基于NIRS法快速检测荞麦蛋白质与淀粉含量的研究

为建立近红外光谱技术测定荞麦蛋白质与淀粉含量的方法,本研究以217份荞麦样品为试验材料,采用最小二乘回归预测和交叉验证构建近红外预测模型。分析表明:前处理采用多元散射校正法(MSC),维数(Rank)分别为5和5,光谱区间6803.9~6094.2/cm所建立的荞麦蛋白质与淀粉含量模型的预测效果较好,其决定系数(R~2)分别为0.9481和0.9167,交叉验证均方根(RMSECV)分别为0.68和2.08,相对分析误差(RPD)分别为4.39和3.46,均大于3.0,外部验证相关系数均大于0.96。本试验所建立的蛋白质与淀粉含量近红外预测模型具有较高的准确度和稳健性,可用于荞麦品质的快速测定。

Rapid determination of protein and starch in buckwheat by Near-Infrared Reflectance Spectroscopy

To establish a rapid determination method for the contents of protein and starch in buckwheat by applying Near-Infrared Reflectance Spectroscopy (NIRS), NIR spectra of 217 buckwheat samples were collected. Calibration models were established based on the spectra and chemical values by partial least-squares (PLS) algorithm with cross-validation. Analysis indicated that the models of protein and starch showed good prediction effect by using multiplicative scattering correction (MSC), with rank of 5 and 5, respectively, and frequency regions of 6803.9-6094.2 cm-1. The R2 of them were 0.9481 and 0.9167, RMSECV were 0.68 and 2.08, RPD were 4.39 and 3.46, respectively, with the coefficients in external validation greater than 0.96. This study has demonstrated the feasibility and reliability of using NIRS to rapidly determine the content of protein and starch in buckwheat.