Month Of Calving Research Articles

Genetic evaluation of udder health traits in the Spanish Holstein Cows

The aims of this study were to estimate the genetic parameters of clinical mastitis (CM) and somatic cell score (SCS) traits, and to compare the performance of genetic evaluations of CM traits using univariate and bivariate analyses (CM-SCS). Data was edited according to the Udder Health Golden Standard harmonization and then, 6 CM traits and 6 SCS traits were considered, as the result of combining 3 lactation classification (1, 2, ≥ 3) and 2 milking periods (early, late). The linear mixed animal models included the ratio of period at risk as a covariate, herd-year of calving, month of calving, and lactation-age as fixed effects, and the permanent environmental effect for traits of ≥ 3 lactations. Prevalence of CM in early lactation was similar regardless the lactation number (5-6%) and the estimated heritabilities were 0.01. Prevalences in late lactation ranged from 10% to 24% and heritabilities ranged from 0.03 to 0.05. Estimated heritabilities of SCS ranged from 0.06 to 0.16 with univariate analyses. Somatic cell count (therefore its log-transformation SCS) showed higher probability of identify correctly healthy cows than infected cows but there was still up to 36% of healthy cows for CM not detected by SCS. Genetic correlations between CM-SCS traits ranged from 0.36 to 0.95, and SCS in lactation 3 and later did not add extra information to SCS in second lactation for predicting CM. Regarding reliabilities of estimated breeding value (EBV) for CM traits, bivariate CM-SCS analyses led to substantial increases with respect to the single-trait model for sires (7-12% more in first lactation and 16-28% more for second lactation). Sire's rank correlations for CM between univariate and bivariate analyses (0.47-0.92) suggest that discarding sires could be more accurate than selecting candidates for sires of dams. We can conclude that SCS in first lactation could be useful to supplement CM data in first and second lactations to improve udder health genetic evaluation.

Unravelling the impact of heat stress on daughter pregnancy rate in Mehsana buffalo through innovative breeding interventions

Heat stress profoundly affects the reproductive success of buffaloes, which are vital for the dairy industry due to their unique anatomical and physiological characteristics, necessitating careful evaluation under such conditions. Hence, this guided our search for quantifying heat stress' impact on Mehsana buffaloes using the best THI model and evaluating sires’ performance. Fertility records (days open converted to daughter pregnancy rate) were collected in the span of over 24 years, w.e.f. 1989 to 2012. Finally, 3070 records of first lactation cows, daughters of 117 sires from DURDA, Gujarat, India, were used in the analysis. Meteorological data were retrieved from IMD, Pune, to understand the relationship between daughter pregnancy rate (DPR) and heat stress indicators. Several heat stress models were compared based on R2, adjusted R2, AIC, and BIC values, and the impact of heat stress was quantified. The year was classified into different heat stress zones, viz., Non heat stress zone (NHSZ), Heat stress zone (HSZ), and critical heat stress zone (CHSZ), drawing from the findings of DPR and THI. The THI 4th model based on dry and wet bulb temperature was identified as the best-fit model, and DPR significantly changed (P < 0.01) by 1.14% per unit change in THI value based on the month of calving. The average EBVs of the sires for DPR were found to be 20.78% (NHSZ), 38.09% (HSZ), and 39.08% (CHSZ) using BLUP-SM and 20.78% (NHSZ), 37.30% (HSZ), and 38.87% (HSZ) using BLUP-AM. Subsequently, the optimum sire for each of the zones was prioritized. It is noteworthy that bulls that performed better in NHSZ did not perform as well in HSZ and CHSZ, and vice versa. This supports the possibility of evaluating bulls independently in each heat stress zone.

Association of uterine health in the first lactation with transition cow health and reproductive performance in the second lactation of Holstein dairy cows

The objective of this study was to evaluate the effects of puerperal metritis (PM) diagnosed and treated during the early postpartum period of the first lactation on transition cow health, milk production, reproduction, and culling of dairy cows in their second lactation. Diagnosis of PM was based on fetid watery red-brown uterine discharge and rectal temperature above 39.5°C. Two farms were enrolled in this retrospective observational cohort study (farms A and B). In both farms, the following diseases were recorded during the first 30 DIM in lactation 1 and 2: clinical hypocalcemia (CH), retained fetal membrane (RFM), PM, hyperketonemia (KET), left displaced abomasum (LDA), and clinical mastitis (MAST). Statistical analyses were performed using SPSS for Windows separately for each farm. Linear and logistic regression models were used for continuous (e.g., milk yield) and binary (e.g., disease, pregnancy per AI, pregnancy loss) outcomes, respectively. Cox proportional hazard regression models were calculated to model the time to event outcomes for culling or death during the first 60 DIM and for pregnancy within 250 d of the second lactation. The initial models contained the following variables: year of calving, month of calving, calving ease, stillbirth, twins, days open in lactation 1, 305-d milk yield in lactation 1, PM in lactation 1, and PM in lactation 2 as explanatory variables. A total of 4,834 cows (farm A) and 4,238 cows (farm B) in the second lactation were considered for statistical analyses. On farm A, the incidence of PM in lactations 1 and 2 were 20.1% and 11.2%, respectively. On farm B, the incidence of PM in lactations 1 and 2 were 14.4% and 8.5%, respectively. On both farms, cows with PM in their first lactation had greater odds for RFM and PM in their second lactation, whereas there was no association of PM in the first lactation with any other nonuterine diseases (i.e., CH, KET, LDA, and MAST) in the second lactation. Cows with PM in lactation 2 had reduced milk yield. The reduction in milk yield in second lactation was greater for cows that already experienced PM in lactation 1. On farm A, cows with PM in their first lactation had a greater hazard for culling within 60 DIM of the second lactation; however, the same association was not present on farm B. Cows with PM in lactation 1 had reduced pregnancy per AI at first service in the second lactation only on farm B. Cows with PM in lactation 2 had reduced pregnancy per AI at first service in the second lactation on both farms. Pregnancy loss in lactation 2 was only associated with PM in lactation 2 but not with PM in lactation 1. On both farms, cows had a reduced hazard for pregnancy in their second lactation within 250 DIM when they experienced PM in either lactation. In conclusion, PM in the first lactation had long-lasting negative consequences (i.e., risk of uterine disease and lower reproductive performance) for cows in their next lactation.

