scholarly journals Genetic and environmental factors influencing milk, protein and fat yields of pasture-based dairy cows in Tasmania

2010 ◽  
Vol 50 (4) ◽  
pp. 265 ◽  
Author(s):  
S. A. Adediran ◽  
P. Nish ◽  
D. J. Donaghy ◽  
D. A. Ratkowsky ◽  
A. E. O. Malau-Aduli
Keyword(s):  
Dairy Cows ◽  
Somatic Cell ◽  
Cell Count ◽  
Milk Fat ◽  
Somatic Cell Count ◽  
Milk Protein ◽  
Herd Size ◽  
Production Traits ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations

The objective of this study was to provide an update on milk production performance, heritability, genetic and phenotypic correlations among production traits that are valuable for management, breeding and selection decisions in pasture-based dairy systems. The study utilised a total of 106 990 lactation records of Holstein–Friesian (FF), Jersey (JJ) and their crossbreds (HF) from 428 Tasmanian dairy herds collected between 2000 and 2005. The data were analysed using the least-squares approach with a general linear model and restricted maximum likelihood approach with a linear animal model. Results indicated highly significant (P < 0.01) effects of breed, herd size, cow’s parity, season and year of calving on milk, protein and fat yields. Average milk and protein yields per cow per lactation were highest in the FF breed (5212 L and 171 kg, respectively) and lowest in the JJ breed (3713 L and 143 kg, respectively). FF cows also produced 13.5 kg more milk fat than JJ and HF cows. Furthermore, milk, fat and protein yields were highest for cows calving during spring and lowest for autumn-calving cows. It was also evident that cows in very large herds (>1110 cows/herd) out-produced those in smaller herds. Heritability was highest for milk yield and lowest for somatic cell count ranging from 0.28 to 0.41. Genetic and phenotypic correlations between milk, fat and protein yields ranged from 0.41 to 0.85, and 0.66 to 0.92, respectively. However, genetic and phenotypic correlations between the log of somatic cell count and the production traits ranged from 0.03 to 0.09 and –0.03 to –0.05. We conclude that breed, herd size, parity, season and year of calving were among the main factors correlated with the productivity of dairy cows in Tasmania and adjustments for these factors would be mandatory for any unbiased comparison of lactation performance within and between pasture-based dairy production systems. The practical application of this information would be valuable to dairy farmers for decisions related to breeding, selection and management of their herds.

scholarly journals Estimation of Genetic and Phenotypic Parameters for Production Traits and Somatic Cell Count for Jersey Dairy Cattle in Zimbabwe

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Edward Missanjo ◽  
Venancio Imbayarwo-Chikosi ◽  
Tinyiko Halimani
Keyword(s):  
Dairy Cattle ◽  
Somatic Cell ◽  
Cell Count ◽  
Somatic Cell Count ◽  
Production Traits ◽  
Fat Percentage ◽  
Milk Traits ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Improvement Programme

Genetic and phenotypic parameters for production traits and somatic cell count (SCC) for Jersey dairy cattle in Zimbabwe were estimated. A total of 10986 lactation records were obtained from Zimbabwe Livestock Identification Trust, with cows calving in the period from 1996 to 2008. An ASReml program fitting an animal model was used for the analyses. Heritability estimates for milk yield, fat yield, protein yield, fat percentage, protein percentage, and Log10SCC were 0.30, 0.32, 0.33, 0.42, 0.44, and 0.08, respectively. The corresponding repeatability estimates were 0.39, 0.38, 0.39, 0.49, 0.51, and 0.16, respectively. The genetic and phenotypic correlations between different production traits ranged from −0.86 to 0.95 and from −0.88 to 0.98, respectively. The genetic and phenotypic correlations between production traits and Log10SCC were weak almost nonsignificantly differentl from zero. The results imply that milk traits for Jersey dairy cattle in Zimbabwe are more heritable. Therefore, these traits may be preferred by breeders as selection criteria for development of effective genetic improvement programme.

