scholarly journals Genetic and environmental parameters estimation for milk traits in Slovenian dairy sheep using random regression model

2013 ◽  
Vol 58 (No. 3) ◽  
pp. 125-135 ◽  
Author(s):  
A. Komprej ◽  
Š. Malovrh ◽  
G. Gorjanc ◽  
D. Kon ◽  
M. Kovač
Keyword(s):  
Regression Model ◽  
Protein Content ◽  
Milk Yield ◽  
Random Regression ◽  
Dairy Sheep ◽  
Milk Traits ◽  
Random Regression Model ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

(Co)variance components for daily milk yield, fat, and protein content in Slovenian dairy sheep were estimated with random regression model. Test-day records were collected by the ICAR A4 method. Analysis was done for 38 983 test-day records of 3068 ewes in 36 flocks. Common flock environment, additive genetic effect, permanent environment effect over lactations, and permanent environment effect within lactation were included into the random part of the model and modelled with Legendre polynomials on the standardized time scale of days in lactation. Estimation of (co)variance components was done with REML. The eigenvalues of covariance functions for random regression coefficients were calculated to quantify the sufficient order of Legendre polynomial for the (co)variance component estimation of milk traits. The existing 13 to 24% of additive genetic variability for the individual lactation curve indicated that the use of random regression model is justified for selection on the level and shape of lactation curve in dairy sheep. Four eigenvalues sufficiently explained variability during lactation in all three milk traits. Heritability estimate for daily milk yield was the highest in mid lactation (0.17) and lower in the early (0.11) and late (0.08) lactation. In fat content, the heritability was increasing throughout lactation (0.08–0.13). Values in protein content varied from the beginning toward mid lactation (0.15–0.19), while they rapidly increased at the end of lactation (0.28). Common flock environment explained the highest percentage of phenotypic variability: 27–41% in daily milk yield, 31–41% in fat content, and 41–49% in protein content. Variance ratios for the two permanent environment effects were the highest in daily milk yield (0.10–0.27), and lower in fat (0.04–0.08) and protein (0.01–0.10) contents. Additive genetic correlations during the selected test-days were high between the adjacent ones and they tended to decrease at the extremes of the lactation trajectory.

scholarly journals Covariance components by a repeatability model in Slovenian dairy sheep using test-day records

2009 ◽  
Vol 54 (No. 9) ◽  
pp. 426-434 ◽  
Author(s):  
A. Komprej ◽  
G. Gorjanc ◽  
D. Kon ◽  
M. Kovač
Keyword(s):  
Protein Content ◽  
Litter Size ◽  
Milk Yield ◽  
Genetic Correlations ◽  
Dairy Sheep ◽  
Milk Traits ◽  
Environment Effect ◽  
Covariance Components ◽  
Daily Milk Yield ◽  
Daily Milk

The estimation of covariance components for daily milk yield, fat and protein content was performed in three Slovenian dairy sheep breeds (Bovec, Improved Bovec, and Istrian Pramenka). In the period 1994–2002, 38 983 test-day records of 3 068 ewes were collected according to ICAR regulations (method A4). All the available relationships between animals were considered. For that reason, information on 3 534 animals was included. Test-day records were analysed by a multiple-trait repeatability animal model. In its fixed part, the model contained breed and season of lambing as classes. Days after lambing, parity, and litter size were treated as covariates. Days after lambing were modelled with modified Ali-Schaeffer’s lactation curve, parity with quadratic, and litter size with linear regression. The random part of the model consisted of flock-test month effect, additive genetic effect, permanent environment effect over lactations, and permanent environment effect within lactation. Covariance components were estimated using the restricted maximum likelihood method (REML). The estimated heritabilities were 0.11 for daily milk yield, 0.08 for fat content, and 0.10 for protein content. A relatively high variance ratio for all milk traits was explained by the flock-test month effect (from 0.27 for daily milk yield to 0.57 for protein content), while ratios explained by both permanent environment effects were lower (up to 0.13). Additive genetic correlations between daily milk yield and fat content, and daily milk yield and protein content were negative and similar (–0.36 and –0.37). A high and positive (0.67) additive genetic correlation between fat and protein content was found. Correlations for environmental effects showed a pattern similar to additive genetic correlations. Genetic parameters estimated in Slovenian dairy sheep showed that genetic progress in milk traits could be achieved using test-day milk records.

