Chu Chu, Li Weiqi, Wen Peipei, Wang Dongwei, Ren Xiaoli, Li Chunfang, Zhang Ning, Xu Gang, Liu Li, Li Yongqing, Fan Yikai, Wang Kun, Hu Bo, Zheng Wenxin, Xu Xuewen, Zhang Shujun
Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Ministry of Education, Wuhan 430070, China; Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China.
Ningxia Hui Autonomous Region Animal Husbandry Workstation, Yinchuan 750000, China.
J Dairy Sci. 2025 Sep;108(9):9113-9128. doi: 10.3168/jds.2024-25903. Epub 2025 May 30.
Mid-infrared spectroscopy (MIRS) is increasingly used as a rapid and effective analytical method for the quantitative prediction of detailed milk composition, such as minerals, fatty acids, and AA. These analyses require the transportation of samples to a certified laboratory. In this case, storage time may affect MIRS and its prediction results. This study aimed to determine the effect of milk storage time on MIRS and its predictions of AA content. A total of 373 individual milk samples for the development of AA content prediction equations were collected from 7 commercial dairy farms (dataset 1), and 103 individual milk samples for the analysis of the effect of storage time were collected from 2 farms (dataset 2). First, separate quantitative prediction models based on dataset 1 were developed for each AA using partial least squares regression; the accuracy of prediction was assessed using a cross-validation set. Second, repeatability and reproducibility of the predictions of AA were calculated using milk samples in dataset 2, whose spectra were measured once a day for 7 consecutive days after sampling storing at 4°C, to assess the effect of storage time on the consistency of MIRS predicted AA content. Moderate to high prediction accuracy of AA was achieved, with the ratio of performance to deviation of the cross-validation set and the R of the cross-validation set being in the range of 1.59 (Gly) to 2.39 (Leu), and from 0.58 (Gly) to 0.79 (Leu), respectively. Results demonstrated that the absorbance of spectral points was affected by milk storage time, especially in the absorption areas associated with fat, protein, lactose, SCC, urea, and acetone. However, the predictions of all the AA by MIRS were repeatable and reproducible across different milk storage times until 6 d after sampling, except for Tyr, His, and Phe, with repeatability and reproducibility both greater than or close to 90%. In conclusion, for milk stored at 4°C and preserved with bronopol, MIRS can provide relatively consistent and accurate predictions for AA content for 0 to 6 d after milk collection. However, a shorter storage time, such as within 3 d after collection, is recommended when conditions permit.
中红外光谱法（MIRS）越来越多地被用作一种快速有效的分析方法，用于定量预测详细的牛奶成分，如矿物质、脂肪酸和氨基酸。这些分析需要将样品运送到经过认证的实验室。在这种情况下，储存时间可能会影响MIRS及其预测结果。本研究旨在确定牛奶储存时间对MIRS及其对氨基酸含量预测的影响。从7个商业奶牛场收集了373份用于建立氨基酸含量预测方程的个体牛奶样本（数据集1），并从2个农场收集了103份用于分析储存时间影响的个体牛奶样本（数据集2）。首先，使用偏最小二乘回归为每个氨基酸基于数据集1建立单独的定量预测模型；使用交叉验证集评估预测准确性。其次，使用数据集2中的牛奶样本计算氨基酸预测的重复性和再现性，这些样本在4°C储存取样后连续7天每天测量一次光谱，以评估储存时间对MIRS预测氨基酸含量一致性的影响。实现了对氨基酸的中等到高的预测准确性，交叉验证集的性能与偏差比和交叉验证集的R分别在1.59（甘氨酸）至2.39（亮氨酸）以及0.58（甘氨酸）至0.79（亮氨酸）的范围内。结果表明，光谱点的吸光度受牛奶储存时间的影响，特别是在与脂肪、蛋白质、乳糖、体细胞数、尿素和丙酮相关的吸收区域。然而，除了酪氨酸、组氨酸和苯丙氨酸外，MIRS对所有氨基酸的预测在不同的牛奶储存时间直至取样后6天都是可重复和可再现的，重复性和再现性均大于或接近90%。总之，对于在4°C储存并用布罗波尔保存的牛奶，MIRS可以在牛奶采集后0至6天为氨基酸含量提供相对一致和准确的预测。然而，在条件允许时，建议储存时间更短，例如在采集后3天内。
