化学计量学
柚皮素
偏最小二乘回归
化学
近红外光谱
决定系数
数学
色谱法
统计
类黄酮
生物
生物化学
抗氧化剂
神经科学
作者
Xiangting She,Jing Huang,Xiaoqing Cao,Mingjiang Wu,Yue Yang
出处
期刊:Foods
[Multidisciplinary Digital Publishing Institute]
日期:2024-04-15
卷期号:13 (8): 1199-1199
被引量:10
标识
DOI:10.3390/foods13081199
摘要
Dendrobium officinale has drawn increasing attention as a dual-use plant with herbal medicine and food applications. The efficient quality evaluation of D. officinale is essential to ensuring its nutritional and pharmaceutical value. Given that traditional analytical methods are generally time-consuming, expensive, and laborious, this study developed a rapid and efficient approach to assess the quality of D. officinale from different geographical origins by near-infrared (NIR) spectroscopy and chemometrics. Total saponins, mannitol, and naringenin were utilized as quality indicators. Two wavelength selection methods, namely, uninformative variable elimination and competitive adaptive reweighted sampling (CARS), were utilized to enhance the prediction accuracy of the quantification model. Moreover, multiple spectral pretreatment methods were applied for model optimization. Results indicated that the partial least squares (PLS) model constructed based on the wavelengths selected by CARS exhibited superior performance in predicting the contents of the quality indicators. The coefficient of determination (RP2) and root mean square error (RMSEP) in the independent test sets were 0.8949 and 0.1250 g kg−1 for total saponins, 0.9664 and 0.2192 g kg−1 for mannitol, and 0.8570 and 0.003159 g kg−1 for naringenin, respectively. This study revealed that NIR spectroscopy and the CARS-PLS model could be used as a rapid and accurate technique to evaluate the quality of D. officinale.
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