@article{lauber_peñagaricano_fourdraine_clay_fricke_2023, title={Characterization of semen type prevalence and allocation in Holstein and Jersey females in the United States}, url={https://doi.org/10.3168/jds.2022-22494}, DOI={10.3168/jds.2022-22494}, abstractNote={Our objective was to characterize semen type prevalence and allocation to inseminate US Holstein and Jersey females by year, parity, service number, and herd size. A secondary objective was to identify the prevalence of beef breed sires selected to create beef × Holstein and beef × Jersey crossbred calves. The final data set included 8,244,653 total inseminations of 4,880,752 Holstein females across 9,155 herds, and 435,267 total inseminations of 266,058 Jersey females across 2,759 herds from October 2019 to July 2021. This data set represents approximately 42 and 27% of the total dairy cows and heifers, respectively, across approximately 40% of the total licensed dairy herds in the continental United States. Holstein and Jersey females were inseminated with 1 of 4 semen types: (1) beef, (2) conventional, (3) sexed, or (4) other dairy. The top 4 beef breeds used to produce beef × Holstein and beef × Jersey crossbred calves, respectively, were Angus (55.1 and 39.1%), Limousin (13.9, and 23.5%), Simmental (11.7 and 20.5%), and Crossbreed Beef (11.3 and 4.8%). From 2019 to 2021, the use of sexed semen to inseminate Holstein and Jersey females increased from 11.0 and 24.5% to 17.7 and 32.1%, respectively, and the use of beef semen to inseminate Holstein and Jersey females increased from 18.2 and 11.4% to 26.1 and 21.2%, respectively. The use of beef semen to inseminate Holstein and Jersey females increased with increasing parity and service number, whereas the use of sexed semen decreased with increasing parity and service number supporting that farmers used sexed semen more aggressively in higher fertility and younger females with greater genetic merit. Overall, the increase in sexed and beef semen inseminations was driven primarily by larger herds. In conclusion, sexed and beef semen inseminations in US Holstein and Jersey females increased from 2019 to 2021 and was allocated differentially based on parity and service number. This increase was driven primarily by larger dairy herds possibly due to differences in reproductive performance and economies of scale.}, journal={Journal of Dairy Science}, author={Lauber, M.R. and Peñagaricano, F. and Fourdraine, R.H. and Clay, J.S. and Fricke, P.M.}, year={2023}, month={May} }
 @article{pattamanont_galvao_marcondes_clay_de vries_2021, title={Associations between dry period length and time to culling and pregnancy in the subsequent lactation}, volume={104}, ISSN={["1525-3198"]}, url={https://doi.org/10.3168/jds.2021-20119}, DOI={10.3168/jds.2021-20119}, abstractNote={The association between dry period length (DPL) and time to culling and pregnancy in the subsequent lactation may be important for the economically optimal length of the dry period. Therefore, this study aimed to (1) quantify the association between DPL and hazard of culling and pregnancy in the subsequent lactation; (2) develop continuous functions of DPL for the hazard ratios of culling and pregnancy; and (3) investigate the effect of a cause-specific hazards model and a subdistribution model to analyze competing events. The data used in this observational cohort study were from dairy herd improvement milk test lactation records from 40 states in the United States. After edits, there remained 1,108,515 records from 6,730 herds with the last days dry in 2014 or 2015. The records from 2 adjacent lactations (current, subsequent) were concatenated with the DPL of interest, 21 to 100 d, in between both lactations. We defined 8 DPL categories of 10 d each. Kaplan-Meier survival curves were used to show associations between DPL and time to culling or pregnancy for 3 lactation groups: lactation 1 and 2, lactation 2 and 3, and lactation 3 and greater. To control for confounding factors in Cox proportional models, we included 6 current lactation covariates and 3 time-dependent variables in the survival models. Hazard ratios of culling were estimated for 4 days in milk (DIM) categories from 1 to 450 DIM. Hazard ratios of pregnancy were estimated for 3 DIM categories from 61 to 300 DIM. Competing risk analysis of 8 disposal codes (i.e., farmer reported reasons) for