Random Effect Of Herd Research Articles

Estimation of the nutrient variation in feed delivery and impacts on lactating dairy cattle

Diets formulated for dairy cattle are designed to supply nutrients, but rations delivered to the animal may deviate from original formulations resulting in implications on milk production, composition, and even pregnancy rate. The objective of this study is to evaluate retrospective feed mixing records collected from 8 commercial dairy farms over 52 weeks. Farms ranged from 2,982 – 29,783 animals, producing 31.8 ± 5.93 kg milk with 4.14 ± 0.461% fat and 3.26 ± 0.218% protein. Data collected included daily TMR nutrient deviation; calculated as diet nutrient content minus the observed divided by the formulated diet concentrations of CP, fat, NDF, and starch. Data were analyzed with fixed effects of time (modeled as 28-d periods) and days of positive nutrient deviation in fat, CP, NDF and starch with each nutrient alone and in combination with the other nutrients, random effects of herd, and repeated measure of time within herd. The nutrient deviation by farm averaged (±SD) 1.68 ± 2.655, 2.28 ± 4.473, 1.75 ± 2.621, and 1.47 ± 2.147% for CP, fat, NDF, and starch. Days of positive nutrient deviation per period averaged (±SD) 25.5 ± 3.47, 25.5 ± 3.72, 25.6 ± 3.49, and 25.9 ± 2.61. Dry matter intake (DMI; 17.2 ± 1.78 kg/d) decreased with increasing positive deviation days in starch (−0.0483 ± 0.01265; P < 0.01) and increased with increasing positive deviation days in CP (0.0211 ± 0.00942; P = 0.03). Milk yield (31.4 ± 2.50 kg/d) increased with positive deviation days in starch (0.0486 ± 0.02110; P = 0.02) and decreased with increased positive deviation days in NDF (−0.0298 ± 0.02202; P = 0.18). Finally, pregnancy rate (21.7 ± 4.34) increased with increasing positive deviation days in fat (0.385 ± 0.1635; P = 0.02) and decreased with increasing positive deviation days in CP (−0.420 ± 0.1879; P = 0.03). For these models, period significantly affected milk yield (P < 0.01) and but was not observed to affect pregnancy rate and DMI (P ≥ 0.12). Results suggest farm and nutrient type were significant sources of variation and overall, farms overfeed nutrients CP, fat, NDF, and starch 92% of the days of a 28-d period.

The association between time-series milk β-hydroxybutyrate dynamics and early reproductive performance of dairy cows

The DeLaval Herd Navigator is an on-farm sensor system that measures on a frequent basis milk progesterone (P4) and BHB in individual cows to closely monitor reproductive performance and energy balance. This information provides the opportunity to investigate the dynamics of BHB measured in milk (mBHB) and study the association between mBHB and early reproductive performance. The objectives of the study were (1) to describe mBHB dynamics within the first 20 DIM, and (2) to evaluate the association between mBHB dynamics and early reproductive performance at cow level. Two-year time-series data from 4,133 dairy cows in 38 Dutch dairy farms were available for analysis. Data included information on mBHB, daily milk yield, and the indicators of early reproductive performance, days from calving to resumption of cyclicity, days from calving to first estrus, and days from calving to first insemination. The following mBHB dynamic parameters were defined based on the first 20 DIM for each individual cow: average mBHB (AvgBHB), DIM when mBHB was for the first time ≥80 μmol/L (OnsetKeto), the total number of consecutive days a cow had mBHB concentration ≥80 μmol/L, and the number of measurements mBHB concentration was ≥80 μmol/L. Three Cox proportional hazard regression models with random herd effect were developed to evaluate the association between cow-level mBHB dynamics and days from calving to resumption of cyclicity, first estrus, and first insemination. Results showed that the mean AvgBHB within 20 DIM among all cows was 73 μmol/L. The mean OnsetKeto within 20 DIM, was 8 DIM. Among all cows having hyperketolactia, 55.8% (1,350/2,419) had OnsetKeto in the first week of lactation. In total, 41.5% (1,714/4,133) of the cows did not have OnsetKeto in the first 20 DIM. An early onset of hyperketolactia was associated with delayed fertility events. Cows with higher AvgBHB have a prolonged time interval from calving to resumption of cyclicity and first estrus. Information on mBHB dynamics and the association with early reproductive performance provides insights that might be helpful to improve reproductive performance of individual dairy cows.

