scholarly journals Genetic relationship between milk dry matter and other milk traits in extended lactations of Polish Holstein cows

2010 ◽  
Vol 55 (No. 3) ◽  
pp. 91-104 ◽  
Author(s):  
K. Yazgan ◽  
J. Makulska ◽  
A. Węglarz ◽  
E. Ptak ◽  
M. Gierdziewicz
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Fixed Effects ◽  
Dry Matter ◽  
Genetic Correlations ◽  
Random Regression ◽  
Holstein Cows ◽  
Milk Traits ◽  
Data Set ◽  
The Third

The objective of this research was to examine heritabilities and genetic, phenotypic and permanent environmental relationships between milk dry matter (DM) and milk traits such as milk, fat, protein and lactose yields, milk urea nitrogen (MUN) and somatic cell score (SCS) in extended (to 395 days) lactations of Holstein cows from a big farm in Poland. The data set consisted of 78 059 test day records from the first, second and third lactations of 3 792 cows, daughters of 210 sires and 1 677 dams. Single- or two-trait random regression models were used with fixed effects of calving year, calving month, dry period and calving interval and random additive genetic and permanent environmental effects. The last two fixed effects were not included in the analysis of first lactation data. The highest values of heritabilities for all traits, except DM, were observed in the second lactation. First lactation heritabilities for all traits – except milk yield and SCS – were smaller than those in the third lactation. Lactose yield was highly heritable, with average h<SUP>2</SUP> equal to 0.25, 0.29 and 0.28 in lactations 1, 2 and 3, respectively. Heritability for DM was slightly lower than that for lactose (0.22, 0.26 and 0.28 for lactations 1, 2 and 3, respectively). In all lactations heritabilities for SCS were below 0.1. Genetic correlations between DM and milk yield (0.64–0.74) were lower than those between MUN and milk yield (0.67–0.79) as well as between lactose and milk yield (0.72–0.82). In general, DM was much more closely correlated with fat or protein yield (0.55–0.79) than with MUN or lactose (0.38–0.76). Only in the third lactation the correlation between DM and protein (0.72) was lower than between lactose and protein (0.76). For all lactations there were very high genetic correlations between DM and lactose (0.96–0.98) and high correlations between DM and MUN (0.63–0.83) and between lactose and MUN (0.70–0.85). The results suggest that further research is needed, focused on DM and its relationship with other traits in larger populations. &nbsp;

scholarly journals Genetic parameters for milk production and persistency in the Iranian Holstein population by the multitrait random regression model

2014 ◽  
Vol 57 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Khabat Kheirabadi ◽  
Sadegh Alijani
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Genetic Correlations ◽  
Random Regression ◽  
Genetic Dissection ◽  
Production Traits ◽  
Data Set ◽  
Random Regression Model ◽  
Regression Test ◽  
Fat Yield

Abstract. For genetic dissection of milk, fat, and protein production traits in the Iranian primiparous Holstein dairy cattle, records of these traits were analysed using a multitrait random regression test-day model. Data set included 763 505 test-day records from 88 204 cows calving since 1993. The (co)variance components were estimated by Bayesian method. The obtained results indicated that as in case of genetic correlations within traits, genetic correlations between traits decrease as days in milk (DIM) got further apart. The strength of the correlations decreased with increasing DIM, especially between milk and fat. Heritability estimates for 305-d milk, fat, and protein yields were 0.31, 0.29, and 0.29, respectively. Heritabilities of test-day milk, fat, and protein yields for selected DIM were higher in the end than at the beginning or the middle of lactation. Heritabilities for persistency ranged from 0.02 to 0.24 and were generally highest for protein yield (0.05 to 0.24) and lowest for fat yield (0.02 to 0.17), with milk yield having intermediate values (0.06 to 0.22). Genetic correlations between persistency measures and 305-d production were higher for protein and milk yield than for fat yield. The genetic correlation of the same persistency measures between milk and fat yields averaged 0.76, and between milk and protein yields averaged 0.82.

