Application of laser-induced backscattering imaging for predicting and classifying ripening stages of ''Berangan'' bananas

This study investigates the potential of laser light backscattering imaging (LLBI) for predicting and classifying Musa Acuminata cv. Berangan at different ripening stages. Backscattering images of Berangan bananas at various ripening stages from 2 to 7 were acquired by a charge coupled device (CCD)...

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Main Authors: Hashim, Norhashila, Zulkifli, Nurazwin, Abdan, Khalina, Hanafi, Marsyita
Format: Article
Language:English
Published: Elsevier 2019
Online Access:http://psasir.upm.edu.my/id/eprint/80705/1/BANANAS.pdf
http://psasir.upm.edu.my/id/eprint/80705/
https://www.sciencedirect.com/science/article/pii/S016816991831473X
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Institution: Universiti Putra Malaysia
Language: English
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spelling my.upm.eprints.807052020-11-04T12:58:28Z http://psasir.upm.edu.my/id/eprint/80705/ Application of laser-induced backscattering imaging for predicting and classifying ripening stages of ''Berangan'' bananas Hashim, Norhashila Zulkifli, Nurazwin Abdan, Khalina Hanafi, Marsyita This study investigates the potential of laser light backscattering imaging (LLBI) for predicting and classifying Musa Acuminata cv. Berangan at different ripening stages. Backscattering images of Berangan bananas at various ripening stages from 2 to 7 were acquired by a charge coupled device (CCD) camera coupled with a laser diode emitting light at a wavelength of 658 nm. The grey level intensity and the size of the backscattering area were extracted from the backscattering images and used as parameters for estimating the quality properties of the bananas. The results showed strong correlation between the LLBI parameters and the colour of the bananas as well as the total soluble solids content (TSS) with a coefficient of determination (R2) of over 0.70. Statistical analysis using Linear Discriminant Analysis (LDA) successfully classified the samples into their ripening stages accordingly with the percentage of correct classification up to 94.2%. Thus, it can be concluded that the LLBI could potentially be used for predicting and classifying the ripening stages of bananas and be further developed for an automated quality control system. Elsevier 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/80705/1/BANANAS.pdf Hashim, Norhashila and Zulkifli, Nurazwin and Abdan, Khalina and Hanafi, Marsyita (2019) Application of laser-induced backscattering imaging for predicting and classifying ripening stages of ''Berangan'' bananas. Computers and Electronics in Agriculture, 160. pp. 100-107. ISSN 0168-1699; ESSN: 1872-7107 https://www.sciencedirect.com/science/article/pii/S016816991831473X 10.1016/j.compag.2019.02.031
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This study investigates the potential of laser light backscattering imaging (LLBI) for predicting and classifying Musa Acuminata cv. Berangan at different ripening stages. Backscattering images of Berangan bananas at various ripening stages from 2 to 7 were acquired by a charge coupled device (CCD) camera coupled with a laser diode emitting light at a wavelength of 658 nm. The grey level intensity and the size of the backscattering area were extracted from the backscattering images and used as parameters for estimating the quality properties of the bananas. The results showed strong correlation between the LLBI parameters and the colour of the bananas as well as the total soluble solids content (TSS) with a coefficient of determination (R2) of over 0.70. Statistical analysis using Linear Discriminant Analysis (LDA) successfully classified the samples into their ripening stages accordingly with the percentage of correct classification up to 94.2%. Thus, it can be concluded that the LLBI could potentially be used for predicting and classifying the ripening stages of bananas and be further developed for an automated quality control system.
format Article
author Hashim, Norhashila
Zulkifli, Nurazwin
Abdan, Khalina
Hanafi, Marsyita
spellingShingle Hashim, Norhashila
Zulkifli, Nurazwin
Abdan, Khalina
Hanafi, Marsyita
Application of laser-induced backscattering imaging for predicting and classifying ripening stages of ''Berangan'' bananas
author_facet Hashim, Norhashila
Zulkifli, Nurazwin
Abdan, Khalina
Hanafi, Marsyita
author_sort Hashim, Norhashila
title Application of laser-induced backscattering imaging for predicting and classifying ripening stages of ''Berangan'' bananas
title_short Application of laser-induced backscattering imaging for predicting and classifying ripening stages of ''Berangan'' bananas
title_full Application of laser-induced backscattering imaging for predicting and classifying ripening stages of ''Berangan'' bananas
title_fullStr Application of laser-induced backscattering imaging for predicting and classifying ripening stages of ''Berangan'' bananas
title_full_unstemmed Application of laser-induced backscattering imaging for predicting and classifying ripening stages of ''Berangan'' bananas
title_sort application of laser-induced backscattering imaging for predicting and classifying ripening stages of ''berangan'' bananas
publisher Elsevier
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/80705/1/BANANAS.pdf
http://psasir.upm.edu.my/id/eprint/80705/
https://www.sciencedirect.com/science/article/pii/S016816991831473X
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