Association between hyperketolactia and production in early-lactating dairy cows

Study aims were to investigate associations of hyperketolactia (HYKL) status of Holstein dairy cows between 6 and 60 d in milk (DIM), defined by milk acetone (mACE) and β-hydroxybutyrate (mBHB) content, with daily milk yield and composition. Milk samples (∼5.0 million) were collected over a 5-yr period (2014-2019) within the milk recording system in Poland. Concentrations of mACE and mBHB determined by Fourier-transform infrared spectroscopy were used to categorize samples into 4 ketolactia groups. Based on threshold values of ≥0.15 mmol/L mACE and ≥0.10 mmol/L mBHB, ketolactia groups were normoketolactia (NKL; mACE <0.15 mmol/L and mBHB <0.10 mmol/L), BHB hyperketolactia (HYKLBHB; mACE <0.15 mmol/L and mBHB ≥0.10 mmol/L), ACE hyperketolactia (HYKLACE; mACE ≥0.15 mmol/L and mBHB <0.10 mmol/L), and ACE and BHB hyperketolactia (HYKLACEBHB; mACE ≥0.15 mmol/L and mBHB ≥0.10 mmol/L). To investigate ketolactia association with production outcomes, a linear model was developed, including ketolactia group, DIM, parity, their interactions, year-season as fixed effects, and random effects of herd and cow. Among all milk samples, 31.2% were classified as HYKL, and of these, 52.6%, 39.6%, and 7.8% were HYKLACEBHB, HYKLBHB, and HYKLACE, respectively. Ketolactia groups differed for all traits studied in all parities and DIM. Among HYKL groups, lowest milk yield was found in HYKLACEBHB cows, except for 6 to 30 DIM in first- and second-lactation cows. Milk yield of HYKLBHB cows was higher than that of NKL cows until 20 to 30 DIM, and then it was lower than NKL cows. Milk yield of HYKLACE cows was mostly lower than NKL cows. Energy-corrected milk (ECM) yield of HYKLACEBHB cows was higher than that of NKL cows until 30 to 35 DIM for second lactation and third lactation or greater, and in the whole study period for first lactation. The yield of ECM for HYKLBHB cows was mostly higher than that of NKL cows, whereas HYKLACE cows had higher ECM than NKL cows until 15 to 25 DIM and then was lower for the HYKLACE group. Milk composition differed among HYKL groups. Highest milk fat (MF) and lowest milk lactose (ML) contents were observed in HYKLACEBHB cows. Cows in HYKLACEBHB and HYKLBHB groups had higher MF and lower milk protein (MP; except in 6-8 DIM in first lactation) and ML content than NKL cows. Milk fat content was higher in HYKLACE than NKL cows in first lactation and during the first 30 to 40 DIM in older cows. Lactose content was lower in HYKLACE than in NKL cows within 30 to 40 DIM; afterward it was higher in NKL cows. Lower MP content was found in HYKLACE than in NKL cows, except during 6 to 9 DIM for cows in first lactation and third lactation or greater. In conclusion, HYKL is associated with altered milk production in all parities, but a range of these negative relations depends on ketone status addressing both ACE and BHB contents. Further research is needed to ascertain underpinning biochemical defects of HYKL from elevated ACE, alone or in combination with BHB, during early lactation.

Prevalence and risk factors associated with high somatic cell count in Chinese dairy herds.

This study aimed to (1) estimate the prevalence of cow-level high somatic cell count (SCC) in Chinese dairy herds and (2) identify potential factors associated with cow- and herd-level SCC variables. The monthly data on dairy herd improvement were collected from a total of 131 dairy herds in 11 provinces in China in 2019. Mixed models were constructed using the cow composite milk SCC and the variance of cow SCC as dependent variables separately and parity, seasons, days in milk (DIM), herd size, and farm types (family-owned vs. company-owned) as fixed effects, accounting for the nested random herd and cow effect. We used negative binomial regression using herd-level SCC-related variables, namely, monthly proportion of high SCC, monthly proportion of new high SCC, monthly proportion of chronic high SCC, and monthly proportion of new chronic high SCC as dependent variables separately against seasons, herd size, and farm types with the random herd effect. The overall average prevalence of high SCCs for each month per farm was 0.26 (2.5-97.5% quantile: 0-0.56). Company-owned farms performed better in herd SCC management. Seasons were significantly associated with all the aforementioned variables, and summer and autumn were the seasons associated with worse outcomes in herd SCCs. This study is the first to assess high SCC in a large number of Chinese dairy herds, which is useful for farms to tailor the on-farm mastitis control programs in China.

Investigating the effect of temporal, geographic, and management factors on US Holstein lactation curve parameters.

We fit the Wood's lactation model to an extensive database of test-day milk production records of US Holstein cows to obtain lactation-specific parameter estimates and investigated the effects of temporal, spatial, and management factors on lactation curve parameters and 305-d milk yield. Our approach included 2 steps as follows: (1) individual animal-parity parameter estimation with nonlinear least-squares optimization of the Wood's lactation curve parameters, and (2) mixed-effects model analysis of 8,595,413 sets of parameter estimates from individual lactation curves. Further, we conducted an analysis that included all parities and a separate analysis for first lactation heifers. Results showed that parity had the most significant effect on the scale (parameter a), the rate of decay (parameter c), and the 305-d milk yield. The month of calving had the largest effect on the rate of increase (parameter b) for models fit with data from all lactations. The calving month had the most significant effect on all lactation curve parameters for first lactation models. However, age at first calving, year, and milking frequency accounted for a higher proportion of the variance than month for first lactation 305-d milk yield. All parameter estimates and 305-d milk yield increased as parity increased; parameter a and 305-d milk yield rose, and parameters b and c decreased as year and milking frequency increased. Calving month estimates parameters a, b, c, and 305-d milk yield were the lowest values for September, May, June, and July, respectively. The results also indicated the random effects of herd and cow improved model fit. Lactation curve parameter estimates from the mixed-model analysis of individual lactation curve fits describe well US Holstein lactation curves according to temporal, spatial, and management factors.

