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Visible/Near-Infrared Spectra for Linear and Nonlinear Calibrations: A Case to Predict Soluble Solids Contents and pH Value in Peach

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Abstract

Two sensitive wavelength (SWs) selection methods combined with visible/near-infrared (Vis/NIR) spectroscopy were investigated to determine the soluble solids content (SSC) and pH value in peaches, including latent variables analysis (LVA) and independent component analysis (ICA). A total of 100 samples were prepared for the calibration (n = 70) and prediction (n = 30) sets. Calibration models using SWs selected by LVA and ICA were developed, including linear regression of partial least squares (PLS) analysis and nonlinear regression of least squares-support vector machine (LS-SVM). In the nonlinear models, four SWs selected by ICA achieved the optimal ICA-LS-SVM model compared with LV-LS-SVM and both of them better than linear model of PLS. The correlation coefficients (r p and r cv), root mean square error of cross validation, root mean square error of prediction, and bias by ICA-LS-SVM were 0.9537, 0.9485, 0.4231, 0.4155, and 0.0167 for SSC and 0.9638, 0.9657, 0.0472, 0.0497, and −0.0082 for pH value, respectively. The overall results indicated that ICA was a powerful way for the selection of SWs, and Vis/NIR spectroscopy incorporated to ICA-LS-SVM was successful for the accurate determination of SSC and pH value in peach.

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Acknowledgments

This study was supported by National Science and Technology Support Program (2006BAD10A04), Natural Science Foundation of China (project no. 30671213), Natural Science Foundation of Zhejiang (project no. Y307158), and Science and Technology Department of Ningbo (project no. 2008C10037).

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  1. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310029, China

    Yongni Shao, Yidan Bao & Yong He

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  1. Yongni Shao
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  2. Yidan Bao
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  3. Yong He
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Correspondence to Yidan Bao or Yong He.

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Shao, Y., Bao, Y. & He, Y. Visible/Near-Infrared Spectra for Linear and Nonlinear Calibrations: A Case to Predict Soluble Solids Contents and pH Value in Peach. Food Bioprocess Technol 4, 1376–1383 (2011). https://doi.org/10.1007/s11947-009-0227-6

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