status and inflammation, uterine health, endocrine status, response to synchronization, and estrous behavior in dairy cows. Lactating Holstein cows entering their first (n = 82) or second (n = 37) lactation were enrolled at parturition and fitted with an ear-attached sensor for automated detection of estrus. Ear-notch tissue samples were collected from all cows and submitted for genotyping using a commercial genomic test. Based on genomic predicted transmitting ability values for daughter pregnancy rate (gDPR) cows were classified into a high (Hi-Fert; gDPR >0.6; n = 36), medium (Med-Fert; gDPR -1.3 to 0.6; n = 45), and low (Lo-Fert; gDPR <-1.3; n = 38) group. At 33 to 39 d in milk (DIM), cohorts of cows were enrolled in the Presynch-Ovsynch protocol for synchronization of estrus and ovulation. Body weights, body condition scores (BCS), and uterine health measurements (i.e., vaginal discharge, uterine cytology) were collected from parturition to 60 DIM and milk yield was collected through 90 DIM. Blood samples were collected weekly through 3 wk of lactation for analysis of β-hydroxybutyrate, non-esterified fatty acids, and haptoglobin plasma concentrations. Body weight, BCS, NEFA, BHB, and Haptoglobin were not associated with fertility groups from 1 to 9 wk after parturition. The proportion of cows classified as having endometritis at 33 to 36 DIM tended to be greater for the Lo-Fert than the Hi-Fert group. The proportion of cows that resumed cyclicity did not differ at any timepoint evaluated and there were no significant associations between probability or duration and intensity of estrus with fertility group. Cows of superior genetic merit for fertility were more likely to ovulate, have a functional CL, have greater circulating P4, and have larger ovulatory size than cows of inferior fertility potential at key time points during synchronization of estrus and ovulation. Despite observing numerical differences with potential performance consequences for the proportion of cows that responded to synchronization of ovulation and were both cyclic and responded to the Ovsynch portion of the synchronization protocol, we did not observe significant differences between fertility groups. Although not consistent and modest in magnitude, the collective physiological and endocrine differences observed suggested that cows of superior genetic fertility potential might have improved reproductive performance, at least in part, because of modestly improved endocrine status, uterine health, and ability to ovulate
The ovarian function and endocrine phenotypes of lactating dairy cows during the estrous cycle were associated with genomic-enhanced predictions of fertility potential
Sitko, Emily; Laplacette, Ana; Rial, Clara; Duhatschek, Douglas; Giordano, Julio O.; Perez, Martin M.; Tompkins, Sheridan; Kerwin, Allison L.; Wiltbank, Milo C.; Domingues, Rafael R. (Journal of Dairy Science, 2024-04-29)
The objectives of this prospective cohort study were to characterize associations among genomic merit for fertility with ovarian and endocrine function and the estrous behavior of dairy cows during an entire, non-hormonally manipulated estrous cycle. Lactating Holstein cows entering their first (n = 82) or second (n = 37) lactation had ear-notch tissue samples collected for genotyping using a commercial genomic test. Based on genomic predicted transmitting ability values for daughter pregnancy rate (gDPR) cows were classified into a high (Hi-Fert; gDPR >0.6 n = 36), medium (Med-Fert; gDPR -1.3 to 0.6 n = 45), and low fertility (Lo-Fert; gDPR <-1.3 n = 38) group. At 33 to 39 DIM, cohorts of cows were enrolled in the Presynch-Ovsynch protocol for synchronization of ovulation and initiation of a new estrous cycle. Thereafter, the ovarian function and endocrine dynamics were monitored daily until the next ovulation by transrectal ultrasonography and concentrations of progesterone (P4), estradiol, and FSH. Estrous behavior was monitored with an ear-attached automated estrus detection system that recorded physical activity and rumination time. Overall, we observed an association between fertility group and the ovarian and hormonal phenotype of dairy cows during the estrous cycle. Cows in the Hi-Fert group had greater circulating concentrations of P4 than cows in the Lo-Fert group from day 4 to 13 after induction of ovulation and from day -3 to -1 before the onset of luteolysis. The frequency of atypical estrous cycles was 3-fold greater for cows in the Lo-Fert than the Hi-Fert group. We also observed other modest associations between genomic merit for fertility with the follicular dynamics and estrous behavior. There were several associations between milk yield and parity with ovarian, endocrine, and estrous behavior phenotypes as cows with greater milk yield and in the second lactation were more likely to have unfavorable phenotypes. These results demonstrate that differences in reproductive performance between cows of different genomic merit for fertility classified based on gDPR may be partially associated with circulating concentrations of P4, the incidence of atypical phenotypes during the estrous cycles, and to a lesser extent the follicular wave dynamics. The observed physiological and endocrine phenotypes might help explain part of the differences in reproductive performance between cows of superior and inferior genomic merit for fertility.
