The goal of this study was to calculate the cost of purulent vaginal discharge (PVD) in dairy cows. The dataset included 11,051 cows from 16 dairy herds located in 4 regions of the United States. Purulent vaginal discharge was characterized as a mucopurulent, purulent, or reddish-brownish vaginal discharge collected at 28 f 7 DIM. Gross profit was calculated as the difference between incomes and expenses, and the cost of PVD was calculated by subtracting the gross profit of cows with PVD from the gross profit of cows without PVD. Continuous outcomes such as milk production (kg/cow), milk sales ($/cow), cow sales ($/cow), feed costs ($/cow), reproductive management costs ($/cow), replacement costs ($/ cow), and gross profit ($/cow) were analyzed using linear mixed effects models. Pregnancy and culling by 305 DIM were analyzed by generalized linear mixed effects models using logistic regression. Models included the fixed effects of PVD, metritis, parity, region, season of calving, and morbidity in the first 60 DIM, as well as the interactions between PVD and metritis, PVD and parity group, and PVD and morbidity. Farm and the interaction between PVD and farm were considered random effects in all the statistical models. A stochastic analysis was conducted using 10,000 iterations with varying relevant inputs. Cows with PVD produced less milk (9,753.2 f 333.6 vs. 9,994.6 f 330.9 kg/cow), were less likely to be pregnant (70.7 f 1.7% vs. 78.9 f 1.2%), and were more likely to be culled by 305 DIM (34.6 f 1.7% vs. 27.2 f 1.3%) compared with cows without PVD. Consequently, milk sales (4,744.7 f 162.3 vs. 4,862.1 f 161.0 $/cow) and residual cow value (1,079.6 f 23.0 vs. 1,179.3 f 20.3 $/cow) were lesser for cows with PVD. Replacement (639.4 f 26.4 vs. 526.0 f 23.4 $/cow) and reproductive management costs (76.3 f 2.5 vs. 69.0 f 2.4 $/cow) were greater for cows with PVD. The mean cost of PVD was $202. The stochastic analysis also showed a mean cost of $202, ranging from $152 to $265. The robust dataset and the stochastic analysis strengthen both the external and internal validity of our findings, offering a deeper understanding of the economic consequences of PVD. In conclusion, PVD resulted in large economic losses to dairy herds by being associated with decreased milk yield, impaired reproduction, and greater culling.

The objective was to assess differences in productive and reproductive performance, and survival associated with vaginal discharge characteristics and fever in postpartum dairy cows located in Western and Southern states of the U.S.A. This retrospective cohort study included data from 3 experiments conducted in 9 dairies. Vaginal discharge was evaluated twice within 12 DIM and scored on a 5-point scale. The highest score observed for each cow was used for group assignment (VD group) as follows: VD 1 and 2 (VD 1/2; n = 1,174) = clear mucus/lochia with or without flecks of pus; VD 3 (n = 1,802) = mucopurulent with < 50% pus; VD 4 (n = 1,643) = mucopurulent with ≥50% of pus or non-fetid reddish/brownish mucous, n = 1,643; VD 5 = fetid, watery, and reddish/brownish, n = 1,800. All VD 5 cows received treatment according to each herd's protocol. Rectal temperature was assessed in a subset of VD 5 cows, and subsequently divided into Fever (rectal temperature ≥39.5°C; n = 334) and NoFever (n = 558) groups. A smaller proportion of cows with VD 5 (67.6%) resumed ovarian cyclicity compared with VD 1/2 (76.2%) and VD 4 (72.9%) cows; however, a similar proportion of VD5 and VD 3 (72.6%) cows resumed ovarian cyclicity. A smaller proportion of VD 5 (85.8%) cows received at least one artificial insemination (AI) compared with VD 1/2 (91.5%), VD 3 (91.0%), or VD 4 (91.6%) cows. Although we did not detect differences in pregnancy at first AI according to VD, fewer cows with VD 5 (64.4%) were pregnant at 300 DIM than cows with VD 1/2 (76.5%), VD 3 (76.2%), or VD 4 (74.7%). Hazard of pregnancy by 300 DIM was smaller for VD 5 compared with VD 1/2, VD 3, or VD 4 cows. A greater proportion of VD 5 cows were removed from the herd within 300 DIM compared with other VD groups. There was 760 kg lesser milk production within 300 DIM for VD 5 compared with VD 2, VD 3, and VD 4, whereas VD 2, VD 3, and VD 4 had similar milk production. We did not detect an association between fever at diagnosis of VD 5 and reproductive performance or milk production. A greater proportion of VD 5 cows without fever were removed from the herd by 300 DIM compared with VD 5 cows with fever. Differences in productive and reproductive performance, and removal of the herd were restricted to fetid, watery, and reddish/brownish vaginal discharge, which was independent of fever.