Predicting bovine daily milk yield by leveraging genomic breeding values

The main goal of this work, conducted on a herd of 502 Holstein cows situated in Italy, is to propose a machine learning-based approach to forecast the individual bovine daily milk production by explicitly leveraging genotypic information. As part of our study, we also evaluated the importance in the prediction of genotypic and phenotypic variables usually available within herd. The methodology we propose is based on two consecutive models: a genomic prediction one to calculate the animal’s genomic breeding value from marker data, followed by a feed forward neural network combining such additive genetic effect and the environmental features (parity, days in milk, age at calving in months, month of calving) for milk yield forecasting. In particular, we both assess the inclusion of genomic breeding values calculated within herd or provided by the breeders’ association, discovering that the latter ones allow for better final predictions. The results of our model outperform the ones by a linear mixed model with the same inputs on average, day by day and at the individual level. Moreover, we propose a problem formulation that also leverages additional factors partially controllable by breeders: in this case, features such as the number of milkings and the concentrate consumption inside the automatic milking system prove to highly impact on the final prediction, and hence on milk production. To the best of our knowledge, the proposed problem formulation based on genomic breeding values is a novelty in the individual bovine milk yield machine learning forecasting literature. Given the low genotyping costs and the availability of a larger number of environmental features in farms equipped with a wide range of sensors, as automatic milking systems, our solution can support breeders’ herd management and animal monitoring, thanks to the possibility to forecast the full lactation curve in advance even for primiparous bovines and newborn calves. With this work, we successfully achieve our objectives of including genomic information in bovine milk yield machine learning-based forecasting, thus improving the performance on this task, and of evaluating the impact on prediction of common genotypic and phenotypic information available to breeders.

Investigating lactation curve characteristics of dairy cows

The main goal of this study was to analysis of the main characteristics (latent variables) of lactation curve in dairy cows using multivariate Principal Component Analysis. This work used primary database from the milk production of Holstein cows (n = 238 heads) in the PJSC “Pedigree farm ‘Stepnoy’ Kamianka-Dniprovska Raion of Zaporizhzhia Oblast over a 4-yr period (2014-2017). Recording is done with an interval of 30 days for 10 test-days (TD1-TD10), i.e., TD1 is milk production recorded on milking day 30th, TD2 is day 60th, TD3 is day 90th, etc., and 305-day milk yield records (Y305) were used also. High significant correlations were found between daily milk yields for certain test-days. The Principal Component Analysis performed on the variance-correlation matrix of TD1-TD10 records are able to explain about 90.33 % of the total variance. The first principal component (PC1) explained 66.32 % of the total variance and was highly-positively correlated with TD2-TD10 records. Thus, PC1 were defined as “total milk production”. The second principal component (PC2) explained 19.06 % of the total variance and was highly-positively correlated with TD1-TD2 records and highly-negatively correlated with TD9-TD10 records. Thus, PC2 were defined as “lactation curve persistency”. Finally, the third principal component (PC3) explained 4.95 % of the total variance and was highly-positively correlated with TD1 and TD10 records and highly-negatively correlated with TD4-TD5 records. Thus, PC3 were defined as “lactation curve type”. The use of a multivariate method (namely, the PCA) for the analysis of lactation curve characteristics based on monthly test-day records gave very close results of the analysis of milk productivity in different groups of domestic animals (cattle, goats and sheep). In all cases, the first principal component (PC1) described the absolute level of milk productivity during lactation, and the second principal component (PC2) described the persistency of the lactation curve. Significant influence on the PC1-PC3 factor scores was revealed to the greatest extent for such non-genetic factors as age of cow (in lactations), year and month of calving. Of the genetic factors, the greatest influence on the shape of the lactation curve was not so much the differences between the bull lines (Bell, Valiant, Elevation, Starbuck and Chief), but differences between individual bulls within some lines.

