Food and Fermentation Industries >

2022 , Vol. 48 >Issue 12: 249 - 254

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.031112

The establishment and optimization of the model for predicting the sugar content of loquat by Vis/NIR spectroscopy

  • MENG Qinglong ,
  • FENG Shunan ,
  • SHANG Jing ,
  • HUANG Renshuai ,
  • ZHANG Yan ,
  • CAO Sen
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  • 1(Food and Pharmaceutical Engineering Institute, Guiyang University, Guiyang 550005, China)
    2(Research Center of Nondestructive Testing for Agricultural Products, Guiyang University, Guiyang 550005, China)

Received date: 2022-02-10

  Revised date: 2022-02-22

  Online published: 2022-07-15

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Abstract

The optimum model for rapidly nondestructive predicting the sugar content of Kaiyang loquat was explored and established. The fiber-optic spectrometer was used to collect reflectance spectra of Kaiyang loquat. The preprocessing effectiveness of standard normal variation (SNV) and multi-scatter calibration (MSC) on the original spectra data was compared and evaluated. Furthermore, the partial least square regression (PLSR) and principal component regression (PCR) models were established based on original full spectra and preprocessed full spectra to predict the sugar content of Kaiyang loquat, respectively. Finally, the successive projection algorithm (SPA) and competitive adaptive reweighted sampling (CARS) were applied to select characteristic spectra. And the multi linear regression (MLR) model was established based on characteristic spectra to predict the sugar content of Kaiyang loquat. The results showed that 23 characteristic wavelengths were extracted by CARS algorithm from 785 full spectra. The working efficiency of the prediction model was not only improved, but also CARS-MLR model showed the best calibration ability (RC=0.89, RMSEC=0.62) and prediction ability (RP=0.89, RMSEP=0.65, RPD=2.29). Consequently, Kaiyang loquat by Vis/NIR spectroscopy and chemometrics could be used to predict the sugar content, and the CARS-MLR model was best. These results can provide important theoretical and technical basis for the rapidly nondestructive prediction and sorting the quality of loquat.

Key words： Vis/NIR spectroscopy; Kaiyang loquat; sugar content; optimized model; nondestructive detection

Cite this article

MENG Qinglong , FENG Shunan , SHANG Jing , HUANG Renshuai , ZHANG Yan , CAO Sen . The establishment and optimization of the model for predicting the sugar content of loquat by Vis/NIR spectroscopy[J]. Food and Fermentation Industries, 2022 , 48(12) : 249 -254 . DOI: 10.13995/j.cnki.11-1802/ts.031112

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