Variation in protein metabolism biomarkers during the transition period and associations with health, colostrum quality, reproduction, and milk production traits in Holstein cows.

The aims of this study were to assess (1) the variation of protein metabolism biomarkers and factors affecting them during the transition period, (2) the association of each biomarker with skeletal muscle reserves and their changes, and (3) the association of these biomarkers with postpartum health, colostrum quality, reproduction, and milk production. For this purpose, 238 multiparous Holstein cows from 6 herds were used in a prospective cohort study. Plasma concentrations of 3-methylhistidine (3-MH) and 1-methylhistidine (1-MH) and serum concentrations of total protein (TP), albumin (ALB), urea nitrogen (BUN), and creatinine (SCR) were determined for each cow at -21, -7, 7, 21, and 28 d relative to calving. Clinical diseases were recorded during the first 28 d postcalving, and presence of subclinical ketosis (scKET) was investigated at 7 and 21 d. Colostrum quality was estimated by Brix refractometry. Reproduction data by 150 d in milk (DIM) and milk production records were also available. Linear mixed models including the fixed effects of time point, herd, parity, body condition score (-21 d), duration of dry period and postparturient diseases were fitted to assess the variation in each biomarker's concentration. The association between the biomarkers' concentration during the prepartum period with the odds for each postparturient disease and for a combined trait (CD_1-28), defined as the presence of at least one clinical condition during the first 28 d after calving, were assessed with separate binary logistic models for time points -21 d and -7 d. The relationship of each biomarker's concentration with longissimus dorsi thickness (LDT) and the changes in LDT (ΔLDT) was assessed with pairwise correlations. Separate general linear models were used to assess the association of each biomarker with colostrum Brix values and milk production traits. Finally, the associated hazard for first artificial insemination (AI) and for pregnancy by 150 DIM (PREG_150DIM) was assessed with Cox proportional hazard models, whereas odds for pregnancy to the first AI (PREG_1stAI) were assessed with binary logistic models. The level of 3-MH was affected mainly by herd, time points, and their interaction. Higher 3-MH was associated with increased odds for metritis and CD_1-28, increased hazard for PREG_150 DIM and with increased milk production. 1-Methylhistidine was affected mainly by herd, scKET and occurrence of displaced abomasum. Higher 1-MH was associated with better colostrum quality, increased odds for scKET, increased hazard for first AI by 150 DIM and with decreased milk production. Both 3-MH and 1-MH were weakly to moderately negatively correlated with LDT and moderately to strongly negatively correlated with ΔLDT at the corresponding time periods. Additionally, higher TP was associated with increased odds for metritis and CD_1-28 and increased milk production, while higher ALB was associated with increased odds for scKET and increased milk production. Moreover, higher BUN was associated with decreased odds for scKET, increased odds for PREG_1stAI and increased milk production. Higher SCR was associated with decreased odds for retained fetal membranes, metritis, and CD_1-28. Periparturient protein metabolism is significantly associated with postpartum health, colostrum quality, reproduction, and milk production; mechanisms involved require further investigation.

Development and validation of a fully automated 2-dimensional imaging system generating body condition scores for dairy cows using machine learning.

