花生籽仁蛋白质含量近红外光谱模型的建立

Establishment of Model of Seeds Protein Content in Peanut Using Near Infrared Spectroscopy

采用近红外漫反射光谱非破坏性分析,结合偏最小二乘法,以河北省地方花生品种为研究对象建立了花生籽仁蛋白质含量的近红外光谱模型。结果表明,对原始光谱数据采用"一阶导数+变量标准化"处理的方法建立的模型其校正或预测效果最佳。该模型的校正集和验证集决定系数分别为0.9245和0.9018,校正标准误和预测标准误分别为0.3601和0.4153。用该模型对16个未参与建模的花生品种进行了预测,结果表明该模型具有很好的预测能力,可以用于花生品种蛋白质含量的快速检测。

Near-infrared reflectance spectroscopy （NIRS） model of seeds protein content of peanut landraces in Hebei Province,which was developed by means of partial least-squares （PLS） regression.The results showed that the model developed by the spectral data pretreatment of the first derivative ＋ standard normalized variety was the best one.The determination coefficients （R2） of calibration and validation sets were 0.9245 and 0.9018,the standard error of calibration and prediction were 0.3601 and 0.4153,respectively.This model was used to predict the protein content of 16 peanut varieties,and it had a high ability of prediction,which showed that it was feasible to be used in determination of seeds protein content of peanut varieties.