Daily Milk Yield Research Articles

The Health-Related Fatty Acid Profile of Milk from Holstein–Friesian Cows as Influenced by Production System and Lactation Stage

This study aimed to evaluate the effect of production system and lactation stage (LS) on the yield, centesimal composition, and fatty acid profile of milk from Holstein–Friesian cows. A total of 539 milk samples were collected in winter from cows in six certified organic dairy herds (ODHs) and eight conventional dairy herds (CDHs). The samples were collected randomly from up to 30% of cows at a given stage of lactation (7–45, 46–90, 91–135, 136–180, 181–225, 226–270, 271–315, and 316–360 days after calving). Milk samples were analyzed for proximate composition and the concentrations of fatty acids. The average daily milk yield was 11.4 kg higher (p < 0.01) in CDHs than in ODHs (28.1 kg vs. 16.7 kg). The concentrations of milk fat, protein, and lactose were also higher in CDHs than in ODHs. The fatty acid profile of milk fat was more desirable in ODHs than in CDHs (higher concentrations of polyunsaturated fatty acids (PUFAs), including n-3 PUFAs, trans-vaccenic acid, linolenic acid, and conjugated linoleic acid, and a higher desaturase index). Milk yield decreased (the decrease was more pronounced in ODHs), the concentrations of milk constituents increased, and the proportion of short-chain fatty acids in milk fat decreased (p < 0.05) with advancing lactation.

Influence of garden cress seeds supplementation on immunity, hormonal status, and milk quality during the last third of pregnancy and lactation period of rabbit does

During the last third of pregnancy period, rabbits are exposed to many challenges, such as health complications and oxidative stress. The present study aims to use garden cress seeds (GAC) as a natural antioxidant to mitigate these challenges and evaluate its effects on reproductive performance, immunity, hormones, protein profile and milk quality. A total of 24 pregnant V-Line rabbits (pregnant at 20 days proved by palpation), with an initial body weight of 2395.83 g and about 6–7 months of age, were randomly distributed to 4 groups, the control group was fed the basal diet without GAC, the other treated groups GAC 3, GAC 4.5 and GAC 6 were fed the basal diet supplemented with 3, 4.5, and 6% GAC, respectively. The experiment lasted six weeks. The results revealed that treated female rabbits with different levels of GAC did not have a noticeable effect on milk yield, average daily milk yield, or most of the milk analysis parameters (milk density, total solids, solids not fat, lactose, ash, and protein). On the other hand, GAC showed a significant increase in milk fat, and GAC 3% rabbits displayed a higher percentage of milk fat (p < 0.050) than the other groups. Likewise, treatment with GAC also had a significant impact on serum total protein, globulin, IgG, and IgM. The 3% GAC rabbits showed significantly higher total protein, globulin, and IgM values than the control group. However, all GAC treatments significantly improved serum IgG and the best value was found in the 3% GAC group. In conclusion, our results demonstrated that feeding lactating rabbits a diet supplemented with GAC could be considered a good strategy to enhance immunity, protein profile, MY and milk fat. The best results were obtained with the GAC 3% treatment.

The effect of ambient temperature and relative humidity in postpartum dairy cows on productive and reproductive performance and biochemical blood indices in the subsequent lactation

Abstract This study evaluated the effects of ambient temperature (T) and relative humidity (RH) during the postpartum transition period on dairy cows’ milk performance, fertility, and immunometabolic blood indices in the subsequent lactation. A total of 100 Polish Holstein-Friesian cows originating from five commercial dairy farms were categorized into three groups based on average T (&lt;16 °C, 16-20 °C and &gt;20 °C) and RH (&lt;65%, 65-75%, and &gt;75%) on the calving day (0d), and days 7, 14, 21 after calving. With increasing T and RH postpartum, the average daily milk yield during the first 150 days in milk decreased gradually, and the differences between T &lt;16 °C and &gt;20 °C and RH &lt;65% and &gt;75% groups were approx. 3.48 and 2.78 kg, respectively. Milk of cows exposed to increased T and RH was lower in protein, and lactose and higher in fat, milk urea, and somatic cell count. It was also characterized by altered fat composition. Ambient T during the postpartum period had a negative effect on cows’ fertility, which, however, was not affected by RH. The increasing T from &lt;16 °C to &gt;20 °C resulted in the later manifestation of the first estrous (by 27.7 days), a more extended artificial insemination service period (by 19.4 days), a higher number of insemination services per conception (by 0.92 on average), more days open (by 43.3 days), and a longer calving interval (by 43.3 days). Within ranges used in this study, increasing T and RH during the period from d 0 to d 14 postpartum led to decreased body condition score on day 21 by approx. 0.48 and 0.51 points, respectively. Furthermore, T and RH on a calving day were associated with altered biochemical blood indices on d 21 after calving, indicating a more severe negative energy balance and a state of inflammation. The results of this study suggest that dairy cows that calve when T &gt;16 °C should be provided cooling to ensure optimal environmental conditions for high milk production and prevent economic losses associated with reduced milk yield and low fertility.