Monitoring body condition score (BCS) is a useful management tool to estimate the energy reserves of an individual cow or a group of cows. The aim of this study was to develop and evaluate the performance of a fully automated 2-dimensional imaging system using a machine learning algorithm to generate real-time BCS for dairy cows. Two separate datasets were used for training and testing. The training dataset included 34,150 manual BCS (MAN_BCS) assigned by 5 experienced veterinarians during 35 visits at 7 dairy farms. Ordinal regression methods and deep learning architecture were used when developing the algorithm. Subsequently, the testing dataset was used to evaluate the developed BCS prediction algorithm on 4 of the participating farms. An experienced human assessor (HA1) visited these farms and performed 8 whole-milking-herd BCS sessions. Each farm was visited twice, allowing for 30 d (±2 d) to pass between visits. The MAN_BCS assigned by HA1 were considered the ground truth data. At the end of the validation study, MAN_BCS were merged with the stored automated BCS (AI_BCS), resulting in a testing dataset of 9,657 single BCS. A total of 3,817 cows in the testing dataset were scored twice 30 d (±2 d) apart, and the change in their BCS (ΔBCS) was calculated. A subset of cows at one farm were scored twice on consecutive days to evaluate the within-observer agreement of both the human assessor and the system. The manual BCS of 2 more assessors (HA2 and HA3) were used to assess the interobserver agreement between humans. Finally, we also collected ultrasound measurements of backfat thickness (BFT) from 111 randomly selected cows with available MAN_BCS and AI_BCS. Using the testing dataset, intra- and interobserver agreement for single BCS and ΔBCS were estimated by calculating the simple percentage agreement (PA) at 3 error levels and the weighted kappa (κw) for the exact agreement. A Bland-Altman plot was constructed to visualize the systematic and proportional bias. The association between MAN_BCS and AI_BCS and the BFT was assessed with Passing-Bablok regressions. The system had an almost perfect repeatability with a κw of 0.99. The agreement between MAN_BCS and AI_BCS was substantial, with an overall κw of 0.69. The overall PA at the exact, ± 0.25-unit, and ± 0.50-unit BCS error range between MAN_BCS and AI_BCS was 44.4%, 84.6%, and 94.8%, respectively, and greater than the PA obtained between HA1 and HA3. The Bland-Altman plot revealed a minimal systematic bias of -0.09 with a proportional bias at the extreme scores. Furthermore, despite the low κw of 0.20, the overall PA at the exact and ± 0.25-unit of BCS error range between MAN_BCS and AI_BCS regarding the ΔBCS was 45.7 and 88.2%, respectively. A strong linear relationship was observed between BFT and AI_BCS (ρ = 0.75), although weaker than that between BFT and MAN_BCS (ρ = 0.91). The system was able to predict single BCS and ΔBCS with satisfactory accuracy, comparable to that obtained between trained human scorers.

Skeletal muscle and adipose tissue reserves and mobilisation in transition Holstein cows: Part 1 Biological variation and affecting factors.

Nutrient deficit during the periparturient period leads to mobilisation of body energy and protein reserves. Research regarding fat reserves and mobilisation is extensive, while, on the contrary, investigation of muscle mobilisation during the periparturient period is limited. The aim of this cohort study was to simultaneously investigate the biological variation of skeletal muscle and subcutaneous fat reserves together with their mobilisation in transition Holstein cows of different herds, using ultrasonography, and to assess potential affecting factors. For this purpose, ultrasound measurements of longissimus dorsi muscle thickness (LDT) and backfat thickness (BFT) from 238 multiparous cows of six dairy farms were obtained at six time points across the transition period (from 21 days pre- to 28 days postpartum). Concentrations of serum creatinine and non-esterified fatty acids were determined in order to confirm the loss of muscle mass and adipose tissue, respectively. Cases of clinical postparturient diseases and subclinical ketosis (scKET) during the first 28 days postcalving were recorded. Cows mobilised on average 32.8% and 37.3% of LDT and BFT reserves, respectively. Large between-cow variation was observed for both the onset and the degree of mobilisation. Time point, initial body condition score and parity were the most important predictors of LDT variation. Cows diagnosed with metritis (MET) had lower LDT postpartum and mobilised more muscle depth compared to cows not diagnosed with MET. Initial BCS, time point, initial BW (estimated by heart girth measurement) and parity were the most important predictors of BFT variation. Cows diagnosed with MET mobilised more backfat between -7d and 7d compared to cows not diagnosed with MET. Cows with scKET mobilised more backfat between 7- and 21 days postpartum compared to healthy ones. Variation of subcutaneous fat and skeletal muscle reserves during the transition period was large and affected by herd and several cow-level factors.