Multi-trait covariance functions to estimate genetic correlations between milk yield, dry-matter intake and live weight during lactation

1999 ◽  
Vol 24 ◽  
pp. 147-151 ◽  
Author(s):  
R. F. Veerkamp ◽  
R. Thompson
Keyword(s):  
Energy Balance ◽  
Milk Yield ◽  
Fixed Effects ◽  
Dry Matter ◽  
Genetic Correlations ◽  
Live Weight ◽  
Random Regression ◽  
Dry Matter Intake ◽  
Covariance Functions ◽  
High Level

AbstractEnergy balance is a function of dry-matter intake (DMI), live weight and milk yield over a certain time period. To investigate potential strategies to use genetic selection for the improvement of the negative energy balance, genetic co-variances were estimated among DMI, live weight and milk yield during the first 15 weeks of lactation (no.=628). Rather than estimating the full 45 by 45 matrix a random regression model was used to estimate a second order covariance functions for the additive genetic and permanent environmental effects. Fixed effects were test-day, a group effect and week in lactation. Estimates for the genetic covariance function demonstrated that a high level of milk yield is only moderately correlated with a high level of DMI (0.21) but very strongly correlated to an increase of intake (0.97) and a loss of live weight (-0.46) during the first 15 weeks of lactation. Levels of weight and intake were correlated strongly (0.81). Estimates for the genetic correlations between weeks 1 and 15 were 0.79, 0.34 and 0.83 for milk yield, DMI and live weight respectively. DMI during early lactation was negatively correlated with milk yield but DMI during the later weeks was positively correlated with milk yield. The implication is that when selection is for a linear combination of milk yield, DMI and live weight (i.e. energy balance or efficiency) the moment in lactation of measuring each trait on the cow is of importance

Genetic parameters of milk traits in Latxa dairy sheep

2001 ◽  
Vol 73 (3) ◽  
pp. 407-412 ◽  
Author(s):  
A. Legarra ◽  
E. Ugarte
Keyword(s):  
Milk Fat ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Selection Criterion ◽  
Genetic Effect ◽  
Milk Composition ◽  
Additive Genetic Effect ◽  
Dairy Sheep ◽  
Milk Traits

AbstractA total of 7444 lactation records which include milk, fat and protein yields (MY, FY, PY) and fat and protein content (F%, P%) from 6429 Black-Faced Latxa ewes were employed to estimate genetic parameters for milk traits. Traits were standardized to 120 days of lactation. For the calculation of composition traits, not all test-days had their composition measured and therefore a correction taking this into account was included in the analysis. A first-derivative restricted maximum likelihood algorithm was used on an animal model with repeatability analysis, using models including fixed effects (flock-year-season of lambing, age-parity at lambing, number of lambs, interval between lambing and first milk recording and the combination of sampled test-days) and random effects (the additive genetic effect and the permanent environmental effect). The resulting heritabilities were 0·20, 0·16, 0·18, 0·14 and 0·38 for MY, FY, PY, F% and P% respectively. Heritability of F% was much lower than expected, probably due to problems derived from the recording method. Genetic correlations were high and positive between yields and moderately positive between F% and P%, and negative or null between yields and composition, as has been reported for other European dairy sheep breeds. As most of the milk produced by Latxa dairy sheep is processed into cheese, the inclusion of milk sampling in official milk recording and a change in the selection criterion are recommended to avoid a long-term worsening in milk composition.

scholarly journals Random regression models to estimate genetic parameters for test-day milk yield and composition in Iranian buffaloes

2013 ◽  
Vol 56 (1) ◽  
pp. 276-284 ◽  
Author(s):  
M. Madad ◽  
N. Ghavi Hossein-Zadeh ◽  
A. A. Shadparvar ◽  
D. Kianzad
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Milk Protein ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Random Regression ◽  
Production Traits ◽  
Environmental Correlations ◽  
Protein Percentage ◽  
Heritability Estimates

Abstract. The objective of this study was to estimate genetic parameters for milk yield and milk percentages of fat and protein in Iranian buffaloes. A total of 9,278 test-day production records obtained from 1,501 first lactation buffaloes on 414 herds in Iran between 1993 and 2009 were used for the analysis. Genetic parameters for productive traits were estimated using random regression test-day models. Regression curves were modeled using Legendre polynomials (LPs). Heritability estimates were low to moderate for milk production traits and ranged from 0.09 to 0.33 for milk yield, 0.01 to 0.27 for milk protein percentage and 0.03 to 0.24 for milk fat percentage, respectively. Genetic correlations ranged from −0.24 to 1 for milk yield between different days in milk over the lactation. Genetic correlations of milk yield at different days in milk were often higher than permanent environmental correlations. Genetic correlations for milk protein percentage ranged from −0.89 to 1 between different days in milk. Also, genetic correlations for milk percentage of fat ranged from −0.60 to 1 between different days in milk. The highest estimates of genetic and permanent environmental correlations for milk traits were observed at adjacent test-days. Ignoring heritability estimates for milk yield and milk protein percentage in the first and final days of lactation, these estimates were higher in the 120 days of lactation. Test-day milk yield heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in Iranian milking buffaloes.

