Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy.
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy.
J Dairy Sci. 2021 Apr;104(4):3947-3955. doi: 10.3168/jds.2020-18712. Epub 2021 Jan 21.
Curd samples (n = 83) from 3 European dairy companies were analyzed for micellar and soluble mineral fractions content using inductively coupled plasma optical emission spectrometry as a gold standard method. The same curd samples were analyzed through 3 different near-infrared (NIR) instruments, and NIR spectra were merged with reference data. Prediction equations were developed using modified partial least squares analysis, and the accuracy of prediction was evaluated through leave-one-out cross validation. Overall, NIR spectroscopy was capable of predicting micellar and soluble mineral fractions in curd, but with differences among instruments. Fitting statistics showed that the visible NIR instrument in reflectance mode outperformed the NIR instrument in transmittance mode as well as the portable NIR instrument in reflectance mode. Prediction accuracies for most of the analyzed mineral fractions can be used for curd quality control in dairy companies and to aid in decision-making during the cheesemaking process.
对 3 家欧洲乳制品公司的凝乳样本（n = 83）进行了分析，采用电感耦合等离子体光学发射光谱法作为金标准方法，对胶束和可溶性矿物质的含量进行分析。对相同的凝乳样本使用 3 种不同的近红外（NIR）仪器进行了分析，并将 NIR 光谱与参考数据进行了合并。使用改进的偏最小二乘分析建立了预测方程，并通过留一法交叉验证评估了预测的准确性。总的来说，近红外光谱能够预测凝乳中的胶束和可溶性矿物质，但不同仪器之间存在差异。拟合统计表明，反射模式的可见近红外仪器比透射模式的近红外仪器以及反射模式的便携式近红外仪器表现更好。对大多数分析的矿物质的预测精度可用于乳制品公司的凝乳质量控制，并在奶酪制作过程中辅助决策。