The effect of new bovine viral diarrhea virus introduction on somatic cell count, calving interval, culling, and calf mortality of dairy herds in the Dutch bovine viral diarrhea virus–free program

Bovine viral diarrhea virus (BVDV) infection has a major effect on the health of cows and consequently on herd performance. Many countries have implemented control or eradication programs to mitigate BVDV infection and its negative effects. These negative effects of BVDV infection on dairy herds are well documented, but there is much less information about the effects of new introduction of BVDV on dairy herds already participating in a BVDV control program. The objective of our study was to investigate the effect of a new BVDV introduction in BVDV-free herds participating in the Dutch BVDV-free program on herd performance. Longitudinal herd-level surveillance data were combined with herd information data to create 4 unique data sets, including a monthly test-day somatic cell count (SCC) data set, annual calving interval (CIV) and culling risk (CR) data sets, and a quarterly calf mortality rate (CMR) data set. Each database contained 2 types of herds: herds that remained BVDV free during the whole study period (defined as free herds), and herds that lost their BVDV-free status during the study period (defined as breakdown herds). The date of losing the BVDV-free status was defined as breakdown date. To compare breakdown herds with free herds, a random breakdown date was artificially generated for free herds by simple random sampling from the distribution of the breakdown month of the breakdown herds. The SCC and CIV before and after a new introduction of BVDV were compared through linear mixed-effects models with a Gaussian distribution, and the CR and CMR were modeled using a negative binomial distribution in generalized linear mixed-effects models. The explanatory variables for all models included herd type, BVDV status, year, and a random herd effect. Herd size was included as an explanatory variable in the SCC, CIV, and CMR model. Season was included as an explanatory variable in the SCC and CMR model. Results showed that free herds have lower SCC, CR, CMR, and shorter CIV than the breakdown herds. Within the breakdown herds, the new BVDV introduction affected the SCC and CMR. In the year after BVDV introduction, the SCC was higher than that in the year before BVDV introduction, with a factor of 1.011 [2.5th to 97.5th percentile (95% PCTL): 1.002, 1.020]. Compared with the year before BVDV breakdown, the CMR in the year of breakdown and the year after breakdown was higher, with factors of 1.170 (95% PCTL: 1.120; 1.218) and 1.096 (95% PCTL: 1.048; 1.153), respectively. This study reveals that a new introduction of BVDV had a negative but on average relatively small effect on herd performance in herds participating in a BVDV control program.

Blood calcium as a prognostic indicator of success after surgical correction of left displaced abomasum

Subclinical hypocalcemia, a reduction in blood calcium concentrations without apparent clinical signs of milk fever, occurs in 25 to 50% of early-postpartum dairy cows. Research has shown that these cows are at an increased risk of additional early-lactation diseases, including left displaced abomasum (LDA), compared with their normocalcemic counterparts. However, no work has assessed the association of total calcium (tCa) concentration at the time of LDA correction with subsequent milk yield and survival within the herd. Pending future development of an economical and accurate on-farm test for hypocalcemia, the ability to assess LDA prognosis after surgical correction based on precorrection blood tCa concentration is of interest to practitioners. Therefore, our objective was to determine the association of blood tCa concentration at the time of LDA surgical correction with milk yield and herd removal in the 60 d after correction. Nine bovine practitioners, located in New York State, were involved in sample collection from 17 herds for this prospective cohort study. Immediately following LDA diagnosis and before surgical correction, blood samples were collected from 152 dairy cows within the first 30 d in milk for serum tCa determination. The association of tCa with milk yield (n = 110) and herd removal (n = 127) in the first 60 d after LDA surgical correction was analyzed using repeated-measures ANOVA and a generalized linear mixed model, respectively, controlling for parity and days in milk at LDA surgical correction and the random effect of herd or practitioner. We found no evidence to support an association of tCa at time of LDA diagnosis with subsequent milk yield, and when cows were grouped by median tCa into low and high groups (tCa ≤2.1 and >2.1 mmol/L, respectively), subsequent milk production was similar (39.4 ± 1.6 and 40.1 ± 1.4 kg/d for low and high, respectively). Furthermore, we found no evidence to support an association of tCa at time of LDA diagnosis with the odds of herd removal (odds ratio = 0.6; 95% confidence interval = 0.4–1.7). Therefore, our study provided no clear evidence to support the association of tCa at time of LDA diagnosis and correction with either milk yield or herd removal during the 8 wk after correction. However, it did demonstrate low to extremely low tCa concentration in cows with LDA. Whether calcium supplementation would improve health and production outcomes in these cows is unclear and worth investigating further.