scholarly journals Genetic Parameters of Bovine Milk Fatty Acid Profile, Yield, Composition, Total and Differential Somatic Cell Count

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2406
Author(s):  
Tania Bobbo ◽  
Mauro Penasa ◽  
Martino Cassandro
Keyword(s):  
Animal Models ◽  
Somatic Cell ◽  
Cell Count ◽  
Milk Yield ◽  
Milk Fat ◽  
Fixed Effects ◽  
Somatic Cell Count ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Bovine Milk

The growing interest of consumers for milk and dairy products of high nutritional value has pushed researchers to evaluate the feasibility of including fatty acids (FA) in selection programs to modify milk fat profile and improve its nutritional quality. Therefore, the aim of this study was to estimate genetic parameters of FA profile predicted by mid-infrared spectroscopy, milk yield, composition, and total and differential somatic cell count. Edited data included 35,331 test-day records of 25,407 Italian Holstein cows from 652 herds. Variance components and heritability were estimated using single-trait repeatability animal models, whereas bivariate repeatability animal models were used to estimate genetic and phenotypic correlations between traits, including the fixed effects of stage of lactation, parity, and herd-test-date, and the random effects of additive genetic animal, cow permanent environment and the residual. Heritabilities and genetic correlations obtained in the present study reflected both the origins of FA (extracted from the blood or synthesized de novo by the mammary gland) and their grouping according to saturation or chain length. In addition, correlations among FA groups were in line with correlation among individual FA. Moderate negative genetic correlations between FA and milk yield and moderate to strong positive correlations with fat, protein, and casein percentages suggest that actual selection programs are currently affecting all FA groups, not only the desired ones (e.g., polyunsaturated FA). The absence of association with differential somatic cell count and the weak association with somatic cell score indicate that selection on FA profile would not affect selection on resistance to mastitis and vice versa. In conclusion, our findings suggest that genetic selection on FA content is feasible, as FA are variable and moderately heritable. Nevertheless, in the light of correlations with other milk traits estimated in this study, a clear breeding goal should first be established.

scholarly journals Meta-analysis of the effect of glycerin inclusion in dairy cattle diet on milk fatty acid profile

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Rodrigo N S Torres ◽  
João P A Bertoco ◽  
Maria C G de Arruda ◽  
Julia L Rodrigues ◽  
Larissa M Coelho ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Dairy Cows ◽  
Milk Yield ◽  
Milk Fat ◽  
Dry Matter ◽  
Meta Analysis ◽  
Random Effect ◽  
Milk Fatty Acid ◽  
Data Set

Abstract The use of glycerin in diets for dairy cows initially emerged as an alternative for the prevention and control of ketosis. However, despite some controversy, there are still several studies associating glycerin with increases in daily milk yield, with possible changes in its constituents. Therefore, the objective of this study was to evaluate, using a meta-analysis approach, the effect of glycerin inclusion in dairy cow diets on milk fatty acid. Twenty-two peer-reviewed publications with 66 treatment means were included in data set. The effect of glycerin inclusion in diet (treatment) were evaluated using random-effect models to examine the weighted mean differences (WMD) between a control diet (without glycerin in the diet) and the treatment diet. Heterogeneity was explored by meta-regression and subgroup analysis performed for: genetic type; days in milk; experimental period; glycerin in diet; glycerin type and concentrate in diet. Inclusion of glycerin in the diet increased the digestibility of dry matter and protein, as well as ruminal propionate. It did not affect dry matter intake (P = 0.351) and milk yield (P = 0.730). The effect of glycerin inclusion on the milk fat yield is dependent on the genetic group, in which Holstein (WMD = −0.04 kg/d; P = 0.010) and Holstein-crossbreed (WMD = −0.10 kg/d; P &lt; 0.0001) cows produced less fat in milk compared to Jersey cows, when glycerin was included in the diets. Glycine inclusions of up to 100 g/kg in the diet of dairy cows did not negatively affect milk production and composition. However, inclusions above 150 g/kg of glycerin in the diet reduced the concentration of fat, and of unsaturated, monounsaturated, polyunsaturated fatty acids and conjugated linoleic acid (CLA C18: 2 cis-9 and trans-11) in milk. The results reported in our meta-analysis does not demonstrate the effectiveness of glycerin in improving the composition of milk and a group of fatty acids of importance for human health such as C18: 2 cis-9, trans-11 CLA.