scholarly journals  Lactation curves for milk yield, fat and protein content in Slovenian dairy sheep

2012 ◽  
Vol 57 (No. 5) ◽  
pp. 231-239 ◽  
Author(s):  
A. Komprej ◽  
G. Gorjanc ◽  
D. Kon ◽  
M. Kovač
Keyword(s):  
Animal Model ◽  
Protein Content ◽  
Litter Size ◽  
Milk Yield ◽  
Additive Genetic Effect ◽  
Dairy Sheep ◽  
Stage Of Lactation ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

Lactation curves for daily milk yield, fat, and protein content in three dairy sheep breeds were estimated by the repeatability animal model using test-day records. A total of 38 983 records from 3068 ewes of Bovec, Improved Bovec, and Istrian Pramenka breeds, collected between the years 1994 and 2002, were analysed. The three-trait repeatability animal model included breed and lambing season as fixed. The stage of lactation within each breed was modelled by the modified Ali-Schaeffer’s lactation curve. Parity and litter size were used as covariates in quadratic and linear regression, respectively. Common flock environment, additive genetic effect, permanent environment over lactations as well as within lactation were treated as random. The average daily milk yield was 1090 g in Bovec, 1010 g in Improved Bovec, and 731 g in Istrian Pramenka breeds. Overall means for fat and protein content were 6.59 and 5.53% for Bovec, 6.22 and 5.33% for Improved Bovec, and 7.20 and 5.63% for Istrian Pramenka. Breed, lambing season, stage of lactation, parity, and litter size significantly (P < 0.001) affected all three observed milk traits, with the only exception of parity in fat and litter size in protein content. The shape of lactation curves for daily milk yield in Bovec and Improved Bovec breeds fitted well to the general lactation curve in dairy sheep. Daily milk yield was increasing in the first month of lactation and decreasing thereafter. In Istrian Pramenka, the shape of lactation curve was more or less atypical, with daily milk yield decreasing almost throughout the entire lactation. Lactation curves for fat and protein content were opposite to the lactation curves for daily milk yield in all three breeds.  

Effects of crossbreeding on milk production and composition in dairy sheep under organic management

2014 ◽  
Vol 54 (10) ◽  
pp. 1641 ◽  
Author(s):  
Octavio A. Castelan Ortega ◽  
Manuel González Ronquillo
Keyword(s):  
Protein Content ◽  
Milk Yield ◽  
Fat Content ◽  
Dairy Sheep ◽  
Organic Management ◽  
Total Solids ◽  
Lactation Curve ◽  
Fat Yield ◽  
Daily Milk Yield ◽  
Daily Milk

The crossbreeding of local sheep breeds with dairy breeds is an option to improve dairy production parameters in organic sheep dairy systems. Weekly milk yield (WMY) was recorded and individual samples of milk for chemical analysis were taken during 17 weeks from 45 dairy ewes of the following three genotypes: 15 East Friesian (EF), 15 EF × Suffolk (EF × SF) and 15 EF × Pelibuey (EF × PL) under organic management. For analysis of the lactation curve the Wood gamma model was used. The effect of genotype on the WMY was analysed using repeated-measures. The comparison of the least square means among genotypes for total milk yield (TMY), daily milk yield, protein content, protein yield, fat content, fat yield, non-fat solids concentration, non-fat solids yield, total solids yield and acidity was analysed using a general linear model. The genetic group influenced only in the ascent phase of the lactation curve, with values of the Parameter b of model Wood higher in EF (P = 0.01). There were no differences (P > 0.05) between genotypes in relation to the WMY, TMY, protein content and acidity; however, the effects of week of lactation trial and the interaction of genotype and week of lactation trial on WMY were significant (P < 0.05). The values of daily milk yield, fat yield, protein yield and total solids yield were higher (P < 0.005) in EF and EF × SF than EF × PL. Fat content was higher in EF × PL. EF × SF had similar values of TMY than EF and better chemical composition, which places this genotype as an option of crossbreeding in dairy sheep systems under organic management with similar agro climatic characteristics to the present study.

