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Classification Method for Viability Screening of Naturally Aged Watermelon Seeds Using FT-NIR Spectroscopy

Viability analysis of stored seeds before sowing has a great importance as plant seeds lose their viability when they exposed to long term storage. In this study, the potential of Fourier transform near infrared spectroscopy (FT-NIR) was investigated to discriminate between viable and non-viable tri...

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Autores principales: Yasmin, Jannat, Raju Ahmed, Mohammed, Lohumi, Santosh, Wakholi, Collins, Kim, Moon S., Cho, Byoung-Kwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427422/
https://www.ncbi.nlm.nih.gov/pubmed/30857184
http://dx.doi.org/10.3390/s19051190
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author Yasmin, Jannat
Raju Ahmed, Mohammed
Lohumi, Santosh
Wakholi, Collins
Kim, Moon S.
Cho, Byoung-Kwan
author_facet Yasmin, Jannat
Raju Ahmed, Mohammed
Lohumi, Santosh
Wakholi, Collins
Kim, Moon S.
Cho, Byoung-Kwan
author_sort Yasmin, Jannat
collection PubMed
description Viability analysis of stored seeds before sowing has a great importance as plant seeds lose their viability when they exposed to long term storage. In this study, the potential of Fourier transform near infrared spectroscopy (FT-NIR) was investigated to discriminate between viable and non-viable triploid watermelon seeds of three different varieties stored for four years (natural aging) in controlled conditions. Because of the thick seed-coat of triploid watermelon seeds, penetration depth of FT-NIR light source was first confirmed to ensure seed embryo spectra can be collected effectively. The collected spectral data were divided into viable and nonviable groups after the viability being confirmed by conducting a standard germination test. The obtained results showed that the developed partial least discriminant analysis (PLS-DA) model had high classification accuracy where the dataset was made after mixing three different varieties of watermelon seeds. Finally, developed model was evaluated with an external data set (collected at different time) of hundred samples selected randomly from three varieties. The results yield a good classification accuracy for both viable (87.7%) and nonviable seeds (82%), thus the developed model can be considered as a “general model” since it can be applied to three different varieties of seeds and data collected at different time.
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spelling pubmed-64274222019-04-15 Classification Method for Viability Screening of Naturally Aged Watermelon Seeds Using FT-NIR Spectroscopy Yasmin, Jannat Raju Ahmed, Mohammed Lohumi, Santosh Wakholi, Collins Kim, Moon S. Cho, Byoung-Kwan Sensors (Basel) Article Viability analysis of stored seeds before sowing has a great importance as plant seeds lose their viability when they exposed to long term storage. In this study, the potential of Fourier transform near infrared spectroscopy (FT-NIR) was investigated to discriminate between viable and non-viable triploid watermelon seeds of three different varieties stored for four years (natural aging) in controlled conditions. Because of the thick seed-coat of triploid watermelon seeds, penetration depth of FT-NIR light source was first confirmed to ensure seed embryo spectra can be collected effectively. The collected spectral data were divided into viable and nonviable groups after the viability being confirmed by conducting a standard germination test. The obtained results showed that the developed partial least discriminant analysis (PLS-DA) model had high classification accuracy where the dataset was made after mixing three different varieties of watermelon seeds. Finally, developed model was evaluated with an external data set (collected at different time) of hundred samples selected randomly from three varieties. The results yield a good classification accuracy for both viable (87.7%) and nonviable seeds (82%), thus the developed model can be considered as a “general model” since it can be applied to three different varieties of seeds and data collected at different time. MDPI 2019-03-08 /pmc/articles/PMC6427422/ /pubmed/30857184 http://dx.doi.org/10.3390/s19051190 Text en © 2019 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
Yasmin, Jannat
Raju Ahmed, Mohammed
Lohumi, Santosh
Wakholi, Collins
Kim, Moon S.
Cho, Byoung-Kwan
Classification Method for Viability Screening of Naturally Aged Watermelon Seeds Using FT-NIR Spectroscopy
title Classification Method for Viability Screening of Naturally Aged Watermelon Seeds Using FT-NIR Spectroscopy
title_full Classification Method for Viability Screening of Naturally Aged Watermelon Seeds Using FT-NIR Spectroscopy
title_fullStr Classification Method for Viability Screening of Naturally Aged Watermelon Seeds Using FT-NIR Spectroscopy
title_full_unstemmed Classification Method for Viability Screening of Naturally Aged Watermelon Seeds Using FT-NIR Spectroscopy
title_short Classification Method for Viability Screening of Naturally Aged Watermelon Seeds Using FT-NIR Spectroscopy
title_sort classification method for viability screening of naturally aged watermelon seeds using ft-nir spectroscopy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427422/
https://www.ncbi.nlm.nih.gov/pubmed/30857184
http://dx.doi.org/10.3390/s19051190
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