Development of individual models for predicting cow milk production for real-time monitoring

Daily milk yield serves as a physiological indicator in dairy cows and is a primary target for prediction and real-time monitoring in smart livestock farming. This study attempted to develop an individual model for predicting daily milk yield and applied it to monitor the health status of dairy cows by designing a real-time monitoring algorithm. A total of 580 datasets were used for model development after data preprocessing and screening, which were subsequently used to develop the model by modifying the existing models based on nonlinear regression analysis. The developed model was then applied to short-term real-time monitoring of abnormal daily milk yields. The optimal model was able to predict the daily milk yield, with an R2 value of 0.875 and a root mean squared error of 2.192. Real-time monitoring was designed to detect abnormal daily milk yields by collectively considering a 90% confidence interval and the difference between predicted values and expected trends. This study is the first to design a monitoring algorithm for daily milk yield from dairy cows based on an individual model capable of predicting the daily milk yield. This study expects that a platform will be necessary for highly efficient smart livestock farming, enabling high productivity with minimal inputs.

Investigating non-genetic factors impacting first lactation milk yield in Mehsana buffaloes

Buffaloes are known as the backbone of dairy industry in India by contributing about half of milk production. Milk production, a complex trait, is influenced by various non-genetic factors. This study investigated the impact of non-genetic factors on the first lactation performance of Mehsana buffaloes, focusing on their 305-day milk yield (305DMY). The dataset, comprising 23,608 records, was obtained from the National Dairy Development Board (NDDB), Anand, recorded through the Indian Network for Animal Productivity and Health (INAPH). Age at first calving, year of calving, month of calving, and union (milk co-operative society) were considered as non-genetic factors. Statistical analysis, including Least Squares Analysis and Duncan’s Multiple Range Test, revealed that all factors had a highly significant (P &lt; 0.01) influence on 305DMY. These findings contribute valuable insights into dairy herd management strategies, aiding dairy farmers, policymakers, and researchers to optimize milk production and improve the overall productivity of Mehsana buffaloes.

Genetic and Phenotypic Correlations between Production and Reproduction Traits in Frieswal Cattle under Field Progeny Testing Programme

Aim: To estimate the genetic and phenotypic correlations in production and reproduction traits in Frieswal Cattle under FPT. Place and Duration of Study: G B Pant University of Agricultural and Technology, Pantnagar, Uttarakhand, India, Between March, 2023 to March, 2024. Methodology: The present study was conducted on Frieswal cattle, a synthetic breed, using data from 1163 first lactation records, progenies of 67 sires, spread over period of nine years (2013-2021) as part of an ongoing field progeny testing programme at GBPUA&amp;T, Pantnagar, Uttarakhand. The study aimed to estimate genetic and phenotypic correlations among various production and reproduction traits, such as test day peak yield (TDPY), first lactation 305-days milk yield (FL305D-MY), fat percentage (FP), first lactation length (FLL), age at sexual maturity (ASM), age at first calving (AFC), gestation period (GP), first calving interval (FCI), first service period (FSP), and number of services per conception (NSPC).The data were analyzed using WOMBAT software. Results: The study revealed that age at first service (ASM) and age at first calving (AFC) had very high genetic (0.99) and phenotypic (0.99) correlations, suggesting they were influenced by the same genes. A strong genetic correlation (0.71) between ASM and gestation period (GP) indicates a close association, while the negative correlation between ASM and total days to peak yield (TDPY) (-0.76) suggests younger cows reach higher peak yields. ASM’s negative genetic correlation (-0.57) with first lactation 305-days milk yield (FL305D-MY) implied that selecting for earlier maturity could enhance milk production. Positive correlation between ASM and reproductive traits (FCI, FSP, NSPC, and FDP) were observed, while FL305D-MY showed high negative correlation with traits like FLL and FP but positive phenotypic correlation with FLL, FCI, and FSP. Additionally, there were varied genetic correlation among FCI, FSP, NSPC and FDP, highlighting complex inter-trait relationships. Conclusions: The present study highlighted the potential of Frieswal herd for selective breeding to improve both milk production and reproductive efficiency. By focusing on traits like age at sexual maturity (ASM), age at first calving (AFC), and milk yield indicators such as test day peak yield (TDPY) and first lactation 305-days milk yield (FL305D-MY), breeders can target genetically associated traits for enhanced overall productivity. These findings provide a valuable foundation for future genetic improvement strategies in Frieswal cattle.

