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Inferring genetic parameters on latent variables underlying milk yield and quality, protein composition, curd firmness and cheese-making traits in dairy cattle

机译:推断牛奶产量和质量,蛋白质组成,乳品牛的蛋白质组成,豆腐和奶酪制作性状的潜在变量的遗传参数

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We studied the genetics of cheese-related latent variables (factors; Fs) for application in dairy cattle breeding. In total, 26 traits, recorded in 1264 Brown Swiss cows, were analyzed through multivariate factor analysis (MFA). Traits analyzed were descriptors of milk quality and yield (including protein fractions) and measures of coagulation, curd firmness (CF), cheese yields (%CY) and nutrient recoveries in the curd (REC). A total of 10 Fs (mutual orthogonal with a varimax rotation) were obtained. To assess the practical use of the Fs into breeding, we inferred their genetic parameters using single and bivariate animal models under a Bayesian framework. Heritability estimates (intra-herd) varied between 0.11 and 0.72 (F3: Yield and F7: κ-β-CN, respectively). The Fs underlined basic characteristics of the cheese-making process, milk components and udder health, while retaining 74% of the original variability. The first two Fs were indicators of the CY percentage (F1: %CY) and the CF process (F2: CF t ), and presented similar heritability estimates: 0.268 and 0.295, respectively. The third factor was associated with the yield of milk and solids (F3: Yield) characterized by a low heritability (0.108) and the fourth with the cheese nitrogen (N) (F4: Cheese N) that conversely appeared to be characterized by a high heritability (0.618). Three Fs were associated with the proportion of the basic milk caseins on total milk protein (F5: as1-β-CN, F7: κ-β-CN, F8: as2-CN), also highly heritable (0.565, 0.723 and 0.397, respectively) and 1 factor with the phosphorylated form of the as1-CN (F9: as1-CN-Ph; 0.318). Moreover, 1 factor was linked to the whey protein α-LA (F10: α-LA; 0.147). An indicator factor of a cow’s udder health (F6: Udder health) was also obtained and showed a moderate heritability (0.204). Although the Fs were phenotypically uncorrelated, considerable additive genetic correlations existed among them, with highest values observed between F10: α-LA and F6: Udder health (?0.67) as well as between F9: as1-CN-Ph and F3: Yield (?0.60). Our results show the usefulness of MFA in dairy cattle breeding. The ability to replace a large number of variables with a few latent indicators of the same biological meaning marks MFA as a valuable tool for developing breeding strategies to improve cow’s cheese-related traits.
机译:我们研究了奶酪相关潜在变量的遗传(因素; FS),用于奶牛养殖中的应用。通过多变量因子分析(MFA)分析了总共26个以1264棕色瑞士奶牛中记录的特征。分析的性状是乳质和产量(包括蛋白质分数)的描述符和凝固,凝乳固体(CF),奶酪产量(%CY)和凝乳(REC)中的营养回收率。获得总共10 fs(相互正交与varimax旋转)。为了评估FS进入育种的实际用途,我们在贝叶斯框架下使用单一和双变量动物模型推断出遗传参数。遗传性估计(群体内)在0.11和0.72(F3:产量和F7:κ-β-CN)之间变化。 FS强调奶酪制造过程,牛奶成分和乳房健康的基本特征,同时保留了74%的原始变异性。前两个FS是Cy百分比(F1:%Cy)和CF过程(F2:CF T)的指示剂,并分别呈现类似的可遗传性估算:0.268和0.295。第三因素与牛奶的产率和固体(F3:产率)相关,其特征在于低遗传性(0.108)和第四个与奶酪氮(n)(f4:奶酪n)相反似乎以高度为特征遗传性(0.618)。三个FS与总牛奶蛋白的基本乳酪蛋白的比例相关(F5:As1-β-CN,F7:κ-β-CN,F8:As2-CN),也是高度遗传的(0.565,0.723和0.397,分别为AS1-CN的磷酸化形式的1因素(F9:As1-CN-pH; 0.318)。此外,1因素与乳清蛋白α-La(F10:α-La; 0.147)连接。还获得了牛乳头健康(F6:乳液健康)的指示因素,并显示了中等的遗传性(0.204)。虽然FS是表型不相关的,但它们中存在相当大的添加遗传相关性,但在F10:α-La和F6之间观察到的最高值:乳液健康(β0.67)以及F9:As1-CN-pH和F3:产量( ?0.60)。我们的结果显示了MFA在奶牛养殖中的有用性。能够用不同的生物学意义的一些潜在的指标替换大量变量,标志着MFA作为开发育种策略以改善牛奶酪相关性状的有价值的工具。

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