Breed, heterosis, and recombination effects for lactation curves in Brazilian cattle

The objective of this study was to estimate the breed, heterosis, and recombination effects on different components of the lactation curve of Girolando cattle. The dataset used consisted of 12,121 purebred cows of Holstein (H) and Gyr (G) breeds, and six H×G crossbred cows (Girolando). The model used presents random effects of herd and cow, regression coefficient associated with linear effect of proportion of H breed, regression coefficient associated with the linear effect of heterosis between H and G [...]

Dry cow therapy and early lactation udder health problems—Associations and risk factors

Mastitis remains the most expensive disease of dairy cows, and antibiotic dry cow therapy (DCT) at dry-off is an important part of mastitis control. Regardless of the infection status, blanket DCT is administered to all quarters of all cows, which is controversial due to the worldwide problem of antimicrobial resistance. Even though selective DCT of only infected cows is a more sustainable approach, choosing animals for treatment is not always straightforward. Our aim was to evaluate whether the herd-level DCT approach is associated with early lactation udder health problems, taking into account the cow characteristics. The information source was 2015–2017 Dairy Herd Improvement data with 7461 multiparous cows from 241 Finnish dairy herds. Information on the herd-level DCT approach was obtained from farmers' questionnaire responses in 2017, and the three different approaches were selective DCT, blanket DCT, and no DCT. The statistical tool for the data analysis was a generalized linear mixed model with a random herd effect for binary outcomes and a linear mixed model with a random herd effect for a continuous outcome. The two binary outcomes were the odds of having high milk somatic cell count (SCC ≥ 200 000 cells/mL) on the first test-day within 5–45 days in milk (DIM) and the odds of mastitis treatment in early lactation up to 45 DIM. The third outcome was the mean milk lnSCC (× 1000 cells/mL) within 120 DIM. Selective DCT was the prevailing treatment practice in our data. Blanket DCT was associated with lower SCC after calving. Cows more likely to have high SCC after calving were older cows, cows with high average SCC during the previous lactation, and cows with high milk yield near dry-off. A mastitis treatment in the early lactation was more likely if, during the previous lactation, the cow had high average SCC, high peak milk production, or high milk yield near dry-off. Our findings indicate that DCT is still effective in mastitis control. Cows with high milk yield, especially near dry-off, and cows with persistently high SCC require attention when considering next lactation udder health.

The effect of bovine viral diarrhea virus introduction on milk production of Dutch dairy herds

Dairy cows are negatively affected by the introduction of bovine viral diarrhea virus (BVDV), and consequently, produce less milk. Existing literature on potential milk production losses is based on relatively outdated data and hardly evaluates milk production loss in relation to a new BVDV infection in a surveillance system. This study determined the annual and quarterly loss in milk production of BVDV introduction in 3,126 dairy herds participating in the Dutch BVDV-free program between 2007 and 2017. Among these herds, 640 were "breakdown-herds" that obtained and subsequently lost their BVDV-free status during the study period, and 2,486 herds obtained and retained their BVDV-free status during the study period. Milk yields before and after BVDV introduction were compared through annual and quarterly linear mixed models. The fixed variables for both models included herd type (breakdown-herd or free-herd), bovine viral diarrhea status (on an annual and quarterly basis), year, season, and a random herd effect. The dependent variable was the average daily milk yield on the test day. To define the possible BVDV-introduction dates, 4 scenarios were developed. In the default scenario, the date of breakdown (i.e., loss of the BVDV-free status) was assumed as the BVDV-introduction date. For the other 3 scenarios, the BVDV-introduction dates were set at 4, 6, and 9 mo before the date of breakdown, based on the estimated birth date of a persistently infected calf. In the default scenario, the loss in milk yield due to BVDV introduction occurred mainly in the first year after breakdown, with a reduction in yield of 0.08 kg/cow per day compared with the last year before breakdown. For the other 3 scenarios, the greatest yield reduction occurred in the second year after BVDV introduction, with a loss of 0.09, 0.09, and 0.1 kg/cow per day, respectively. For the first 4 quarters after BVDV introduction in the default scenario, milk yield loss was 0.14, 0.09, 0.02, and 0.08 kg/cow per day, respectively. These quarterly results indicated that milk yield loss was greatest in the first quarter after BVDV introduction. Overall, BVDV introduction had a negative, but on average a relatively small, effect on milk yield for herds participating in the BVDV-free program. This study will enable dairy farmers and policymakers to have a clearer understanding of the quantitative milk production effect of BVDV on dairy farms in a control program.