The objective of this study was to estimate the cost of metritis in dairy herds. Data from 11,733 dairy cows from 16 different farms located in 4 different regions of the United States were compiled for up to 305 d in milk, and 11,581 cows (2,907 with and 8,674 without metritis) were used for this study. Metritis was defined as fetid, watery, red-brownish vaginal discharge that occurs ≤21 d in milk. Continuous outcomes such as 305-d milk production, milk sales ($/cow), cow sales ($/cow), metritis treatment costs ($/cow), replacement costs ($/cow), reproduction costs ($/cow), feeding costs ($/cow), and gross profit per cow ($/cow) were analyzed using mixed effect models using the MIXED procedure of SAS (SAS Institute Inc., Cary, NC). Gross profit was also compared using the Kruskal-Wallis test. Dichotomous outcomes such as pregnant and culling by 305 d in milk were analyzed using the GLIMMIX procedure of SAS. Time to pregnancy and culling were analyzed using the PHREG procedure of SAS. Models included the fixed effects of metritis, parity, and the interaction between metritis and parity, and farm as the random effect. Variables were considered significant when P ≤ 0.05. Metritis cost was calculated by subtracting the gross profit of cows with metritis from the gross profit of cows without metritis. A stochastic analysis was performed with 10,000 iterations using the observed results from each group. Milk yield and proportion of cows pregnant were lesser for cows with metritis than for cows without metritis, whereas the proportion of cows leaving the herd was greater for cows with metritis than for cows without metritis. Milk sales, feeding costs, residual cow value, and gross profit were lesser for cows with metritis than for cows without metritis. Cow sales and replacement costs were greater for cows with metritis than for cows without metritis. The mean cost of metritis from the study herds was $511 and the median was $398. The stochastic analysis showed that the mean cost of a case of metritis was $513, with 95% of the scenarios ranging from $240 to $884, and that milk price, treatment cost, replacement cost, and feed cost explained 59%, 19%, 12%, and 7%, respectively, of the total variation in cash flow differences. In conclusion, metritis caused large economic losses to dairy herds by decreasing milk production, reproduction, and survival in the herd.

The objective of this study was to characterize incidences of health disorders during early lactation in a large population of Holstein cows calving in 2 seasons across multiple US dairy herds. In addition, cumulative effects of combinations of health-related events on fertility and survival by season of calving and parity number were tested. Data were prospectively collected from a total of 11,729 cows in 16 herds located in 2 regions in the United States [north (7,820 cows in 10 herds) and south (3,909 cows in 6 herds)]. Cows were enrolled at parturition and monitored weekly for disease occurrence, reproductive events, and survival. Health-related events were grouped into reproductive disorders (REP; dystocia, twins, retained fetal membranes, metritis, and clinical endometritis) and other disorders (OTH; subclinical ketosis, mastitis, displaced abomasum, and pneumonia). Counts of health events within 50 d postpartum were added into each of the groups and categorized as 0, 1, 2, 3, and ≥4 for REP and 0, 1, 2, and ≥3 for OTH. Multivariable logistic regression was used for testing potential associations between categories of disease occurrence and outcome variables, including resumption of ovarian cyclicity, pregnancy per artificial insemination (AI), pregnancy loss, and survival up to and after 50 DIM. The incidence of disease varied with season of calving and parity, and these 2 variables were associated with the reproductive and survival outcomes. The size of the detrimental effect of disease incidence on reproduction and survival depended on disease group and varied for each specific outcome. Resumption of ovarian cyclicity decreased as incidences of disorders increased in both REP and OTH categories. Pregnancy at first AI also was smaller in greater number of REP categories, but the effect of number of OTH categories on pregnancy at first AI was not consistent. Similarly, pregnancy loss at first AI was not affected consistently by REP or OTH. Survival was reduced by REP and OTH. The magnitude of these negative effects was variable, depending on season of calving and parity, but consistently increased with the number of health events during early lactation.

