Non-parametric analysis of the effects of αS1-casein genotype and parturition non-genetic factors on milk yield and composition in Murciano-Granadina goats

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 Non-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. Non-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.

即便已有研究报道相关性状符合参数假设，但有限的样本量仍可能导致参数假设被违背。此前的参数化研究表明，CSN1S1基因对穆尔西亚-格拉纳达山羊（Murciano-Granadina）的产奶量、乳脂、乳蛋白及乳干提取物无显著影响。本研究采用非参数分类检验法，旨在探寻替代统计方法，以分析其对该种群中产奶量及其相关组分表型变异的解释效力。我们共分析了710头经CSN1S1基因分型的穆尔西亚-格拉纳达山羊的2090条产奶量及其组分相关记录。本研究构建了分类回归方程，以预测哪些因素以及在何种水平下可对产奶量（千克）、乳脂量（千克）、乳蛋白量（千克）及乳干提取物量（千克）产生决定作用。所有环境因素（养殖场、分娩年份）及动物固有因素（基因型、出生类型、年龄）均具有统计学显著性（原文此处p值信息缺失）。若正态性与异方差性检验无法通过，则非参数检验方法必不可少。相较于经过高强度选育的国际品种，穆尔西亚-格拉纳达山羊的乳性状表现独具特点，其中E等位基因组合与BB基因型对乳成分及产奶量的影响最为显著。