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Assessment of Tomato Maturity in Different Layers by Spatially Resolved Spectroscopy

Tomato maturity is important to determine the fruit shelf life and eating quality. The objective of this research was to evaluate tomato maturity in different layers by using a newly developed spatially resolved spectroscopic system over the spectral region of 550–1650 nm. Thirty spatially resolved...

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Autores principales: Huang, Yuping, Si, Wan, Chen, Kunjie, Sun, Ye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766491/
https://www.ncbi.nlm.nih.gov/pubmed/33348611
http://dx.doi.org/10.3390/s20247229
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author Huang, Yuping
Si, Wan
Chen, Kunjie
Sun, Ye
author_facet Huang, Yuping
Si, Wan
Chen, Kunjie
Sun, Ye
author_sort Huang, Yuping
collection PubMed
description Tomato maturity is important to determine the fruit shelf life and eating quality. The objective of this research was to evaluate tomato maturity in different layers by using a newly developed spatially resolved spectroscopic system over the spectral region of 550–1650 nm. Thirty spatially resolved spectra were obtained for 600 tomatoes, 100 for each of the six maturity stages (i.e., green, breaker, turning, pink, light red, and red). Support vector machine discriminant analysis (SVMDA) models were first developed for each of individual spatially resolved (SR) spectra to compare the classification results of two sides. The mean spectra of two sides with the same source-detector distances were employed to determine the model performance of different layers. SR combination by averaging all the SR spectra was also subject to comparison with the classification model performance. The results showed large source-detector distances would be helpful for evaluating tomato maturity, and the mean_SR 15 obtained excellent classification results with the total classification accuracy of 98.3%. Moreover, the classification results were distinct for two sides of the probe, which demonstrated even if in the same source-detector distances, the classification results were influenced by the measurement location due to the heterogeneity for tomato. The mean of all SR spectra could only improve the classification results based on the first three mean_SR spectra, but could not obtain the accuracy as good as the following mean_SR spectra. This study demonstrated that spatially resolved spectroscopy has potential for assessing tomato maturity in different layers.
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spelling pubmed-77664912020-12-28 Assessment of Tomato Maturity in Different Layers by Spatially Resolved Spectroscopy Huang, Yuping Si, Wan Chen, Kunjie Sun, Ye Sensors (Basel) Article Tomato maturity is important to determine the fruit shelf life and eating quality. The objective of this research was to evaluate tomato maturity in different layers by using a newly developed spatially resolved spectroscopic system over the spectral region of 550–1650 nm. Thirty spatially resolved spectra were obtained for 600 tomatoes, 100 for each of the six maturity stages (i.e., green, breaker, turning, pink, light red, and red). Support vector machine discriminant analysis (SVMDA) models were first developed for each of individual spatially resolved (SR) spectra to compare the classification results of two sides. The mean spectra of two sides with the same source-detector distances were employed to determine the model performance of different layers. SR combination by averaging all the SR spectra was also subject to comparison with the classification model performance. The results showed large source-detector distances would be helpful for evaluating tomato maturity, and the mean_SR 15 obtained excellent classification results with the total classification accuracy of 98.3%. Moreover, the classification results were distinct for two sides of the probe, which demonstrated even if in the same source-detector distances, the classification results were influenced by the measurement location due to the heterogeneity for tomato. The mean of all SR spectra could only improve the classification results based on the first three mean_SR spectra, but could not obtain the accuracy as good as the following mean_SR spectra. This study demonstrated that spatially resolved spectroscopy has potential for assessing tomato maturity in different layers. MDPI 2020-12-17 /pmc/articles/PMC7766491/ /pubmed/33348611 http://dx.doi.org/10.3390/s20247229 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Huang, Yuping
Si, Wan
Chen, Kunjie
Sun, Ye
Assessment of Tomato Maturity in Different Layers by Spatially Resolved Spectroscopy
title Assessment of Tomato Maturity in Different Layers by Spatially Resolved Spectroscopy
title_full Assessment of Tomato Maturity in Different Layers by Spatially Resolved Spectroscopy
title_fullStr Assessment of Tomato Maturity in Different Layers by Spatially Resolved Spectroscopy
title_full_unstemmed Assessment of Tomato Maturity in Different Layers by Spatially Resolved Spectroscopy
title_short Assessment of Tomato Maturity in Different Layers by Spatially Resolved Spectroscopy
title_sort assessment of tomato maturity in different layers by spatially resolved spectroscopy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766491/
https://www.ncbi.nlm.nih.gov/pubmed/33348611
http://dx.doi.org/10.3390/s20247229
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