The study is part of a research effort investigating potential associations between genomic variation and fertility of Holstein cows. The objective was to compare the reproductive performance of Holstein cows in 3 categories of 2 reproductive indices (RI) that were developed for the allocation of cows in a ranking for potential fertility, based on the predicted probability of pregnancy. The associations between categories of the developed indices and multiple fertility variables in a large multistate population of Holstein cows were tested. In addition, we analyzed associations among the RI categories with milk yield and survival. Based on phenotypic information from individual cows, 2 reproductive indices (RI1 and RI2) were developed, representing a predicted probability that a cow will become pregnant at first artificial insemination postpartum, as a function of explanatory variables used in a logistic model. Data from a total of 11,733 cows calving in 16 farms located in 4 regions of the United States (Northeast, Midwest, Southeast, and Southwest) were available. Cows were enrolled at parturition and monitored weekly for reproductive events, health status, milk yield, and survival. To develop the indices, potential significant effects were initially tested by univariate analyses. Effects with P ≤ 0.05 were offered to the multivariate analysis, and the final models were determined through backward elimination, considering potentially significant interactions. The final model for RI1 included the random effect of farm and a complement of significant fixed effects as explanatory variables influencing a pregnancy outcome: (1) incidence of retained fetal membranes; (2) metritis; (3) clinical endometritis; (4) lameness at 35 days in milk (DIM); (5) resumption of postpartum ovulation by 50 DIM; (6) season of calving; and (7) parity number. The model for RI2 included (1) parity number; (2) body condition score at 40 DIM; (3) incidence of retained fetal membranes; (4) metritis; (5) resumption of postpartum ovulation by 50 DIM; (6) region; (7) subclinical ketosis; (8) mastitis; (9) clinical endometritis; and (10) milk yield at the first milk test after calving; as well as the interaction effects of postpartum resumption of ovulation by 50 DIM × region; mastitis × region; and milk yield at the first milk test after calving × parity number. Multivariate logistic regression, ANOVA, and survival analysis were used to test the correspondence between the resulting RI and individual fertility, milk yield, and survival from the population. To facilitate the analyses, the resulting RI values were categorized as low for cows in the lowest quartile, medium for cows within the interquartile range, or high for cows in the top quartile. We found consistent agreement between categories of the predicted RI and the measures of fertility and survival collected from individual cows. We conclude that the proposed RI represent a viable approach to refine the allocation of cows into potential low- and high-fertility populations.

SummaryThe objective of this study was to compare accuracies of different Bayesian regression models in predicting molecular breeding values for health traits in Holstein cattle. The dataset was composed of 2505 records reporting the occurrence of retained fetal membranes (RFM), metritis (MET), mastitis (MAST), displaced abomasum (DA), lameness (LS), clinical endometritis (CE), respiratory disease (RD), dystocia (DYST) and subclinical ketosis (SCK) in Holstein cows, collected between 2012 and 2014 in 16 dairies located across the US. Cows were genotyped with the Illumina BovineHD (HD, 777K). The quality controls for SNP genotypes were HWEP‐value of at least 1 × 10−10; MAF greater than 0.01 and call rate greater than 0.95. TheFImputeprogram was used for imputation of missing SNP markers. The effect of each SNP was estimated using the Bayesian Ridge Regression (BRR), Bayes A, Bayes B and Bayes Cπ methods. The prediction quality was assessed by the area under the curve, the prediction mean square error and the correlation between genomic breeding value and the observed phenotype, using a leave‐one‐out cross‐validation technique that avoids iterative cross‐validation. The highest accuracies of predictions achieved were: RFM [Bayes B (0.34)], MET [BRR (0.36)], MAST [Bayes B (0.55), DA [Bayes Cπ (0.26)], LS [Bayes A (0.12)], CE [Bayes A (0.32)], RD [Bayes Cπ (0.23)], DYST [Bayes A (0.35)] and SCK [Bayes Cπ (0.38)] models. Except for DA, LS and RD, the predictive abilities were similar between the methods. A strong relationship between the predictive ability and the heritability of the trait was observed, where traits with higher heritability achieved higher accuracy and lower bias when compared with those with low heritability. Overall, it has been shown that a high‐density SNP panel can be used successfully to predict genomic breeding values of health traits in Holstein cattle and that the model of choice will depend mostly on the genetic architecture of the trait.

