Relationship between female fertility and production traits in Canadian Holsteins

The objectives of this study were a) to estimate the genetic correlation between milk production and some female fertility traits such as 56-d nonreturn rate in cows (NRRC), calving to first service (CTFS), and first service to conception (FSTC); b) to assess the influence of including milk production as a correlated trait on the genetic evaluation of these traits in Canadian Holsteins; and c) to determine if using heifer nonreturn rate (NRRH) had a similar effect as using milk production on cow NRRC evaluation. The data included fertility and production records of first-parity Holstein cows. Genetic parameters were estimated using uni- and bivariate analyses in which milk production at around 90 DIM (TD90M) was included as a correlated trait to NRRC, CTFS, and FTSC. A bivariate analysis was also carried out in which NRRH was included as a correlated trait to NRRC. The models were compared by genetic trend (NRRC, CTFS, and FSTC) and cross-validation and predictability (NRRC). The heritability estimates for NRRC from the uni- and bivariate analyses were 0.017 and 0.020, respectively. The corresponding figures for CTFS were 0.07 and 0.08 and for FSTC were 0.049 and 0.05. The genetic trends for NRRC of the 2 models (NRRC+TD90M and NRRC+NRRH) gave very similar results. However, when milk production was included in the genetic evaluation of CTFS and FSTC, the genetic trends of the 2 fertility traits were higher compared with the univariate analysis. In NRRC evaluation by cross-validation and predictability, the bivariate analyses were more consistent and gave a better predictability than the univariate analysis. However, there was no major difference between the 2 models. Consequently, it might be worth including milk production or heifer fertility as correlated traits in the genetic evaluation of female fertility traits.     

Evaluation of reproductive performance in lactating dairy cows with prostaglandin F2alpha, gonadotropin-releasing hormone, and timed artificial insemination

Nine hundred and twenty Holstein cows from 16 commercial dairy herds to evaluate three systematic breeding protocols: 14-d PGF2alpha, timed artificial insemination (AI), and GnRH-PGF2alpha, relative to AI following estrus detection without hormone intervention. The timed AI protocol involved GnRH, followed by PGF2alpha 7 d later and GnRH again 2 d after PGF2alpha, with AI 6 to 18 h after the second GnRH. The GnRH-PGF2alpha protocol consisted of GnRH followed by PGF2alpha 7 d later. Eight herds relied on visual observation to detect estrus, and eight herds utilized the HeatWatch estrus detection system. The average interval to first postpartum AI was shortest for the timed AI protocol (77.1 d) followed by the 14-d PGF2alpha protocol (81.6 d). There was no difference in days to first AI between the control (86.1 d) and GnRH-PGF2alpha (89.5 d) protocols. Percent pregnant per first AI did not differ among control (45.6%), 14-d PGF2alpha (43.7%), or GnRH-PGF2alpha (44.0%) protocols, but all protocols had a higher percent pregnant per first AI than the timed AI protocol (30.1%). Response to the GnRH-PGF2alpha protocol was limited because 44.0% of the cows submitted to the protocol were not detected in estrus < or = 10 d post-PGF2, administration and had an interval to first AI of 103.8 d. Cumulative percent pregnant by 120 d postpartum did not differ between control cows (53.1%) and hormonally treated cows (50.6%). Visual observation herds had a shorter interval to first postpartum AI (82.8 d) than the HeatWatch herds (84.8 d), with a higher overall rate of estrus detection across all protocols (75.3 and 67.6%, respectively).     

An alternative AI breeding protocol for dairy cows exposed to elevated ambient temperatures before or after calving or both

Our objective was to determine if a timed artificial insemination (AI) protocol (Ovsynch) might produce greater pregnancy rates than AI after a synchronized, detected estrus during summer. Lactating Holstein cows (n = 425) were grouped into breeding clusters and then assigned randomly to each of two protocols for AI between 50 and 70 days in milk. All cows were treated with GnRH followed 7 d later by PGF2alpha. Ovsynch cows then were treated with a second injection of GnRH 48 h after PGF2alpha and inseminated 16 to 19 h later. Controls received no further treatment after PGF2alpha and were inseminated after detected estrus. Pregnancy was diagnosed once by transrectal ultrasonography (27 to 30 d after AI) and again by palpation (40 to 50 d). Based on concentrations of progesterone in blood collected before each hormonal injection, only 85.4% of 425 cows were considered to be cycling. Although conception rates were not different between protocols at d 27 to 30, AI submission rates and pregnancy rates were greater after Ovsynch (timed AI) than after detected estrus. A temperature-humidity index > or = 72 was associated with fewer controls detected in estrus with lower conception than for controls detected in estrus when index values were < 72, whereas the reverse was true for cows after the Ovsynch protocol. We concluded that a timed AI protocol increased pregnancy rates at d 27 to 30 because its success was independent of either expression or detection of estrus. However, because of poorer embryonic survival in Ovsynch cows during heat stress only (39.5 vs. 69.2% survival for Ovsynch and control, respectively), pregnancy rates were not different by d 40 to 50 after timed AI.     