Increase in dairy production of goats with subclinical nematode infection using injectable eprinomectin

The effect of the treatment with an injectable product containing eprinomectin on milk yield, milk composition, and somatic cell count (SCC) was investigated in naturally infected dairy goats with low gastrointestinal nematode faecal egg and pulmonary larval counts. The study involved 394 lactating goats and was conducted on a farm in southern Spain. Before treatment, faeces from all animals were analysed to establish two homogeneous groups according to the gastrointestinal nematode egg counts (185 treated and 209 untreated). On day 0, each goat in the treatment group received a single subcutaneous injection of 12 mg of eprinomectin (0.6 ml of Eprecis®, CEVA, Spain). The control goats were left untreated. Faecal egg counts and coprocultures were performed on days 0, 30, 60, and 90 post-treatment. Milk samples were taken on days 0, 30, 60, 90, and 120 and analysed to determine individual production and milk composition parameters, including fat (F), protein (P), lactose (L), total dry extract (TDE), and SCC. Examination of faecal samples indicated that the goats were mainly infected with gastrointestinal strongylids of the genera Teladorsagia and Trichostrongylus and Muellerius lungworms. The percentage reduction of gastrointestinal nematode faecal egg counts on days 30, 60, and 90 was 97.55 % (90 % CI = 95.1 % - 99.9 %), 90.65 % (90 % CI = 83.7 % - 97.6 %) and 87.5 % (90 % CI = 79.5 % - 95.5 %), respectively, and that of lung larval counts in faeces was 98.48 % (90 % CI = 96.3 % - 100 %), 96.91 % (90 % CI = 84.2 % - 98.9 %), and 82.05 % (90 % CI = 66.9 % - 97.2 %), respectively. Milk yield was consistently and significantly higher in the treated group than in the control group (p = 0.004). The treated goats showed a 4 % increase in daily milk yield (60 ml/day) compared with the untreated goats. There was a significant decrease in F and TDE in the treated goats compared with the untreated goats, but eprinomectin did not affect P, L, and SCC. The estimated economic benefit of using injectable eprinomectin was around 6.46€ per goat over the 120-day period. In conclusion, treatment with injectable eprinomectin has an economical positive effect on milk yield in goats, even those infected with a low burden of gastrointestinal and pulmonary nematodes.

Lactation curves for milk, fat and protein in dairy cows under regenerative versus conventional farming practices

ABSTRACT Regenerative agriculture aims to utilise more diverse pasture species and enhance animal performance through sustainable soil management and pasture quality. This study evaluated the influence of regenerative and conventional farming on dairy cow performance and milk production under different pasture mixes and management strategies. Monthly herd test records were used to model individual lactation curves for daily milk, fat, and protein yield for the 2022–2023 season using random regression with third-order orthogonal polynomials. Total yields were calculated from predicted daily yield. Treatments were SPCM: Standard pasture under conventional management, DPCM: Diverse pasture mix under conventional management, and DPRM: Diverse pasture mix under regenerative management. Total milk yield was similar across treatments, averaging 3370 kg (SPCM), 3649 kg (DPCM), and 3626 kg (DPRM) for the 2022–2023 season. No significant differences were observed in fat, protein, milk solids yield, or milk composition. Cows on diverse pastures, regardless of management approach, showed heavier liveweights than those on standard pastures. DPCM and DPRM cows averaged 474 kg, significantly greater than SPCM cows at 464 kg (P < 0.0001), likely due to longer grazing rotation and higher post-graze mass. These findings suggest that pasture species diversity, regardless the management, enhances liveweight without affecting milk composition.