The effect of suckling following mechanical milking on milk yield, milk composition and somatic cell count in dairy cattle

2000 ◽  
Vol 25 ◽  
pp. 175-177 ◽  
Author(s):  
J.K. Margerison ◽  
C.J.C. Phillips
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Protein Content ◽  
Milk Yield ◽  
Milk Fat ◽  
Somatic Cell Count ◽  
Milk Protein ◽  
Milk Composition ◽  
Fat Content ◽  
Daily Milk Yield

AbstractSuckling following mechanical milking is common practice in organic dairy production systems and in developing countries. The objective of the experimental work was to assess the effect of suckling and suckling frequency following mechanical milking on milk yield, milk composition and somatic cell count. Two experiments were completed using multiparous dairy cows allocated at 3 days post partum to their respective treatment groups. In experiment one, twenty–four multiparous dairy cows were allocated to one of two treatments for 305 days; 12 cows not suckled (NS) and 12 cows, which were suckled twice daily following mechanical milking (S2). Daily milk yield was significantly greater (P<0.05) in suckled cows, NS 8.0, S2 8.9 (sem 0.18) kg/d. Milk fat content was significantly lower (P<0.05) in suckled cows (NS 32.0, S2 30.7 (sem 0.56) g/kg). However, milk protein was not significantly different in suckled cows, NS 29.2, S2 27.6 (sem 10.79) g/kg compared with non suckled cows. Somatic cell count was significantly lower (P<0.05) in suckled cows NS 106, S2 85 (sem 2.85) 000/ml, compared with non suckled cows. In experiment two, thirty-eight cows were allocated one of two treatments for 120 days; 19 cows not suckled (NS) and 19 cows, which were suckled once daily following the afternoon milking (S1). Suckling took place for fifteen minutes daily following machine milking only. The calves were weaned at 6 months of age. Total daily milk yield was significantly greater (P<0.05) in suckled cows, NS 11.7, S1 12.5 (sem 0.04) (kg/d) compared with non suckled cows. The milk fat and protein content were not significantly different in suckled and non suckled cows. Milk fat content NS 33.4, S1 32.9 (sem 0.14) g/kg and milk protein content NS 29.8, S1 30.0 (sem 0.07) g/kg. In conclusion, suckled cows had significantly higher milk yields. Cows suckled twice daily had significantly lower milk fat content. Suckling did not affect milk protein content. Suckling cows twice daily significantly reduced SCC.

scholarly journals Associations between Bovine β-Defensin 4 Genotypes and Production Traits of Polish Holstein-Friesian Dairy Cattle

Animals ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 723
Author(s):  
Brodowska ◽  
Zwierzchowski ◽  
Marczak ◽  
Jarmuż ◽  
Bagnicka
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Milk Fat ◽  
Somatic Cell Count ◽  
High Rate ◽  
Breeding Value ◽  
Production Traits ◽  
Milk Traits ◽  
Breeding Values ◽  
Holstein Friesian

This study analyzed the associations between two single-nucleotide polymorphisms (C2239T and A1674C), used together as a genotype located in BNBD4, and milk traits and breeding values of productivity traits of Polish Holstein-Friesian dairy cows. The research was carried out on 322 cows, with 7070 milk parameter and somatic cell count records in daily milking, as well as 897 records covering data on whole lactations, and 2209 breeding value records for productivity traits. The DMU statistical package with a one-trait repeatability test-day animal model was used to estimate the associations. The differences between the genotype effects were analyzed using Duncan’s post-hoc tests. The CC/AA and CT/AC genotypes had the highest frequencies (0.62 and 0.23, respectively). For use in marker-assisted selection, the CC/AC genotype is the most promising as an indicator of high-yielding cows potentially resistant to mastitis, because it was associated with the lowest somatic cell count (SCC), highest milk, fat, and protein yields in daily milking, as well as with milk yield in the whole lactation. The studied genotypes were also related to the breeding values of all the investigated production traits. However, some simulation studies have indicated a high rate of false-positives in GWAS based on classically calculated EBVs.

Association of Milk Protein Genotypes with Production Traits and Somatic Cell Count of Holstein Cows

2008 ◽  
Vol 8 (7) ◽  
pp. 1231-1235 ◽  
Author(s):  
M. Ahmadi ◽  
Y. Mohammadi ◽  
H. Darmani Ku ◽  
R. Osfoori ◽  
S. Qanbari
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Somatic Cell Count ◽  
Milk Protein ◽  
Holstein Cows ◽  
Production Traits

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

Animals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 753 ◽  
Author(s):  
Giorgia Stocco ◽  
Andrea Summer ◽  
Claudio Cipolat-Gotet ◽  
Lucio Zanini ◽  
Diego Vairani ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Somatic Cell ◽  
Cell Count ◽  
Milk Fat ◽  
Fixed Effects ◽  
Somatic Cell Count ◽  
Positive Association ◽  
Milk Composition ◽  
Repeated Measurements ◽  
Milk Fatty Acids

