Department of Food Measurements and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary.
Department of Livestock Product and Food Preservation Technology, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary.
Molecules. 2024 Aug 23;29(17):3989. doi: 10.3390/molecules29173989.
Milk powders are becoming a major attraction for many industrial applications due to their nutritional and functional properties. Different types of powdered milk, each with their own distinct chemical compositions, can have different functionalities. Consequently, the development of rapid monitoring methods is becoming an urgent task to explore and expand their applicability. Lately, there is growing emphasis on the potential of near-infrared spectroscopy (NIRS) as a rapid technique for the quality assessment of dairy products. In the present work, we explored the potential of NIRS coupled with chemometrics for the prediction of the main functional and chemical properties of three types of milk powders, as well as their important processing parameters. Mare, camel and cow milk powders were prepared at different concentrations (5%, 10% and 12%) and temperatures (25 °C, 40 °C and 65 °C), and then their main physicochemical attributes and NIRS spectra were analyzed. Overall, high accuracy in both recognition and prediction based on type, concentration and temperature was achieved by NIRS-based models, and the quantification of quality attributes (pH, viscosity, dry matter content, fat content, conductivity and individual amino acid content) also resulted in high accuracy in the models. RCV and Rpr values ranging from 0.8 to 0.99 and 0.7 to 0.98, respectively, were obtained by using PLSR models. However, SVR models achieved higher RCV and Rpr values, ranging from 0.91 to 0.99 and 0.80 to 0.99, respectively.
奶粉因其营养和功能特性，成为许多工业应用的主要吸引力。不同类型的奶粉，其化学成分各不相同，具有不同的功能。因此，开发快速监测方法成为探索和扩大其适用性的紧迫任务。最近，人们越来越关注近红外光谱（NIRS）作为一种快速技术来评估乳制品质量的潜力。在本工作中，我们探讨了 NIRS 与化学计量学相结合，预测三种奶粉的主要功能和化学性质及其重要加工参数的潜力。分别在不同浓度（5%、10%和 12%）和温度（25°C、40°C 和 65°C）下制备马奶、驼奶和牛奶粉，然后分析其主要物理化学特性和 NIRS 光谱。总体而言，基于 NIRS 的模型在基于类型、浓度和温度的识别和预测方面均具有很高的准确性，并且对质量属性（pH 值、粘度、干物质含量、脂肪含量、电导率和个别氨基酸含量）的定量也导致了模型的高精度。使用 PLSR 模型获得的 RCV 和 Rpr 值范围分别为 0.8 至 0.99 和 0.7 至 0.98。然而，SVR 模型实现了更高的 RCV 和 Rpr 值，范围分别为 0.91 至 0.99 和 0.80 至 0.99。
