Prediction of soluble solids content of pineapple via non-invasive low cost visible and shortwave near infrared spectroscopy and artificial neural network
Prediction of soluble solids content of pineapple via non-invasive low cost visible and shortwave near infrared spectroscopy and artificial neural network
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DOI：
10.1016/j.biosystemseng.2012.07.003
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发表时间：
2012-10-01
影响因子：
5.1
通讯作者：
Rahim, Ruzairi Abdul
中科院分区：
文献类型：
--
作者：
Chia, Kim Seng;Rahim, Herlina Abdul;Rahim, Ruzairi Abdul
评价了低成本可见光和短波近红外（维斯-SWNIR）光谱仪与人工神经网络相结合在菠萝可溶性固形物含量非侵入性评估中的潜力。采集并独立处理了不同日期菠萝样品的四组数据（即可见-近红外光谱和可溶性固形物含量参考）。使用一阶导数结合一阶Savitzky-Golay平滑滤波器去除反射光谱中的基线偏移效应。通过应用稳健的主成分分析，减少了光谱数据的分散性。通过外部学生化残差方法识别潜在离群值。使用四个数据集之一训练人工神经网络，并使用其他三个数据集进行验证。由插值分析可知，前两个鲁棒主成分的人工神经网络的校正均方根误差（RMSEG）、校正相关系数（r（c））、预测均方根误差（RMSEP）和预测相关系数（r（p））分别为0.84 ° Brix、0.85、0.87 ° Brix和0.68。利用3个不同日期的数据集进行预测的结果表明，使用低成本的可见-短波近红外光谱仪是有前途的菠萝可溶性固形物含量的非侵入性评估。(C)2012年IAgRE。由爱思唯尔有限公司出版。保留所有权利。
The potential of a combination of a low cost visible and shortwave near infrared (VIS -SWNIR) spectrometer and an artificial neural network in the non-invasive soluble solids content assessment of pineapple was evaluated. Four data sets (i.e. VIS-SWNIR spectra and soluble solids content reference) of pineapple samples from different days were acquired and independently processed. Baseline shift effect in the reflectance spectra was removed using a first order derivative coupled with a first order Savitzky-Golay smoothing filter. The dispersion of the spectral data was reduced by applying robust principal component analysis. Potential outliers were identified via an externally studentised residual approach. An artificial neural network was trained using one of the four data sets and validated using the other three data sets. From interpolation analysis, the root mean square error of calibration (RMSEG), correlation coefficient of calibration (r(c)), root mean square error of prediction (RMSEP) and correlation coefficient of prediction (r(p)) of the artificial neural network with the first two robust principal components were 0.84 degrees Brix, 0.85, 0.87 degrees Brix and 0.68, respectively. The predicted results by using three data sets from different days suggest that the use of a low cost VIS-SWNIR spectrometer is promising for the non-invasive soluble solids content assessment of pineapple. (C) 2012 IAgrE. Published by Elsevier Ltd. All rights reserved.