Recent available instruments allow to record the number of differential somatic cell count (DSCC), representing the combined proportion of polymorphonuclear leukocytes and lymphocytes, on a large number of milk samples. Milk DSCC provides indirect information on the udder health status of dairy cows. However, literature is limited regarding the effect of DSCC on milk composition at the individual cow level, as well as its relation to the somatic cell score (SCS). Hence, the aims of this study were to (i) investigate the effect of different levels of DSCC on milk composition (fat, protein, casein, casein index, and lactose) and (ii) explore the combined effect of DSCC and SCS on these traits. Statistical models included the fixed effects of days in milk, parity, SCS, DSCC and the interaction between SCS × DSCC, and the random effects of herd, animal within parity, and repeated measurements within cow. Results evidenced a decrease of milk fat and an increase in milk fatty acids at increasing DSCC levels, while protein, casein and their proportion showed their lowest values at the highest DSCC. A positive association was found between DSCC and lactose. The interaction between SCS and DSCC was important for lactose and casein index, as they varied differently upon high and low SCS and according to DSCC levels.

scholarly journals Hyperketonemia Predictions Provide an On-Farm Management Tool with Epidemiological Insights

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1291
Author(s):  
Ryan S. Pralle ◽  
Joel D. Amdall ◽  
Robert H. Fourdraine ◽  
Garrett R. Oetzel ◽  
Heather M. White
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Milk Yield ◽  
Milk Fat ◽  
Somatic Cell Count ◽  
Past Research ◽  
Management Tool ◽  
Milk Analysis ◽  
Linear Regression Models ◽  
High Throughput Detection

Prediction of hyperketonemia (HYK), a postpartum metabolic disorder in dairy cows, through use of cow and milk data has allowed for high-throughput detection and monitoring during monthly milk sampling. The objective of this study was to determine associations between predicted HYK (pHYK) and production parameters in a dataset generated from routine milk analysis samples. Data from 240,714 lactations across 335 farms were analyzed with multiple linear regression models to determine HYK status. Data on HYK or disease treatment was not solicited. Consistent with past research, pHYK cows had greater previous lactation dry period length, somatic cell count, and dystocia. Cows identified as pHYK had lower milk yield and protein percent but greater milk fat, specifically greater mixed and preformed fatty acids (FA), and greater somatic cell count (SCC). Differential somatic cell count was greater in second and fourth parity pHYK cows. Culling (60d), days open, and number of artificial inseminations were greater in pHYK cows. Hyperketonemia prevalence decreased linearly in herds with greater rolling herd average milk yield. This research confirms previously identified risk factors and negative outcomes associated with pHYK and highlights novel associations with differential SCC, mixed FA, and preformed FA across farm sizes and production levels.

Evaluation of the udder health status in subclinical mastitis affected dairy cows through bacteriological culture, somatic cell count and thermographic imaging

2015 ◽  
Vol 18 (4) ◽  
pp. 799-805 ◽  
Author(s):  
A. Bortolami ◽  
E. Fiore ◽  
M. Gianesella ◽  
M. Corrò ◽  
S. Catania ◽  
...  
Keyword(s):  
Health Status ◽  
Dairy Cows ◽  
Somatic Cell ◽  
Cell Count ◽  
Somatic Cell Count ◽  
Subclinical Mastitis ◽  
Bacteriological Culture ◽  
Udder Health ◽  
Streptococcus Uberis ◽  
Thermographic Imaging

Abstract Subclinical mastitis in dairy cows is a big economic loss for farmers. The monitoring of subclinical mastitis is usually performed through Somatic Cell Count (SCC) in farm but there is the need of new diagnostic systems able to quickly identify cows affected by subclinical infections of the udder. The aim of this study was to evaluate the potential application of thermographic imaging compared to SCC and bacteriological culture for infection detection in cow affected by subclinical mastitis and possibly to discriminate between different pathogens. In this study we evaluated the udder health status of 98 Holstein Friesian dairy cows with high SCC in 4 farms. From each cow a sample of milk was collected from all the functional quarters and submitted to bacteriological culture, SCC and Mycoplasma spp. culture. A thermographic image was taken from each functional udder quarter and nipple. Pearson’s correlations and Analysis of Variance were performed in order to evaluate the different diagnostic techniques. The most frequent pathogen isolated was Staphylococcus aureus followed by Coagulase Negative Staphylococci (CNS), Streptococcus uberis, Streptococcus agalactiae and others. The Somatic Cell Score (SCS) was able to discriminate (p<0.05) cows positive for a pathogen from cows negative at the bacteriological culture except for cows with infection caused by CNS. Infrared thermography was correlated to SCS (p<0.05) but was not able to discriminate between positive and negative cows. Thermographic imaging seems to be promising in evaluating the inflammation status of cows affected by subclinical mastitis but seems to have a poor diagnostic value.

Sign in / Sign up

Export Citation Format

Share Document