基于近红外光谱技术的花生酸败特性检测研究

Fast and Nondestructive Testing of the Oxidative Rancidity Characteristics in Peanut by Near Infrared Reflectance Spectroscopy

酸价、过氧化值是衡量花生贮藏过程中氧化酸败的重要指标,基于近红外光谱分析技术,结合化学计量分析,利用偏最小二乘法建立花生酸价、过氧化值的近红外预测模型,并对平滑、导数、多元散射校正、归一化等多种预处理方法对建模准确性的影响进行比较。结果表明:对原始光谱数据采用一阶微分处理的方法建立的模型其预测效果最佳,酸价模型的主成分维数为10,决定系数为0.955,均方根误差为0.080;过氧化值模型的主成分维数10,决定系数为0.940,均方根误差为0.459。研究表明,近红外光谱分析技术可用于花生酸价、过氧化值的快速无损检测。

The acid value and peroxide value are key indicators of oxidative rancidity during peanut storage. Based on near - infrared spectroscopy technology and combined with stoiehiometrie analysis, partial least squares were used to establish a near - infrared prediction model of peanut aid value and peroxide value. And then the effects of modeling accuracy were compared according to multiple approaches of smoothing, differential coefficient, muhiplicative scatter correction and normalization etc. The results indicate that optimal prediction effects come to the model established through first -order differential approach upon original spectroscopic data;principle component dimensionality of acid value model is 10, determination coefficient is 0. 955, and root - mean - square error is 0. 080 ; principle component dimensionality of peroxide value model is 10, determination coefficient is 0.940, and root -mean -square error is 0.459. The research shows that NIR（ Near Infrared Spectrum）analysis technique can be applied in rapid and intact detection on acid value and peroxide value of peanuts.