Herd-level associations between somatic cell counts and economic performance indicators in Brazilian dairy herds

The aims of the present study were to provide a portrait of the techno-economic status of dairy herds in Minas Gerais, Brazil, particularly with respect to bulk-tank somatic cell count (BTSCC) data, and to examine the herd-level associations of BTSCC with various economic performance indicators (EPI). Data from 543 herds, 1,052 herd-year records in total, spread over 3 years (2015-2017), from the South and Southwest mesoregions of Minas Gerais State were provided by the Brazilian Support Agency to Micro and Small Companies Division Minas Gerais (SEBRAE). Herds had an average of 82 lactating cows per herd, milk yield of 17 L/cow per day, and availability of financial information via routine monthly economic surveys. The EPI data (revenue, gross margin, GM; net margin, NM; profit; break-even point; and operational profitability) of each herd was measured monthly by SEBRAE personnel, and herd-year averages of all variables were computed. Bulk-tank data (SCC, total bacterial count, content of crude protein and fat) taken by producers or dairy processors were recorded by SEBRAE personal; and corresponding herd-year averages were calculated and included in the SEBRAE database. There were 209 selected herds, which passed all edit checks, and which had data for all 3 years. The EPI (all expressed on a per-cow basis, $/cow per year) were analyzed, including the effects of region, year, log (ln) BTSCC, production level, and herd size, together with the random effect of herd nested within region. A high proportion of herds (94.6%) presented data records (herd-years) with an average BTSCC > 200 × 103 cells/mL: 37.8% of herd-year records had BTSCC between >200 and ≤400, 14.5% with BTSCC between >400 and ≤500, 25% with BTSCC between >500 and ≤750, and 17.3% with BTSCC >750. For each unit increase in ln BTSCC, revenue declined by $228.5/cow per year, GM by $155.6/cow per year, and profit by $138.6/cow per year. Herds with cows of lower production (<14 kg/d) presented lower GM ($286.8/cow per year) compared with herds containing cows producing ≥14 kg/d (≥14 and <19 kg/d = $446.5, and ≥19 kg/d = $601.9). The small-scale milk producers (<39 lactating cows) presented lower revenue ($1,914.9/cow per year) and GM ($274.5/cow per year) and consequently a negative profit (-$224.1/cow per year) compared with other herd size categories (≥39 lactating cows). The reduction in milk yield was 641 L/cow per lactation for each unit increase in ln BTSCC; this represented 9.4% of the milk yield per lactation, assuming an average milk production of 6,843.3 L/cow per lactation of cows from herds that had BTSCC ≤ 200 × 103 cells/mL. Consequently, we found a negative association of BTSCC with profit; profit declining from $227.0 to -53.1/cow per year when the BTSCC increased from 100 to 750 × 103 cell/mL. In short, the lower the BTSCC, the greater the revenue, GM and NM, profit, and operational profitability of the herds. The reduction of milk yield was the main factor associated with higher BTSCC.

Differential Somatic Cell Count as a Novel Indicator of Milk Quality in Dairy Cows.

Simple SummaryRecently, high-throughput instruments have been used to analyze milk differential somatic cell count, represented by the combined proportion of polymorphonuclear leukocytes and lymphocytes, providing indirect information on the udder inflammation status of dairy cows. No information is available about the relationship between differential somatic cell count and milk quality, so the aim of this study was to investigate the effect of differential somatic cell count on the composition of a large number of individual milk samples. Results showed that milk quality worsened when differential somatic cell count was high. In particular, it was evidenced lower milk fat, protein, casein contents and casein index, and augmented milk fatty acids could be found with an increasing differential somatic cell count level. These findings confirmed that differential somatic cell count could be a new informative tool for dairy farmers to monitor the quality of milk.Recent available instruments allow to record the number of differential somatic cell count (DSCC), representing the combined proportion of polymorphonuclear leukocytes and lymphocytes, on a large number of milk samples. Milk DSCC provides indirect information on the udder health status of dairy cows. However, literature is limited regarding the effect of DSCC on milk composition at the individual cow level, as well as its relation to the somatic cell score (SCS). Hence, the aims of this study were to (i) investigate the effect of different levels of DSCC on milk composition (fat, protein, casein, casein index, and lactose) and (ii) explore the combined effect of DSCC and SCS on these traits. Statistical models included the fixed effects of days in milk, parity, SCS, DSCC and the interaction between SCS × DSCC, and the random effects of herd, animal within parity, and repeated measurements within cow. Results evidenced a decrease of milk fat and an increase in milk fatty acids at increasing DSCC levels, while protein, casein and their proportion showed their lowest values at the highest DSCC. A positive association was found between DSCC and lactose. The interaction between SCS and DSCC was important for lactose and casein index, as they varied differently upon high and low SCS and according to DSCC levels.