Estimates of genetic trend in an artificial insemination progeny test program and their association with herd characteristics.

Individual lactation records from Holstein cows in 3449 herds participating in an AI stud's young sire sampling program from 1971 to 1987 were used to characterize the sampling program and to estimate genetic merit and trend. Average genetic merit of cows in sampling program herds was consistently superior to the average genetic merit of cows in the US population. Genetic trend of sires of first-crop cows was 58 kg of milk and 1.5 kg of fat/yr from 1971 to 1978 and 176 kg of milk and 5.5 kg of fat/yr from 1979 to 1987. The average genetic merit of sires of first-crop cows born after 1983 was equivalent to or exceeded the genetic level of sires of other cows in the herd. Within-herd-year means and standard deviations of yield, genetic evaluation, and management traits (herd-year characteristics) were computed for a subset of 341 herds contributing first-crop daughters for at least 10 yr. The average of each herd-year characteristic during 10 or more years was used to predict within-herd genetic trend. Herd characteristics explained up to 51% of differences in within-herd genetic trends. Average sire genetic merit of daughters other than first-crop daughters accounted for up to 80% of the explained differences. Other herd characteristics suggested that herds with larger within-herd standard deviation milk yields, a larger number of young sires represented, younger cows, and greater percentage of cows sired by AI sires made greater genetic improvement. Results indicated that the average genetic merit of cows and the rate of within-herd genetic improvement are higher in herds that participate in a young sire sampling program.     

Effect of interval between induction of ovulation and artificial insemination (AI) and supplemental progesterone for resynchronization on fertility of dairy cows subjected to a 5-d timed AI program

Objectives were to investigate 2 intervals from induction of ovulation to artificial insemination (AI) and the effect of supplemental progesterone for resynchronization on fertility of lactating dairy cows subjected to a 5-d timed AI program. In experiment 1, 1,227 Holstein cows had their estrous cycles presynchronized with 2 injections of PGF_2α at 46 and 60 d in milk (DIM). The timed AI protocols were initiated with GnRH at 72 DIM, followed by 2 injections of PGF_2α at 77 and 78 DIM and a second injection of GnRH at either 56 (OVS56) or 72 h (COS72) after the first PGF_2α of the timed AI protocols. All cows were time-inseminated at 72 h after the first PGF_2α injection. Pregnancy was diagnosed on d 32 and 60 after AI. In experiment 2, 675 nonpregnant Holstein cows had their estrous cycles resynchronized starting at 34 d after the first AI. Cows received the OVS56 with (RCIDR) or without (RCON) supplemental progesterone, as an intravaginal insert, from the first GnRH to the first PGF_2α. Pregnancy diagnoses were performed on d 32 and 60 after AI. During experiment 2, subsets of cows had their ovaries scanned by ultrasonography at the first GnRH, the first PGF_2α, and second GnRH injections of the protocol. Blood was sampled on the day of AI and 7 d later, and concentrations of progesterone were determined in plasma. Cows were considered to have a synchronized ovulation if they had progesterone <1 and >2.26 ng/mL on the day of AI and 7 d later, respectively, and if no ovulation was detected between the first PGF_2α and second GnRH injections during resynchronization. In experiment 1, the proportion of cows detected in estrus at AI was greater for COS72 than OVS56 (40.6 vs. 32.4%). Pregnancy per AI (P/AI) did not differ between OVS56 (46.4%) and COS72 (45.5%). In experiment 2, cows supplemented with progesterone had greater P/AI compared with unsupplemented cows (51.3 vs. 43.1%). Premature ovulation tended to be greater for RCON than RCIDR cows (7.5 vs. 3.6%), although synchronization of the estrous cycle after timed AI was similar between treatments. Timing of induction of ovulation with GnRH relative to insemination did not affect P/AI of dairy cows enrolled in a 5-d timed AI program. Furthermore, during resynchronization starting on d 34 after the first AI, supplementation with progesterone improved P/AI in cows subjected to the 5-d timed AI protocol.     

