大米胶稠度近红外光谱分析数学模型的建立

    Development of mathematical model for predicting rice gel consistency by near infrared spectroscopy

    • 摘要: 胶稠度是评价大米蒸煮食用品质的重要指标之一。研究了运用近红外光谱分析技术检测大米胶稠度的测试原理,对60个样品的光谱数据用偏最小二乘法(PLS)建立了测定大米胶稠度的数学模型,其回判结果与化学分析值之间的相关系数为0.95,建模标准差为0.66;用41个样品对建立的数学模型进行了交叉验证,其检测结果与用标准化学分析方法测得结果的相关系数达0.92,预测标准差为0.78。试验证明,可以利用近红外光谱分析技术对大米胶稠度进行快速检测。

       

      Abstract: Gel consistency(GC) is one of the most important cooking and eating characteristics of rice. The testing method of rice GC by near infrared spectroscopy (NIRS) was developed, and the prediction models of rice GC was set up based on the partial least squares(PLS) methods. Sixty spectrums of rice samples were calibrated for their GC values. It shows that the correlation coefficient between the PLS evaluation and chemical method is 0.95, and the standard error of calibration(SEC) is 0.66. To validate the calibration, an independent set of 41 rice samples of the same breed was used. The correlation coefficient is 0.92, and the standard error of validation is 0.78. The result shows that the infrared spectroscopy technique can be used to test the rice GC rapidly.

       

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