&lt;i&gt;Corrigendum to&lt;/i&gt;: Production and performance of commercial beef breeding females in northern Australia. 4. Factors influencing the occurrence of lactating cows becoming pregnant within 4 months of calving

&lt;sec&gt; Context Sound reproductive efficiency is a key determinant for the overall productivity of a beef breeding business. For beef breeding herds to obtain high levels of reproductive productivity, breeding females need to efficiently become pregnant while lactating. &lt;/sec&gt; &lt;sec&gt; Aims This study aimed to determine and quantify the major factors associated with lactating cows becoming pregnant within 4months of calving (P4M) in commercial beef breeding herds of northern Australia. &lt;/sec&gt; &lt;sec&gt; Methods A prospective epidemiological study was conducted using 78 commercial northern Australian beef breeding herds and involved 78&amp;#x2009;000 cattle that were monitored for 3&amp;#x2013;4years. A multivariable model-building process was employed to scrutinise the resulting dataset to identify what herd-management practices, and nutritional, environmental and individual cow factors were major determinants of lactating cows becoming pregnant within 4months of calving (P4M) and to estimate their magnitudes of effect. &lt;/sec&gt; &lt;sec&gt; Key results Overall, 41.6% of cows per production year were successful for P4M. Country type was strongly associated with 65.4%, 57.5%, 61.8% and 16.4% P4M for the Southern Forest, Central Forest, Northern Downs, and Northern Forest respectively. Between-year variability ranged between 3.3 and 11.7 percentage points. Cows calving in December&amp;#x2013;January (61%) had a substantially higher occurrence of P4M than did cows calving between July and September (15%). The difference in P4M when comparing availability of wet-season pasture protein and phosphorus was 12.7 and 20.3 percentage points respectively. Modelling of the impact of group seroprevalence and management group prevalence of recent infection with several infectious diseases was estimated, with a large negative association between group bovine viral diarrhoea seroprevalence and P4M suggested. &lt;/sec&gt; &lt;sec&gt; Conclusions This study further demonstrated the substantial impact that environment, herd management practices, nutrition and disease factors can have on the reproductive performance of females. &lt;/sec&gt; &lt;sec&gt; Implications To optimise the performance of females (through increasing the occurrence of cows contributing calves in consecutive years) under commercial conditions in northern Australia, herd managers should focus on maximising the proportion of cows within a herd calving at the desired time of the year, ensuring that any nutritional deficiencies and herd health issues are managed, and that cows are managed such that they are of good body condition score at the time of calving. &lt;/sec&gt;

Impact of heat stress on milk yield, antioxidative levels, and serum metabolites in primiparous and multiparous Holstein cows

This study aimed to access the effect of heat stress on milk yield, antioxidative levels, and serum metabolites in primiparous and multiparous Holstein dairy cows during the early lactation stage. A total of 200 cows were selected based on their month of calving (June, temperature humidity index (THI) = 66.72; July, THI = 70.30; August, THI = 69.32; September, THI = 67.20; October, THI = 59.45). Blood samples were collected on days 0, 21, 50, 80, and 100 after calving for serum oxidative status analysis and milk yield was recorded daily. The lower average daily milk yield was recorded among the cows that calved in June and July (P < 0.05), and the average daily milk yield of multiparous cows was higher than that of primiparous cows that calved in the same month (P < 0.05) from d1 to d100, suggesting that seasonal (June, July) heat stress negatively affected milk yield in both primiparous and multiparous cows at early lactation. The study also indicated that there was seasonal variation in most of the serum metabolites across the studied months. The study shows that heat stress (average THI = 70.30) was higher among the cows calving in June vis-à-vis those calving in October and differences were also observed among the primiparous cows and multiparous cows, respectively. These metabolites (e.g., glycine, serine, etc.) which showed significant variations were mainly involved in the pathways of aminoacyl-tRNA biosynthesis, glyoxylate and dicarboxylate metabolism, and the metabolism of glycine, serine and threonine. These data suggested that heat stress negatively affected the elevation of the serum oxidative and antioxidative index and thus badly influence milk yield. Metabolic biomarkers in serum associated with heat stress could be a reliable way to identify heat stress of primiparas and multiparas dairy cows.

Adjustment Factors for Month of Calving, Age at Calving and Days in Milk for Holteins in Tunisia

Multiplicative adjustment factors for month of calving, age at calving and lactation length were computed for complete lactation records (n= 11’175) recorded between 2012 and 2017 from 6251 dairy cattle raised in 33 Holstein dairy herds. An animal model was used with fixed effects for herd-year-sector, month of calving and age at calving and random and the residual random error. The objectives of this study were: 1) to examine the effect of the non-genetic factors on the milk yield production, 2) to adjust milk yield for non-genetic sources of variation and 3) to examine the effect of milk yield adjustments on estimates of the genetic trend. Main results showed that month of calving, age at calving and lactation length were significant sources of variation for milk yield. Cows calving in the fall and early winter yielded 430 kg and 455 kg more milk than cows calving in spring and summer, respectively. Holsteins in Tunisia reached their maximum milk yield between 68 and 70 months of age. Average adjusted milk yield for days in milk, month and age of calving was 6621±2883 kg. An overall rate of increase in milk yield was found to be 22.68 kg/year over the 15 years period.