culling and the culling event for pregnancy were conducted by a cause-specific hazards model and a subdistribution model. Hazard ratios were also estimated as quadratic polynomials of DPL. Compared with the reference DPL category of 51 to 60 d, hazard ratios of culling and pregnancy of the other 7 DPL categories ranged between 0.70 and 1.49, and 0.93 and 1.15, respectively. Short DPL were associated with lower risk of culling in the early lactation but not over the entire lactation. Short DPL were associated with greater hazard of pregnancy. Trends in hazard ratios over the ranges of the 8 DPL categories were not always consistent. Competing risk analysis with both models provided little differences in hazard ratios of culling and pregnancy. In conclusion, variations in DPL were associated with meaningful differences in the hazard ratios for culling and pregnancy and minor differences in the relative frequency of disposal codes. Subdistribution hazards models produced hazard ratios similar to cause-specific hazard models. The quadratic polynomials may be useful for decision support on customization of DPL for individual cows.}, number={8}, journal={JOURNAL OF DAIRY SCIENCE}, publisher={American Dairy Science Association}, author={Pattamanont, P. and Galvao, K. N. and Marcondes, M. I. and Clay, J. S. and De Vries, A.}, year={2021}, month={Aug}, pages={8885–8900} }
 @article{swartz_bradford_clay_2021, title={Intergenerational cycle of disease: Maternal mastitis is associated with poorer daughter performance in dairy cattle}, url={https://doi.org/10.3168/jds.2020-19249}, DOI={10.3168/jds.2020-19249}, abstractNote={Adverse prenatal environments, such as maternal stress and infections, can influence the health and performance of offspring. Mastitis is the most common disease in dairy cattle, yet the intergenerational effects have not been specifically investigated. Therefore, we examined the associations between the dam's mammary gland health and daughter performance using somatic cell score (SCS) as a proxy for mammary health. Using data obtained from Dairy Records Management Systems (Raleigh, NC), we linked daughter records with their dam's records for the lactation in which the daughter was conceived. Linear and quadratic relationships of dam mean SCS with the daughter's age at first calving (AFC; n = 15,992 daughters, 4,366 herds), first- (n = 15,119 daughters, 4,213 herds) and second-lactation SCS (n = 3,570 daughters, 1,554 herds), first- and second-lactation mature equivalent 305-d milk yield, and milk component yields were assessed using mixed linear regression models. We uncovered a phenomenon similar to those found in human and mouse models examining prenatal inflammation effects, whereby daughters born from dams with elevated SCS had poorer performance. Dam mean SCS was positively associated with daughter's AFC and first- and second-lactation mean SCS. Furthermore, for every 1-unit increase in dam mean SCS, daughter's first- and second-lactation mature equivalent fat yield declined by 0.34% and 0.91% (-1.6 ± 0.49 kg, -4.0 ± 1.0 kg, respectively), although no effect was found on first- or second-lactation milk or milk protein yield. When accounting for genetics, daughter SCS, and AFC (first lactation only), dam mean SCS was associated with reduced second-lactation milk fat yield (-3.5 ± 1.8 kg/unit SCS), and a tendency was found for first-lactation milk fat yield (-1.9 ± 1.0 kg/unit SCS). Taken together, the association of greater dam mean SCS with lesser daughter milk fat yield is likely due to a few underlying mechanisms, in particular, a predisposition for mastitis and alterations in the epigenome controlling milk fat synthesis. As such, future studies should examine epigenetic mechanisms as a potential underpinning of this phenomenon.}, journal={Journal of Dairy Science}, author={Swartz, T.H. and Bradford, B.J. and Clay, J.S.}, year={2021}, month={Apr} }