scholarly journals Conditioning Factors of Linearized Wood’s Function Lactation Curve Shape Parameters, Milk Yield, Fat and Protein Content in Murciano-Granadina Primiparous Does

Animals ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 2115
Author(s):  
Juan Vicente Delgado Bermejo ◽  
Francisco Antonio Limón Pérez ◽  
Francisco Javier Navas González ◽  
Jose Manuel León Jurado ◽  
Javier Fernández Álvarez ◽  
...  
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Random Regression ◽  
Total Production ◽  
Curve Shape ◽  
Conditioning Factors ◽  
Lactation Length ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

A total of 137,927 controls of 22,932 Murciano-Granadina first lactation goats (measured between 1996–2016) were evaluated to determine the influence of the number of kids, season, year and farm on total milk yield, daily milk yield, lactation length, total production of fat and protein and percentages of fat and protein. All factors analyzed had a significant effect on the variables studied, except for the influence of the number of kids on the percentages of fat and protein, where the variation was very small. Goats with two offspring produced nearly 15% more milk, fat and protein per lactation compared to goats with simple kids. Kiddings occurring in summer–autumn resulted in average milk, fat and protein yields nearly 14, 19 and 23% higher when compared to winter–spring kiddings. Lactation curves were evaluated to determine the effects of the number of kids and season, using the linearized version of the model of Wood in random regression analyses. Peak Yield increased by about 0.3 kg per additional offspring at kidding, but persistence was higher in goats with single offspring. The kidding season significantly influenced the lactation curve shape. Hence summer-kidding goats were more productive, and peak occurred earlier, while a higher persistence was observed in goats kidding during autumn.

scholarly journals Comparison of different lactation curve models in Holstein cows raised on a farm in the south-eastern Anatolia region

2008 ◽  
Vol 51 (4) ◽  
pp. 329-337
Author(s):  
Ö. Koçak ◽  
B. Ekiz
Keyword(s):  
Milk Yield ◽  
Goodness Of Fit ◽  
Mean Squared Error ◽  
Exponential Model ◽  
Eastern Anatolia ◽  
Mean Squared Errors ◽  
Squared Error ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

Abstract. The objective of this study was to compare the goodness of fit of seven mathematical models (including the gamma function, the exponential model, the mixed log model, the inverse quadratic polynomial model and their various modifications) on daily milk yield records. The criteria used to compare models were mean R2, root mean squared errors (RMSE) and difference between actual and predicted lactation milk yields. The effect of lactation number on curve parameters was significant for models with three parameters. Third lactation cows had the highest intercept post-calving, greatest incline between calving and peak milk yield and greatest decline between peak milk yield and end of lactation. Latest peak production occurred in first lactation for all models, while third lactation cows had the earliest day of peak production. The R2 values ranged between 0.590 and 0.650 for first lactation, between 0.703 and 0.773 for second lactation and between 0.686 and 0.824 for third lactation, depending on the model fitted. The root mean squared error values of different models varied between 1.748 kg and 2.556 kg for first parity cows, between 2.133 kg and 3.284 kg for second parity cows and between 2.342 kg and 7.898 kg for third parity cows. Lactation milk yield deviations of Ali and Schaeffer, Wilmink and Guo and Swalve Models were close to zero for all lactations. Ali and Schaeffer Model had the highest R2 for all lactations and also yielded smallest RMSE and actual and predicted lactation milk yield differences. Wilmink and Guo and Swalve Models gave better fit than other three parameter models.