Effect of bST and reproductive management on reproductive performance of Holstein dairy cows

The objective was to determine the effects of bovine somatotropin (bST) and two artificial insemination (AI) protocols on reproductive performance of Holstein cows. Lactating cows (n = 840) were assigned at 37 d in milk (DIM) to one of four treatments in a 2 x 2 factorial arrangement. Treatments consisted of either bST (500 mg/14 d) starting at 63 +/- 3 DIM or no bST (control), with cows either submitted for timed AI following a synchronized ovulation (Ovsynch) protocol or assigned to receive AI based on estrus detection (ED). Two injections of PGF2, at 37 +/- 3 and 51 +/- 3 DIM were used to presynchronize estrous cycles. Cows then received an injection of GnRH at 63 +/- 3 DIM, followed 7.5 d later by PGF2. Cows assigned to ED treatments were inseminated after observed estrus during a 7-d period. Cows in Ovsynch treatments received a second GnRH injection 48 h after the last PGF2alpha and received timed AI 16 to 18 h later. Pregnancy was diagnosed by ultrasound at 31 d after AI and confirmed 14 d later. Frequency of anovulation (18.5%) at 63 DIM was similar across treatments, but proportions of anovulatory cows decreased quadratically as body condition at 70 DIM increased from 2.25 to 3.75. Estrus detection rate after PGF2alpha tended to be lower in multiparous cows receiving bST, and bST reduced returns to estrus in nonpregnant cows. Conception rates were higher in cows receiving AI after ED and bST improved conception rates to first AI in cyclic cows by reducing embryonic mortality. Pregnancy loss was similar for cows inseminated following ED or the Ovsynch protocol. There was a positive impact of bST on fertility of cyclic cows inseminated at fixed time or at detected estrus, but effective resynchronization protocols are needed to optimize reinsemination of non-pregnant bST-treated cows.     

Effect of reducing the period of follicle dominance in a timed artificial insemination protocol on reproduction of dairy cows

Objectives were to determine the effect of reducing the period of follicle dominance in a timed artificial insemination (AI) protocol on pregnancy per AI (P/AI) in Holstein cows. In experiment 1, 165 cows received 2 injections of PGF_2α at 36 and 50 d in milk (DIM). At 61 DIM, cows were assigned randomly to Cosynch 72 h (CoS72: d 61 GnRH, d 68 PGF_2α, d 71 GnRH) or to a 5-d Cosynch 72 h with 1 (5dCoS1: d 61 GnRH, d 66 PGF_2α, d 69 GnRH) or 2 injections of PGF_2α (5dCoS2: d 61 GnRH, d 66 and 67 PGF_2α, d 69 GnRH). Blood was sampled at the first GnRH, first PGF_2α, and at the second GnRH of the protocols and assayed for progesterone. Ovulatory responses to GnRH were evaluated by ultrasonography. Cows were considered synchronized if they had concentrations of progesterone ≥1 ng/mL and <1 ng/mL on the days of the PGF_2α, and the second GnRH of the protocols, respectively, and if they ovulated within 48 h of the second GnRH injection. In experiment 2, 933 cows were assigned randomly to CoS72 or 5dCoS2. Blood was assayed for progesterone and ovaries were scanned as in experiment 1. Plasma on the days of the first PGF_2α and final GnRH of the timed AI protocols was assayed for estradiol in 75 cows. Pregnancy was diagnosed on d 38 and 66 after AI. In experiment 1, the proportions of cows with corpora lutea (CL) regression on the day of AI differed and were 79.0, 59.1, and 95.7% for CoS72, 5dCoS1, and 5dCoS2, respectively. Cows that ovulated to the first GnRH of the Cosynch tended to have lesser CL regression than cows that did not ovulate (73.0 vs. 86.4%). Protocol synchronization differed between treatments and they were greater for CoS72 (69.4%) and 5dCoS2 (78.4%) than for 5dCoS1 (42.3%). In experiment 2, CL regression was lesser (91.5 vs. 96.3%) but detection of estrus at timed AI (30.9 vs. 23.6%) was greater for CoS72 than 5dCoS2, and cows in estrus had increased P/AI (46.2 vs. 31.9%). Cows in CoS72 ovulated a larger follicle and had greater concentrations of estradiol on the day of AI than cows in 5dCoS2, but protocol synchronization tended to increase in cows receiving the 5dCoS2. When all 933 cows were evaluated, P/AI was greater for 5dCoS2 than for CoS72 (37.9 vs. 30.9%). Similarly, when only cows with progesterone <1 ng/mL on the day of AI were evaluated, P/AI was greater for 5dCoS2 than for CoS72 (39.3 vs. 33.9%). Treatment with PGF_2α on d 5 and 6 after GnRH resulted in increased luteolysis and allowed for reducing the interval from GnRH to timed AI, which increased P/AI. Reducing time of follicle dominance in timed AI protocols improves fertility of lactating dairy cows.     

