McDermott A, De Marchi M, Berry D P, Visentin G, Fenelon M A, Lopez-Villalobos N, McParland S
Teagasc Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork, Ireland; Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Universita 16, 35020 Legnaro (PD), Italy.
Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Universita 16, 35020 Legnaro (PD), Italy.
J Dairy Sci. 2017 Aug;100(8):6272-6284. doi: 10.3168/jds.2016-12410. Epub 2017 Jun 16.
The objective of the present study was to identify the factors associated with both the protein composition and free amino acid (FAA) composition of bovine milk predicted using mid-infrared spectroscopy. Milk samples were available from 7 research herds and 69 commercial herds. The spectral data from the research herds comprised 94,286 separate morning and evening milk samples; the spectral data from the commercial herds comprised 40,260 milk samples representing a composite sample of both the morning and evening milkings. Mid-infrared spectroscopy prediction models developed in a previous study were applied to all spectra. Factors associated with the predicted protein and FAA composition were quantified using linear mixed models. Factors considered in the model included the fixed effects of calendar month of the test, milking time (i.e., morning, evening, or both combined), parity (1, 2, 3, 4, 5, and ≥6), stage of lactation, the interaction between parity and stage of lactation, breed proportion of the cow (Friesian, Jersey, Norwegian Red, Montbéliarde, and other), and both the general heterosis and recombination coefficients of the cow. Contemporary group as well as both within- and across-lactation permanent environmental effects were included in all models as random effects. Total proteins (i.e., total casein, CN; total whey; and total β-lactoglobulin) and protein fractions (with the exception of α-lactalbumin) decreased postcalving until 36 to 65 days in milk and increased thereafter. After adjusting the statistical model for differences in crude protein content and milk yield separately, irrespective of stage of lactation, younger animals produced more total proteins (i.e., total CN, total whey, and total β-lactoglobulin) as well as more total FAA, Glu, and Asp than their older contemporaries. The concentration of all protein fractions (except β-CN) in milk was greatest in the evening milk, even after adjusting for differences in the crude protein content of the milk. Relative to a purebred Holstein cow, Jersey cows, on average, produced a greater concentration of all CN fractions but less total FAA, Glu, Gly, Asp, and Val in milk. Relative to their respective purebred parental average, first-cross cows produced more total CN and more β-CN. Results from the present study indicate that many cow-level factors, as well as other factors, are associated with protein composition and FAA composition of bovine milk.
本研究的目的是确定与利用中红外光谱预测的牛乳蛋白质组成和游离氨基酸（FAA）组成相关的因素。牛奶样本来自7个研究牛群和69个商业牛群。研究牛群的光谱数据包括94286个单独的早晚牛奶样本；商业牛群的光谱数据包括40260个牛奶样本，代表早晚挤奶的混合样本。在先前研究中开发的中红外光谱预测模型应用于所有光谱。使用线性混合模型对与预测的蛋白质和FAA组成相关的因素进行量化。模型中考虑的因素包括测试的日历月份的固定效应、挤奶时间（即早上、晚上或两者合并）、胎次（1、2、3、4、5和≥6）、泌乳阶段、胎次与泌乳阶段的相互作用、奶牛的品种比例（弗里生牛、泽西牛、挪威红牛蒙贝利亚尔牛和其他），以及奶牛的一般杂种优势和重组系数。所有模型均将当代组以及泌乳期内和泌乳期间的永久环境效应作为随机效应纳入。总蛋白质（即总酪蛋白、CN；总乳清蛋白；和总β-乳球蛋白）和蛋白质组分（α-乳白蛋白除外）在产犊后至产奶36至65天期间下降，此后增加。在分别对粗蛋白含量和产奶量的差异调整统计模型后，无论泌乳阶段如何，年轻动物比年龄较大的同代动物产生更多的总蛋白质（即总CN、总乳清蛋白和总β-乳球蛋白）以及更多的总FAA、Glu和Asp。即使在对牛奶粗蛋白含量的差异进行调整后，牛奶中所有蛋白质组分（β-CN除外）的浓度在晚奶中最高。相对于纯种荷斯坦奶牛，泽西奶牛平均在牛奶中产生的所有CN组分浓度更高，但总FAA、Glu、Gly、Asp和Val含量更低。相对于各自纯种亲本的平均值，第一代杂交奶牛产生更多的总CN和更多的β-CN。本研究结果表明，许多奶牛水平的因素以及其他因素与牛乳的蛋白质组成和FAA组成相关。