scholarly journals On designing the average lactation curve at the ascending phase

1962 ◽  
Vol 34 (1) ◽  
pp. 162-168
Author(s):  
Aarne Mäkelä
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Lactation Period ◽  
Lactation Curve ◽  
The Mean ◽  
The Individual ◽  
Daily Milk Yield ◽  
Daily Milk

Comparisons are made between different methods to find the peak production (maximum daily milk yield) and methods to design the average lactation curve at the ascending phase in dairy cows. It was noted that in order to determine the height and location of the maximal producing capacity of a cow in a known lactation period, it is preferable to choose the peak production as a mean of three subsequent best days. It was also noted that the usual methods for drawing the average lactation curves do not give a true picture of the height and location of the peak. The author suggests a method for determining the average lactation curve at the ascending phase by using the averages of both milk productions and times involved in reaching the peak and known fractions (e.g. 1/8, 1/4, 1/2, 3/4, and 5/4) of it. In this lactation curve the peak production is the mean of the peaks of individual cows, and the time involved in reaching it is the mean of the durations of the ascending phases of the individual cows.

scholarly journals Test-day or 305-day milk yield for genetic evaluation of Gir cattle

2019 ◽  
Vol 54 ◽  
Author(s):  
Rodrigo Junqueira Pereira ◽  
Denise Rocha Ayres ◽  
Mário Luiz Santana Junior ◽  
Lenira El Faro ◽  
Aníbal Eugênio Vercesi Filho ◽  
...  
Keyword(s):  
Regression Model ◽  
Milk Yield ◽  
Genetic Evaluation ◽  
Random Regression ◽  
Breeding Values ◽  
Random Regression Model ◽  
The Mean ◽  
Yield Record ◽  
Genetic Evaluations ◽  
Dairy Breed

Abstract: The objective of this work was to compare genetic evaluations of milk yield in the Gir breed, in terms of breeding values and their accuracy, using a random regression model applied to test-day records or the traditional model (TM) applied to estimates of 305-day milk yield, as well as to predict genetic trends for parameters of interest. A total of 10,576 first lactations, corresponding to 81,135 test-day (TD) records, were used. Rank correlations between the breeding values (EBVs) predicted with the two models were 0.96. The percentage of animals selected in common was 67 or 82%, respectively, when 1 or 5% of bulls were chosen, according to EBVs from random regression model (RRM) or TM genetic evaluations. Average gains in accuracy of 2.7, 3.0, and 2.6% were observed for all animals, cows with yield record, and bulls (sires of cows with yield record), respectively, when the RRM was used. The mean annual genetic gain for 305-day milk yield was 56 kg after 1993. However, lower increases in the average EBVs were observed for the second regression coefficient, related to persistency. The RRM applied to TD records is efficient for the genetic evaluation of milk yield in the Gir dairy breed.

Influence of dry period length on reproductive performance and productivity of Lacaune dairy sheep under an intensive management system

2012 ◽  
Vol 79 (3) ◽  
pp. 352-360 ◽  
Author(s):  
Fernando Hernandez ◽  
Laura Elvira ◽  
Juan-Vicente Gonzalez-Martin ◽  
Susana Astiz
Keyword(s):  
Milk Yield ◽  
Global Analysis ◽  
Dairy Farm ◽  
Period Length ◽  
Intensive Management ◽  
Dairy Sheep ◽  
Dry Period ◽  
Key Factor ◽  
Daily Milk Yield ◽  
Daily Milk

