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Application of Long-Wave Near Infrared Hyperspectral Imaging for Measurement of Soluble Solid Content (SSC) in Pear

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Abstract

Soluble solid content (SSC) in fruit is one of the most crucial internal quality factors, which could provide valuable information for commercial decision-making. Near-infrared (NIR) technique has effective potentials for determining the SSC since NIR was sensitive to the concentrations of organic materials. In this study, a novel NIR technique, long-wave near infrared (LWNIR) hyperspectral imaging with a spectral range of 930–2548 nm, was investigated for measuring the SSC in pear, which has never been examined in the past. A new combination of Monte Carlo-uninformative variable elimination (MC-UVE) and successive projections algorithm (SPA) was proposed to select most effective variables from LWNIR hyperspectral data. The selected variables were used as the inputs of partial least square (PLS) to build calibration models for determining the SSC of ‘Ya’ pear. The results indicated that calibration model built using MC-UVE-SPA-PLS on 18 effective variables achieved the optimal performance for prediction of SSC comparing with other developed PLS models (MC-UVE-PLS and SPA-PLS) by comprehensively considering the accuracy, robustness, and complexity of models. The correlation coefficients between the predicted and actual SSC were 0.88 and 0.88 and the root mean square errors were 0.49 and 0.35 °Brix for calibration and prediction set, respectively. The overall results indicated that long-wave near infrared hyperspectral imaging incorporated to MC-UVE-SPA-PLS model could be applied as an alternative, fast, accurate, and nondestructive method for the determination of SSC in pear.

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Authors and Affiliations

  1. Beijing Research Center of Intelligent Equipment for Agriculture, Beijing, 100097, China

    Jiangbo Li, Xi Tian, Wenqian Huang, Baohua Zhang & Shuxiang Fan

  2. National Research Center of Intelligent Equipment for Agriculture, Beijing, 100097, China

    Jiangbo Li, Xi Tian, Wenqian Huang, Baohua Zhang & Shuxiang Fan

  3. Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing, 100097, China

    Jiangbo Li & Wenqian Huang

  4. Beijing Key Laboratory of Intelligent Equipment Technology for Agriculture, Beijing, 100097, China

    Jiangbo Li & Wenqian Huang

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  1. Jiangbo Li
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  2. Xi Tian
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  3. Wenqian Huang
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Correspondence to Jiangbo Li.

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Funding

This work is financially supported by the National Key Technologies R&D Program (No. 2015BAD19B03-03), Young Scientist Funds of the National Natural Science Foundation of China (No. 31401283), and Young Scientist Fund of Beijing Academy of Agriculture and Forestry Sciences of China (No. QNJJ201528).

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Jiangbo Li declares that he has no conflict of interest. Xi Tian declares that he has no conflict of interest. Wenqian Huang declares that he has no conflict of interest. Baohua Zhang declares that he has no conflict of interest. Shuxiang Fan declares that he has no conflictof interest.

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Li, J., Tian, X., Huang, W. et al. Application of Long-Wave Near Infrared Hyperspectral Imaging for Measurement of Soluble Solid Content (SSC) in Pear. Food Anal. Methods 9, 3087–3098 (2016). https://doi.org/10.1007/s12161-016-0498-2

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