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Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy

Fourier transform near-infrared (FT-NIR) spectroscopy is a nondestructive, rapid, real-time analysis of technical detection methods with an important reference value for producers and consumers. In this study, the feasibility of using FT-NIR spectroscopy for the rapid quantitative analysis and quali...

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Autores principales: Lu, Zhaohui, Lu, Ruitao, Chen, Yu, Fu, Kai, Song, Junxing, Xie, Linlin, Zhai, Rui, Wang, Zhigang, Yang, Chengquan, Xu, Lingfei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9026391/
https://www.ncbi.nlm.nih.gov/pubmed/35454663
http://dx.doi.org/10.3390/foods11081076
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author Lu, Zhaohui
Lu, Ruitao
Chen, Yu
Fu, Kai
Song, Junxing
Xie, Linlin
Zhai, Rui
Wang, Zhigang
Yang, Chengquan
Xu, Lingfei
author_facet Lu, Zhaohui
Lu, Ruitao
Chen, Yu
Fu, Kai
Song, Junxing
Xie, Linlin
Zhai, Rui
Wang, Zhigang
Yang, Chengquan
Xu, Lingfei
author_sort Lu, Zhaohui
collection PubMed
description Fourier transform near-infrared (FT-NIR) spectroscopy is a nondestructive, rapid, real-time analysis of technical detection methods with an important reference value for producers and consumers. In this study, the feasibility of using FT-NIR spectroscopy for the rapid quantitative analysis and qualitative analysis of ‘Zaosu’ and ‘Dangshansuli’ pears is explored. The quantitative model was established by partial least squares (PLS) regression combined with cross-validation based on the spectral data of 340 pear fresh fruits and synchronized with the reference values determined by conventional assays. Furthermore, NIR spectroscopy combined with cluster analysis was used to identify varieties of ‘Zaosu’ and ‘Dangshansuli’. As a result, the model developed using FT-NIR spectroscopy gave the best results for the prediction models of soluble solid content (SSC) and titratable acidity (TA) of ‘Dangshansuli’ (residual prediction deviation, RPD: 3.272 and 2.239), which were better than those developed for ‘Zaosu’ SSC and TA modeling (RPD: 1.407 and 1.471). The results also showed that the variety identification of ‘Zaosu’ and ‘Dangshansuli’ could be carried out based on FT-NIR spectroscopy, and the discrimination accuracy was 100%. Overall, FT-NIR spectroscopy is a good tool for rapid and nondestructive analysis of the internal quality and variety identification of fresh pears.
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spelling pubmed-90263912022-04-23 Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy Lu, Zhaohui Lu, Ruitao Chen, Yu Fu, Kai Song, Junxing Xie, Linlin Zhai, Rui Wang, Zhigang Yang, Chengquan Xu, Lingfei Foods Article Fourier transform near-infrared (FT-NIR) spectroscopy is a nondestructive, rapid, real-time analysis of technical detection methods with an important reference value for producers and consumers. In this study, the feasibility of using FT-NIR spectroscopy for the rapid quantitative analysis and qualitative analysis of ‘Zaosu’ and ‘Dangshansuli’ pears is explored. The quantitative model was established by partial least squares (PLS) regression combined with cross-validation based on the spectral data of 340 pear fresh fruits and synchronized with the reference values determined by conventional assays. Furthermore, NIR spectroscopy combined with cluster analysis was used to identify varieties of ‘Zaosu’ and ‘Dangshansuli’. As a result, the model developed using FT-NIR spectroscopy gave the best results for the prediction models of soluble solid content (SSC) and titratable acidity (TA) of ‘Dangshansuli’ (residual prediction deviation, RPD: 3.272 and 2.239), which were better than those developed for ‘Zaosu’ SSC and TA modeling (RPD: 1.407 and 1.471). The results also showed that the variety identification of ‘Zaosu’ and ‘Dangshansuli’ could be carried out based on FT-NIR spectroscopy, and the discrimination accuracy was 100%. Overall, FT-NIR spectroscopy is a good tool for rapid and nondestructive analysis of the internal quality and variety identification of fresh pears. MDPI 2022-04-08 /pmc/articles/PMC9026391/ /pubmed/35454663 http://dx.doi.org/10.3390/foods11081076 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lu, Zhaohui
Lu, Ruitao
Chen, Yu
Fu, Kai
Song, Junxing
Xie, Linlin
Zhai, Rui
Wang, Zhigang
Yang, Chengquan
Xu, Lingfei
Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy
title Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy
title_full Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy
title_fullStr Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy
title_full_unstemmed Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy
title_short Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy
title_sort nondestructive testing of pear based on fourier near-infrared spectroscopy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9026391/
https://www.ncbi.nlm.nih.gov/pubmed/35454663
http://dx.doi.org/10.3390/foods11081076
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