Bias in genetic evaluations by records of cows treated with bovine somatotropin

Records from Dairy Records Management Systems in Raleigh were used to estimate effects of bovine somatotropin (bST) treatment and to predict breeding values for milk production traits. The data comprised 5245 test-day records of bST-treated cows and 126,223 test-day records of untreated cows in first lactation for milk, fat, and protein yields. Fixed effects of bST treatment were estimated from test-day animal models with herd-test-date as another fixed factor. Percentage increases due to bST treatment ranged from 7 to 8% for test-day milk, fat, and protein yields. Random regression coefficients for additive genetic and permanent environmental effects were included in the model. To assess the potential for bias in genetic evaluations when some and not all cows are treated with bST, breeding values predicted by the test-day model with and without effects of bST treatment were compared for cows and sires. Correlations between breeding values predicted from models with and without effects of bST treatment were 0.99. However, relatively large bias was found for individual animals. This result suggests that bias in genetic evaluation caused by ignoring bST treatment may be significant.     

Genetic analysis of an artificial insemination progeny test program

The success of the progeny test (PT) program from one Spanish artificial insemination (AI) organization was evaluated. The annual genetic trend for the organization was compared with PT programs from other countries. The relationships among parents' estimated breeding values (EBV) and PT results for sons were also studied. Estimated breeding values for type and production traits were obtained from international genetic evaluations from February 2004. The annual genetic gain of the Spanish PT program was similar to that of other international programs. The Spanish AI organization graduated 13% of its sampled bulls, and 52% of primiparous cows were daughters of Spanish bulls (32% from proven bulls and 20% from sampling bulls).Correlations between EBV for PT bulls and their pedigree indices (0.52 to 0.70) were slightly lower than correlations between EBV for PT bulls and their parent averages (0.63 to 0.73). Both young and mature cows contributed to genetic progress. Success of PT bulls (defined by number of second-crop daughters) depended mainly on their EBV for final score, protein yield, and the type-production index. Significant correlations of sire EBV were found for final score and type-production index with the number of second-crop daughters (0.22 and 0.17). Likewise, significant correlations of dam EBV for final score and type-production index with the number of second crop daughters were found (0.25 and 0.18). Final score and protein yield were the main factors in success of a PT bull. The type-production index for PT bulls was not important for success unless it was 2.5 standard deviations above average. The PT bulls with low EBV for type-production index were used as proven bulls when they had higher EBV either for protein or final score.     

Effect of synchronized breeding on genetic evaluations of fertility traits in dairy cattle

Estrus detection has become more difficult over the years due to decreases in the estrus expression of high-producing dairy cows, and increased herd sizes and animal density. Through the use of hormonal synchronization protocols, also known as timed artificial insemination (TAI) protocols, it is possible to alleviate some of the challenges associated with estrus detection. However, TAI masks cows' fertility performance, resulting in an unfair comparison of treated animals and innately fertile animals. Consequently, genetically inferior and superior cows show similar phenotypes, making it difficult to distinguish between them. As genetic programs rely on the collection of accurate phenotypic data, phenotypes collected on treated animals likely add bias to genetic evaluations. In this study, to assess the effect of TAI, the rank correlation of bulls for a given trait using only TAI records were compared with the same trait using only heat detection records. A total of 270,434 records from 192,539 animals split across heifers, first and second parity cows were analyzed for the traits: calving to first service, first service to conception, and days open. Results showed large reranking across all traits and parities between bulls compared based on either having only TAI records or only heat detection records, suggesting that a bias does indeed exist. Large reranking was also observed for both the heat detection and TAI groups among the top 100 bulls in the control group, which included all records. Furthermore, breeding method was added to the model to assess its effect on bull ranking. However, there were only minor changes in the rank correlations between scenario groups. Therefore, more complex methods to account for the apparent bias created by TAI should be investigated; for this, the method by which these data are collected needs to be improved through creating a standardized way of recording breeding codes. Though the results of this study suggest the presence of bias within current fertility evaluations, additional research is required to confirm the findings of this study, including looking at high-reliability bulls specifically, to determine if the levels of reranking remain. Future studies should also aim to understand the potential genetic differences between the fertility traits split via management technology, possibly in a multiple-trait analysis.     

Prediction of genetic merit for live weight and body condition score in dairy cows using routinely available linear type and carcass data