Genetic correlation estimates between milk production traits, mastitis and different measures of somatic cells in Holstein cows

2019 ◽  
Vol 59 (6) ◽  
pp. 1031 ◽  
Author(s):  
Arash Chegini ◽  
Navid Ghavi Hossein-Zadeh ◽  
Seyed Hossein Hosseini-Moghadam ◽  
Abdol Ahad Shadparvar
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Linear Models ◽  
Genetic Correlations ◽  
Holstein Cows ◽  
Threshold Models ◽  
Production Traits ◽  
Environmental Variance ◽  
Udder Health ◽  
Cell Counts

The objective of this study was to estimate genetic parameters including repeatability, heritability as well as genetic and environmental relationships between 305-day milk yield, milk fat and protein yield (Fat and Pro), milk fat and protein percentages (Fat% and Pro%), mastitis (Mast), number of mastitis occurrence and different measurements of somatic cell counts using linear and threshold animal as well as linear and threshold sire models in Holstein cows of Iran. Records of 33851 first lactation Holstein cows from five large dairy herds with calving dates from March 2002 to September 2014 were analysed, using Gibbs sampling methodology. Heritabilities of production traits estimated by linear animal model ranged from 0.14 (Fat%) to 0.29 (Pro%). Generally, udder health traits had low heritability (ranged from 0.005 to 0.10). Estimates of heritability for Mast using linear models were higher than those obtained with threshold models. However, in general estimates of heritabilities using threshold models were higher than those from linear models. There were unfavourable genetic correlations between production traits and Mast, which implies that breeding programs with emphasis on 305-day milk yield will experience deterioration in udder health. Despite low heritability of udder health traits, genetic variability exists for these traits that allow selecting superior animals and increasing resistance to Mast and animal welfare. Considering relatively high ratio of permanent environmental variance for Mast, culling decisions can be made with higher accuracy in order to reduce Mast incidence phenotypically over time.

scholarly journals Einfluss systematischer Umwelteffekte auf die Milchleistungsmerkmale bei Bunten Deutschen Edelziegen

2004 ◽  
Vol 47 (3) ◽  
pp. 275-285
Author(s):  
D. Bömkes ◽  
H. Hamann ◽  
O. Distl
Keyword(s):  
Somatic Cell ◽  
Protein Content ◽  
Milk Yield ◽  
Significant Influence ◽  
Milk Fat ◽  
Fixed Effects ◽  
Fat Content ◽  
Protein Yield ◽  
Production Traits ◽  
Milk Traits

Abstract. Title of the paper: Influence of systematic environmental effects on milk performance traits in German Improved Fawn The objectives of this study were to analyse the influence of fixed effects on milk traits of German Improved Fawn. The analysis was based on 27,778 test day records of 1,848 German Improved Fawn with 3,574 lactation records. The milk records were sampled between 1988 and 2002 from 229 flocks in Lower Saxony, Saxony and Baden-Wuerttemberg. The average daily milk yield was 2.87 ± 1.20 kg with a fat content of 3.08 ± 0.54% and a protein content of 3.38 ± 0.95%. Somatic cell count (SCC) was transformed into somatic cell score (SCS). Mean SCS was 5.49 ± 1.93. The average lactation length was 234.1 ± 76.4 days. The analysis of variance showed a significant influence of lactation number, stage of lactation, year of lambing and month of lambing on all analysed milk production traits. Milk yield was highest in the fourth lactation number and fat as well as protein content in the 7th to 13th lactation number. Litter size had a significant influence on milk and fat yield and on fat and protein content. The region significantly influenced protein yield and fat and protein content of German Improved Fawn but had no effect on milk and protein yield and SCS. Animals from Baden-Wuerttemberg reached the highest milk protein content but the lowest milk fat content.

scholarly journals Genetic Analysis of Persistency for Milk Fat Yield in Iranian Buffaloes (Bubalus bubalis)