 @article{pattamanont_marcondes_clay_bach_de vries_2021, title={Piecewise modeling of the associations between dry period length and milk, fat, and protein yield changes in the subsequent lactation}, volume={104}, ISSN={["1525-3198"]}, url={https://doi.org/10.3168/jds.2020-18363}, DOI={10.3168/jds.2020-18363}, abstractNote={Our objective was to develop predictive models of 305-d mature-equivalent milk, fat, and protein yields in the subsequent lactation as continuous functions of the number of days dry (DD) in the current lactation. In this retrospective cohort study with field data, we obtained DHIA milk recording lactation records with the last DD in 2014 or 2015. Cows included had DD from 21 to 100 d. After editing, 1,030,141 records from cows in 7,044 herds remained. Three parity groups of adjacent (current, subsequent) lactations were constructed. We conducted all analyses by parity group and yield component. We first applied control models to pre-adjust the yields in the subsequent lactation for potentially confounding effects. Control models included the covariates mature-equivalent yield, days open, somatic cell score at 180 d pregnant, daily yield at 180 d pregnant, and a herd-season random effect, all observed in the current lactation. Days dry was not included. Second, we modeled residuals from control models with smooth piecewise regression models consisting of a simple linear, quadratic, and another simple linear equation depending on DD. Yield deviations were calculated as differences from predicted mature-equivalent yield at 50 DD. For validation, predictions of yield deviations from piecewise models by DD were compared with predictions from local regression for the DHIA field records and yield deviations reported in 38 experimental and field studies found in the literature. Control models reduced the average root mean squared prediction error by approximately 21%. Yield deviations were increasingly more negative for DD shorter than 50 d, indicating lower yields in the subsequent lactation. For short DD, the decrease in 305-d mature-equivalent milk yield ranged from 43 to 53 kg per DD. For mature-equivalent fat and protein yields, decreases were between 1.28 and 1.71 kg per DD, and 1.06 and 1.50 kg per DD, respectively. Yield deviations often were marginally positive and increasing for DD >50, so that the highest yield in the subsequent lactation was predicted for 100 DD. For long DD, the 305-d mature-equivalent milk yield increased at most 4.18 kg per DD. Patterns in deviations for fat and protein yield were similar to those for milk yield deviations. Predictions from piecewise models and local regressions were very similar, which supports the chosen functional form of the piecewise models. Yield deviations from field studies in the literature typically were decreasing when DD were longer, likely because of insufficient control for confounding effects. In conclusion, piecewise models of mature-equivalent milk, fat, and protein yield deviations as continuous functions of DD fit the observed data well and may be useful for decision support on the optimal dry period length for individual cows.}, number={1}, journal={JOURNAL OF DAIRY SCIENCE}, publisher={American Dairy Science Association}, author={Pattamanont, P. and Marcondes, M. and Clay, J. S. and Bach, A. and De Vries, A.}, year={2021}, month={Jan}, pages={486–500} }
 @article{ferreira_clay_vries_2020, title={Distribution of seasonality of calving patterns and milk production in dairy herds across the United States}, volume={103}, url={https://doi.org/10.3168/jds.2019-18138}, DOI={10.3168/jds.2019-18138}, abstractNote={Calving patterns and milk production are seasonal throughout the United States; however, the distribution of seasonality, and the extent to which this seasonality is due to direct effects of climate on milk production and reproductive performance or farm management, is not well quantified. Summer-to-winter (SW) ratios have been used as measures of seasonality, but other measures such as low-to-peak (LP) ratios have been proposed. Our objectives were (1) to describe the distribution of seasonality in calving pattern and milk production among herds in the US, (2) to compare SW and LP ratios of calving pattern and milk production, (3) to quantify the effect of a seasonal calving pattern, parity, and percentage of dry cows on seasonality of milk production, and (4) to describe the association between seasonality in calving pattern and milk production, herd size, and daily milk production per cow. The final data set contained Dairy Herd Improvement Association lactation records from 2015 from 5,292 (calving pattern) and 5,200 (milk production) herds for 41 states in the US. We used generalized linear regression models with 1 sinusoidal curve to model calving pattern and milk production