Genetic improvement of indigenous cattle breeds in Ethiopia: A systematic review of the Fogera cattle open nucleus breeding scheme

Fogera cattle are one of the valuable indigenous milk-type local breeds of Ethiopia, widely adapted to the area around Lake Tana in the Amhara region. The objective of this systematic review was to evaluate the performance of the Fogera cattle breed under an open nucleus breeding scheme. The review was done systematically by collecting published and unpublished data sources on the breed. The overall milk yield of the nucleus Fogera cattle herd was 2.26±0.794L/day. From the total herd, the top 10% and 25% of them produced daily milk yields of 3.31 and 2.87L, respectively, and some elite cows gave an average of 5.45±0.73L/day with a maximum yield of 8L/day. The predicted 305-day milk yield for the top 10% and 25% of the total herd was 883.64 and 772.83L, respectively. The average lactation milk yield and lactation length were reported to be 489±184L and 243±72.79 days, respectively. The respective heritability estimates for the aforementioned traits were 0.20±0.23 and 0.27±0.001. The birth and weaning weights (at 8 months of age) of village Fogera cattle born from community-based breeding programmes (CBBP) were 23.77±.21 and 85.89±1.07kg, respectively. The average weaning age for the CBBP herds was reduced to 8 months. The overall calf mortality in the nucleus herd was 3%. The CBBP demonstrated that it could act as a significant entry point for ensuring the conservation and restocking efforts of this breed as a country asset.

Genetic Evaluation of Monthly Test-Day Milk Yields of Jersey Crossbred Cattle Under Farmers' Production System in Tamil Nadu, India.

Tamil Nadu, a state in southern India, is bereft of any native dairy or dual-purpose cattle breeds, and the state depends chiefly on crossbred cattle for milk production. Jersey crossbred cattle account for 90% of the state's milk production. This genetic evaluation study aimed to assess milk production traits, including test-day milk yields (TDMYs), total lactation milk yield (TMY), and 305-day milk yield (305MY), in these cattle reared under farmers' conditions. Data on monthly TDMYs (TDMY1 to TDMY10) of Jersey crossbred cows (n = 75,627) reared by the farmers over 11 years (2012-2022) were collected for evaluation. The influence of non-genetic factors viz., location (agroclimatic zones), period and season of calving, and parity on TDMYs, TMY and 305MY were assessed, and the variance and covariance components for genetic parameters (heritability and genetic correlation) of the traits were estimated by the method of restricted maximum likelihood (REML) under a multivariate animal model and by a random regression model (RRM). The overall means of various TDMYs ranged from 4.98 (TDMY10) to 9.95 kg (TDMY2), and for TMY and 305MY, the means were 2480.33 and 2393.71 kg, respectively. The heritabilities estimated by the multivariate animal model for TDMYs were moderate and ranged from 0.26 ± 0.02 to 0.37 ± 0.02 and the estimates were less variable throughout lactation, while the estimates obtained by RRM were medium to high and ranged between 0.29 ± 0.01 and 0.67 ± 0.02 for milk yield on day 5 to 305 (DIM 5-DIM 305). The heritabilities estimated for TMY and 305MY were 0.43 ± 0.02 and 0.43 ± 0.02, respectively. The estimates of heritability for mid-lactation yields were comparatively less than those at the beginning and the end of lactation. The moderate to high estimates of heritabilities for TDMYs, TMY, and 305MY obtained in the present study offer ample scope for improving milk production through selective breeding. Genetic correlations between TDMYs estimated by the multivariate animal model were positive and high, with a range between 0.75 ± 0.03 and 0.99 ± 0.00. Considerably higher estimates (0.98-0.99) were observed between adjacent TDMYs showing strong genetic associations. By RRM, genetic correlations estimated between DIMs were positive (except for DIM 5 with DIM 125 to DIM 185 and DIM 125 with DIM 305), and the magnitude of genetic correlation decreased with an increase in the interval between the DIMs. The high genetic correlation observed between the TDMYs (in the early stage of lactation) and total lactation milk yield suggested that these test-day yields could be used favorably for the early selection of cows for milk production, which facilitates reduction in the generation interval and consequently increases the annual genetic gain for the milk production traits.

