ESTIMATION OF VARIANCE COMPONENTS RELATED TO MILK YIELD OF JERSEY CATTLE BY DIFFERENT METHODS

Abstract. Milk production in Thailand has been growing into an important agricultural sector, but it still faces numerous difficulties in environmental constraints. The main intention of this study was to identify significant environmental effects on production and fertility traits to give advices for farm management. Additionally, adjusting records for environmental impact is essential to define appropriate models for estimation of variance components and improving selection procedures. The data consists of production and reproduction records and body measurements from 2764 Holstein upgrade cows in 252 farms. With a body weight of 415 kg and a production level of 3668 kg milk Thai Holsteins only reach approximately 60 % of performances of Holsteins in temperate zones. Percentages of Holstein genes of cows and quality of roughage sources showed a certain effect on calving interval and services per conception but not on milk performances. Despite seasonal effects were not very pronounced on milk yield, there was a strong interaction between years and calving seasons. Estimates of variance components applying REML and animal models were in the range as expected, i.e. heritabilities for production traits between 0.34 and 0.37, for fertility lower than 0.03 and for body weight 0.46. Genetic correlations between fertility and production traits were near zero. Economic weights for milk yield and calving interval were derived as first derivation of profit functions and used for selection index calculations. Suc

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Estimation of variance components in normal linear mixed models with additivity

10.1063/1.4912414 ◽

2015 ◽

Cited By ~ 1

Author(s):

Dário Ferreira ◽

Sandra S. Ferreira ◽

Célia Nunes ◽

João T. Mexia

Keyword(s):

Mixed Models ◽

Variance Components ◽

Linear Mixed Models ◽

Estimation Of Variance

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On invariant quadratic unbiased estimation of variance components

Communication in Statistics- Theory and Methods ◽

10.1080/03610929108830593 ◽

1991 ◽

Vol 20 (5-6) ◽

pp. 1705-1730 ◽

Cited By ~ 2

Author(s):

J. Subramani

Keyword(s):

Variance Components ◽

Unbiased Estimation ◽

Estimation Of Variance

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A report on management practices and milk production from jersey cows raised in Ibadan

Journal of Agriculture Forestry and the Social Sciences ◽

10.4314/joafss.v11i2.10 ◽

2015 ◽

Vol 11 (2) ◽

pp. 98-104

Author(s):

OA Olorunnisomo ◽

AA Oni ◽

JO Abiola

Keyword(s):

Milk Production ◽

Milk Yield ◽

Management Practices ◽

Cooling System ◽

Zebu Cattle ◽

Tropical Condition ◽

Jersey Cattle ◽

Lactation Length ◽

The University ◽

University Of Ibadan

In order to kick-start milk production and upgrade genetic base of local zebu cattle at the University of Ibadan, four in-calf Jersey heifers and one bull were acquired in September 2012, from a pure herd of Jersey cattle maintained on a private farm in Shonga, Kwara State, Nigeria. Management at Shonga was based on an intensive, zero-grazing system. The animals were apparently in a good state of health at the time of procurement. At the University of Ibadan, management was also intensive, with partial grazing, fortified grass silage and concentrates supplementation. Health management of Jersey cattle involved preventive and curative measures. Calving occurred within 7 and 156 days of arrival at Ibadan. Two out of four heifers calved successfully while two had still-births. Calves were allowed to suckle their dams for 14 days after calving and bottle-fed from milk collected from their dams afterwards. Milking was done twice daily at 7am and 4pm using a portable milking machine. Milk yield averaged 8.8 kg/cow/day with lactation length ranging between 93 and 246 days. Average composition of milk was 13.69, 3.60, 4.73, 0.65 and 4.71% for total solids, protein, fat, ash and carbohydrate respectively. In order to maximize milk production from Jersey cattle under the humid tropical condition of Ibadan, there is need to maintain a high plane of nutrition, adopt a preventive healthcare system and incorporate a cooling system to ameliorate the effects of high ambient temperatures.Key words: calving age, dairy cattle, lactation length, milk composition, milk yield