Accurate estimates of genetic merit for both live weight and body condition score (BCS) could be useful additions to both national- and herd-breeding programs. Although recording live weight and BCS is not technologically arduous, data available for use in routine genetic evaluations are generally lacking. The objective of the present study was to explore the usefulness of routinely recorded data, namely linear type traits (which also included BCS but only assessed visually) and carcass traits in the pursuit of genetic evaluations for both live weight and BCS in dairy cows. The data consisted of on-farm records of live weight and BCS (assessed using both visual and tactile cues) from 33,242 dairy cows in 201 commercial Irish herds. These data were complemented with information on 6 body-related linear type traits (i.e., stature, angularity, chest width, body depth, BCS, and rump width) and 3 cull cow carcass measures (i.e., carcass weight, conformation, and fat cover) on a selection of these animals plus close relatives. (Co)variance components were estimated using animal linear mixed models. The genetic correlation between the type traits stature, angularity, body depth, chest width, rump width, and visually-assessed BCS with live weight was 0.68, ?0.28, 0.43, 0.64, 0.61, and 0.44, respectively. The genetic correlation between angularity and BCS measured on farm (based on both visual and tactile appraisal) was ?0.79; the genetic and phenotypic correlation between BCS assessed visually as part of the linear assessment with BCS assessed by producers using both tactile and visual cues was 0.90 and 0.27, respectively. The genetic (phenotypic) correlation between cull cow carcass weight and live weight was 0.81 (0.21), and the genetic (phenotypic) correlation between cull cow carcass fat cover and BCS assessed on live cows was 0.44 (0.12). Estimated breeding values (EBV) for live weight and BCS in a validation population of cows were generated using a multitrait evaluation with observations for just the type traits, just the carcass traits, and both the type traits and carcass traits; the EBV were compared with the respective live weight and BCS phenotypic observations. The regression of phenotypic live weight on its EBV from the multitrait evaluations was 1.00 (i.e., the expectation) when the EBV was generated using just linear type trait data, but less than 1 (0.83) when using just carcass data. However, the regression changed across parities and stages of lactation. The partial correlation (after adjusting for contemporary group, parity by stage of lactation, heterosis, and recombination loss) between phenotypic live weight and EBV for live weight estimated using the 3 different scenarios (i.e., type only, carcass only, type plus carcass) ranged from 0.38 to 0.43. Although the prediction of phenotypic BCS from its respective EBV was relatively good when using just the linear type trait data (regression coefficient of 0.83 with a partial correlation of 0.22), the predictive ability of BCS EBV based on just carcass data was poor and should not be used. Overall, linear type trait data are a useful source of information to predict live weight and BCS with minimal additional predictive value from also including carcass data. Nonetheless, in the absence of linear type trait data, information on carcass traits can be useful in predicting genetic merit for mature cow live weight. Prediction of cow BCS from cow carcass data is not recommended.     

Differing genetic trend estimates from traditional and genomic evaluations of genotyped animals as evidence of preselection bias in US Holsteins

The objective of this study was to compare genetic trends from single-step genomic BLUP (ssGBLUP) and traditional BLUP models for milk production traits of US Holsteins. Phenotypes were 305-d milk, fat, and protein yields from 21,527,040 cows recorded between January 1990 and August 2015. The pedigree file included 29,651,623 animals and was limited to 3 generations back from recorded or genotyped animals. Genotypes for 764,029 animals were used, and analyses were by a 3-trait repeatability model as used in the US official genetic evaluation. Unknown-parent groups were incorporated into the inverse of a relationship matrix (H^?1 in ssGBLUP and A^?1 in BLUP) with the QP transformation. For ssGBLUP, 18,359 genotyped animals were randomly chosen as core animals to calculate the inverse of the genomic relationship matrix with the APY algorithm. Computations took 6.5 h and 1.4 GB of memory for BLUP, and 13 h and 115 GB of memory for ssGBLUP. For genotyped sires with at least 10 daughters, the average genetic levels for predicted transmitting ability (PTA) and genomic PTA were similar up to 2008, with a higher level for ssGBLUP later (approximately by 36 kg for milk, 2.1 kg for fat, and 1.1 kg for protein for bulls born in 2010). For genotyped cows, the average genetic levels were similar up to 2006, with a higher level for ssGBLUP (approximately by 91 kg for milk, 3.6 kg for fat, and 2.7 kg for protein for cows born in 2012). For all cows, the average levels were slightly higher for ssGBLUP, with much smaller differences than for genotyped cows. Trends for BLUP indicate bias due to genomic preselection for genotyped sires and cows. For official evaluations released in December 2016, traditional PTA had the same trend as multiple-step genomic PTA for both genotyped bulls and cows except for the youngest bulls, who had traditional PTA slightly lower than genomic PTA. For genotyped bulls born in recent years, genetic gain for official traditional and genomic evaluations was similar in contrast to ssGBLUP and BLUP differences. Official PTA for cows were adjusted so that the Mendelian sampling variance was comparable with that for bulls, and those adjustments likely removed bias due to genomic preselection from traditional PTA, especially for genotyped cows. The ssGBLUP method seems to account partially for that bias and is computationally suitable for national evaluations.     