Automated data collection systems were used to identify periods of increased activity at estrus and to assess factors affecting the magnitude and duration of estrous activity. In total, 4,172 estrous periods in 1,454 cows across 5 herds in Europe and Canada were studied. Each herd used automated management systems manufactured by DeLaval (Tumba, Sweden) including a milk progesterone (MP4) measurement and analysis system (Herd Navigator), a body condition scoring system (BCS Camera) and an activity system (DelPro). A “heat alarm” (HA) was defined as 2 consecutive MP4 samples below 5 ng/mL following a luteal phase. Estrus was defined as an increase in activity within 7 d after HA. Peaks in activity (estrus) were detected with an algorithm and the magnitude (fold change above baseline), duration, and area were determined. Cows were classified according to parity, month, BCS (≤2.75, 2.75–3.0, 3.0–3.25, >3.25), days in milk (DIM; ≤56, 57–84, 85–140, and >140), and daily milk production (<40, 40–50, and >50 kg/d) at the time of HA. Data were analyzed using a mixed model (PROC MIXED; SAS) with animal nested within herd defined as random. There was an effect of herd (range: 65.7 to 78.7%; P < 0.001), month (range: 69.0% for May–Jun to 78.7% for Nov-Dec; P < 0.002) and BCS (range: 70.0% for ≤2.75 to 77.1% for >3.25; P < 0.004) on the percentage of cows with an activity peak after HA. Neither DIM, parity, nor milk affected peak detection. For cows with an activity peak, the peak area was affected by herd (P < 0.001), DIM (P < 0.001), month (P < 0.001) and BCS (P < 0.001). Differences in peak area were primarily associated with greater peak duration and not peak magnitude. Peak duration (h) differed for herds (range: 16.9 ± 0.3 to 19.2 ± 0.2; P < 0.001), DIM (range: 17.4 ± 0.2 for ≤56 to 19.3 ± 0.3 for >140; P < 0.001), month (range: 17.3 ± 0.3 for May–June to 19.1 ± 0.2 for Nov-Dec) and BCS (range: 17.6 ± 0.3 for ≤2.75 to 18.9 ± 0.2 for >3.25; P < 0.001). Neither parity nor milk affected peak area or duration. Conclusions were that estrous activity is affected by herd, season (lowest in summer), BCS (lowest in low BCS cows) and DIM (lowest in early lactation cows).

In dairy cows, severe environmental conditions, such as heat stress during late gestation and early lactation, have been related to reduced subsequent milk yield and reproductive performance. Although these associations are supported by previous research, studies comparing the effect of season in multiple US regions are scarce. Here we analyze the association among season of calving and multiple indicators of fertility in multiple farms located in 4 US regions.

In the initial stage of lactation, dairy cattle experience negative energy balance, as the energy expenditure of milk production exceeds the amount of energy the cow is able to take up through eating. In this state, there is increased body fat mobilization by the cow, with consequences in milk composition, particularly in fatty acid profile and possibly increased ketone bodies in both blood and milk. On-farm technologies allow novel monitoring techniques and increase the overall amount of data available to producers and researchers. The objective of this study is to analyze the pallet of automatically collected data sources currently recorded at the University of Guelph’s Livestock Research and Innovation Centre (LRIC) and relate them to changes in milk composition. The automatically collected data sources currently recorded at LRIC include, but are not limited to, automatically recorded cow weights via a walkover parlour scale, automatic body condition scoring via 3-dimensional imaging, as well as individual feed intake events. Moreover, milk testing is performed weekly, with the mid-infrared spectral data also obtained for every test. Major milk fatty acid groups were predicted using previously developed calibration equations, and predicted milk beta-hydroxybutyrate contents also obtained. Changes in cow body weight in the initial stage of lactation were examined, along with milk composition. The results of this study improve the understanding of the phenotypic relationship between body weight changes and milk composition in early-lactation dairy cattle. Furthermore, we explore phenotypes associated with energy balance with implications for cow health and future genetic selection strategies.