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Analysis of litter size and days to lambing in the Ripollesa ewe. II. Estimation of variance components and response to phenotypic selection on litter size1

Journal of Animal Science ◽

10.2527/jas.2006-368 ◽

2007 ◽

Vol 85 (3) ◽

pp. 625-631 ◽

Cited By ~ 6

Author(s):

J. Casellas ◽

G. Caja ◽

A. Ferret ◽

J. Piedrafita

Keyword(s):

Litter Size ◽

Variance Components ◽

Phenotypic Selection ◽

Estimation Of Variance

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Improved Nonnegative Estimation of Variance Components in Balanced Multivariate Mixed Models

Journal of Multivariate Analysis ◽

10.1006/jmva.1994.1051 ◽

1994 ◽

Vol 51 (1) ◽

pp. 83-101 ◽

Cited By ~ 12

Author(s):

T. Mathew ◽

A. Niyogi ◽

B.K. Sinha

Keyword(s):

Mixed Models ◽

Variance Components ◽

Estimation Of Variance

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Estimation of variance components, genetic parameters and genetic trends for litter size of swines

Revista Brasileira de Zootecnia ◽

10.1590/s1516-35982010001000008 ◽

2010 ◽

Vol 39 (10) ◽

pp. 2155-2159 ◽

Cited By ~ 4

Author(s):

Leandro Barbosa ◽

Paulo Sávio Lopes ◽

Adair José Regazzi ◽

Robledo de Almeida Torres ◽

Mário Luiz Santana Júnior ◽

...

Keyword(s):

Litter Size ◽

Variance Components ◽

Genetic Parameters ◽

Random Effect ◽

Additive Model ◽

Fixed Effect ◽

Likelihood Method ◽

Phenotypic Variance ◽

Estimation Of Variance ◽

Genetic Trends

Records of Large White breed animals were used to estimate variance components, genetic parameters and trends for the character total number of born piglets (TNBP) as measure of litter size. For obtaining variance components and genetic parameters, it was used the Restricted Maximum Likelihood Method using MTDFREML software. Two mixed models (additive and repeatability) were evaluated. The additive model contained fixed effect of the contemporary group and the following random effects: direct additive genetic and residual effect for the first parturition. Repeatability model had the same effects of the additive model plus parturition order fixed effect and non-correlated animal permanent environment random effect for the second, third and forth parturition. Direct additive heritability estimates for TNBP were 0.15 and 0.20 for the additive and repeatability models, respectively. The estimate of the ration among variance of the non-correlated effect of animal permanent environment effect and the phenotypic variance, expressed as total variance proportion (c2) was 0.09. The estimates of yearly genetic trends obtained in the additive and repeatability models have similar behaviors (0.02 piglets/sow/year).

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Estimation of variance components of milk, fat, and protein yields of Tunisian Holstein dairy cattle using Bayesian and REML methods

Archives Animal Breeding ◽

10.5194/aab-59-243-2016 ◽

2016 ◽

Vol 59 (2) ◽

pp. 243-248 ◽

Cited By ~ 3

Author(s):

Hafedh Ben Zaabza ◽

Abderrahmen Ben Gara ◽

Hedi Hammami ◽

Mohamed Amine Ferchichi ◽

Boulbaba Rekik

Keyword(s):

