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首页> 外文期刊>Current topics in nutraceutical research >DETERMINATION OF STARCH ADULTERATION IN GANODERMA LUCIDUM POLYSACCHARIDE BY NEAR INFRARED REFLECTANCE SPECTROSCOPY WITH PARTIAL LEAST SQUARES ALGORITHM
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DETERMINATION OF STARCH ADULTERATION IN GANODERMA LUCIDUM POLYSACCHARIDE BY NEAR INFRARED REFLECTANCE SPECTROSCOPY WITH PARTIAL LEAST SQUARES ALGORITHM

机译:偏最小二乘近红外光谱法测定灵芝多糖中淀粉的淀粉糊化。

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摘要

This paper reports the feasibility of determining the adulterated starch levels in Ganoderma lucidum polysaccharide using near infrared reflectance (NIR) spectroscopy coupled with multivariate methods. Multivariate calibration modeling procedures such as partial least squares (PLS), interval partial least squares, backward interval partial least squares, and forward interval partial least squares were applied to select the effective spectral regions that provided the lowest prediction error. According to the sum of squared differences and the root mean square error of prediction by the external validation, the optimal combinations of 8 spectral intervals were selected by forward interval partial least squares model. The optimal model was achieved with determination coefficient of 0.9962 and root mean square error of cross validation of 0.0252 in calibration set, and determination coefficient of 0.9957 and root mean square error of prediction of 0.0258 in validation set. The results indicated that NIR spectroscopy with forward interval partial least squares algorithm could be applied to determine the adulterated levels of starches in Ganoderma lucidum polysaccharide.
机译:本文报道了使用近红外反射(NIR)光谱结合多元方法确定灵芝多糖中掺假淀粉水平的可行性。应用多元校准建模程序(例如,偏最小二乘(PLS),间隔偏最小二乘,后向间隔偏最小二乘和正向间隔偏最小二乘)来选择提供最低预测误差的有效光谱区域。根据外部验证的平方差和和预测的均方根误差,通过前向间隔偏最小二乘模型选择了8个光谱区间的最佳组合。在校正集中,确定系数为0.9962,交叉验证的均方根误差为0.0252,确定模型的最佳模型为:验证组确定系数为0.9957,预测的均方根误差为0.0258。结果表明,采用前向间隔偏最小二乘算法的近红外光谱法可用于测定灵芝多糖中淀粉的掺假水平。

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