Combining reproductive outcomes predictors and automated estrus alerts recorded during the voluntary waiting period identified subgroups of cows with different reproductive performance potential
Rial, Clara (Elsevier, 2024-03-11)
The objective was to compare differences in reproductive performance for dairy cows grouped based on the combination of data for predictors available during the prepartum period and before the end of the VWP, automated estrus alerts (AEA) during the VWP, and the combination of both factors. In a cohort study, data for AEA and potential predictors of the percentage of cows inseminated in estrus (AIE) and pregnancies per AI (P/AI) for first service, and the percentage of cows pregnant by 150 DIM (P150) were collected from -21 to 49 DIM for lactating Holstein cows (n=886). The association between each reproductive outcome with calving season (cool, warm), calving-related events (yes, no), genomic daughter pregnancy rate (gDPR; high, medium, low), days in the close-up pen (ideal, not ideal), health disorder events (yes, no), rumination time (high or low CV prepartum and high or low increase rate postpartum), and milk yield (MY) by 49 DIM (high, medium, low) were evaluated in univariable and multivariable logistic regression models. Individual predictors (health disorders, gDPR, and MY) associated with the three reproductive outcomes in all models were used to group cows based on risk factors (RF; yes, n=535 or no, n=351) for poor reproductive performance. Specifically, cows were included in the RF group if any of the following conditions were met: the cow was in the high MY group, had low gDPR, or had at least one health disorder recorded. Cows were grouped into estrus groups during the VWP based on records of AEA (E-VWP, n=476 or NE-VWP, n=410). Finally, based on the combination of levels of AEA and RF cows were grouped into an estrus and no RF (E-NoRF, n=217), no estrus and RF (NE-RF, n=276), no estrus and no RF (NE-NoRF, n=134), and estrus and RF (E-RF, n=259) groups. Cows received AIE up to 31 d after the end of the VWP, and if not AIE, received timed AI after an Ovsynch plus progesterone protocol. Logistic and Cox proportional hazard regression compared differences in reproductive outcomes for different grouping strategies. The NoRF (AIE:76.9%; P/AIE:53.1%; P150:84.5%) and E-VWP (AIE:86.8%; P/AIE:44.8%; P150:82.3%) groups had more cows AIE, P/AI, and P150 than the RF (AIE:64.5%; P/AIE:34.9%; P150:72.9%) and NE-VWP (AIE:50.0%; P/AIE:38.9%; P150:72.1%) groups, respectively. When both factors were combined, the largest and most consistent differences were between the E-NoRF (AIE:91.3%; P/AIE:58.7%; P150:88.5%) and NE-RF groups (AIE:47.3%; P/AIE:35.8%; P150:69.5%). Compared with the whole population of cows or cows grouped based on a single factor, the E-NoRF and NE-RF groups had the largest and most consistent differences with the whole cow cohort. The E-NoRF and NE-RF group also had statistically significant differences of a large magnitude when compared with the remaining cow cohort after removal of the respective group. We conclude that combining data for AEA during the VWP with other predictors of reproductive performance could be used to identify groups of cows with larger differences in expected reproductive performance than if AEA and the predictors are used alone.
Effects of targeted clinical examination based on alerts from automated health monitoring systems on herd health and performance of lactating dairy cows
M. M. Perez, E. M. Cabrera, and J. O. Giordano (Journal of Dairy Science, 2023-07-05)
Our objectives were to compare the proportion of lactating dairy cows diagnosed with health disorders (HD) and herd performance when using a health monitoring program designed to rely primarily but not exclusively on alerts from automated health monitoring (AHM) systems or a health monitoring program based primarily on systematic clinical examinations, milk yield monitoring, and visual observation of cows. In a clinical trial, at ~30 d before expected parturition, nulliparous and parous Holstein cows, stratified by parity and days in gestation, were randomly assigned to the high intensity clinical monitoring (HIC-M; n = 625) or automated monitoring (AUT-M; n = 624) treatment. Cows were fitted with a neck-attached rumination and physical activity monitoring tag and individual daily milk yield data was collected from parlor milk meters. For cows in HIC-M, clinical examination was conducted daily until 10 days in milk (DIM) and then in response to milk yield reduction alerts or visual observation of clinical signs of HD in the course of 21 DIM. For cows in AUT-M, clinical examination until 21 DIM was because of health index (HI) score alerts generated with a combination of rumination time and physical activity and reduced milk yield alerts. Visual observation of clinical signs of HD was used for identifying cows potentially missed by automated alerts. Binomial and quantitative data were analyzed by logistic regression and ANOVA with repeated measures, respectively. The percentage of cows diagnosed with at least one HD during the experimental treatments risk period tended to be greater and the incidence rate ratio of HD diagnosed was greater for the HIC-M than AUT-M treatment. There was no difference between treatments for cows that exited the herd to 60 or 150 DIM, but there tended to be more cows that exited the herd from 61 to 150 DIM for the HIC-M than the AUT-M treatment. There were no differences between treatments for daily or total milk yield to 21 DIM or for weekly mean milk yield and total milk yield to 150 DIM. More cows were inseminated in estrus for first service if in the HIC-M treatment and had no HD diagnosed than if in the HIC-M treatment but with HD diagnosed, or in the AUT-M treatment and had no HD diagnosed. Cows in the AUT-M treatment with HD diagnosed did not differ from other groups. No differences between treatments were observed for pregnancies per AI or pregnancy loss for first service. Despite a reduction in the risk of diagnosis of HD, there was no evidence that a health monitoring program that relied on AHM systems alerts to select cows for clinical examination reduced herd performance when compared with a more intensive program that included systematic clinical examinations of all cows for the first 10 DIM, reduced milk yield alerts, and visual observation. However, to obtain the same herd performance than with the HIC-M treatment, the AUT-M treatment required use of VO. In conclusion, a health monitoring program designed to rely primarily on targeted clinical examination based on alerts from automated health monitoring systems might be a feasible alternative to programs that rely more on clinical examination provided that visual observation is used to identify cows not detected by automated alerts.
Characteristics of the Beef x Dairy Industry in New York State: A summary of survey data collected from New York State farmers in 2020-2021
Quaassdorff, Margaret; Hicks, Betsy (2023-07)
Data presented in this white paper are from a Qualtrics survey conducted online between the months of October 2020 and June 2021. Farmers were surveyed to assess how they utilize beef sires in their dairy herds, their criteria in selecting dairy animals to breed to beef sires, and sire selection criteria. Farmers were also surveyed on their management practices of producing, raising, marketing and selling BxD cattle, as well as information needed. The survey was open to all farmers in New York State who had an interest in, or were currently producing or growing, BxD animals.

Browse

Recent Submissions