2 results
Lactation curves of Sarda breed goats estimated with test day models
- Nicolò PP Macciotta, Pancrazio Fresi, Graziano Usai, Aldo Cappio-Borlino
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- Journal:
- Journal of Dairy Research / Volume 72 / Issue 4 / November 2005
- Published online by Cambridge University Press:
- 22 September 2005, pp. 470-475
- Print publication:
- November 2005
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Test day records of milk yield (38765), fat and protein contents (11357) of Sarda goats (the most numerous Italian goat breed) were analysed with mixed linear models in order to estimate the effects of test date (month and year of kidding for fat and protein contents) parity, number of kids born, altitude of location of flocks (<200 m asl, 200–500 m asl, >500 m asl), flocks within altitude and lactation stage (eight days-in-milk intervals of 30 d each) on milk production. All factors considered in the models affected milk traits significantly. Milk yield was lower in first parity goats than in higher parities whereas fat and protein contents showed an opposite trend. Goats with two kids at parturition had a higher milk yield than goats with one kid and tended to have lower fat and protein percentages. Repeatability between test days within lactation was 0·34, 0·17 and 0·45 for milk yield, fat content and protein content, respectively. Lactation curves of goats farmed at different altitudes were clearly separated, especially for milk yield. Results of the present study highlight differences in milk production traits among the three subpopulations that have been previously identified within the Sarda breed on the basis of the morphological structure of animals and altitude of location of flocks.
Effect of β-lactoglobulin polymorphism on milk-related traits of dairy ewes analysed by a repeated measures design
- PIETRO GIACCONE, LILIANA DI STASIO, NICOLÒ P. P. MACCIOTTA, BALDASSARRE PORTOLANO, MASSIMO TODARO, ALDO CAPPIO-BORLINO
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- Journal:
- Journal of Dairy Research / Volume 67 / Issue 3 / August 2000
- Published online by Cambridge University Press:
- 19 October 2000, pp. 443-448
- Print publication:
- August 2000
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Among specific genes that may affect economically important traits in sheep, the β-lactoglobulin (LGB) locus has been extensively studied. Polymorphism has been detected in several breeds, but studies of the effect of LGB alleles on milk production traits have given conflicting results. Some found that LGB polymorphism significantly affects milk yield (Bolla et al. 1989; Herget et al. 1995; Fraghì et al. 1996), fat and protein content (Garzon & Martínez 1992; Giaccone et al. 1997; Kukovics et al. 1998), only fat content (Pirisi et al. 1998) and cheese yield and composition (Di Stasio et al. 1997; Rampilli et al. 1997). However, other studies failed to detect any effect of the gene on milk production traits (Barillet et al. 1993; Recio et al. 1997). These inconsistencies, similar to those reported for dairy cattle, can be explained by breed differences, population size, frequency distribution of the genetic variants and a failure to consider relationships among animals (Sabour et al. 1996).
Moreover, both the production data considered and the methods used for statistical analysis could be further causes of conflicting results (Ng-Kwai-Hang, 1997). Investigations of the relationships between milk protein polymorphism and milk production usually consider accumulated yields for standardized lactation lengths, assuming that environmental effects average out over a lactation. Such an assumption is not always valid, because there can be marked effects peculiar to individual test day (TD) measures that may not average out (Jamrozik & Schaeffer, 1997). The direct modelling of TD measures offers the advantage of a more accurate removal of environmental variation from phenotypic observations (Stanton et al. 1992). However, particular attention to the temporal dependence of the covariance structure among TD is required. In TD analysis performed by mixed linear models a simple covariance structure, known as compound symmetry, is usually assumed. This structure assumes an equal variance for all TD and an equal correlation between all pairs of TD within each lactation. An initial drawback of this assumption arises because of the heterogeneity of variance throughout lactation. Moreover, since TD values within a lactation are a sequence of repeated measures taken on the same experimental unit (Van der Werf & Schaeffer, 1997), measures close in time are likely to be more highly correlated than measures far apart in time. All these potential patterns of correlation and variation may combine to produce a complicated structure of covariance among TD that, when ignored, may result in inadequate analysis or incorrect conclusions (Littel et al. 1998). In particular, there can be marked differences in the estimates of the fixed factors considered in the analysis; such a bias is enhanced when the data structure is highly unbalanced, as in the case of studies on relationships between milk protein polymorphisms and milk production traits.
A possible solution can be found in the property of mixed linear models to assume different (co)variance structures in order to find the one that best fits experimental data. The aim of the present study was to test the possible influence of the statistical model used on the results when the relationships between β-lactoglobulin polymorphism and milk production traits in dairy ewes were analysed. With this aim in view, TD measures were directly modelled with mixed linear models and the effects of alternative (co)variance structures on fixed factors estimates were compared.