per cow for each herd. For milk production, a model adjusting for days in milk (DIM) and the interaction of DIM and parity (ADJ) and a model that was not adjusted (NO) were run. Both models included the effect of the percentage of dry cows. We used SW and LP ratios calculated from the parameters of the sinusoidal component of the models as measures of seasonality. The variability within states for all seasonality measures was large. The median LP ratio of calving pattern was 0.61, and small herds were more seasonal (LP ratio 0.56) than large herds (LP ratio 0.75). For milk production, the median LP ratio-NO was 0.88, and the LP ratio-ADJ was 0.90. Small herds were more seasonal (0.89) than large herds (0.92) when their LP ratios-ADJ were compared. States in the south of the US were the most seasonal for calving patterns and milk production. Adjusting for DIM and parity increased the LP ratio of milk production by 8.9% for 66% of the herds. Adjusting for the percentage of dry cows increased the LP ratio in 72.9% of the herds by a median value of 21.8%. The correlations between SW and LP ratios were weak. Herds that were more seasonal for milk production had a lower average daily milk per cow than less-seasonal herds. In conclusion, seasonality in calving patterns and milk production among herds varied greatly across the US. Sinusoidal models with covariates allowed for quantification of the effects of calving pattern, DIM, and parity on the seasonality in milk production. The LP ratios captured the maximum seasonality better than SW ratios did.}, number={9}, journal={Journal of Dairy Science}, publisher={American Dairy Science Association}, author={Ferreira, Fernanda C. and Clay, John S. and Vries, Albert De}, year={2020}, month={Sep}, pages={8161–8173} }
 @article{brown_stallings_clay_rhoads_2016, title={Periconceptional Heat Stress of Holstein Dams Is Associated with Differences in Daughter Milk Production during Their First Lactation}, volume={11}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0148234}, abstractNote={The fertility of lactating Holstein cows is severely reduced during periods of heat stress. Despite this reduction in fertility, however, some inseminations conducted during heat stress result in successful pregnancies from which heifer calves are born. Many of these heifer calves are retained and raised to enter the milking herd as replacement animals. Heat stress experienced by these females around the time they were conceived may confer long-lasting effects that alter subsequent milk production capacity. The objective of this study was to examine the relationship between periconceptional heat stress and subsequent milk production of primiparous cows. National Dairy Herd Improvement Association data was obtained from Dairy Records Management Systems. Records included Holstein cows that had completed at least one lactation in one of three states with large populations of dairy cattle and which are known for having hot, humid summers: Georgia, Florida or Texas. Dates of conception were calculated by subtracting 276 d from the recorded birth date of each individual cow. Records for cows conceived within the months of June, July, and August were retained as heat stress-conceived (HSC) cows (n = 94,440); cows conceived within the months of December, January, and February were retained as thermoneutral-conceived (TNC) contemporaries (n = 141,365). In order to account for the effects of environmental conditions on total milk production for a given lactation, cows were blocked by season of calving (winter, spring, summer or fall). Adjusted 305-day mature-equivalent milk production was evaluated with a mixed model ANOVA using SAS, in which random effects were used to account for variability between herds. Of the cows that calved in the summer, fall and winter, TNC cows had higher milk yield than the HSC cows in all states. Interestingly, the cows that calved in the spring presented a unique relationship, with HSC cows producing more milk. Overall however, heat stress at the time of conception is associated with lower milk production during the first lactation. While this association does not prove cause and effect, it does provide justification for additional investigation into whether heat stress around the time of conception results in long-term, detrimental consequences for the conceptus.}, number={2}, journal={PLOS ONE}, author={Brown, Britni M. and Stallings, Jon W. and Clay, John S. and Rhoads, Michelle L.}, year={2016}, month={Feb} }