Genomic evaluation for wellness traits in US Jersey cattle

The number of Jersey cows in the United States has been steadily increasing in recent years according to Council on Dairy Cattle Breeding statistics. To help producers reduce the risk of health disorders in their Jersey animals, Zoetis has developed genomic predictions for wellness traits in Jersey cattle using producer-recorded data. The traits included mastitis (MAST), metritis, retained placenta, displaced abomasum (DA), ketosis, lameness, and milk fever in cows and respiratory disease, scours, and calf livability (DEAD) in calves. Phenotypic data on health events, pedigree, and genotypes were collected directly from producers upon obtaining their permission. Each trait was defined as a binary event, having a value of 1 if an animal has been recorded with a disorder and 0 otherwise. The number of phenotypic records ranged from 216,166 for DA to 628,958 for MAST for cow traits and from 186,505 for scours to 380,429 for DEAD for calf traits. The number of genotyped animals was 41,271. All traits were analyzed using a univariate threshold animal model. The model for cow wellness traits included the fixed effect of parity and random effects of herd × year × season of calving, animal, and permanent environment. The model for calf wellness traits included the fixed effect of year of birth × calving season × region and random effects of herd × year of birth and animal. A total of 45,163 SNP were used in genomic analyses. Animals genotyped with low-density chips were imputed to the required number of markers. All analyses were based on the single-step genomic BLUP. Heritabilities ranged from 0.061 for DA to 0.120 for lameness. Predicted transmitting abilities were expressed in percentage points as deviations from the average estimated probability of a disorder in the base population. Reliabilities of genomic predicted transmitting abilities had average values between 32% (DA) and 51% (MAST and DEAD). The results indicate that a direct evaluation of cow and calf wellness traits under a genomic threshold model is feasible and offers predictions with average reliabilities comparable with other lowly heritable traits for Jersey cattle.

Genomic evaluation for calf wellness traits in Holstein cattle

Reducing calf morbidity and mortality is important for attaining financial sustainability and improving animal welfare on commercial dairy operations. Zoetis (Kalamazoo, MI) has developed genomic predictions for calf wellness traits in Holsteins that include calf respiratory disease (RESP; recorded between 0 and 365 d of age), calf scours (DIAR; recorded between 2 and 50 d of age), and calf livability (DEAD; recorded between 2 and 365 d of age). Phenotype and pedigree data were from commercial dairies and provided directly by producers upon obtaining their permission. The number of records ranged from 741,484 for DIAR to 1,926,261 for DEAD. The number of genotyped animals was 325,025. All traits were analyzed using a univariate threshold animal model including fixed effect of year of birth × calving season × region, and random effects of herd × year of birth and animal. A total of 45,425 SNP were used in genomic analyses. Animals genotyped with low-density chips were imputed to the required number of SNP. All analyses were conducted using single-step genomic BLUP implementing the "algorithm for proven and young" (APY) animals designed to accommodate very large numbers of genotypes. Estimated heritabilities were 0.042, 0.045, and 0.060 for RESP, DIAR, and DEAD, respectively. The genomic predicted transmitting abilities ranged between -8.0 and 24.0, -11.5 and 28.5, and -6.5 to 22.8 for RESP, DIAR, and DEAD, respectively. Reliabilities of breeding values were obtained by approximation based on partitioning of a function of reliability into contributions from records, pedigree, and genotypes, where the genotype contribution was approximated using the diagonal value of the genomic relationship matrix. The average reliabilities for the genotyped animals were 41.9, 42.6, and 47.3% for RESP, DIAR, and DEAD, respectively. Estimated genomic predicted transmitting abilities and reliabilities were approximately normally distributed for all analyzed traits. Approximated genetic correlations of calf wellness with Zoetis dairy wellness traits and traits included in the US national genetic evaluation were low to moderate. The results indicate that direct evaluation of calf wellness traits under a genomic threshold model is feasible and offers predictions with average reliabilities comparable to other lowly heritable traits. Genetic selection for calf wellness traits presents a compelling opportunity for dairy producers to help manage herd replacement costs and improve overall profitability.

Changes in milk characteristics and fatty acid profile during the estrous cycle in dairy cows

The relationship of the estrous cycle to milk composition and milk physical properties was assessed on Holstein (n = 10,696), Brown Swiss (n = 20,501), Simmental (n = 17,837), and Alpine Grey (n = 8,595) cows reared in northeastern Italy. The first insemination after calving for each cow was chosen to be the day of estrus and insemination. Test days surrounding the insemination date (from 10 d before to 10 d after the day of the estrus) were selected and categorized in phases relative to estrus as diestrus high-progesterone, proestrus, estrus, metestrus, and diestrus increasing-progesterone phases. Milk components and physical properties were predicted on the basis of Fourier-transform infrared spectra of milk samples and were analyzed using a linear mixed model, which included the random effects of herd, the fixed classification effects of year-month, parity number, breed, estrous cycle phase, day nested within the estrous cycle phase, conception, partial regressions on linear and quadratic effects of days in milk nested within parity number, as well as the interactions between conception outcome with estrous cycle phase and breed with estrous cycle phase. Milk composition, particularly fat, protein, and lactose, showed clear differences among the estrous cycle phases. Fat increased by 0.14% from diestrus high-progesterone to estrous phase, whereas protein concomitantly decreased by 0.03%. Lactose appeared to remain relatively constant over diestrus high-progesterone, rising 1 d before the day of estrus followed by a gradual reduction over the subsequent phases. Specific fatty acids were also affected across the estrous cycle phases: C14:0 and C16:0 decreased (-0.34 and -0.48%) from proestrus to estrus with a concomitant increase in C18:0 and C18:1 cis-9 (0.40 and 0.73%). More general categories of fatty acids showed a similar behavior; that is, unsaturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, trans fatty acids, and long-chain fatty acids increased, whereas the saturated fatty acids, medium-chain fatty acids, and short-chain fatty acids decreased during the estrous phase. Finally, urea, somatic cell score, freezing point, pH, and homogenization index were also affected indicating variation associated with the hormonal and behavioral changes of cows in standing estrus. Hence, the variation in milk profiles of cows showing estrus should potentially be taken into account for precision dairy farming management.

