A selection index for dairy cows

Hill, William G.; Swanson, G. J. T.

doi:10.1017/s0003356100001914

Cited by 14 publications

(6 citation statements)

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“…It therefore seems appropriate when data are scaled relative to herd mean in the cow genetic index (CGI) calculations in Britain (MMB, 1982;Hill and Swanson, 1983), equivalent to using log transformations of yield, that these ratios should be further scaled to constant CV. Further, when selection indices are constructed assuming homogeneity of variance, showed that, on average, rather too much weight was given to yield in high CV herds compared to low CV herds.…”

Section: Resultsmentioning

confidence: 99%

“…If 10 kg of the index is attributed to the sire and dam plus herd base, and 25 kg is an individual deviation, then the adjustment will give the cow an index of +30 kg and remove it from the top 0 002 proportion to the top 0-007 of the range existing in 1982 (Hill and Swanson, 1983). This scaling can be undertaken simply in the cow index or other calculation.…”

Section: Resultsmentioning

confidence: 99%

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Heterogeneity of variance amongst herds for milk production

Brotherstone

Hill

1986

Anim. Sci.

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Estimates were obtained of the variability among herds of dairy cattle of the standard deviation (s.d.) and coefficient of variation (CV) of milk, fat and protein yield. For fat yield, for example, the mean s.d. within herds for heifers was about 30 kg, the s.d. among herds was 5-2 kg and the mean and s.d. of CV were 0-15 and 0-026, respectively. Correlations of both s.d. and CV were high between both heifers and cows in the same herd and year and between heifers or cows in the same herd in successive years, showing that variability was consistent over time and over age groups.Ways of correcting for the heterogeneity of variance for use in cow index calculations are suggested; because CVs are heterogeneous, simple log transformation is not sufficient.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Heterogeneity of variance amongst herds for milk production

Brotherstone

Hill

1986

Anim. Sci.

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“…Typically, EBVs for cows were calculated using selection index methods. For instance, cow genetic indices (CGIs), based on up to five lactations and including a herd genetic level to allow comparisons across herds, were introduced in the UK in 1981 (Hill & Swanson 1983). The CGI was a selection index that included the genetic merit of the sire, the CGI of the dam and the cow's own milk records.…”

Section: (B) Best Linear Unbiased Predictormentioning

confidence: 99%

Artificial selection and maintenance of genetic variance in the global dairy cow population

Brotherstone

Goddard

2005

Phil. Trans. R. Soc. B

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Genetic improvement of dairy cows, which has increased the milk yield of cows in the UK by 1200 kg per lactation in 12 years, is an excellent example of the application of quantitative genetics to agriculture. The most important traits of dairy cattle are expressed only in females, but the main opportunity for selection is in males. Despite this, genetic improvement was achieved by the invention of a new statistical methodology, called 'best linear unbiased prediction' to estimate the breeding value of bulls. Intense selection of the best bulls, combined with the worldwide use of these bulls through artificial insemination and frozen semen, has created a global population and caused concern that the genetic variation available in the future will be reduced. Maintenance of genetic variation and long-term genetic gains would be aided by rational payment systems, use of crossbreeding where profitable, inclusion of all economically important traits in the breeding objective, recognition of genotype by environment interactions and the use of selection algorithms that balance estimated breeding value against the average relationship among the selected animals. Fortunately, all of these things are happening to some degree.

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“…Dairy cattle sire evaluation in many countries is carried out using best linear unbiased prediction (BLUP) (Interbull, 1988), while cows are usually evaluated separately using a selection index type approach (eg Hill and Swanson, 1983).…”

Section: Introductionmentioning

confidence: 99%

Univariate and multivariate parameter estimates for milk production traits using an animal model. I. Description and results of REML analyses

Visscher¹,

Thompson²

1992

Genet. Sel. Evol.

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REML) selon le modèle animal. Le nombre des données pour chaque lactation a été de 38 811, 26 223 et 16 542 pour les lactations 1, 2 et 3 respectivement. Les héritabilités des 3 critères de production ont été similaires: approximativement 0,36 en première lactation et 0,30 en seconde et troisième lactation. Les corrélations génétiques entre les caractères de production en lactations 1 et 2, par exemple la production laitière, ont été approximativement de 0,86. Les corrélations génétiques entre critères de production aux lactations 2 et 3 ont été pratiquement égaux à 1.

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A selection index for dairy cows

Cited by 14 publications

References 10 publications

Heterogeneity of variance amongst herds for milk production

Heterogeneity of variance amongst herds for milk production

Artificial selection and maintenance of genetic variance in the global dairy cow population

Univariate and multivariate parameter estimates for milk production traits using an animal model. I. Description and results of REML analyses

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