Expansion of Projected Lactation Yield to Stabilize Genetic Variance

VanRaden, P.M.; Wiggans, G.R.; Ernst, Christian

doi:10.3168/jds.s0022-0302(91)78630-x

Cited by 27 publications

(9 citation statements)

References 7 publications

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“…The deviation of an individual from the population mean at one or two early ages can be used to estimate its performance at any later age or set of ages by the standard methods of part-whole correlation (see, e.g. Falconer, 1989;VanRaden et al 1991). Given the economic incentives, the relatively small amount of additional computation required by the infinite-dimensional method seems a small price to pay.…”

Section: Discussionmentioning

confidence: 99%

Estimating the covariance structure of traits during growth and ageing, illustrated with lactation in dairy cattle

1994

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Quantitative variation in traits that change with age is important to both evolutionary biologists and breeders. We present three new methods for estimating the phenotypic and additive genetic covariance functions of a trait that changes with age, and illustrate them using data on daily lactation records from British Holstein-Friesian dairy cattle. First, a new technique is developed to fit a continuous covariance function to a covariance matrix. Secondly, this technique is used to estimate and correct for a bias that inflates estimates of phenotypic variances. Thirdly, we offer a numerical method for estimating the eigenvalues and eigenfunctions of covariance functions. Although the algorithms are moderately complex, they have been implemented in a software package that is made freely available.Analysis of lactation shows the advantages of the new methods over earlier ones. Results suggest that phenotypic variances are inflated by as much as 39 % above the underlying covariance structure by measurement error and short term environmental effects. Analysis of additive genetic variation indicates that about 90 % of the additive genetic variation for lactation during the first 10 months is associated with an eigenfunction that corresponds to increased (or decreased) production at all ages. Genetic tradeoffs between early and late milk yield are seen in the second eigenfunction, but it accounts for less than 8 % of the additive variance. This illustrates that selection is expected to increase production throughout lactation.

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Section: Discussionmentioning

confidence: 99%

Estimating the covariance structure of traits during growth and ageing, illustrated with lactation in dairy cattle

1994

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“…This is analogous to the deregression step in multiple-trait across-country evaluations. The expanded persistency contains the corresponding true value plus an independent error (VanRaden et al, 1991):…”

Section: Derivationmentioning

confidence: 99%

Genetic Evaluation and Best Prediction of Lactation Persistency

Cole

VanRaden

2006

Journal of Dairy Science

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Cows with high persistency tend to produce less milk than expected at the beginning of lactation and more than expected at the end. Best prediction of persistency was calculated as a function of a trait-specific standard lactation curve and a linear regression of test-day deviations on days in milk. Regression coefficients were deviations from a balance point to make yield and persistency phenotypically uncorrelated. The objectives of this study were to calculate (co)variance components and breeding values for best predictions of persistency of milk (PM), fat (PF), protein (PP), and SCS (PSCS) in Holstein cows. Data included 8,682,138 lactations from 4,375,938 cows calving since 1997, and 39,354 sires were evaluated. Sire estimated breeding values (EBV) for PM, PF, and PP were similar and ranged from -0.70 to 0.75 for PM; EBV for PSCS ranged from -0.37 to 0.28. Regressions of sire EBV on birth year were near zero (<0.003) but positive for PM, PF, and PP, and negative for PSCS. Genetic correlations of PM, PF, and PP with PSCS were moderate and favorable, indicating that increasing SCS decreases yield traits, as expected. Genetic correlations among yield and persistency were low to moderate and ranged from -0.09 (PSCS) to 0.18 (PF). This definition of persistency may be more useful than those used in test-day models, which are often correlated with yield. Routine genetic evaluations for persistency are feasible and may allow for improved predictions of yield traits. As calving intervals increase, persistency may have greater value.

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“…Second, VanRaden and Klaaskate (1993) proposed estimating life expectancy of live cows and including these records in a linear model analysis. Estimates based on incomplete data are regressed toward the mean, and therefore have lower heritability and variance than do complete records (VanRaden et al, 1991;Settar and Weller, 1999). In the method first proposed by Weller (1988), incomplete records are multiplied by a factor to bring all records to an equal genetic variance.…”

Section: Introductionmentioning

confidence: 99%

Environmental and genetic factors affecting cow survival of Israeli Holsteins

Weller

Ezra

2015

Journal of Dairy Science

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The objectives were to investigate the effects of various environmental factors that may affect herd-life of Israeli Holsteins, including first-calving age and season, calving ease, number of progeny born, and service sire for first calving in complete and truncated records; and to estimate heritabilities and genetic correlations between herd-life and the other traits included in the Israeli breeding index. The basic data set consisted of 590,869 cows in milk recording herds with first freshening day between 1985 and at least 8 yr before the cut-off date of September 15, 2013. Herd-life was measured as days from first calving to culling. The phenotypic and genetic trends for herd-life were 5.7 and 16.8d/yr. The genetic trend was almost linear, whereas the phenotypic trend showed 4 peaks and 3 valleys. Cows born in February and March had the shortest herd-life, whereas cows born in September had the longest herd-life. Herd-life was maximal with calving age of 23mo, which is 1mo less than the mean calving age, and minimal at 19 and 31mo of calving age. Dystocia and twinning on first-parity calving reduced herd-life by approximately180 and 120d, but the interaction effect increased herd-life by 140d. Heritability for herd-life was 0.14. Despite the fact that the service sire effect was significant in the fixed model analysis, service sire effect accounted for <0.05% of the total variance. In the analysis of 1,431,938 truncated records, the effects of dystocia and twinning rate were very similar but less than 50% of the effects found in the analysis of complete records. Pregnancy at the truncation date increased expected herd-life by 432d. The correlation between actual herd-life and predicted herd-life based on truncated records was 0.44. Genetic correlations between the truncated records and actual herd-life were 0.75 for records truncated after 6mo but approached unity for records truncated after 3 yr. The genetic correlations of herd-life with first-parity milk, fat, and protein production, somatic cell score (SCS), and female fertility were all positive, except for SCS, in which negative values are economically favorable. The highest correlations with herd-life in absolute value were with female fertility and SCS.

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Expansion of Projected Lactation Yield to Stabilize Genetic Variance

Cited by 27 publications

References 7 publications

Estimating the covariance structure of traits during growth and ageing, illustrated with lactation in dairy cattle

Estimating the covariance structure of traits during growth and ageing, illustrated with lactation in dairy cattle

Genetic Evaluation and Best Prediction of Lactation Persistency

Environmental and genetic factors affecting cow survival of Israeli Holsteins

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