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Evaluation of Quality Parameters of Apple Juices Using Near-Infrared Spectroscopy and Chemometrics

机译:使用近红外光谱和化学计量学评估苹果汁的质量参数

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Near-infrared (NIR) spectra were recorded for commercial apple juices. Analysis of these spectra using partial least squares (PLS) regression revealed quantitative relations between the spectra and quality- and taste-related properties of juices soluble solids content (SSC), titratable acidity (TA), and the ratio of soluble solids content to titratable acidity (SSC/TA). Various spectral preprocessing methods were used for model optimization. The optimal spectral variables were chosen using the jack-knife-based method and different variants of the interval PLS (iPLS) method. The models were cross-validated and evaluated based on the determination coefficients (R2), root-mean-square error of cross-validation (RMSECV), and relative error (RE). The best model for the prediction of SSC (R2 = 0.881, RMSECV = 0.277 °Brix, and RE = 2.37%) was obtained for the first-derivative preprocessed spectra and jack-knife variable selection. The optimal model for TA (R2 = 0.761, RMSECV = 0.239 g/L, and RE = 4.55%) was obtained for smoothed spectra in the range of 6224–5350 cm−1. The best model for the SSC/TA (R2 = 0.843, RMSECV = 0.113, and RE = 5.04%) was obtained for the spectra without preprocessing in the range of 6224–5350 cm−1. The present results show the potential of the NIR spectroscopy for screening the important quality parameters of apple juices.
机译:记录了商用苹果汁的近红外(NIR)光谱。使用偏最小二乘(PLS)回归分析这些光谱,揭示了光谱与果汁可溶性固形物含量(SSC),可滴定酸度(TA)和可溶性固形物含量与可滴定度之比之间的定量关系酸度(SSC / TA)。各种光谱预处理方法用于模型优化。使用基于千斤顶刀的方法和间隔PLS(iPLS)方法的不同变体来选择最佳光谱变量。根据确定系数(R2),交叉验证的均方根误差(RMSECV)和相对误差(RE)对模型进行交叉验证和评估。对于一阶导数预处理光谱和千斤顶刀变量选择,获得了预测SSC的最佳模型(R2 = 0.881,RMSECV = 0.277°Brix,RE = 2.37%)。对于6224-5350 cm-1范围内的平滑光谱,获得了TA的最佳模型(R2 = 0.761,RMSECV = 0.239 g / L,RE = 4.55%)。对于未经预处理在6224-5350 cm-1范围内的光谱,获得了SSC / TA的最佳模型(R2 = 0.843,RMSECV = 0.113,RE = 5.04%)。目前的结果表明,近红外光谱技术可用于筛选苹果汁的重要质量参数。

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