 @article{tiezzi_parker-gaddis_cole_clay_maltecca_2015, title={A Genome-Wide Association Study for Clinical Mastitis in First Parity US Holstein Cows Using Single-Step Approach and Genomic Matrix Re-Weighting Procedure}, volume={10}, ISSN={["1932-6203"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84922687710&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0114919}, abstractNote={Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profitability and animal welfare. The objective of this study was to perform a genome-wide association study (GWAS) for CM in first-lactation Holstein. Producer-recorded mastitis event information for 103,585 first-lactation cows were used, together with genotype information on 1,361 bulls from the Illumina BovineSNP50 BeadChip. Single-step genomic-BLUP methodology was used to incorporate genomic data into a threshold-liability model. Association analysis confirmed that CM follows a highly polygenic mode of inheritance. However, 10-adjacent-SNP windows showed that regions on chromosomes 2, 14 and 20 have impacts on genetic variation for CM. Some of the genes located on chromosome 14 (LY6K, LY6D, LYNX1, LYPD2, SLURP1, PSCA) are part of the lymphocyte-antigen-6 complex (LY6) known for its neutrophil regulation function linked to the major histocompatibility complex. Other genes on chromosome 2 were also involved in regulating immune response (IFIH1, LY75, and DPP4), or are themselves regulated in the presence of specific pathogens (ITGB6, NR4A2). Other genes annotated on chromosome 20 are involved in mammary gland metabolism (GHR, OXCT1), antibody production and phagocytosis of bacterial cells (C6, C7, C9, C1QTNF3), tumor suppression (DAB2), involution of mammary epithelium (OSMR) and cytokine regulation (PRLR). DAVID enrichment analysis revealed 5 KEGG pathways. The JAK-STAT signaling pathway (cell proliferation and apoptosis) and the ‘Cytokine-cytokine receptor interaction’ (cytokine and interleukines response to infectious agents) are co-regulated and linked to the ‘ABC transporters’ pathway also found here. Gene network analysis performed using GeneMania revealed a co-expression network where 665 interactions existed among 145 of the genes reported above. Clinical mastitis is a complex trait and the different genes regulating immune response are known to be pathogen-specific. Despite the lack of information in this study, candidate QTL for CM were identified in the US Holstein population.}, number={2}, journal={PLOS ONE}, author={Tiezzi, Francesco and Parker-Gaddis, Kristen L. and Cole, John B. and Clay, John S. and Maltecca, Christian}, year={2015}, month={Feb} }
 @article{brown_stallings_clay_rhoads_2015, title={Periconceptional Heat Stress of Holstein Dams Is Associated with Differences in Daughter Milk Production and Composition during Multiple Lactations}, volume={10}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0133574}, abstractNote={Heat stress at the time of conception affects the subsequent milk production of primiparous Holstein cows; however, it is unknown whether these effects are maintained across multiple lactations. Therefore, the objective of the current study was to examine the relationship between periconceptional heat stress and measurements of milk production and composition in cows retained within a herd for multiple lactations. National Dairy Herd Improvement Association data was obtained from Dairy Records Management Systems. Records included milk production data and milk composition data from over 75,000 and 44,000 Holstein cows, respectively, born between 2000 and 2010 in Florida, Georgia, and Texas. Conception dates were calculated by subtracting 276 d from the recorded birth date. Records for cows conceived within the months of June, July, and August were retained as heat stress conceived (HSC) cows; cows conceived within the months of December, January, and February were retained as thermoneutral conceived (TNC) contemporaries. Adjusted 305-d mature equivalent milk, protein percent and fat percent were evaluated with a mixed model ANOVA using SAS. Milk production was significantly affected by periconceptional heat stress. When a significant difference or tendency for a difference was detected between the HSC and TNC cows, the TNC produced more milk in all but one comparison. The advantage in milk production for the TNC cows over the HSC cows ranged from 82 ± 42 to 399 ± 61 kg per lactation. Alterations in fat and protein percentage were variable and most often detected in first lactations (first > second or third). Overall, the most striking result of this study is the consistency of the relationship between HSC and milk production. The nature of this relationship suggests that heat stress at or around the time of conception impairs cow milk yield throughout her lifetime.