Franzoi Marco, Niero Giovanni, Penasa Mauro, De Marchi Massimo
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy.
Animals (Basel). 2019 Jul 9;9(7):430. doi: 10.3390/ani9070430.
Milk and dairy products are major sources of minerals in human diet. Minerals influence milk technological properties; in particular, micellar and diffusible minerals differentially influence rennet clotting time, curd firmness and curd formation rate. The aim of the present study was to investigate the ability of mid-infrared spectroscopy to predict the content of micellar and diffusible mineral fractions in bovine milk. Spectra of reference milk samples (n = 93) were collected using Milkoscan™ 7 (Foss Electric A/S, Hillerød, Denmark) and total, diffusible and micellar content of minerals were quantified using inductively coupled plasma optical emission spectrometry. Backward interval partial least squares algorithm was applied to exclude uninformative spectral regions and build prediction models for total, diffusible and micellar minerals content. Results showed that backward interval partial least squares analysis improved the predictive ability of the models for the studied traits compared with traditional partial least squares approach. Overall, the predictive ability of mid-infrared prediction models was moderate to low, with a ratio of performance to deviation in cross-validation that ranged from 1.15 for micellar K to 2.73 for total P.
牛奶和乳制品是人类饮食中矿物质的主要来源。矿物质会影响牛奶的工艺特性；特别是，胶束态矿物质和可扩散矿物质对凝乳酶凝结时间、凝乳硬度和凝乳形成速率有不同的影响。本研究的目的是探讨中红外光谱法预测牛乳中胶束态和可扩散矿物质含量的能力。使用Milkoscan™ 7（丹麦希勒勒德Foss Electric A/S公司）收集参考牛奶样品（n = 93）的光谱，并使用电感耦合等离子体发射光谱法定量测定矿物质的总量、可扩散量和胶束态含量。采用反向间隔偏最小二乘算法排除无信息的光谱区域，并建立总矿物质、可扩散矿物质和胶束态矿物质含量的预测模型。结果表明，与传统偏最小二乘法相比，反向间隔偏最小二乘分析提高了模型对所研究性状的预测能力。总体而言，中红外预测模型的预测能力为中等至较低，交叉验证中的性能与偏差比范围从胶束态钾的1.15到总磷的2.73。