Uterine diseases, such as metritis and endometritis, are highly prevalent in dairy cows. Clinical endometritis, more precisely identified as purulent vaginal discharge (PVD), is characterized by presence of purulent (>50% pus) uterine discharge detectable in the vagina ≥21 days after parturition, or mucopurulent (approximately 50% pus, 50% mucus) discharge detectable in the vagina >26 days postpartum. This condition has been associated with variable degrees of reduced fertility; however, the reported effects on subsequent survival in the herd are conflicting. The analysis of a large experimental data set, using a standardized disease definition would help to clarify these long-term responses. Therefore, the objective was to analyze the effect of PVD on multiple reproductive responses and survival in a large population of Holstein cows across US regions.

Due to pain and discomfort associated with lameness, this disorder represents a significant animal-welfare challenge for the dairy industry. In addition, the high incidence of this condition results in substantial economic losses that include treatment and control costs, premature culling, decreased milk yield, and impaired reproductive performance. Although previous studies established an association between lameness and reproduction, large multi-state prospective studies using standardized definitions and procedures can provide new insights on the magnitude of the effects of lameness on fertility of dairy cows. Therefore, our objective was to test the effect of lameness at early stages of lactation on fertility and survival of a large population of Holstein cows in dairies across multiple states.

Fertility is a critical component of dairy production and failures to attain and maintain pregnancy are major reasons for production losses in dairy herds. Reproductive efficiency is determined by a number of complex cow and environmental factors. Methodologies refining the identification of cows with low and high fertility would be a valuable tool for research in multiple areas, including genetic selection. Therefore, our objective was to develop a Reproductive Index (RI) to predict the probability of a timely pregnancy in a large population of dairy cows.

Endocrine changes at calving and drastic metabolic adjustments to support milk synthesis result in negative energy balance and immune suppression. Consequently, a substantial proportion of cows are affected by disease around the time of calving, and most health disorders occur in the first 30 DIM. Diseases have been associated with reduced reproductive performance and increased risk of death and culling. However, large multi-state prospective studies analyzing the effect of health events by use of standardized disease definitions and times of assessment are scarce. Therefore, our objective was to test the cumulative effect of combinations of health events on fertility and survival of a large population of Holstein cows in multiple states.

The decline in reproductive performance in cattle is of major concern to farmers and the dairy industry worldwide. Most fertility studies in cattle have focused on fertility of the cow, whereas the genetics of male fertility have not been thoroughly investigated. The present study hypothesizes that the high conservation of spermatogenesis genes from fly to human implies important roles of these genes in male fertility in cattle. To test this hypothesis, we performed an association analysis between highly conserved spermatogenesis genes and sire conception rate (SCR) in US Holsteins as a measure of bull fertility. Sequencing analysis revealed 24 single nucleotide polymorphisms (SNP) in 9 genes in the bull population using the pooled DNA sequencing approach. Five SNP previously identified in 5 genes from the POU1F1 pathway were also included in this study because they have shown significant associations with female and male fertility traits. Overall, 29 SNP located in 14 candidate genes were tested for association with sire conception rate in a population of 1,988 bulls. Three SNP located in MAP1B and 1 SNP in PPP1R11 showed significant associations with SCR. For the POU1F1 pathway, single gene analysis revealed significant associations of POU1F1 and STAT5A with SCR. Analysis of genotypic interactions between adjacent genes in the pathway revealed significant associations of STAT5A and UTMP genotypic combinations with SCR. The most significant spermatogenesis gene, MAP1B, was found to be associated with fertilization and blastocyst rates. Thus, the association of these genes with bull fertility testifies to the usefulness of the comparative genomics approach in selecting candidate male fertility genes.