}, number={10}, journal={PLOS ONE}, author={Brown, Britni M. and Stallings, Jon W. and Clay, John S. and Rhoads, Michelle L.}, year={2015}, month={Oct} }
 @article{dhakal_tiezzi_clay_maltecca_2015, title={Short communication: Genomic selection for hoof lesions in first-parity US Holsteins}, volume={98}, ISSN={["1525-3198"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84928093134&partnerID=MN8TOARS}, DOI={10.3168/jds.2014-8830}, abstractNote={Hoof lesions contributing to lameness are crucial economic factors that hinder the profitability of dairy enterprises. Producer-recorded hoof lesions data of US Holsteins were categorized into infectious (abscess, digital and interdigital dermatitis, heel erosion, and foot rot) and noninfectious (korn, corkscrew, sole and toe ulcer, sole hemorrhage, white line separation, fissures, thin soles, and upper leg lesions) categories of hoof lesions. Pedigree- and genomic-based univariate analyses were conducted to estimate the variance components and heritability of infectious and noninfectious hoof lesions. A threshold sire model was used with fixed effects of year-seasons and random effects of herd and sire. For genomic-based analysis, a single-step procedure was conducted, incorporating H matrix to estimate genomic variance components and heritability for hoof lesions. The pedigree-based analysis produced heritability estimates of 0.11 (±0.05) for infectious hoof lesions and 0.08 (±0.05) for noninfectious hoof lesions. The single-step genomic analysis produced heritability estimates of 0.14 (±0.06) for infectious hoof lesions and 0.12 (±0.08) for noninfectious hoof lesions. Approximated genetic correlations between hoof lesion traits and hoof type traits along with productive life and net merit were all low and ranged between -0.25 and 0.14. Sire reliabilities increased, on average, by 0.24 and 0.18 for infectious and noninfectious hoof lesions, respectively, with incorporation of genomic data.}, number={5}, journal={JOURNAL OF DAIRY SCIENCE}, author={Dhakal, K. and Tiezzi, F. and Clay, J. S. and Maltecca, C.}, year={2015}, month={May}, pages={3502–3507} }
 @article{gaddis_cole_clay_maltecca_2014, title={Genomic selection for producer-recorded health event data in US dairy cattle}, volume={97}, ISSN={["1525-3198"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84899070158&partnerID=MN8TOARS}, DOI={10.3168/jds.2013-7543}, abstractNote={Emphasizing increased profit through increased dairy cow production has revealed a negative relationship of production with fitness and health traits. Decreased cow health can affect herd profitability through increased rates of involuntary culling and decreased or lost milk sales. The development of genomic selection methodologies, with accompanying substantial gains in reliability for low-heritability traits, may dramatically improve the feasibility of genetic improvement of dairy cow health. Producer-recorded health information may provide a wealth of information for improvement of dairy cow health, thus improving profitability. The principal objective of this study was to use health data collected from on-farm computer systems in the United States to estimate variance components and heritability for health traits commonly experienced by dairy cows. A single-step analysis was conducted to estimate genomic variance components and heritabilities for health events, including cystic ovaries, displaced abomasum, ketosis, lameness, mastitis, metritis, and retained placenta. A blended H matrix was constructed for a threshold model with fixed effects of parity and year-season and random effects of herd-year and sire. The single-step genomic analysis produced heritability estimates that ranged from 0.02 (standard deviation = 0.005) for lameness to 0.36 (standard deviation = 0.08) for retained placenta. Significant genetic correlations were found between lameness and cystic ovaries, displaced abomasum and ketosis, displaced abomasum and metritis, and retained placenta and metritis. Sire reliabilities increased, on average, approximately 30% with the incorporation of genomic data. From the results of these analyses, it was concluded that genetic selection for health traits using producer-recorded data are feasible in the United States, and that the inclusion of genomic data substantially improves reliabilities for these traits.