FTIR光谱法测定稻米品质

Wilda Prihasty, A. Nasution, Isnaeni
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引用次数: 3

摘要

印度尼西亚是世界第三大大米生产国,拥有种类繁多、质量优良的大米。根据SNI 6128:2015,大米质量可以根据米粒的形状、颜色和水分含量进行分类。另一方面,食用大米是为了满足身体的营养需求。所以,重要的是要知道哪种大米能提供最好的营养成分。本文报道了利用傅里叶红外光谱技术测定直链淀粉酚类和类黄酮含量来预测大米品质的初步研究。化学分析方法对该预测系统进行了验证。用偏最小二乘法(PLS)测定大米中直链淀粉、酚类和类黄酮的含量,并用主成分分析(PCA)方法聚类大米的类型和质量。结果表明,所建立的直链淀粉含量、酚类和黄酮含量预测体系的确定系数为0.95;0.86;分别为0.95,RMSE值分别为1.4;0.72;0.44. 使用这种技术,所使用的大米样品可以分为三类,即优质大米,优质大米和中等质量大米。
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Rice Grain Quality Determination Using FTIR Spectroscopy Method
Indonesia is the third world's largest rice producer, which has wide variety of types and qualities of rice. Based on SNI 6128:2015, rice quality can be classified based on the form, colour and moisture content of the rice grain. On the other hand, rice is consumed to fulfill the nutritional needs of the body. So, it is important to know the type of rice which provide best nutrient content. In this paper, we report preliminary research to predictively determine the quality of rice based on amylose phenolic and flavonoid content measured using FTIR Spectroscopy technique. Chemical analysis method was used as a validation to this developed predictive system. Partial Least Square (PLS) were used to determine the levels of amylose, phenolic, and flavonoids of rice and the Principal Component Analysis (PCA) methods for clustering the types and quality of rices. Results showed that the coefficient of determination of the proposed prediction system of amylose content, phenolic and flavonoids were 0.95; 0.86; 0.95, respectively, with respective RMSE value were 1.4; 0.72; 0.44. Using this technique, rice samples used can be classified into three class of quality, i.e, high quality, premium quality, and the medium quality rice.
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