Production and performance of commercial beef breeding females in northern Australia. 4. Factors influencing the occurrence of lactating cows becoming pregnant within 4 months of calving

Context Sound reproductive efficiency is a key determinant for the overall productivity of a beef breeding business. For beef breeding herds to obtain high levels of reproductive productivity, breeding females need to efficiently become pregnant while lactating. Aims This study aimed to determine and quantify the major factors associated with lactating cows becoming pregnant within 4 months of calving (P4M) in commercial beef breeding herds of northern Australia. Methods A prospective epidemiological study was conducted using 78 commercial northern Australian beef breeding herds and involved 78 000 cattle that were monitored for 3–4 years. A multivariable model-building process was employed to scrutinise the resulting dataset to identify what herd-management practices, and nutritional, environmental and individual cow factors were major determinants of lactating cows becoming pregnant within 4 months of calving (P4M) and to estimate their magnitudes of effect. Key results Overall, 41.6% of cows per production year were successful for P4M. Country type was strongly associated with 65.4%, 57.5%, 61.8% and 16.4% P4M for the Southern Forest, Central Forest, Northern Downs, and Northern Forest respectively. Between-year variability ranged between 3.3 and 11.7 percentage points. Cows calving in December–January (61%) had a substantially higher occurrence of P4M than did cows calving between July and September (15%). The difference in P4M when comparing availability of wet-season pasture protein and phosphorus was 12.7 and 20.3 percentage points respectively. Modelling of the impact of group seroprevalence and management group prevalence of recent infection with several infectious diseases was estimated, with a large negative association between group bovine viral diarrhoea seroprevalence and P4M suggested. Conclusions This study further demonstrated the substantial impact that environment, herd management practices, nutrition and disease factors can have on the reproductive performance of females. Implications To optimise the performance of females (through increasing the occurrence of cows contributing calves in consecutive years) under commercial conditions in northern Australia, herd managers should focus on maximising the proportion of cows within a herd calving at the desired time of the year, ensuring that any nutritional deficiencies and herd health issues are managed, and that cows are managed such that they are of good body condition score at the time of calving.

Genetic evaluation to design a reference cow population for the Holstein breed in Tunisia: a first step toward genomic selection

Context There is a large gap between developed and developing countries in the field of genetic evaluation of livestock animals. Introduction of genomic evaluation procedures and methods could contribute to reducing this gap. Aims The goal of this study was to select a reference cow population for the Holstein breed in Tunisia. Specific objectives were to update adjustments for non-genetic factors affecting milk yield, estimate genetic parameters for milk yield, and predict cow breeding values. Methods A BLUP animal model was used for 11 175 lactations recorded between 2012 and 2017 from 6251 dairy cattle raised in 33 Holstein dairy herds from three types of herds or production sectors. A pedigree file of 16 211 males and females was included in the genetic evaluation. Multiplicative adjustment factors were computed for age and month of calving, using adjusted 305 days in milk. Key results Month of calving, age at calving and farm ownership were significant sources of variation for milk yield. Cows calving in autumn and early winter (September–January) yielded more milk than those calving in spring (February–May) by 430 kg, and summer (June–August) by 455 kg. Holstein cows in Tunisia reached their maximum milk yield during the fourth lactation. Average adjusted milk yield for days in milk, month and age of calving was 6621 ± 2883 kg. Heritability estimates of adjusted milk yield were 0.14 ± 0.02 for all seven lactations and 0.16 ± 0.03 for the three first lactations. Phenotypic correlations among lactations were all positive, ranging from 0.25 to 0.43. On the basis of two main traditional designs (extreme yield and top accuracy), 1000 cows were selected to form the Tunisian female reference population. Conclusion The first step of genomic evaluation has been realised by forming a reference population from cows selected for adjusted milk yield production, based on their predicted breeding values and accuracies, using a BLUP animal model. Implication In the absence of progeny testing and sufficient proven sires, a cow reference population could represent the alternative for implementing genomic selection in developing countries.

Management-related factors in dry cows and their associations with colostrum quantity and quality on a large commercial dairy farm

