Abstract
Limited sample sizes imply parametric assumptions could be violated, even if traits have been reported to fulfil parametric assumptions. Parametric studies have addressed a non-significant influence of CSN1S1 genes on Murciano-Granadina milk yield, fat, protein and dry extract. We used non-parametric categorical tests to find alternative statistical methods to analyse the power to explain the variability found in the population regarding milk yield and its components. We analysed 2090 records for milk yield, and its components from 710 Murciano-Granadina CSN1S1-genotyped goats. Categorical regression equations were issued to predict which and at what level these factors may determine milk yield (kg), fat (kg), protein (kg) and dry extract (kg). All environmental (farm and parturition year) and animal-inherent factors (genotype, birth type and age) resulted statistically significant (p < .05) except for birth season and month. CSN1S1 genotype was highly statistically significant and explained from 8.3% to 9.2% of protein and fat content variability, resembling the values for highly selected French breeds. Seasonal peaks and lows resembled other breeds’. Heterozygote advantage of certain combinations of E allele with those alleles strongly or weakly influencing milk components and yield such as A, B, B2, F and homozygote BB genotype reported the highest statistically significant effects on milk components and yield. Our results suggest that non-parametric tests may report contextually valid results when having a large sample size is not possible. Selecting for certain CSN1S1 genotypes may promote the efficient production of better-quality milk in greater amounts, improving the international competitiveness and profitability of local breeds.HighlightsNon-parametric tests are crucial if normality and heteroskedasticity analyses fail.Murciano-Granadina milk traits compared with highly selected international breeds’.E allele combinations and BB reported highest effects on milk components and yield.
Highlights
Among non-genetic factors, those linked to environment strongly impact on the survival and productivity of dairy goats
Genetic factors account for a high proportion of the high variability between individuals, within and between breeds. Such property of internal and external heterogeneity of milk yield and composition is the basis for the improvement of milk traits in goats
This study aims to assess the influence of non-genetic factors, such as farm, parturition year, parturition month, birth season and birth type on the milk yield and milk components of Murciano-Granadina goats, isolating and overcoming the physiological response of the animals to be expected considering their aS1-casein genotype
Summary
Among non-genetic factors, those linked to environment strongly impact on the survival and productivity of dairy goats These factors affect productivity at a quantitative level and affect the composition and, the quality of goat milk-derived products (milk, cheese, among others) (Samson and Olajumoke 2017). Genetic factors account for a high proportion of the high variability between individuals, within and between breeds Such property of internal and external heterogeneity of milk yield and composition is the basis for the improvement of milk traits in goats. This improvement is carried out selecting the does and bucks accounting for the highest yields and producing the milk with the composition of the best quality (Samson and Olajumoke 2017). The importance of determining the exact impact that can be attributed to each group of factors separately
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