}, number={5}, journal={JOURNAL OF DAIRY SCIENCE}, author={Gaddis, K. L. Parker and Cole, J. B. and Clay, J. S. and Maltecca, C.}, year={2014}, month={May}, pages={3190–3199} }
 @article{clay_mcdaniel_brown_2004, title={Variances of and correlations among progeny tests for reproductive traits of cows sired by AI bulls}, volume={87}, ISSN={["0022-0302"]}, DOI={10.3168/jds.S0022-0302(04)70052-1}, abstractNote={Estimates of daughter fertility were computed using first artificial insemination (AI) breedings reported to the US Dairy Herd Improvement Association (DHIA) from 1995 through 1997. An animal model was used to compute estimated breeding values (EBV) of daughter groups with fixed effects of herd-year-month bred and classes of early lactation energy-corrected milk, days in milk (DIM) when bred, and parity. Standard deviations and ranges of bull EBV for daughter fertility for DIM were 9.1 and -31 to 18; standard deviations and ranges of bull EBV for daughter fertility for nonreturn were 3.8 and -11 to 10. Correlations were computed for EBV for daughter fertility with EBV for mating bull fertility and with predicted transmitting abilities (PTA) for milk, somatic cell score (SCS), and productive life for bulls (213) with minimums of 200 matings and 100 progeny with reproductive traits. None of the correlations among EBV for reproductive traits differed from 0.0. Correlations of EBV for daughter fertility with PTA for productive life were significantly positive. PTA for yield traits were not correlated with EBV for daughter differences in nonreturn or DIM. Very low correlations of EBV for daughter reproductive traits with PTA for yield indicate that, in order to improve daughter fertility, fertility must be incorporated in sire selection decisions.}, number={7}, journal={JOURNAL OF DAIRY SCIENCE}, author={Clay, JS and McDaniel, BT and Brown, CH}, year={2004}, month={Jul}, pages={2307–2313} }
 @article{clay_mcdaniel_2001, title={Computing mating bull fertility from DHI nonreturn data}, volume={84}, ISSN={["0022-0302"]}, DOI={10.3168/jds.S0022-0302(01)74585-7}, abstractNote={Animal model methodology was used to compute yearly measures of relative fertility of Holstein AI mating bulls based upon 70-d nonreturn of first breedings as reported to U.S. DHIA from 1988 through 1997. Estimated Relative Conception Rates (ERCR) were computed for bulls with a minimum of 50 first breedings in a single year using variance ratios 45.5 for mating bull, 45.5 for animal genetic effects, and 31 for permanent environment. The model assumed repeatability across lactations of 0.05 and included fixed effects of herd-year-month bred and classes of parity, early lactation energy-corrected milk and days open when bred. Estimates of fertility were greater for breedings to cows that were young, had low early lactation production, and were in late stages of lactation. ERCR were expressed as difference in nonreturn from the average AI mating bull of herdmates. Values ranged from -18 to +13. For ERCR computed from a minimum of 1000 breedings, 90% were within four units of zero. Early ERCR computed from a few breedings in a single year were tested for ability to predict later ERCR computed from a minimum of 1000 different breedings. Early ERCR computed from 300 or more matings accurately predicted later independent ERCR. For yearly estimates each based upon a minimum of 1000 breedings, 8% changed more than three units, and 4% declined more than three units. Correlations between ERCR and predicted transmitting abilities protein and type production index were significant but accounted for little variance. Correlations between ERCR and other traits were not significant.}, number={5}, journal={JOURNAL OF DAIRY SCIENCE}, author={Clay, JS and McDaniel, BT}, year={2001}, month={May}, pages={1238–1245} }