Skeletal muscle and adipose tissue reserves and mobilisation in transition Holstein cows: Part 2 association with postpartum health, reproductive performance and milk production.

The aim of this study was, for the first time, to simultaneously assess the association of skeletal muscle and subcutaneous fat reserves and their mobilisation, measured by ultrasonography, with the incidence of specific postparturient health, reproduction, and milk production traits. For this purpose, ultrasound measurements of longissimus dorsi thickness (LDT) and backfat thickness (BFT) from 238 multiparous cows from 6 dairy farms were obtained at 6 time points during the transition period (from 21 days pre- to 28 days postpartum). In each case, LDT and BFT measurements at each time point and LDT and BFT mobilisation variables at each study period were assessed simultaneously. Cases of specific clinical postparturient diseases and subclinical ketosis were recorded. An additional disease trait was used, defined as the presence or absence of at least one clinical condition after calving (CD_1-28). The associated disease odds with LDT/BFT variables were assessed with binary logistic regression models. The associated hazard for 1st artificial insemination (AI) and for pregnancy by 150 days-in-milk (PREG_150DIM) was assessed with Cox proportional hazard models. Moreover, binary logistic models were used to assess the associated odds for pregnancy to 1stAI (PREG_1stAI). Finally, association with 30d, 100d and 305d milk yield was assessed with linear regression models. Increased muscle depth during transition was negatively associated with odds for metritis and CD_1-28, while associations with odds for subclinical ketosis were inconclusive. Moreover, increased LDT reserves were associated with greater hazard for 1st AI by 150 days-in-milk, but results were inconclusive regarding odds for PREG_1stAI. Increased LDT mobilisation was associated with increased odds for metritis. Increased BFT reserves were positively associated with odds for metritis, CD_1-28 and subclinical ketosis and with decreased hazard for PREG_150DIM. Increased BFT mobilisation was associated with increased odds for subclinical ketosis and with decreased odds for PREG_1stAI and decreased hazard for PREG_150DIM. Cows with moderate BFT reserves performed better. Finally, increased BFT mobilisation during -21d to -7d from parturition was associated with less milk by 30d and 100d. On the contrary, increased BFT mobilisation during -7d to 7d was associated with more milk by 305d. Metabolism of muscle and fat tissue during transition period was differently associated with different postparturient health, reproduction and milk production traits. In general, greater muscle mass and moderate fat reserves with limited muscle and fat mobilisation were associated with better performance.

Association of post-partum serum Ca patterns with reproduction in Holstein cows.