The objective of this observational study was to evaluate the association of management-related factors in dry cows and colostrum quantity and quality in Holstein cows on a large commercial dairy farm. This study was conducted from January 2018 to December 2020 on a commercial dairy farm in Germany, milking approximately 2,500 Holstein cows. Dairy personnel recorded colostrum quantity (n = 7,567) and evaluated colostrum quality in a subsample of animals (n = 2,600) using a digital Brix refractometer. Generalized linear mixed models were constructed to evaluate the association of management-related factors and colostrum quantity and quality. Models were run separately for primiparous or multiparous cows. The outcome variable was either colostrum quantity (kg) or quality (%Brix). Average colostrum quantity was 4.0 ± 2.5 kg, 5.1 ± 3.4 kg, and 5.5 ± 3.5 kg for cows in lactation 1, 2, and ≥3, respectively. In primiparous cows (n = 2,351), colostrum quantity was affected by month of calving (greatest in April = 4.1 kg, and lowest in November = 3.2 kg), sex of the calf (female singleton = 3.50 ± 0.26 kg; male singleton = 3.76 ± 0.27 kg; twins = 2.97 ± 0.66 kg), stillbirth (stillbirth = 3.14 ± 0.39 kg; no stillbirth = 3.68 ± 0.31 kg). In multiparous cows (n = 5,216), colostrum quantity was affected by month of calving (greatest in May = 5.5 kg, and lowest in October = 3.8 kg), calving ease (calving ease 0 = 4.23 ± 0.26 kg; score 1 = 4.77 ± 0.21 kg; score 2 = 4.98 ± 0.22 kg; score 3 = 5.30 ± 0.22 kg), sex of the calf (female singleton = 4.42 ± 0.21 kg; male singleton = 5.00 ± 0.21 kg; twins = 5.03 ± 0.30 kg), stillbirth (stillbirth = 4.24 ± 0.38 kg; no stillbirth = 5.39 ± 0.11 kg), milk yield in previous lactation (+0.1 kg increase for 1,000 kg more milk yield in previous lactation), days spent in the far-off group (0.05 ± 0.003 kg for every day), and days in the close-up pen (0.06 ± 0.010 kg for every day). Average colostrum quality was 25.1 ± 3.4% Brix, 24.7 ± 3.3% Brix, and 27.6 ± 4.4% Brix for cows in lactation 1, 2, and ≥3, respectively. In primiparous cows (n = 817), colostrum quality was affected only by month of calving. Colostrum quality in primiparous cows was greatest in December (26.8%Brix) and lowest in August (23.9% Brix). In multiparous cows (n = 1,783), colostrum quality was affected by parity (lactation 2 = 25.2 ± 2.7% Brix; lactation 3+ = 27.9 ± 2.7%Brix), month of calving (greatest in February = 27.5% Brix, and lowest in August = 25.7% Brix), milk yield in previous lactation, and colostrum quantity. We observed a seasonal pattern for colostrum quantity and quality. Future intervention studies using multiple farms need to elucidate whether management of the photoperiod or length of exposure to close-up diets, or both, can help to optimize colostrum production.

293 Evaluation of the Water Footprint of Beef Cattle Production in Nebraska

Abstract Data were compiled from an experiment evaluating the effects of month of calving, wintering system, and calf management on cow and calf performance to model the amount of water (green and blue) required to produce beef in Nebraska production systems. The referenced study was conducted over four years utilizing 217 cow/calf pairs per year. Cows were wintered on either native range or corn residue and month of calving was March, June, or August. Calves were managed as calf-feds or yearlings and only steer calves were included in the model. A 365-d period was utilized to estimate the cow’s contribution of water inputs based on dry matter intake throughout the year varying by production system. Diet characteristics, dry-matter intake, days on feed, average daily gain, and hot carcass weight were measurements used to estimate water utilization by the calves. The total water footprint was calculated by dividing the total amount of water used for each system (L) by the amount of boneless beef produced (kg). Production systems where cows were wintered on corn residue utilized 18% less water than systems utilizing native range as a wintering source, because of water allocations using the value fraction method. Increasing the dietary inclusion of distillers grains from 0% to 40% decreased the water footprint in the finishing phase by 29%. Utilizing by-products in replacement of primary crops decreases the overall water footprint of production. Across all scenarios modeled, more than 50% of the water footprint was allocated to the cow grazing rainfed pasture (green water) and over 98% of the water footprint was allocated to growing feed. Improvements in crop water use efficiency will benefit livestock production. The water footprint of the beef systems analyzed was 80% green water as rain, minimizing the environmental impact of beef production on freshwater use and ecological water balance.

DYNAMICS OF THE CONTENT OF HEMOGLOBIN, ERYTHROCYTES AND RED BLOOD INDICES IN THE PREGNANCY PERIOD AND THEIR DIAGNOSTIC SIGNIFICANCE IN PROGNOSTICATION OF SUB-INVOLUTION OF THE UTERUS