From cow to cheese: Novel phenotypes related to the sensory profile of model cheeses from individual cows

Milk samples were taken once from a total of 1,224 Brown Swiss cows from 83 herds, and 1,500 mL of raw full-fat milk from each cow was processed according to a laboratory-scale model-cheese-making procedure. A sensory panel was assembled and the members trained to evaluate the sensory profile of individual model cheeses. The protocol scorecard was composed of 7 main sensory descriptors related to smell intensity, flavor intensity, taste (salt and sour), and texture (elasticity, firmness, and moisture), and 40 sensory attributes describing smell and flavor profiles. Sensory data were analyzed using a mixed model that included random effects of herd, animal, and panelist, as well as fixed effects of dairy system, days in milk, parity, and order of cheese presentation, and covariates for cheese weight and fat:protein ratio. The sensory profile was not much affected by the dairy farming systems included in the trial, but it was affected by farm within dairy system: cheeses from traditional dairy farms had a greater wood/humus attribute of both smell and flavor than those from modern farm. Of the modern farms, cheeses from those using total mixed rations including silages had a more intense smell of sour milk and a firmer, less moist texture than those using total mixed rations without silages. Moreover, for all the sensory traits, we found less variance related to herd and animals than that related to the panelists and the residuals. Stage of lactation was found to be the most important, whereas parity was not relevant. In particular, cheese smell intensity (and some related attributes) exhibited a quadratic trend with lower values in mid-lactation, whereas flavor and salt descriptors were more intense in the last period of lactation.

190 SexedULTRA™, A NEW METHOD OF PROCESSING SEX-SORTED BOVINE SPERM IMPROVES CONCEPTION RATES

The gap in fertility between conventional and sex-sorted bovine sperm, known to be on the order of 10 percentage points, has never been bridged, even by increasing the number of sex-sorted sperm per inseminate. A concerted effort in the last few years has resulted in substantial changes in all stages of the sex-sorting process to develop an improved sex-sorted product called SexedULTRA™ (Sexing Technologies, Navasota, TX, USA). In vitro tests show that SexedULTRA™ maintained sperm integrity better than the previous XY method, and field trials were conducted to determine if this translated into improved bovine field fertility. The initial field trial was performed using ejaculates from 8 Holstein bulls located at Select Sires in Plain City (OH, USA). Each ejaculate was split in 2 aliquots that were then processed following the 2 methods (XY method or SexedULTRA™). A total of 6,930 Holstein heifers were inseminated across 41 commercial herds in the United States. Conception rate data were analysed using mixed model ANOVA (JMP 10.0.0; SAS Institute Inc., Cary, NC) with fixed effects of treatment, bull, bull by treatment interaction, and the random effect of herd. Sex-sorted bull sperm following the SexedULTRA™ method resulted in a greater (P &lt; 0.001) conception rate compared with the XY method sperm (45.7 ± 1.7 v. 41.2 ± 1.6%). This is the first report of an improvement in conception rates using sex-sorted bovine semen in a decade since it became commercially available. A second field trial to investigate dose rate effects and compare against conventional semen was performed using 5 dairy bulls located at German Genetics International GmbH in Cloppenburg (Germany). Each ejaculate was split 4 ways, sex-sorted, and frozen in 0.25-mL straws as follows: XY 2.1 million/straw, SexedULTRA™ 2.1 million/straw, SexedULTRA™ 3.0 million/straw, and SexedULTRA™ 4.0 million/straw. A total of 7,855 heifers were inseminated with these sex-sorted straws, whereas 62,398 heifers were inseminated with conventional straws (15 million/straw) produced using contemporary ejaculates from the same bulls. The 56-day nonreturn rate was calculated by sire and treatment combination, and assigned a weight based on the total number of AI for each combination thereof. Table 1 contains the nonreturn rate weighted means and the relative fertility compared to conventional sperm. Data were analysed using a mixed model ANOVA (JMP 10.0.0; SAS Institute Inc.) with treatment and bull as fixed effects. SexedULTRA™ 4.0 sperm presented the greatest (P &lt; 0.001) 56-day nonreturn rate followed by conventional 15.0 (66.73 v. 65.66%); XY 2.1 presented the lowest (P &lt; 0.001) nonreturn rate. This is the first time a dose response effect with sex-sorted bovine sperm and parity in conception rates with conventional semen has been demonstrated. Table 1. Field trial results for number of inseminations, 56-day nonreturn rate (NRR) weighted means, and relative fertility1 compared with conventional sperm