Effects of dry matter concentration in grass silage on milk production of dairy cows fed concentrates high or low in metabolizable protein concentration

Studies have shown that extended wilting of grass before ensiling can improve the metabolizable protein (MP) value of the grass silage, both from increased rumen microbial crude protein (MCP) yield and ruminally undegraded crude protein (RUP). We hypothesised that extending the wilting of grass before ensiling can increase milk and milk protein production in dairy cows. Consequently, increased silage MP can reduce the need for MP in concentrate, estimated as amino acids absorbed in the small intestine (AAT20). To test this, a continuous feeding experiment was conducted, with 48 early- to mid-lactation Norwegian Red dairy cows. Treatments were 2 wilting levels of grass silages: 260 vs. 417 g dry matter (DM) per kg, and 2 qualities of concentrates differing in MP, in a 2 × 2 factorial arrangement (n = 12). The concentrates were low MP (LMP); 104 g AAT20/kg DM, and high MP (HMP); 123 g AAT20/kg DM, supplied at 8.75 kg DM/cow per day. The cows had ad libitum access to the grass silages. The experiment lasted for 11 weeks. The first 2 weeks, where cows received identical diets, were used as the covariate period. Those data together with data collected the last 4 weeks were used for statistical evaluation of treatments. Increasing DM concentration in silage reduced lactic acid, ammonia nitrogen and proportion of methionine in the grass silage, while it increased residual water-soluble carbohydrates, pH, proportion of aspartic acid and rumen degradability of NDF. There was no difference between treatments in daily silage DM intake (13.1 kg), milk yield (30.2 kg) or milk composition. However, feeding HMP increased urea and uric acid in urine, and urea in blood plasma, thereby reduced N efficiency. No major differences were found for rumen pH, or purine derivatives to creatinine index in urine, as indication for MCP. There was significantly more histidine in blood plasma when cows were fed HMP concentrate. In conclusion, increased DM concentration in silage and HMP concentrate did not increase milk production or milk protein yield in this study.

Milk production and viability of the various smallholder dairying models used in Zimbabwe.

An evaluation of milk yield, dairy products and viability of the smallholder dairy production models used in Zimbabwe was carried out. We used secondary data on 1167 smallholder dairy farmers. These were categorised into commercial dairying (119), Milk collection centre (MCC) bulking and processing (145), MCC bulking and delivering to processor (87), farm gate (468) and other (348) models. Data were analysed using SPSS version 25.0. The average daily milk yield per cows was highest in the Commercial dairying model (9.20 ± 0.4l) but was not significantly different from the MCC bulking and processing and MCC bulking and delivering to processor models. Average lactation milk yield per cow was highest (P < 0.05) in the commercial dairying model (2804.91 ± 133.9l) and was significantly different from the rest of the models. The processed milk products identified in the study were fermented milk, pasteurised milk and unspecified products but production volumes were very low in the respective models. There were no differences (P > 0.05) in gross margin across all the smallholder dairying models. The commercial dairying model surpassed all models on proportion of pure exotic dairy breeds, number of milking cows, milk yield. However, it was discovered that all models were underperforming but smallholder dairy farmers can be recommended to adopt the commercial dairying model if measures to improve milk yield per cow and reduce milk production costs are established.

Genome-wide association studies for milk production traits and persistency of first calving Holstein cattle in Türkiye.

The study presents a comprehensive investigation into the genetic determinants of 100-day milk yield (100DMY), 305-day milk yield (305DMY), total milk yield (TMY), and persistency using first lactation records of 374 Holstein heifers reared in a private farm at Çanakkale province of Türkiye, employing a genome-wide association study (GWAS) approach. The research underscores the substantial genetic component underlying these economically important traits through detailed descriptive statistics and heritability estimations. The estimated moderate to high heritabilities (0.32-0.54) for milk production traits suggest the feasibility of targeted genetic improvement strategies. By leveraging GWAS, the study identifies many significant and suggestively significant single nucleotide polymorphisms (SNP) associated with studied traits. Noteworthy genes have identified in this analysis include BCAS3, MALRD1, CTNND2, DOCK1, TMEM132C, NRP1, CNTNAP2, GPRIN2, PLEKHA5, GLRA1, SCN7A, HHEX, KTM2C, RAB40C, RAB11FIP3, and FXYD6. These findings provide valuable understandings of the genetic background of milk production and persistency in Holstein cattle, shedding light on specific genomic regions and candidate genes playing pivotal roles in these traits. This research contributes valuable knowledge to the field of dairy cattle genetics and informs future breeding efforts to improve milk production sustainability and efficiency in Holstein cattle populations.

Inclusion of imputed genotypes from non-genotyped dairy cattle in a Thai multibreed genomic-polygenic evaluation.