The structure of the diet in the experimental farm corresponded to the silo type, as evidenced by the ratio of forage: hay legumes and cereals - 20.0 %, cereal straw - 16.0 %, silo grass - 36.0 %, fodder beets - 20.0 %, compound feed - 8.0 %. This structure of the adopted diets provided the cows: dry matter by 89.8 %, feed units - 85.1 %, metabolism - 91.9 %, digestible protein - 76.5 %, carotene - 72.7 %, crude fat - 95, 2 %, crude fiber - by 96,8 %. With regard to minerals, diets were supplied with Calcium by 99.0 %, Phosphorus - 68.1 %, Iron - 94.5 %, Cobalt - 65.5 %, Manganese - 87.2 %, Copper - 53.6 %, Zinc - 78.1 %, Iodine - 30.0 %.&#x0D; The fluctuations in hemoglobin content in the blood of clinically healthy cows during calving did not go beyond 3–9 %. It was relatively higher in the first trimester (107.10 ± 2.90 - 103.40 ± 2.60 g ∕ l), decreased in the second trimester (to 98.20 ± 1.80 - 98.71 ± 1.13 g ∕ l), slightly increased at the 7th month (102.40 ± 3.60 g ∕ l), then decreased again (to 98.41 ± 1.14 - 97.61 ± 1.91 g ∕ l).&#x0D; In the blood of cows with sub-involution of the uterus, the hemoglobin content was 10.1% lower in the first and second months of pregnancy (p≤0.01). Throughout the body, the hemoglobin content fluctuated, but without any regularity, and was unreliable until the seventh month, staying lower this month by 8.1 % (p≤0.05) and by eighth month by 8.8 % (p≤0.05) control.&#x0D; The number of red blood cells in the blood of clinically healthy cows was highest at the 5th to 8th month (5.74 ± 0.18 - 5.71 ± 0.06 t ∕ l), after which it decreased sharply to 5.46 ± 0.06 t ∕ l . In the blood of cows susceptible to sub-involution of the uterus, the number of erythrocytes at the first, second, seventh and eighth places of body fat was lower, respectively, by 10.0 %, 7.5 %, 7.5 %, 6.0 % (p≤0, 05) against control.&#x0D; The highest saturation of erythrocytes with hemoglobin in cows with physiological overweight, childbirth and postpartum period was 1.04, in the fifth - 0.98 and in the ninth - 1.02 months of pregnancy, and the lowest in the fourth month - 0.90 and in cows prone to uterine sub-evolution - in the first (0.89) and ninth months of pregnancy (0.99), remaining all months of pregnancy low from 0.86 to 0.99.&#x0D; In clinically healthy cows, the average hemoglobin content in one erythrocyte ranged from 1.03 to 1.14 (fmol), which corresponds to the norm (norm-chromium) in all months of calving. In cows susceptible to sub-involution of the uterus, the average hemoglobin content in one erythrocyte ranged from 1.03 to 1.09 (fmol), indicating that it decreased (hypo-chromium) compared to clinically healthy cows.&#x0D; Reduction of hemoglobin content, erythrocyte count, color index and average hemoglobin content in one erythrocyte in cows prone to sub-involvement of the uterus against clinically healthy in the period of calf, indicates alimentary deficiency anemia, which is a consequence of established non-chronic, Zinc, protein and carotene.

Milk somatic cell count and its relationship with milk yield and quality traits in Italian water buffaloes

In Southern Italy, buffalo (Bubalus bubalis) milk is mostly intended for the manufacture of Mozzarella di Bufala Campana Protected Denomination of Origin (PDO) cheese. Despite the economic boost of the last 2 decades, the buffalo farming system should be improved to maximize the efficiency of the dairy industry, improve yield and quality of milk and cheese, and work toward better animal welfare. Milk somatic cell count (SCC) is used worldwide as an indicator of udder health in individual milk and is useful for monitoring farm hygiene in bulk milk. Mastitis data are currently not available on a large scale in Italy; thus, SCC is essential for identifying animals with suspected udder infection and inflammation. Moreover, high milk SCC is associated with altered composition and acidity, and poor technological properties of milk. However, payment systems of the PDO area are based simply on the delivered volume of milk rather than on quality characteristics. Hence, currently there are no penalties for elevated SCC in bulk milk in the Italian buffalo dairy industry. In addition, SCC for buffalo milk is not mentioned by either the European Community regulations or the PDO protocol, evidencing a lack of rules for the maximum SCC limit. To provide a phenotypic characterization of SCC at the population level and to improve knowledge on buffalo milk quality, 876,299 test-day records of 70,156 buffaloes reared in the PDO area were analyzed. Data revealed that around 11% of herd-test-dates (≥5 animals sampled each) showed average milk SCC ≥400,000 cells/mL (i.e., above the threshold fixed by the European Community for bovine milk). This suggests that there is room to improve SCC at both the farm and individual level. Within first parity, more than 28 and 15% of lactations had average SCC ≥200,000 and ≥300,000 cells/mL, respectively. Both percentages increased with parity and were 39 and 25% in sixth parity, respectively. Supporting this, the proportion of lactations with average SCC ≥500,000 cells/mL increased from 6% in first parity to 12% in sixth parity. Milk yield and SCC were negatively correlated with each other, especially when SCC level was high. An ANOVA was carried out on test-day record milk yield and composition traits, with fixed effects of parity, lactation stage, class of somatic cell score (n = 6), month of calving, and their interactions; buffalo, herd-test-date, and residual were considered random effects. Significantly lower milk yield and lactose percentage were estimated in progressively higher classes of somatic cell score, whereas no significant differences were observed for fat and protein percentages. This is the first attempt to investigate milk SCC in a large data set of Italian dairy buffaloes. These findings may be helpful for defining reliable and effective SCC thresholds to be adopted whenever specific penalties for high SCC are included in milk payment systems. Finally, these results could be used in mastitis monitoring plans aiming to reduce SCC and udder issues at both the individual and farm levels in the Italian buffalo population.