Intensive management is almost the only way to ensure dairy farm profitability. The dry period length (DPL) is a key factor in the productivity and health of dairy cows, but whether the same is true of dairy sheep is unclear. This study investigated the effects of DPL on the performance of Lacaune sheep under intensive management. We recorded 8136 lactations from 4220 ewes on one farm for the period 2005–2010, and data from a total of 6762 complete lactations 1–4 were included in the study. The length of the dry period following the current lactation was studied. The larger the total milk yield (MY) and daily milk yield (DMY), the shorter was the DPL before the next lactation. DPL correlated with MY (r=−0·384), DMY (r=−0·277) and the lambing-to-conception interval (LC; r=0·201, P<0·0001) in the global analysis of all lactations (lactations 1–4). The influence of previous-DPL (P-DPL), or the length of the period prior to the start of the next lactation, was studied for 4318 lactations. P-DPL was classified into five intervals: very short (P-DPL-XS), 1–30 d; short (P-DPL-S), 31–60 d; medium (P-DPL-M), 61–90 d; long (P-DPL-L), 91–120 d; and very long (P-DPL-XL), >120 d. P-DPL positively correlated with lambing-to-next conception interval (LNC; r=0·095, P<0·0001) for lactations 1–4. LNC was significantly shorter for P-DPLs that were very short, short, or long (P-PDL-XS, 144·2±67·8 d; P-PDL-S, 149·1±57·2 d; P-PDL-L, 152·0±53·7 d) than for groups with very long or medium P-PDLs (P-DPL-XL, 161·5±62·9 d; P-DPL-M, 169·0±74·8 d; P<0·0001). Moreover, P-DPLs that were very short, long, or very long were associated with the lowest milk yields (P-PDL-XS, 377±215 l; P-PDL-l, 370±168 l; P-PDL-XL, 396±196 l). These yields were significantly lower than the yields for short and medium P-DPLs (P-DPL-S, 432±187 l; P-DPL-M, 436±191 l; P<0·0001) when averages of lactations 1–4 were analysed. These results indicate that lactations with larger MY are followed by a shorter dry period, and that a dry period of 30–90 d leads to larger yields in the next lactation. The best LNC was associated with the shortest Previous-DPL. Hence, 30–60 d should be the optimal dry period length for Lacaune sheep under intensive conditions.

scholarly journals Effect of β-lactoglobulin gene polymorphism, lactation stage and breed on milk traits in Chios and Karagouniko sheep breeds

2017 ◽  
Vol 17 (2) ◽  
pp. 371-384 ◽  
Author(s):  
Kostas A. Triantaphyllopoulos ◽  
Panagiota Koutsouli ◽  
Athanassios Kandris ◽  
Dimitris Papachristou ◽  
Kalliopi E. Markopoulou ◽  
...  
Keyword(s):  
Milk Yield ◽  
Milk Traits ◽  
Weinberg Equilibrium ◽  
Sheep Breeds ◽  
Lactation Stage ◽  
Pcr Rflp ◽  
Hardy Weinberg Equilibrium ◽  
Daily Milk Yield ◽  
Β Lactoglobulin ◽  
Daily Milk

Abstract The animal selection with favourable phenotypes of the past has been, currently, replaced by the genotype selection on quantitative traits, assisted by the expanding molecular techniques in the context of livestock improvement. In this study, the c.112T>C polymorphism in exon II of β-lactoglobulin (β-LG) gene was investigated in Karagouniko and Chios sheep breeds by using polymerase chain reaction - restriction fragment length polymorphism (PCR-RFLP), and possible associations with milk traits were examined. In total, 125 blood DNA samples were isolated for PCR-RFLP analysis and the respective 217 milk samples′ composition profile was obtained. The goodness of fit test to Hardy-Weinberg equilibrium (HWE) for β-LG genotypes was estimated and associations found between β-LG genotypes and raw milk composition. Two alleles and three genotypes were observed (AA, AB and BB) in both breeds, and Chios breed significantly deviated (P≤0.05) from Hardy-Weinberg equilibrium (HWE). Conclusively, linear mixed model analysis on samples, from both breeds collectively, showed significant effects of β-LG genotype on lactose percentage and somatic cell count (SCC), lactation stage on daily milk yield and protein, while the breed effect was significant only on daily milk yield.

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