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Prediction of Total Phenolics and Flavonoids Contents in Chinese Wild Rice (Zizania latifolia) Using FT-NIR Spectroscopy

机译:FT-NIR光谱预测中国野生稻(Zizania latifolia)中的总酚和类黄酮含量

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摘要

Total phenolics and flavonoids contents in Chinese wild rice were predicted using Near Infrared (NIK) spectroscopy as a rapid method. A Partial Least Square (PLS) algorithm was applied to perform the calibration. The models were calibrated by cross-validation and the chosen number of PLS factor was achieved according to the lowest Root Mean Square Error Cross-Validation (RMSECV) in calibration set. The correlation coefficient (R) and Root Mean Square of Error Prediction (RMSEP) in the test set were used as the evaluation parameters for the optimal model as follows: R = 0.985; RMSEP = 2.41 and the Residual Predictive Deviation (RPD) = 6.06 for total phenolics contents prediction by Multiplication Scatter Correction (MSC) model. For flavonoids contents prediction, R = 0.978, RMSEP = 1.23 and RPD = 4.81 by non preprocessing model. It could be concluded that NIR spectroscopy has significant potential in the nondestructive determination of total phenolics and flavonoids.
机译:使用近红外(NIK)光谱法可以快速预测中国野生稻中的总酚和类黄酮含量。应用了偏最小二乘(PLS)算法来执行校准。通过交叉验证对模型进行校正,并根据校正集中最低的均方根交叉验证(RMSECV)获得所选的PLS因子数。测试集中的相关系数(R)和误差均方根预测(RMSEP)被用作最佳模型的评估参数,如下所示:R = 0.985; RMSEP = 2.41,残留预测偏差(RPD)= 6.06,用于通过乘积散射校正(MSC)模型预测总酚含量。对于非类黄酮含量的预测,通过非预处理模型可以得出R = 0.978,RMSEP = 1.23和RPD = 4.81。可以得出结论,近红外光谱法在非破坏性测定总酚和类黄酮方面具有巨大潜力。

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