This study assessed the impact of incorporating imputed SNP information from non-genotyped animals on genomic-polygenic evaluations in a Thai multibreed dairy population under various levels of imputation accuracy. Data encompassed pedigree and phenotypic records for 305-day milk yield (MY), 305-day fat (Fat), and age at first calving (AFC) from 12,859 first-lactation cows, and genotypic records of various densities from 4,364 animals. A set of 64 animals genotyped with GeneSeek Genomic Profiler 80K and with four or more genotyped progenies was defined as target animals to simulate imputation scenarios for non-genotyped individuals. Actual and imputed genotypes were utilized to construct three SNP sets. All SNP Sets contained actual and imputed SNP markers from genotyped animals. SNP Set 1 contained no SNPs from target animals, whereas SNP Set 2 incorporated imputed SNPs from target animals, and SNP Set 3 added actual SNPs from target animals. Genomic-polygenic evaluations were conducted using a 3-trait single-step model that included contemporary group, calving age, and heterozygosity as fixed effects and animal additive genetic and residual as random effects. The imputation accuracy was similar across non-genotyped animals irrespective of the number of genotyped progenies (average: 40.55%; range: 34.68% to 53.82%). Estimates of additive genetic and environmental variances and covariances for MY and AFC varied across SNP sets. SNP Sets 1 and 2 had slightly higher additive genetic and lower environmental variances and covariances than SNP Set 3. Heritabilities and additive genetic, environmental, and phenotypic correlations between MY, Fat, and AFC were similar across all SNP Sets. Spearman rank correlations between genomic-polygenic EBVs from SNP Sets 2 and 3 were high for all traits (0.9990±0.0003). Utilization of phenotypic and pedigree data from imputed non-genotyped animals enhanced the efficiency and cost-effectiveness of the genetic improvement program in the Thai multibreed dairy cattle population.

Assessment of Husbandry Practices, Production and Reproductive Performance of Indigenous Cattle in Urban and Peri -urban Areas of Gambella City, Ethiopia

The objective of the present study was to characterize cattle husbandry practices, production and reproductive performance of cattle in the urban and peri-urban areas of Gambella city. Sample of respondents from each selected kebele were selected randomly using simple random sampling technique. A total of 133 household (70 from urban and 63 from peri-urban) were selected for questionnaire interview. Data was analyzed using SPPS version 23 software. The overall mean of the respondents revealed that, the management system practiced was semi-intensive (87.2%), extensive system (12.8%) and there was no intensive management system practiced. the overall mean daily milk yield was 1.58± 0.017 Littre/cow/day. The overall mean daily milk yield analysis of variance was significantly (P&amp;lt;0.05) difference among urban and peri-urban areas. The current result also indicated that, the overall average lactation length was and 10.59± 0.15 months, and was not significantly (P&amp;gt;0.05) affected by the study areas. The overall average age at first services, age at first calving and calving interval was 46.31±0.33, 51.51±0.54, and 19.01±0.11 months respectively. In Addition, disease prevalence, poor animal health service delivery, grazing land and feed shortage were among the major constraints affecting production and productivity in the study areas. In conclusion, Age at first services, age at first calving and calving interval of indigenous cow was low compared to some of the indigenous breed in other regions, animal health and health services delivery are the problems affecting cattle productivity. Hence, all concerned stakeholders need to take urgent interventions in order to improve production and productivity of cattle.

Genetic assessment of productive and reproductive traits in Friesian, native, and crossbred cattle in Egypt

This study utilized a dataset comprising 3023 lactation records for Friesian cows, 596 records for Native cows (Baladi), and 1189 records for Crossbred cows spanning from 1994 to 2015. The objective was to estimate and assess genetic and phenotypic parameters and breeding values for 305-day milk yield (305-DMY), lactation period (LP), calving interval (CI), and days open (DO) within the Egyptian dairy context. The motivation for this research stemmed from the need to understand the genetic potential of different cattle genotypes in Egypt and identify opportunities for enhancing dairy production. Data were analyzed using the linear mixed model least squares and maximum likelihood (LSMLMW) and multiple-trait derivative-free restricted maximum likelihood (MTDFREML) programs. The analytical model included fixed effects such as season and year of calving, parity, and genotype groups, while random effects included animal and error. Unadjusted means for 305-DMY, LP, CI, and DO were calculated for each genotype group. Genotype groups significantly impacted all studied traits. Heritability estimates varied across genotype groups, with higher estimates observed in Crossbred (0.32, 0.26, 0.25, 0.23) and Native cows (0.26, 0.28, 0.28) compared to Friesian cows (0.24, 0.22, 0.16, 0.17) for productive and reproductive traits, respectively. Genetic correlations among traits ranged from 0.10 to 0.86 for the three genotype groups, while corresponding phenotypic correlations were generally small to moderate and positive. Regarding breeding values, the accuracy estimates suggested that both sires and cows could contribute to genetic improvement. This indicates the potential for enhancing dairy production through selective breeding strategies.