Fertility of lactating Holstein cows submitted to a Double-Ovsynch protocol and timed artificial insemination versus artificial insemination after synchronization of estrus at a similar day in milk range

Our objective was to compare the AI submission rate and pregnancies per artificial insemination (P/AI) at first service of lactating Holstein cows submitted to a Double-Ovsynch protocol and timed artificial insemination (TAI) versus artificial insemination (AI) to a detected estrus after synchronization of estrus at a similar day in milk range. Lactating Holstein cows were randomly assigned to receive their first TAI after a Double-Ovsynch protocol (DO; n = 294) or to receive their first AI after a synchronized estrus (EST; n = 284). Pregnancy status was determined 33 ± 3 d after insemination and was reconfirmed 63 ± 3 d after insemination. Data were analyzed by ANOVA and logistic regression using the MIXED and GLIMMIX procedures of SAS (SAS Institute Inc., Cary, NC). By design, days in milk at first insemination did not differ between treatments (76.9 ± 0.2 vs. 76.7 ± 0.3 for DO vs. EST cows, respectively), but more DO cows were inseminated within 7 d after the end of the voluntary waiting period than EST cows (100.0 vs. 77.5%). Overall, DO cows had more P/AI than EST cows at both 33 d (49.0 vs. 38.6%) and 63 d (44.6 vs. 36.4%) after insemination, but pregnancy loss from 33 to 63 d after insemination did not differ between treatments. Primiparous cows had more P/AI than multiparous cows 33 and 63 d after insemination, but the treatment by parity interaction was not significant. Synchronization rate to the hormonal protocols was 85.3%, which did not differ between treatments; however, synchronized DO cows had more P/AI 33 d after insemination than synchronized EST cows (54.7 vs. 44.5%). In summary, submission of lactating Holstein cows to a Double-Ovsynch protocol and TAI for first insemination increased the percentage of cows inseminated within 7 d after the end of the voluntary waiting period and increased P/AI at 33 and 63 d after first insemination resulting in 64 and 58% more pregnant cows, respectively, than submission of cows for first AI after detection of estrus at a similar day in milk range. We conclude that, because the proportion of synchronized cows did not differ between treatments, DO cows had more P/AI than EST cows because of an intrinsic increase in fertility after submission to a fertility program.     

Evaluating sire selection practices using lifetime net income functions

Dairy farmers do not take full advantage of opportunities available for genetic improvement through use of artificial insemination, perhaps because economic advantages of good sire selection may not be fully recognized or understood. This study was undertaken to document differences between use of AI and non-AI bulls and to develop prediction equations to compare lifetime economic merit of future progeny from alternative sire selection policies. We describe the use of two methods of measuring lifetime economic merit, with and without adjustment for opportunity cost of a postponed replacement. Comparison of lifetime relative net income adjusted for opportunity cost on groups of cows sired by different kinds of bulls showed that daughters of proven AI bulls generated $148 and $120 more lifetime net income under fluid and manufactured milk market conditions than daughters of non-AI bulls. Daughters of proven AI bulls produced $60 more than daughters of AI young sires in progeny testing programs at the time of daughter conception. We developed prediction equations from combinations of genetic evaluations for production, productive life, SCS, and linear type traits on sires to predict lifetime relative net income of progeny produced from alternative sire selection strategies. Prediction equations explained 14 to 18% of variation in relative net income (not adjusted for opportunity cost), but herd and year of first freshening accounted for considerably more variation than did genetic evaluations on the sire of the cow. Finally, two independent data sets were used to develop and test predictions of lifetime relative net income adjusted for opportunity cost using genetic evaluations based on the eight traits included in the Merit indexes for the sire of each cow. Prediction equations from odd numbered herds were used to predict lifetime economic merit in even numbered herds and vice versa. Coefficients of determination ranged from 0.088 to 0.103 and averaged 0.004 higher than prediction equations with Net or Fluid Merit. Accuracy of predictions showed that Net and Fluid Merit were robust and useful indexes that accurately identified bulls whose daughters generated highest lifetime economic merit.     

Genetic parameters and association of national evaluations with breeding values for health traits in US organic Holstein cows

