The objective of this study was to conduct a large-scale investigation of colostrum composition and yield and an evaluation of factors affecting them. In this study, 1017 clinically healthy Holstein cows from 10 farms were used. The colostrum TS were measured using a digital Brix refractometer. Fat, protein and lactose content were determined using an infrared Milk Analyzer. Statistical analysis was conducted using a series of univariate general linear models. The mean (±SD) percentage of colostrum fat, protein, lactose and TS content were 6.37 (3.33), 17.83 (3.97), 2.15 (0.73) and 25.80 (4.68), respectively. Parity had a significant positive effect on the protein and TS content and a negative one on fat content. The time interval between calving and colostrum collection had a significant negative effect on the fat, protein and TS contents and a positive one on lactose. Colostrum yield had a significant negative effect on the protein and TS content, and it was affected by all factors considered. In addition to TS, the evaluation of the colostrum fat content appears essential when neonates’ energy needs are considered. The Brix refractometer, an inexpensive and easy to use devise, can be used effectively in colostrum quality monitoring.

Calcium, Mg, P, and K are of great importance for the health and productivity of dairy cows after calving. So far genetic studies have focused on clinical hypocalcemia, leaving the genetic parameters of these macroelements unstudied. Our objective was to estimate the genetic parameters of Ca, Mg, P, and K serum concentrations and their changes during the first 8d after calving. The study was conducted in 9 herds located in northern Greece, with 1,021 Holstein cows enrolled from November 2010 until November 2012. No herd used any kind of preventive measures for hypocalcemia. Pedigree information for all cows was available. A total of 35 cows were diagnosed and treated for periparturient paresis and, therefore, excluded from the study. The remaining 986 cows were included in genetic analysis. The distribution of cows across parities was 459 (parity 1), 234 (parity 2), 158 (parity 3), and 135 (parity ≥4). A sample of blood was taken from each cow on d1, 2, 4, and 8 after calving and serum concentrations of Ca, P, Mg, and K were measured in each sample. A final data set of 15,390 biochemical records was created consisting of 3,903 Ca, 3,902 P, 3,903Mg, and 3,682K measurements. Moreover, changes of these concentrations between d1 and 4 as well as 1 and 8 after calving were calculated and treated as different traits. Random regression models were used to analyze the data. Results showed that daily heritabilities of Ca, P, and Mg concentrations traits were moderate to high (0.20-0.43), whereas those of K were low to moderate (0.12-0.23). Regarding concentration changes, only Mg change between d1 and 8 after calving had a significant heritability of 0.18. Genetic correlations between Ca, P, Mg, and K concentrations and their concentration changes from d1 to 4 and 1 to 8 after calving were not significantly different from zero. Most phenotypic correlations among Ca, P, Mg, and K concentrations were positive and low (0.09-0.16), whereas the correlation between P and Mg was negative and low (-0.16). Phenotypic correlations among macromineral concentrations on d1 and their changes from d1 to 4 and 1 to 8 after calving varied for each macromineral. This study revealed that genetic selection for normal Ca, P, Mg, and K concentrations in the first week of lactation is possible and could facilitate the management of their deficiencies during the early stages of lactation.

The main objective of this study was to assess the genetic background of colostrum yield and quality traits after calving in Holstein dairy cows. The secondary objective was to investigate genetic and phenotypic correlations among laboratory-based and on-farm-measured colostrum traits. The study was conducted in 10 commercial dairy herds located in northern Greece. A total of 1,074 healthy Holstein cows with detailed pedigree information were examined from February 2015 to September 2016. All cows were clinically examined on the day of calving and scored for body condition. All 4 quarters were machine-milked, and a representative and composite colostrum sample was collected and examined. Colostrum total solids (TS) content was determined on-farm using a digital Brix refractometer. Colostrum fat, protein, and lactose contents were determined using an infrared milk analyzer, and energy content was calculated using National Research Council (2001) equations. Dry period length (for cows of parity ≥2), milk yield of previous 305-d lactation (for cows of parity ≥2), age at calving, parity number, season of calving, time interval between calving and first colostrum milking, and milk yield were recorded. Each trait (colostrum yield and quality traits) was analyzed with a univariate mixed model, including fixed effects of previously mentioned factors and the random animal additive genetic effect. All available pedigrees were included in the analysis, bringing the total animal number to 5,662. Estimates of (co)variance components were used to calculate heritability for each trait. Correlations among colostrum traits were estimated with bivariate analysis using the same model. Mean percentage (±SD) colostrum TS, fat, protein, and lactose contents were 25.8 ± 4.7, 6.4 ± 3.3, 17.8 ± 4.0, and 2.2 ± 0.7%, respectively; mean energy content was 1.35 ± 0.3 Mcal/kg and mean colostrum yield was 6.18 ± 3.77 kg. Heritability estimates for the above colostrum traits were 0.27, 0.21, 0.19, 0.15, 0.22, and 0.04, respectively. Several significant genetic and phenotypic correlations were derived. The genetic correlation of TS content measured on-farm with colostrum protein was practically unity, whereas the correlation with energy content was moderate (0.61). Fat content had no genetic correlation with TS content; their phenotypic correlation was positive and low. Colostrum yield was not correlated genetically with any of the other traits. In conclusion, colostrum quality traits are heritable and can be amended with genetic selection.