Effects of a novel heat-treated protein and carbohydrate supplement on feed consumption, milk production, and cheese yield in early-lactation dairy cows

Protein is an expensive component of the dairy cow diet, and overfeeding protein can have adverse economic and environmental impacts. Our objective was to maintain milk production and components while decreasing dietary crude protein (CP) through use of a heat-treated, rumen-resistant sugar amino acid complex (SAAC) as the Schiff base, as an addition to low-protein diets. Dietary treatments included a negative control [NC, 146 g of CP/kg of dry matter (DM)], a positive control (PC, 163 g of CP/kg of DM), and the NC supplemented with SAAC in lieu of some barley grain (SAAD, 151 g of CP/kg of DM). Diets were fed to 30 multiparous Holstein-Friesian dairy cows for the first 50 d postpartum. Dry matter intake (DMI) was determined daily. Milk yield and content of fat, protein, lactose, and casein were recorded weekly from wk 2 to 7 of lactation. The fixed effects of treatment, week, treatment × week, month of calving, and BCS at calving, and a random effect of cow, were analyzed using the MIXED procedure of SAS (SAS Institute Inc., Cary, NC). The SAAD treatment had greater energy-corrected milk yield than did NC. The PC treatment had greater DMI than did NC, and SAAD tended to have greater DMI than did NC. We found significant treatment effects for fat percentage and yield. The NC and SAAD treatments had higher fat percentages than did PC, and SAAD had a higher fat yield than did the NC and PC treatments. Treatment effects were found for casein yield and percentage. We discovered a treatment effect for protein percentage and yield. The PC treatment had higher protein percentage than did NC and SAAD. The PC treatment had a higher protein yield than did NC, and analysis revealed no difference in protein yield between PC and SAAD. The SAAD treatment had higher total milk solids than did the NC treatment. Lactose yield tended to be higher in PC than in NC, and no differences were found between PC and NC and SAAD treatments. The PC treatment had a higher casein percentage than did NC and SAAD; however, the SAAD and PC treatments had higher casein yields than did NC. The PC treatment had a higher casein:fat ratio than did the NC and SAAD treatments. The NC and SAAD treatments had higher Cheddar cheese yields than did PC. We found no treatment × week interactions for any parameter. Supplementing low-protein dairy cow diets with a heat-treated, rumen-resistant SAAC caused beneficial effects by improving milk components and increasing cheese yield to levels similar to those found when feeding expensive and environmentally damaging high-protein diets.

Phenotypic Characterization of Milk Yield and Quality Traits in a Large Population of Water Buffaloes.

Simple SummaryThe buffalo dairy industry has deep roots in Southern Italy, due to the traditional link with Mozzarella di Bufala, a Protected Designation of Origin cheese with high economic value and market demand. At farm level, strategies aiming to improve milk yield and quality are essential to maximize profitability and dairy chain efficiency. In this study, we analyzed a large data set of Italian Buffaloes (around 70 thousands animals) in order to detect the phenotypic sources of variation of milk yield and quality traits, disclose exploitable favorable correlations among milk traits, and provide useful information for dairy buffalo chain stakeholders.The buffalo milk industry has economic and social relevance in Italy, as linked to the manufacture of traditional dairy products. To provide an overview of the current status of buffaloes’ performances on a large scale, almost 1 million milk test-day records from 72,294 buffaloes were available to investigate milk yield, energy corrected milk, fat, protein, and lactose content, and somatic cell score (SCS). Phenotypic correlations between milk traits were calculated and analysis of variance was carried out through a mixed model approach including fixed effect of parity, stage of lactation, sampling time, month of calving, and all their interactions and random effects of buffalo, herd-test-date, and residual. Third-parity buffaloes were the most productive in terms of milk yield, while the lowest solid content was detected in sixth parity buffaloes. A considerable gap between primiparous and multiparous buffaloes was observed for milk yield, especially in early- and mid-lactation. Overall, SCS progressively increased with parity and showed a negative correlation with milk yield in both primiparous (−0.12) and multiparous (−0.14) buffaloes. Results suggested that, at the industrial level, milk of primiparous buffaloes may be preferred for transformation purposes, since it was characterized by greater solid content and lower SCS. Results of this study provide a picture of the Italian population of buffaloes under systematic performance records and might be beneficial to both dairy industry and breeding organizations.

Genomic Breeding Values for Claw Diseases/Disorders in Czech Holstein Cows

Genomic breeding values (GEBV) were predicted for claw diseases/disorders in Holstein cows. The data sets included 6,498, 6,641 and 16,208 cows for the three groups of analysed disorders. The analysed traits were infectious diseases (ID), including digital and interdigital dermatitis and interdigital phlegmon, and non-infectious diseases (NID), including ulcers, white line disease, horn fissures, and double sole and overall claw disease (OCD), comprising all recorded disorders. Claw diseases/disorders were defined as 0/1 occurrence per lactation. Linear animal models were employed for prediction of conventional breeding values (BV) and genomic breeding values (GEBV), including the random additive genetic effect of animal and the permanent environmental effect of cow and fixed effects of parity, herd, year and month of calving. Both high and intermediate weights (80% and 50%, respectively) of genomic information were employed for GEBV50 and GEBV80 prediction. The estimated heritability for ID was 3.47%, whereas that for NID 4.61% and for OCD was 2.29%. Approximate genetic correlations among claw diseases/disorders traits ranged from 19% (ID x NID) to 81% (NID x OCD). The correlations between predicted BV and GEBV50 (84–99%) were higher than those between BV and GEBV80 (70–98%). Reliability of breeding values was low for each claw disease/disorder (on average, 3.7 to 14.8%) and increased with the weight of genomic information employed.

