Nondestructive Detection for Soluble Solids Content of Kiwifruits Based on Principal Component Regression

MENG Qing-long; SHANG Jing; HUANG Ren-shuai; YANG Xin; ZHANG Yan

doi:10.19554/j.cnki.1001-3563.2021.03.003

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Packaging Engineering ›› 2021 ›› Issue (3) : 19-24. DOI: 10.19554/j.cnki.1001-3563.2021.03.003

Nondestructive Detection for Soluble Solids Content of Kiwifruits Based on Principal Component Regression

MENG Qing-long, SHANG Jing, HUANG Ren-shuai, YANG Xin, ZHANG Yan

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Abstract

The work aims to conduct rapid nondestructive detection on soluble solids content of kiwifruits. Reflecting spectra acquisition system was used to collect reflectance spectra of Guichang kiwifruits in different maturity stages. The influences of standard normal variation, multi-scatter calibration and second derivative on the regression prediction model were compared. And the principal component analysis was used to reduce data dimension from preprocessing reflectance spectra. And a regression model was established based on selected characteristic variables for predicting soluble solids content of kiwifruits. The results showed that the first 16 principal components were selected as the characteristic variables by principal component analysis from 1024 full wavelengths. The regression model based on selected characteristic variables had a relatively good prediction ability (R2P=0.88, RPD=2.94). Therefore, it can accurately predict SSC of kiwifruits based on UV/Visible spectroscopy and principal component regression.

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MENG Qing-long, SHANG Jing, HUANG Ren-shuai, YANG Xin, ZHANG Yan. Nondestructive Detection for Soluble Solids Content of Kiwifruits Based on Principal Component Regression[J]. Packaging Engineering. 2021(3): 19-24 https://doi.org/10.19554/j.cnki.1001-3563.2021.03.003