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Genetic parameters of cheese yield and curd nutrient recovery or whey loss traits predicted using Fourier-transform infrared spectroscopy of samples collected during milk recording on Holstein, Brown Swiss, and Simmental dairy cows

机译:在荷斯坦,布朗·瑞士和西门塔尔奶牛的牛奶记录中,使用傅里叶变换红外光谱法对采集的样品进行奶酪产量和凝乳养分回收或乳清损失性状的遗传参数预测

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摘要

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 (%CY_(CURD)) showed genetic variation and heritability estimates that were slightly higher than those of its components, %CY_(SOLIDS) and %CY_(WATER). The parameter REC_(PROTEIN) 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 REC_(FAT) and REC_(PROTEIN). 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.
机译:奶酪产量是许多国家乳制品业最重要的技术参数。这项研究的目的是推断使用傅立叶变换红外(FTIR)光谱法对在Holstein,Brown Swiss和Red Hat牛奶记录期间收集的样品进行预测的奶酪产量(CY)和凝乳中营养成分回收(REC)的(共)方差成分。西门塔尔牛。总共311,354个FTIR光谱代表了在3年期间收集的来自654个牛群的29,208头奶牛(荷斯坦,布朗瑞士和西门塔尔牛)的测试日记录。每头母牛感兴趣的性状包括3个奶酪的产量性状(%CY:新鲜凝乳,凝乳总固体和凝乳水占加工乳重量的百分比)。 4种凝乳的养分恢复特性(REC:脂肪,蛋白质,总固体和凝乳的能量占加工乳中相同养分的百分比),以及3种每日奶酪生产性状(每日新鲜凝乳,总固体和每头牛的凝乳水)。校准方程式(根据要求可免费提供给通讯作者)用于预测这些特征的各个测试日观察结果。通过每个品种内的一组4-性状分析,估计了CY,REC,产奶量和乳成分性状的(共)方差成分。所有分析均使用REML和线性动物模型进行。与西门塔尔牛(0.14至0.18)相比,荷斯坦奶牛和布朗瑞士奶牛的%CY遗传力始终较高(0.22至0.33)。通常,新鲜奶酪的产量(%CY_(CURD))显示出遗传变异和遗传力估计值略高于其组成成分%CY_(SOLIDS)和%CY_(WATER)。参数REC_(PROTEIN)是所有3个品种中最可遗传的性状,其值范围为0.32至0.41。我们对CY和REC与奶产量和组成的遗传关系的估计表明,目前用于奶牛的选择策略有望对REC性状产生有限的影响。相反,育种者可能能够利用%CY中的遗传变异,尤其是REC_(FAT)和REC_(PROTEIN)。牛奶蛋白质含量不能解释这最后一个成分,这表明直接选择它可能有利于奶酪生产。总体而言,我们的研究结果表明,针对常规从单个乳样品中获取FTIR光谱的奶牛种群,可以轻松快速地实施旨在提高CY和REC的育种策略。

著录项

  • 来源
    《Journal of dairy science》 |2015年第7期|4914-4927|共14页
  • 作者单位

    Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Universita 16, 35020 Legnaro, Italy;

    Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Universita 16, 35020 Legnaro, Italy;

    Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Universita 16, 35020 Legnaro, Italy;

    Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Universita 16, 35020 Legnaro, Italy;

    Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Universita 16, 35020 Legnaro, Italy;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    genetic parameter; mid-infrared spectroscopy; cheese yield; whey loss; dairy breed;

    机译:遗传参数中红外光谱奶酪产量乳清损失奶牛品种;
  • 入库时间 2022-08-17 23:23:40

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