Cecchinato A, Albera A, Cipolat-Gotet C, Ferragina A, Bittante G
Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy.
Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy.
J Dairy Sci. 2015 Jul;98(7):4914-27. doi: 10.3168/jds.2014-8599. Epub 2015 May 7.
Cheese yield is the most important technological parameter in the dairy industry in many countries. The aim of this study was to infer (co)variance components for cheese yields (CY) and nutrient recoveries in curd (REC) predicted using Fourier-transform infrared (FTIR) spectroscopy of samples collected during milk recording on Holstein, Brown Swiss, and Simmental dairy cows. A total of 311,354 FTIR spectra representing the test-day records of 29,208 dairy cows (Holstein, Brown Swiss, and Simmental) from 654 herds, collected over a 3-yr period, were available for the study. The traits of interest for each cow consisted of 3 cheese yield traits (%CY: fresh curd, curd total solids, and curd water as a percent of the weight of the processed milk), 4 curd nutrient recovery traits (REC: fat, protein, total solids, and the energy of the curd as a percent of the same nutrient in the processed milk), and 3 daily cheese production traits (daily fresh curd, total solids, and the water of the curd per cow). Calibration equations (freely available upon request to the corresponding author) were used to predict individual test-day observations for these traits. The (co)variance components were estimated for the CY, REC, milk production, and milk composition traits via a set of 4-trait analyses within each breed. All analyses were performed using REML and linear animal models. The heritabilities of the %CY were always higher for Holstein and Brown Swiss cows (0.22 to 0.33) compared with Simmental cows (0.14 to 0.18). In general, the fresh cheese yield (%CYCURD) showed genetic variation and heritability estimates that were slightly higher than those of its components, %CYSOLIDS and %CYWATER. The parameter RECPROTEIN was the most heritable trait in all the 3 breeds, with values ranging from 0.32 to 0.41. Our estimation of the genetic relationships of the CY and REC with milk production and composition revealed that the current selection strategies used in dairy cattle are expected to exert only limited effects on the REC traits. Instead, breeders may be able to exploit genetic variations in the %CY, particularly RECFAT and RECPROTEIN. This last component is not explained by the milk protein content, suggesting that its direct selection could be beneficial for cheese production aptitude. Collectively, our findings indicate that breeding strategies aimed at enhancing CY and REC could be easily and rapidly implemented for dairy cattle populations in which FTIR spectra are routinely acquired from individual milk samples.
在许多国家，奶酪产量是乳制品行业中最重要的技术参数。本研究的目的是推断使用傅里叶变换红外光谱（FTIR）对荷斯坦、瑞士褐牛和西门塔尔奶牛进行牛奶记录期间采集的样本预测的奶酪产量（CY）和凝乳中养分回收率（REC）的（协）方差分量。本研究共有311354条FTIR光谱，代表了654个牛群中29208头奶牛（荷斯坦、瑞士褐牛和西门塔尔）的测定日记录，这些记录是在3年期间收集的。每头奶牛的目标性状包括3个奶酪产量性状（%CY：新鲜凝乳、凝乳总固体和凝乳水分占加工牛奶重量的百分比）、4个凝乳养分回收性状（REC：脂肪、蛋白质、总固体以及凝乳能量占加工牛奶中相同养分的百分比）和3个每日奶酪生产性状（每头奶牛的每日新鲜凝乳、总固体和凝乳水分）。校准方程（可向通讯作者索取）用于预测这些性状的个体测定日观测值。通过对每个品种进行一组4性状分析，估计CY、REC、牛奶产量和牛奶成分性状的（协）方差分量。所有分析均使用REML和线性动物模型进行。与西门塔尔奶牛（0.14至0.18）相比，荷斯坦和瑞士褐牛奶牛的%CY遗传力始终较高（0.22至0.33）。一般来说，新鲜奶酪产量（%CYCURD）的遗传变异和遗传力估计值略高于其组成部分%CYSOLIDS和%CYWATER。参数RECPROTEIN是所有3个品种中遗传力最高的性状，值范围为0.32至0.41。我们对CY和REC与牛奶产量和成分的遗传关系估计表明，目前奶牛使用的选择策略预计对REC性状的影响有限。相反，育种者可能能够利用%CY中的遗传变异，特别是RECFAT和RECPROTEIN。最后一个成分不能用牛奶蛋白质含量来解释，这表明直接选择它可能有利于奶酪生产能力。总体而言，我们的研究结果表明，对于常规从个体牛奶样本中获取FTIR光谱的奶牛群体，旨在提高CY 和REC的育种策略可以轻松快速地实施。