The objective of this study was to evaluate the effects of subclinical hypocalcemia (SCHCa) patterns on reproductive performance in dairy cows. In a prospective observational study 916 cows from 9 herds were blood sampled on DIMs 1, 2, 4 and 8; Ca concentration was measured with atomic absorption and SCHCa was defined as Ca ≤ 2.09 mmol/L. Cluster analysis revealed 2 normocalcemic (NORM and HIGH) and five hypocalcemic (SCH-1 to 5) clusters. Cows in cluster NORM (n = 151) had mean day-to-day serum Ca (DIMs 1-8) between 2.24 and 2.41 mmol/L, and cows in HIGH (n = 167) between 2.42 and 2.53 mmol/L. Cows in SCH-1 (n = 130) and SCH-2 (n = 102) had transient and mostly mild SCHCa on day 1 and day 2, respectively. Cows in SCH-3 (n = 123) had mostly severe SCHCa on days 1 and 2, extending to day 4. Cows in SCH-4 (n = 120) and SCH-5 (n = 145) had SCHCa which culminated on days 4 and 8, respectively. Information on reproductive outcomes including pregnancy status by 120 and 200 DIM and days open were retrieved from farm records. Median (±SE) days to 1st artificial insemination (AI) until 120 DIM estimated with Kaplan-Meier analysis for cows in SCH-3, SCH-4 and SCH-5 were 100.0 ± 7.2, 109.0 ± 6.6 and 120.0 ± 3.2, respectively, and were statistically significantly higher from those in NORM and HIGH (91.0 ± 3.4 and 87 ± 3.7, respectively). Mean days (±SE) to detected pregnancy until 200 DIM estimated with Kaplan-Meier analysis for cows in SCH-3 were 161.2 ± 4.8 and were statistically significantly higher from those in clusters NORM and HIGH (155.5 ± 4.2 and 151.6 ± 4.3, respectively). The association of Ca clusters with the odds of detected pregnancy for the 1st insemination until 120 and 200 DIM was evaluated with Linear Mixed Models. Odds for pregnancy by 120 DIM did not differ among clusters, however, cows in clusters SCH-3 and SCH-5 had lower odds for pregnancy by 200 DIM compared to HIGH (OR = 0.55, P = 0.02, and OR = 0.49, P = 0.004, respectively). Covariate adjusted survival curves generated by multivariable Cox proportional hazards model revealed that: a) clusters SCH-3 and SCH-5 had the highest (36% and 38%, respectively), while NORM and HIGH the lowest (16% and 17%, respectively) proportion of cows not inseminated for the 1st time by 120 DIM, b) compared to HIGH, cows in SCH-5 had a lower hazard of pregnancy by 120 DIM (HR = 0.42, P = 0.005), c) the proportion of open cows by 200 DIM for NORM and HIGH were 57% and 47%, respectively, while for SCH-3 and SCH-5 66% and 68%, respectively, and d) compared to HIGH, SCH-3 (HR = 0.54, P = 0.008) and SCH-5 (HR = 0.50, P = 0.001) presented the lowest hazard for pregnancy by 200 DIM. In conclusion, cows that during the entire first week after calving were continuously normocalcemic had the best reproductive performance, while those of SCH-3 and SCH-5 the worst.

Subclinical hypocalcaemia follows specific time-related and severity patterns in post-partum Holstein cows.

Hypocalcaemia is a common metabolic disorder of post-parturient dairy cows; enhancement of our knowledge regarding Ca dynamics would improve cow health and welfare. This study investigated the presence of time- and severity-related subclinical hypocalcaemia (SCHCa) patterns in Holstein cows after calving and their association with diseases during the first week of lactation. A total of 938 cows from nine herds were blood sampled on days 1, 2, 4 and 8 post-partum, and serum Ca concentration was measured with atomic absorption. Subclinical ketosis (serum ß-hydroxybutyrate≥1.2 mmol/L) and cases of retained foetal membranes, metritis (MET), mastitis, ketosis and displaced abomasum (DA) were recorded. Using receiver operating characteristic (ROC) analysis, the SCHCa cut-off was identified at serum Ca ≤ 2.09 mmol/L. Hierarchical and two-step cluster analysis classified cows to seven clusters based on test day cow Ca records and overall SCHCa status. Two clusters (NORM and HIGH) included 318 normocalcaemic cows and five clusters (SCH-1 to -5) those that were at least once subclinically hypocalcaemic (n = 620). A second ROC analysis was performed in order to distinguish mild from severe cases of SCHCa in these 620 cows; this cut-off was identified at 1.93 mmol/L. The associated risk of disease with Ca clustership was assessed with generalized linear mixed models. Overall incidence of SCHCa was 66.1%. Clusters SCH-1 and SCH-2 included cows with short-term SCHCa of day 1 and day 2, respectively, while SCH-3 included cows with severe and prolonged SCHCa extending to day 4 and beyond. Clusters SCH-4 and SCH-5 included cows with delayed SCHCa, which culminated on days 4 and 8, respectively. Compared to NORM cows in HIGH had lower risk of MET and no cases of DA. Cows in SCH-3 had higher risk of being diagnosed with retained foetal membranes, DA or any disease during the study period. Cows in SCH-5 had higher risk of being diagnosed with ketosis, subclinical ketosis or any disease. In conclusion, there are multiple normocalcaemic and hypocalcaemic patterns that are differently associated with disease risk.