2021 ◽  
Vol 12 ◽  
Author(s):  
Mohammad Ali Nazari ◽  
Navid Ghavi Hossein-Zadeh ◽  
Abdol Ahad Shadparvar ◽  
Davood Kianzad
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Genetic Correlations ◽  
Bubalus Bubalis ◽  
Random Regression ◽  
Animal Products ◽  
Improvement Programs ◽  
Fat Yield ◽  
The Difference ◽  
Genetic Trends

This study aimed to estimate heritabilities and genetic trends for different persistency measures for milk fat yield and their genetic correlations with 270-day milk yield in Iranian buffaloes. The records of test-day milk fat yield belonging to the first three lactations of buffaloes within 523 herds consisting of 43,818 records were got from the Animal Breeding Center and Promotion of Animal Products of Iran from 1996 to 2012. To fit the lactation curves based on a random regression test-day model, different orders of Legendre polynomial (LP) functions were selected. Three persistency measures were altered according to the specific condition of the lactation curve in buffaloes: (1) The average of estimated breeding values (EBVs) for test day fat yield from day 226 to day 270 as a deviation from the average of EBVs from day 44 to day 62 (PM1), (2) A summation of contribution for each day from day 53 to day 247 as a deviation from day 248 (PM2), and (3) The difference between EBVs for day 257 and day 80 (PM3). The estimates of heritability for PM1, PM2, and PM3 ranged from 0.20 to 0.48, from 0.36 to 0.47, and from 0.19 to 0.35 over the first three lactations, respectively. The estimate of genetic trends for different persistency measures of milk fat yield was not significant over the lactations (P &gt; 0.05). Genetic correlation estimates between various measures of persistency were generally high over the first three lactations. Also, genetic correlations estimates between persistency measures and 270-day milk yield were mostly low and varied from 0.00 to 0.24 (between PM1 and 270-day milk yield), from −0.19 to 0.13 (between PM2 and 270-day milk yield), and from −0.02 to 0.00 (between PM1 and 270-day milk yield) over the first three lactations, respectively. Persistency measures that showed low genetic correlations with milk fat yield were considered the most suitable measures in selection schemes. Besides, medium to high heritability estimates for different persistency measures for milk fat yield indicated that relevant genetic variations detected for these characters could be regarded in outlining later genetic improvement programs of Iranian buffaloes.

scholarly journals Estimation of genetic parameters for daily milk yields of primiparous Iranian Holstein cows

2013 ◽  
Vol 56 (1) ◽  
pp. 455-466
Author(s):  
K. Kheirabadi ◽  
S. Alijani ◽  
L. Zavadilová ◽  
S. A. Rafat ◽  
G. Moghaddam
Keyword(s):  
Milk Fat ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
National Level ◽  
Genetic Correlations ◽  
Protein Yield ◽  
Random Regression ◽  
Production Traits ◽  
Multiple Traits ◽  
Multiple Trait

Abstract. Applying a multiple trait random regression (MT-RR) in national level and for whole test day records of a country is a great advance in animal breeding context. Having reliable (co) variance components is a critical step in applying multiple traits genetic evaluation especially in developing countries. Genetic parameters of milk, fat and protein yields were estimated for Iranian Holstein dairy cows. Data included 276 692 test day (TD) production traits records collected of 30 705 primiparous cows belonging to 619 sires. An animal multi-trait random regression model was employed in the analyses using the restricted maximum likelihood (REML) method. The model included herd-test-date, age-season of calving (by applying a fixed regression for each subclass of this effect) and year of calving as fixed effects and random regression (RR) coefficients for additive genetic (AG) and permanent environmental (PE) effects. Obtained results showed that daily heritabilities ranged from 0.10 to 0.21 for milk, from 0.05 to 0.08 for fat and from 0.08 to 0.18 for protein yield. Estimated heritability for 305-d milk, fat and protein yields were 0.25, 0.20 and 0.25, respectively. Correlations between individual test day records within traits were high for adjacent tests (nearly 1) and decreased as the interval between tests increased. Correlations between yields of milk, fat and protein on a given test day are also high and greater during late lactation than during early or mid-lactation. Genetic correlations between 305-d yield traits ranged from 0.75 to 0.92. The largest genetic correlation, as well as permanent environmental correlation, was observed between milk and protein yield.

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