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Rapid Determination of Total Dietary Fiber and Minerals in Coix Seed by Near-Infrared Spectroscopy Technology Based on Variable Selection Methods

机译:基于可变选择方法的近红外光谱技术快速测定Co仁中总膳食纤维和矿物质

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摘要

The feasibility of near-infrared (NIR) spectroscopy for determining total dietary fiber (TDF) and mineral elements (mainly K, Mg, P, and S) in Coix seed was investigated. Partial least squares regression (PLSR) was applied to establish quantitative models. Norris derivative smoothing (NDS) was used as pretreatment method. A comparison of three variable selection methods, namely competitive adaptive reweighted sampling (CARS), genetic algorithms (GA), and random frog (RF), showed that CARS obtained the best performances of PLSR models with the effective wavelengths mainly concentrated on around 12,000–11,000 cm−1 and 6500–3600 cm−1. For the quantitative determination models of TDF, K, Mg, P, and S, the optimal root mean square error of prediction (RMSEP) values were 0.0923, 182.7224, 75.4987, 162.6993, and 36.6278; the r values were 0.95, 0.88, 0.80, 0.96, and 0.96; the residual predictive deviation (RPD) values were 2.68, 2.05, 1.70, 3.24, and 3.04, respectively. It is concluded that the NIR spectral technique has a potential to determine TDF, K, Mg, P, and S in Coix seed.
机译:研究了用近红外(NIR)光谱法测定ix种子中的总膳食纤维(TDF)和矿物质(主要是K,Mg,P和S)的可行性。应用偏最小二乘回归(PLSR)建立定量模型。使用Norris导数平滑(NDS)作为预处理方法。比较三种变量选择方法,即竞争性自适应加权抽样(CARS),遗传算法(GA)和随机青蛙(RF),发现CARS获得了PLSR模型的最佳性能,其有效波长主要集中在大约12,000– 11,000 cm-1和6500–3600 cm-1。对于TDF,K,Mg,P和S的定量测定模型,预测的最佳均方根误差(RMSEP)值为0.0923、182.7224、75.4987、162.6993和36.6278。 r值为0.95、0.88、0.80、0.96和0.96;剩余预测偏差(RPD)值分别为2.68、2.05、1.70、3.24和3.04。结论是,NIR光谱技术具有测定ix种子中TDF,K,Mg,P和S的潜力。

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