Most cows experience a period of nutrient deficit during the periparturient period. Body condition scoring (BCS) is widely used on farms to assess body nutrient reserves and mobilization. The aims of this study were to: (i) determine the association of BCS with ultrasound measurements of backfat (BFT) and longissimus dorsi muscle thickness (LDT) during the periparturient period of Holstein cows from different herds, accounting for potential sources of variation, such as herd, parity and period relative to calving and (ii) establish reference intervals (RIs) for BFT and LDT per BCS estimate. Two-hundred and fifty-two cows from six commercial farms were used. Body condition scores, BFT and LDT were assessed at seven time-points during the periparturient period. Assessments of BCS estimates as predictors of BFT and LDT and the contribution of BFT and LDT to BCS estimates were performed with the use of linear mixed models. Reference intervals for BFT and LDT per BCS estimate were established with the Reference Value Advisor. One unit of BCS change was associated with 8.2 mm of BFT and 10.9 mm of LDT pre- and postpartum. Range of BFT and LDT in established RIs per BCS was wide with significant overlap. Both subcutaneous fat and, to a lesser degree, skeletal muscle reserves contribute to BCS estimation. Repeated BCS estimations credibly predict energy balance status in periparturient dairy cows. The metabolic state of muscle tissue should be assessed by repeated ultrasound measurements.

The main objective of this study was to assess the genetic parameters of subclinical disorders associated with subclinical hypocalcemia, hypophosphatemia, subclinical hypomagnesemia, hypokalemia, and hyperphosphatemia, as well as major clinical diseases after calving in Holstein cows. The secondary objective was to estimate the associated genetic and phenotypic correlations among these subclinical and clinical conditions after calving in Holstein cows. The study was conducted in 9dairy herds located in Northern Greece. None of the herds used any kind of preventive measures for milk fever (MF). A total of 1,021 Holstein cows with pedigree information were examined from November 2010 until November 2012. The distribution across parities was 466 (parity 1), 242 (parity 2), 165 (parity 3), and 148 (parity 4 and above) cows. All cows were subjected to a detailed clinical examination and blood was sampled on d 1, 2, 4, and 8 after calving. Serum concentrations of Ca, P, Mg, and K were measured in all samples, whereas β-hydroxybutyrate (BHB) was measured only for d 8. The final data set included 4,064 clinical and 16,848 biochemical records (4,020 Ca, 4,019 P, 4,020Mg, 3,792K, and 997 BHB). Data of 1,988 observations of body condition score at d 1 and 8 were also available. All health traits were analyzed with a univariate random regression model. The genetic analysis for macromineral-related disorders included 986 cows with no obvious signs of MF (35 cows with MF were excluded). Analysis for other health traits included all 1,021 cows. A similar single record model was used for the analysis of BHB. Genetic correlations among traits were estimated with a series of bivariate analyses. Statistically significant daily heritabilities of subclinical hypocalcemia (0.13-0.25), hypophosphatemia (0.18-0.33), subclinical hypomagnesemia (0.11-0.38), and hyperphosphatemia (0.14-0.22) were low to moderate, whereas that of hypokalemia was low (0.08-0.10). The heritability of body condition score was 0.20±0.10. Statistically significant daily heritabilities of clinical diseases were those of MF (0.07-0.11), left displaced abomasum (0.19-0.31), and mastitis (0.15-0.41). Results suggest that these health disorders are heritable traits and could be minimized with proper genetic selection. Statistically significant phenotypic correlations were estimated for the first time between macromineral concentrations and almost all transition cow metabolic and infectious health disorders.