Effects of Chitosan-Based Additive on Rumen Fermentation and Microbial Community, Nutrients Digestibility and Lactation Performance in Goats.

Recently, the potential of using chitosan (CHI) as a feed additive to enhance ruminal fermentation and improve animal performance has gained increasing attention in ruminant nutrition. This study was undertaken to investigate the effect of dietary supplementation with increasing doses of CHI on rumen fermentation attributes and microbial composition, digestibility and milk performance in Dhofari goats. Twenty-four lactating goats (27 ± 1.8 kg of initial live body weight) were fed a control diet comprising of Rhodes grass hay plus a concentrate feed mixture. Goats were assigned to one of three experimental treatments (n = 8 per treatment) as: (1) control diet with no supplement (CTRL), (2) control diet with 0.300 g/day CHI (CHI0.3) and (3) control diet supplemented with 0.600 g/day CHI (CHI0.6) for a 45-day experimental period. Dietary supplementation with increasing doses of CHI decreased (p < 0.05) linearly ruminal pH (p = 0.023), total short chain fatty acids concentrations (p = 0.011), acetate (p = 0.013) and butyrate (p = 0.042) proportions, acetate to propionate ratio (p < 0.001), estimated methane (CH4) production (p < 0.001), ammonia nitrogen concentrations (p = 0.003) and protozoa abundance (p = 0.003). However, the ruminal propionate proportion augmented (p = 0.002) linearly with increasing doses of CHI in the diet. Increasing doses of CHI linearly increased the abundance of the ruminal propionate-producing bacteria, while diminished acetate and CH4-producing bacteria (p < 0.05). Serum total protein (p = 0.037) and glucose (p = 0.042) levels linearly increased as CHI doses increased in the diet. However, serum UREA levels decreased linearly (p = 0.002) by 21% with increasing CHI amounts in the diet. The digestibility of organic matter, crude protein and neutral detergent fibre increased linearly with the increasing CHI doses (p < 0.05). Neither linear nor quadratic responses (p > 0.05) were observed in daily milk yield and feed efficiency by supplementing the diet with CHI. In conclusion, supplementing the diet with CHI at a dose of 0.600 g/day as a feed additive for dairy goats reduced estimated CH4 generation and improved fibre and protein digestion, with no influence on feed intake, milk yield or composition.

Detection of putative loci affecting milk yield in Turkish Awassi sheep using microsatellite markers.

On the basis of comparisons between bovine and ovine genome mapping information, the aim of the study was to analyze the genetic diversity of selected DNA microsatellites from the bovine genome and to investigate their correlation with the average daily milk yield in Awassi sheep. 18 informative microsatellite markers were selected from the significant QTL regions affecting milk yield identified in the bovine genome in previous studies. The selected microsatellite markers were then amplified by PCR as reciprocal amplifications on the genomic DNA of Awassi sheep, with standard daily milk yield records. Thus, in this study, 18 microsatellite markers associated with milk yield in the bovine genome were examined for both determination of genetic polymorphism within the flock and the effects of marker loci on average daily milk yield in Awassi sheep. Allele frequencies of markers were determined based on the results of fragment analysis. The analysis of variance showed that the 123bp allele at the marker locus BMS1341 on BTA2 significantly influenced the average daily milk yield of Ivesi sheep (P < 0.01). On the other hand, the BMS381 locus with a 115bp allele on BTA2, the MCM140 locus with a 185bp allele on BTA6, the BMS2721 locus with a 155bp allele, the BM1237 locus with 174 and 180bp alleles on BTA7, and finally, the BMS1967 locus with a 117bp allele, the BM4208 locus with 176 and 182bp alleles, and the INRA locus with a185 bp allele on BTA8 showed moderately significant effects on the average daily milk yield of Ivesi ewes (P < 0.05).