Dairy Cattle ◽

Bayesian Methods ◽

Milk Fat ◽

Variance Components ◽

Genetic Parameters ◽

Genetic Correlations ◽

Bayesian Procedure ◽

Milk Traits ◽

Residual Variances ◽

Estimation Of Variance

Abstract. A multi-trait repeatability animal model under restricted maximum likelihood (REML) and Bayesian methods was used to estimate genetic parameters of milk, fat, and protein yields in Tunisian Holstein cows. The estimates of heritability for milk, fat, and protein yields from the REML procedure were 0.21 ± 0.05, 0.159 ± 0.04, and 0.158 ± 0.04, respectively. The corresponding results from the Bayesian procedure were 0.273 ± 0.02, 0.198 ± 0.01, and 0.187 ± 0.01. Heritability estimates tended to be larger via the Bayesian than those obtained by the REML method. Genetic and permanent environmental variances estimated by REML were smaller than those obtained by the Bayesian analysis. Inversely, REML estimates of the residual variances were larger than Bayesian estimates. Genetic and permanent correlation estimates were on the other hand comparable by both REML and Bayesian methods with permanent environmental being larger than genetic correlations. Results from this study confirm previous reports on genetic parameters for milk traits in Tunisian Holsteins and suggest that a multi-trait approach can be an alternative for implementing a routine genetic evaluation of the Tunisian dairy cattle population.

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Genetic Parameters for First Lactation and Lifetime Traits of Nili-Ravi Buffaloes

Frontiers in Veterinary Science ◽

10.3389/fvets.2021.557468 ◽

2021 ◽

Vol 8 ◽

Author(s):

Pooja Tamboli ◽

Anurag Bharadwaj ◽

Amit Chaurasiya ◽

Yogesh Chandrakant Bangar ◽

Andonissamy Jerome

Keyword(s):

Genetic Correlation ◽

Milk Yield ◽

Phenotypic Correlation ◽

Productive Life ◽

Lactation Length ◽

Service Period ◽

Reproduction Traits ◽

Genetic And Phenotypic Correlations ◽

Breeding Efficiency ◽

Estimation Of Variance

The data on first lactation and lifetime performance records of 501 Nili-Ravi were collected for a period from 1983 to 2017 (35 years) maintained at ICAR-Central Institute for Research on Buffaloes, Sub-Campus, Nabha, Punjab. The data were analyzed to calculate heritability, genetic and phenotypic correlation for first lactation traits, viz., Age at First Calving (AFC), First Lactation Total Milk Yield (FLTMY), First Lactation Standard (305 days or less) Milk Yield (FLSMY), First Peak Milk Yield (FPY), First Lactation Length (FLL), First Dry Period (FDP), First Service Period (FSP) and First Calving Interval (FCI), Herd Life (HL), Productive Life (PL), Productive Days (PD), Unproductive Days (UD), Breeding Efficiency (BE), Total Lifetime Milk Yield (Total LTMY), Standard Lifetime Milk Yield (Standard LTMY), Milk Yield Per Day of Productive Life (MY/PL), Milk Yield Per Day of Productive Days (MY/PD), and Milk Yield Per Day of Herd Life (MY/HL). For estimation of variance component and heritability separately for each trait, the uni-trait animal model was equipped, whereas to estimate genetic and phenotypic correlations between traits, bi-trait animal models were fitted. The estimates of heritability for production and reproduction traits of Nili-Ravi were medium, i.e., 0.365 ± 0.087, 0.353 ± 0.071, 0.318 ± 0.082, 0.354 ± 0.076, and 0.362 ± 0.086 for FLSMY, FDP, FSP, FCI, and AFC, respectively. The estimates of heritability were low, i.e., 0.062 ± 0.088, 0.123 ± 0.090, 0.158 ± 0.090, 0.155 ± 0.091, and 0.129 ± 0.091 for HL, PL, PD, Total LTMY, and Standard LTMY and high, i.e., 0.669 ± 0.096 for BE. Genetic correlation for FLTMY was high with FLL (0.710 ± 0.103), and genetic correlation of FLTMY was high and positive with HL, Total LTMY, MY/PL, and MY/PD while low and positive with PL. Genetic correlation of AFC was low and negative with PL, PD, UD, BE, Total LTMY, Standard LTMY, MY/PL, and MY/PD and negative with MY/HL. Significant positive phenotypic association of FPY was seen with FLTMY, FLSMY, FLL, AFC, HL, Total LTMY, and Standard LTMY. Higher heritability of first lactation traits especially FPY suggests sufficient additive genetic variability, which can be exploited under selection and breeding policy in order to improve overall performance of Nili-Ravi buffaloes.

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