Development of genetic and genomic evaluation for wellness traits in US Holstein cows

In March 2016, Zoetis Genetics offered the first commercially available evaluation for wellness traits of Holstein dairy cattle. Phenotypic data on health events, pedigree, and genotypes were collected directly from producers upon obtaining their permission. Among all recorded health events, 6 traits were chosen to be included in the evaluation: mastitis, metritis, retained placenta, displaced abomasum, ketosis, and lameness. Each trait was defined as a binary event, having a value of 1 if a cow has been recorded with a disorder at any point during the lactation and zero otherwise. The number of phenotypic records ranged from 1.8 million for ketosis to 4.1 million for mastitis. Over 14 million pedigree records and 114,216 genotypes were included in the evaluation. All traits were analyzed using univariate threshold animal model with repeated observations, including fixed effect of parity and random effects of herd by year by season of calving, animal, and permanent environment. A total of 45,425 single nucleotide polymorphisms were used in the genomic analyses. Animals genotyped with low-density chips were imputed to the required number of single nucleotide polymorphisms. All analyses were based on the single-step genomic BLUP, a method that combines phenotype, pedigree, and genotype information. Predicted transmitting abilities were expressed in percentage points as a difference from the average estimated probability of a disorder in the base population. Reliabilities of breeding values were obtained by approximation based on partitioning of a function of reliability into contributions from records, pedigree, and genotypes. Reliabilities of genomic predicted transmitting abilities for young genotyped and pedigreed females without recorded health events had average values between 50.2% (displaced abomasum) and 51.9% (mastitis). Genomic predictions for wellness traits can provide new information about an animal’s genetic potential for health and new selection tools for dairy wellness improvement.

Genome wide association study on beef production traits in Marchigiana cattle breed.

A genomewide association study was carried out on a sample of Marchigiana breed cattle to detect markers significantly associated with carcass and meat traits. Four hundred and nine young bulls from 117 commercial herds were genotyped by Illumina 50K BeadChip assay. Eight growth and carcass traits (average daily gain, carcass weight, dressing percentage, body weight, skin weight, shank circumference, head weight and carcass conformation) and two meat quality traits (pH at slaughter and pH 24h after slaughter) were measured. Data were analysed with a linear mixed model that included fixed effects of herd, slaughter date, fixed covariables of age at slaughter and SNP genotype, and random effects of herd and animal. A permutation test was performed to correct SNP genotype significance level for multiple testing. A total of 96 SNPs were significantly associated at genomewide level with one or more of the considered traits. Gene search was performed on genomic regions identified on the basis of significant SNP position and level of linkage disequilibrium. Interesting loci affecting lipid metabolism (SOAT1), bone (BMP4) and muscle (MYOF) biology were highlighted. These results may be useful to better understand the genetic architecture of growth and body composition in cattle.

Abortion occurrence, repeatability and factors associated with abortions in female pigs in commercial herds

Abortion occurrences disturb the projected production volume and increase non-productive days of female pigs. The objectives of the present study were (1) to define abortion occurrences including abortion rate and abortion risk, (2) to examine risk factors that were associated with abortions, (3) to determine repeatability of abortions and (4) to compare reproductive performance between aborting and non-aborting re-serviced female pigs. Datasets included 122,935 lifetime performance records and 630,363 mating performance records of females in 125 herds between 2008 and 2013 in Spain, Portugal and Italy. Annualized abortion rate was defined as the number of abortion records divided by the sum of the reproductive herd life days×365 days×100. Abortion risk per service was defined as the number of abortion records divided by the number of service records×100. Generalized linear models with random herd effect were applied to the data. Annualized abortion rate (±SE) and abortion risk per service were 3.0±0.05 and 1.2±0.01%, respectively. Factors for an increased abortion risk per service were parity 0 or parity 5 or higher, re-servicing, servicing in July and August, delivering stillborn fetuses in a previous litter and having prolonged weaning-to-first-mating interval (WMI; P<0.05). Gilts (parity 0) and sows in parity 5 or higher had 0.3% higher abortion risk than parity 1 sows (P<0.05). Re-serviced females had 0.5% higher abortion risk than first-serviced females (P<0.05). Females serviced in July and August had 0.4–0.5% higher abortion risk than those serviced in March and April (P<0.05). Sows that had previously delivered stillborn fetuses subsequently had 0.1% higher abortion risk than those that had no stillborn fetuses (P<0.05). Sows mated 7 days or more after weaning had 0.2% higher abortion risk than those mated 0–6 days after weaning (P<0.05). Of the 7187 females that had aborted once, 4.1% experienced a second abortion in the same or a later parity. The repeatability of abortions was estimated to be 24.3–24.4%. Females that were reserviced after aborting had 0.6 lower total number of piglets born than re-serviced females that had not aborted (P<0.05). However, there was no difference in farrowing rate or WMI between aborting and non-aborting re-serviced females (P≥0.11). It is recommended that producers closely monitor female pigs at risk of having an abortion in order to reduce non-productive female days.