Among other regulations, organic cows in the United States cannot receive antibiotics and preserve their organic status, emphasizing the importance of prevention of illness and benefit of high genetic merit for disease resistance. At the same time, data underlying national genetic evaluations primarily come from conventional cows, drawing concern to the possibility of a genotype by environment interaction whereby the value of a genotype varies depending on the environment, and potentially limits the relevance of these evaluations to organic cows. The objectives of this study were to characterize the genetics of and determine the presence of genotype by environment interaction for health traits in US organic dairy cows. Individual cow health data were obtained from 16 US Department of Agriculture certified organic dairy farms from across the United States that used artificial insemination and maintained detailed records. Data were obtained for the following traits: died, lameness, mastitis, metabolic diseases (displaced abomasum, ketosis, and milk fever), reproductive diseases (abortion, metritis, and retained placenta), transition health events (any health event occurring 21 d before or after parturition), and all health events. Binary phenotypes (1 = diseased, 0 = otherwise) for 38,949 lactations on 19,139 Holstein cows were used. Genotypes from 2,347 cows with 87.5% or greater Holstein breed-based representation were incorporated into single-step multitrait threshold animal models that included stayability (1 = completed lactation, 0 = otherwise). Gibbs sampling was used. Genomic predicted transmitting abilities (gPTA) from national genetic evaluations were obtained for sires for production, fitness, health, and conformation traits. We approximated genetic correlations for sires using these gPTA and our estimated breeding values. We also regressed health phenotypes on cow estimated breeding values and sire gPTA. Heritabilities (± standard error) ranged from 0.03 ± 0.01 (reproductive diseases) to 0.11 ± 0.03 (metabolic diseases). Most genetic correlations among health traits were positive, though the genetic correlation between metabolic disease and mastitis was ?0.42 ± 0.17. Approximate genetic correlations between disease resistance for our health trait categories and disease resistance for the nationally-evaluated health traits generally carried the expected sign with the strongest correlation for mastitis (0.72 ± 0.084). Regression coefficients carried the expected sign and were mostly different from zero, indicating that evaluations from primarily conventional herd data predicted health on organic farms. In conclusion, use of national evaluations for health traits should afford genetic improvement for health in US organic herds.     

Inheritance and relationships of linear type traits for age groups of Holsteins

Routine classifications from the linear type trait program of the Holstein Association were analyzed separately for age groups. Inheritance of linear type traits and their genetic and phenotypic relationships were evaluated. Estimates of genetic and phenotypic parameters were compared to other studies with experimental classifications from the Holstein Association and with data from artificial insemination organizations across age groups. Evaluation of sires for type traits across age groups may not properly rank sires if ages of daughters differ for sires. Future genetic evaluations of type by the Holstein Association will consider only classifications of cows closest to 30 mo, so heritabilities for linear type traits for only 2 yr olds from this study may have application. Some linear type traits are very similar genetically. Stature has substantial genetic association with final score as subjectively assigned by classifiers.     

Potential of somatic cell concentration in milk as a sire selection criterion to reduce mastitis in dairy cattle

Lactation records for somatic cell counts in milk, bacteriological culture results, antibiotic treatment for mastitis, and production were formed for cows in 30 cooperating dairy herds in Virginia. A second data set, including somatic cell counts and production information for cows in approximately 400 herds in Virginia (not including the original 30), was used to evaluate sires genetically for somatic cell count. Approximate genetic correlations between measures of cell count and measures of infection ranged from .36 to .67. These were highest (lowest) for frequency of infection by major (minor) pathogens. Corresponding phenotypic correlations were similar but slightly smaller. Neither somatic cell counts nor measures of infection were well correlated with treatment. Production traits generally had small, negative genetic and phenotypic relationships with cell counts, rates of infection, and measures of treatment. Correlations for evaluations of sires for cell count were positive with daughter averages for infection rates (.20 to .38) and treatment measures (.02 to .13). Largest (absolute value) correlations between evaluations of sires for cell count and production traits were for fat percentage (-.38) and fat yield (-.28). Evaluation and selection of sires for decreased somatic cell count may augment management and treatment programs in the reduction of mastitis incidence.     

Genetic associations between clinical mastitis and somatic cell score in early first-lactation cows

The objectives of this study were to examine genetic associations between clinical mastitis and somatic cell score (SCS) in early first-lactation cows, to estimate genetic correlations between SCS of cows with and without clinical mastitis, and to compare genetic evaluations of sires based on SCS or clinical mastitis. Clinical mastitis records from 15 d before to 30 d after calving and first test-day SCS records (from 6 to 30 d after calving) from 499,878 first-lactation daughters of 2,043 sires were analyzed. Results from a bivariate linear sire model analysis of SCS in cows with and without clinical mastitis suggest that SCS is a heterogeneous trait. Heritability of SCS was 0.03 for mastitic cows and 0.08 for healthy cows, and the genetic correlation between the 2 traits was 0.78. The difference in rank between sire evaluations based on SCS of cows with and without clinical mastitis varied from −994 to 1,125, with mean 0. A bivariate analysis with a threshold-liability model for clinical mastitis and a linear Gaussian model for SCS indicated that heritability of liability to clinical mastitis is at least as large as that of SCS in early lactation. The mean (standard deviation) of the posterior distribution of heritability was 0.085 (0.006) for liability to clinical mastitis and 0.070 (0.003) for SCS. The posterior mean (standard deviation) of the genetic correlation between liability to clinical mastitis and SCS was 0.62 (0.03). A comparison of sire evaluations showed that genetic evaluation based on SCS was not able to identify the best sires for liability to clinical mastitis. The association between sire posterior means for liability to clinical mastitis and sire predicted transmitting ability for SCS was far from perfect.     