Caveolin 1 ameliorates nonesterified fatty acid-induced oxidative stress via the autophagy regulator Beclin 1 in bovine mammary gland epithelial cells

High blood concentrations of nonesterified fatty acids (NEFA) during ketosis enhance uptake by the mammary gland and impair autophagy while causing oxidative stress. Caveolin 1 (CAV1) is closely related to autophagy and plays a role in regulating oxidative stress. The aim of this study was to explore the potential role of CAV1 on oxidative stress and autophagy during a high NEFA challenge in the immortalized bovine mammary epithelial cell line MAC-T. Mammary gland tissue biopsies and blood samples were collected from healthy (n = 15) and clinically ketotic (n = 15) Holstein cows at 3 to 10 (average = 6) days in milk. Compared with healthy cows, ketotic cows had lower dry matter intake (DMI), daily milk yield, serum glucose and greater serum NEFA and BHBA, accompanied by greater milk fat and lower milk protein. Malondialdehyde (MDA) was greater but activities of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH) were lower in cows with clinical ketosis. A lower protein abundance of CAV1, Beclin 1, autophagy relative gene 5 (ATG5), and microtubule-associated protein 1 light chain 3 (LC3) as well as greater protein abundance of sequestosome-1 (SQSTM1, also called p62) were detected in mammary tissue of cows with clinical ketosis. In vitro, the MAC-T cells were treated with 0, 0.6 and 1.2 mM NEFA for 12 h or treated with 1.2 mM NEFA for various time points (0, 0.5, 1, 2, 4, 8, 12 and 24 h). Compared with 0 mM NEFA, protein abundance of CAV1, Beclin 1, ATG5 and LC3 was greater in the MAC-T challenged with 0.6 mM NEFA, but lower in the 1.2 mM NEFA group. Protein abundance of p62 was lower with 0.6 mM NEFA, but higher with 1.2 mM NEFA. In response to increasing doses of NEFA, mRNA abundance of CAV1, total antioxidant capacity (T-AOC) and SOD activity decreased while the level of reactive oxygen species (ROS) and content of MDA increased. The protein abundance of CAV1, Beclin 1, ATG5 and LC3 peaked at 0.5 h and 1 h, resulting in both linear and quadratic effects. The protein abundance of p62 decreased, reaching a nadir at 4 h in both a linear and quadratic manner. The silencing of CAV1 in MAC-T cells aggravated the 1.2 mM NEFA-induced decrease in Beclin 1 expression, impaired autophagy, and increase in oxidative stress, whereas the overexpression of CAV1 alleviated these effects. Pretreatment of MAC-T cells with Beclin 1 siRNA (si-Beclin 1) and overexpressing CAV1 followed by challenged with 1.2 mM NEFA reversed the CAV1 induced autophagy, thereby enhancing oxidative stress. Overall, these data suggest that CAV1 protects bovine mammary epithelial cells from NEFA-induced oxidative stress through enhancing the expression of Beclin 1 and activating autophagy.

Short communication: Dairy Victory™ Platform: A Novel Benchmarking Platform to Empower Economic Decisions on Dairy Farms.

In the face of diminishing economic margins, dairy farmers globally are compelled to maintain economic competitiveness. Benchmarking emerges as a strategic tool to establish new, achievable improvement objectives that balance ambition with practicality. This typically requires integrating diverse data sources such as feed, milk production, diet, and market prices. However, many farms lack essential, cow-level data like daily milk output and milk income over feed cost (IOFC), which hampers economic performance visibility and informed decision-making. To address this challenge, we introduce “Dairy Victory™ platform (DVP)” a novel cloud-based benchmarking platform designed to simplify complex analyses. The DVP uniquely calculates zootechnical and economic key performance indicators (KPIs) at the cow and herd levels and benchmarks these against a dynamically selected cohort of farms, facilitating comparisons across various farm sizes, and milk production levels. The primary objective of this paper is to demonstrate the utility of DVP as a decision-making tool in supporting farmers and consultants with both operational and strategic decisions. It emphasizes leveraging benchmarking information to enhance decision-making processes, thereby highlighting the significant value that DVP brings to farmers, consultants, and dairy farm stakeholders. Our study analyzed data from 712 farms from December 2023, focusing on several KPIs, such as milk production, milk quality, feed efficiency, and IOFC using Dairy Herd Improvement (DHI) records. This approach showcases DV's ability to utilize minimal data inputs for detailed analysis, leveraging peer performance to set desirable and/or achievable goals. We present a case study demonstrating how the DVP platform can guide dairy farms using anonymized peer data. This approach enables users to potentially improve their IOFC by up to 35%. Our findings highlight DVP's potential as a powerful tool for generating insightful analyses, simulations, and recommendations, primarily from test-day data, but also integrated with market and estimated data. This supports more strategic decision-making in dairy management, including automatic goal-setting based on peer performance.