Genetic and environmental analysis of diseases with major economic impact in Israeli Holsteins

Incidences of ketosis, metritis, mastitis, and retained placenta were studied in Israeli Holstein cows calving between 2008 and 2017. These diseases were selected based on their economic impact. Ketosis, metritis, and retained placenta were scored dichotomously. Mastitis was scored as absent, a single occurrence during the lactation, or more than 1 occurrence. Ketosis and metritis were recorded during the first 21 d after calving, retained placenta during the first 5 d after calving, and mastitis up to 305 d in milk. The effects of herd-year-season, calving age, month of calving, gestation length, and occurrence of dystocia were included in the first-parity analysis models. All effects were significant for metritis and retained placenta. For ketosis, all effects were significant, except for gestation length. For mastitis, only the effects of herd-year-season and calving age were significant. Variance components were computed by the multitrait animal model. The 4 diseases were analyzed jointly based on first-parity records, and each disease was analyzed separately for parities 1 to 3 with the different parities considered separate traits. The 4 disease traits in first parity were also analyzed jointly with the 6 major traits included in the Israeli breeding index: milk, fat, and protein production; somatic cell score; female fertility; and longevity. Heritability was highest for metritis and lowest for mastitis, but all heritabilities were <0.07, similar to previous studies. For all 4 diseases, genetic correlations among the first 3 parities were >0.65, and all residual correlations were <0.07. Selection of herd-years assumed to have more accurate recording of mastitis did not result in higher heritability estimates. Genetic correlations between the disease traits and milk, fat, and protein production were economically unfavorable, while correlations between the disease traits and somatic cell score, female fertility, and longevity were economically favorable. Expected genetic changes in the disease traits after 10 yr of selection with the current Israeli breeding index were all <1%, except for ketosis, which was predicted to increase by 1.5%. Inclusion of these traits in a proposed index with the disease traits constituting 7% of the index would result in only marginal improvements for the disease traits and adversely affect genetic gain for fat and protein production. Thus, inclusion of these traits in the breeding index cannot be justified economically.

Production and compositional studies of milk in local Pabna cows of Bangladesh

The Pabna is one of the potential local cattle breeds in Bangladesh regarding milk production and its nutritive quality. The aim of the study was to know the effect of lactation length, parity and management on production performance and nutritional/physiochemical composition of the milk of local Pabna cows. Besides the regular milking, 15 days’ interval test day milking was recorded from 12 local Pabna cows with different lactation period (up to fifth month of calving) from BLRI Regional Station, Baghabari during January-September, 2018. In addition, 12 and 16 milk samples (200 ml/sample) were collected from the cows raised at BLRI Regional Station and the community of Dairy Development Research Project at Bera, Pabna district during June, 2018, respectively. Data were analyzed in an ANOVA of Completely Randomized Design and independent sample t-test, respectively, using SAS version 9.1.3 (SAS Institute Inc., Cary, NC, USA) including Tukey’s HSD post hoc test to separate means. The average daily milk yield was significantly (p&lt;0.05) higher during the first month (4.62 L) of lactation and the lowest value recorded at 5th month (3.50 L). Among the test days milking better yield observed at 15 days (4.79 L) of experimental lactation period (p&lt;0.05). The effect of lactation stages and parity number had no significant variations (p&gt;0.05) on nutrient compositions of local Pabna cows’ milk in both on-station and community. However, the overall characteristics of milk between on-station and community had significant differences on the composition of total solids (p&lt;0.001), SNF (p&lt;0.001), fat (p&lt;0.01), and protein (p&lt;0.05) where the highest values found as 14.81, 8.65, 6.17 and 3.53% at on-station, respectively. The first month of lactation observed as best milk producing period among the five months and the management system had positive association with milk composition of local Pabna cows.&#x0D; Asian J. Med. Biol. Res. March 2019, 5(1): 48-51

Haematological indicators in high-produced cows in dynamics of dry period

An analysis of literary sources on issues of a property of the blood and hemostasis suggests that this problem is a significant consideration given to human medicine. There is ongoing research on the properties of blood and systems of hemostasis in female animals at the time of feeding the fetus, their impact on the indices of reproductive function and viability of the offspring remains beyond the attention of researchers. The goal of the work was to study the dynamics of haematological parameters in cows of Holstein Black-and-White breed during the dry period. The research was carried out on the cows in the dynamics of the physiological course of the dry period (from the 8th to the 9th months of calving). Hematologic studies of blood samples taken from the cows in the course of the dry period were carried out according to generally accepted methods. The results of our research indicated that deep- calving cows show a decrease in the number of red blood cells, an increase in the number of leukocytes, an increase in the oxygen capacity of the blood and an increase in the colour index. The haemoglobin content and energy potential increased, the number of lymphocytes and neutrophils with segmental nucleus increased, and the number of neutrophils with a stick-shaped nucleus decreased as well. Consequently, the characteristics features of homeostasis of deep-calving cows are: reducing the number of erythrocytes and increasing the number of leukocytes, increasing the oxygen capacity of the blood and increasing the color index, hemoglobin content and energy potential; an increasing the number of lymphocytes, segmental neutrophils, as well as reducing neutrophils with a stick-shaped nucleus. Further work will have a focus on determining the haematological parameters of high-yielding cows in the post-partum period for studying the overall resistance of the body, as well as the prediction and correction of obstetric pathology.