Synchronization of breeding and its impact on genetic parameters and evaluation of female fertility traits

Achieving an acceptable level of fertility in herds is difficult for many dairy producers because identifying cows in estrus has become challenging owing to poor estrus expression, increased herd size, and lack of time and skilled labor for estrus detection. As a result, synchronization of estrus is often used to manage reproduction. The aims of this study were (1) to identify artificial inseminations (AI) that were performed following synchronization and (2) to assess the effect of synchronization on genetic parameters and evaluation of fertility traits. This study used breeding data collected between 1995 and 2021 from over 4,600 Australian dairy herds that had at least 30 matings per year. Because breeding methods were not reported, the recording pattern of breeding dates showing a large proportion of the total AI being recorded on a single date of the year served as an indicator of synchronization. First, the proportion of AI recorded on each day of the year was calculated for each herd-year. Subsequently, synchronization was defined when a herd with, for instance, only 30 matings in a year, had at least 0.20 or more AI on the same day. As the number of breedings in a herd-year increased, the threshold for classifying AI was continuously reduced from 0.20 to as low as 0.03 under the assumption that mating of many cows on a single date becomes increasingly difficult without synchronization. From the current data, we deduced that 0.11 of all AI were possibly performed following synchronization (i.e., timed AI, TAI). The proportion of AI classified as TAI increased over time and with herd size. Although the deviation from equal numbers of mating on 7 d of the week was not used for classifying AI, 0.44 of AI being categorized as TAI were performed on just 2 d of the week. When data classified as TAI were used for estimating genetic parameters and breeding values, the interval between calving and first service (CFS) was found to be the most affected trait. The phenotypic and additive genetic variance and heritability, as well as variability and reliability of estimated breeding values of bulls and cows for CFS were lower for TAI than for AI performed following detected estrus (i.e., estrus-detected AI, EAI). For calving interval, first service nonreturn rate (FNRR), and successful calving rate to first service, genetic correlations between the same trait measured in TAI and EAI were close to 1, in contrast to 0.55 for CFS. The lower genetic variances and heritabilities for FNRR and calving interval in TAI than in EAI suggests that synchronization reduces the genetic variability of fertility. In conclusion, TAI makes CFS an ineffective measure of fertility. One approach to minimize this effect on genetic evaluations is to identify TAI (using the method described for example) and then set the CFS of these cows as missing records when running multitrait genetic evaluations of fertility traits that include CFS. In the long term, the most practical and accurate way to reduce the effect of synchronization on genetic evaluations is to record TAI along with mating data.     

Combined use of Ovsynch and progesterone supplementation after artificial insemination in dairy cattle

The objective of this study was to evaluate the effects of different Ovsynch protocols combined with progesterone (P4) supplementation after artificial insemination (AI) of Holstein-Friesian cows. Cows were randomly synchronized at 52 to 63 d after parturition with either the classical Ovsynch protocol (GnRH on d 0, PGF(2α) on d 7, GnRH 48 h after PGF(2α)) or with a modified Ovsynch protocol (second GnRH 60 h after PGF(2α)). On d 4 after timed AI (TAI), the cows were blocked by parity and randomly divided into 2 groups. Half of the cows were supplemented with P4 (P4+) by applying a P4-releasing intravaginal device intravaginally for 14 d, whereas the other half remained untreated (P4-). In 50% of randomly chosen cows, plasma P4 was measured on d 4, 5, and 18 after TAI. Sonographic pregnancy diagnosis was performed on d 33 after TAI in a total of 398 cows. Health status and body condition score (BCS) of all cows were examined at several stages of the study. Cows in the modified Ovsynch protocol tended to have higher P4 values on d 4 after TAI than cows in the classical Ovsynch protocol (2.1 ± 0.2 vs. 1.6 ± 0.2 ng/mL), but no difference in pregnancy per AI (P/AI) was observed between the 2 Ovsynch protocols (38.4% vs. 44.1%). Independent of the Ovsynch protocols, P4+ cows tended to have higher P/AI compared with P4- cows (44.4% vs. 38.1%). The retention of fetal membranes and BCS at the time of insemination affected P/AI. Moreover, an interaction between BCS at the time of insemination and P4 supplementation was apparent; that is, the difference in P/AI between P4+ and P4- cows was significant in cows with BCS ≥3.25. Progesterone-supplemented cows showed higher P4 values on d 5 (4.9 ± 0.2 vs. 2.6 ± 0.2) and d 18 (7.8 ± 0.2 vs. 6.3 ± 0.2) after TAI, respectively. In conclusion, the elongation of the time interval between the injections of PGF(2α) and the second GnRH from 48 to 60 h had no effect on P/AI. Progesterone supplementation after insemination improved the P/AI of the Ovsynch protocols, but this effect was more apparent in cows with BCS ≥3.25.