RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.).

Kenaf (Hibiscus cannabinus L.) is an industrial crop used as a raw material in various fields and is cultivated worldwide. Compared to high potential for its utilization, breeding sector is not vigorous partially due to laborous breeding procedure. Thus, efficient breeding methods are required for v...

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Autores principales:	Gyung Doeok Han, GyuJin Jang, Jaeyoung Kim, Dong-Wook Kim, Renato Rodrogues, Seong-Hoon Kim, Hak-Jin Kim, Yong Suk Chung
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/edf27e728e404980b7d9d01c9ca71a78
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id	oai:doaj.org-article:edf27e728e404980b7d9d01c9ca71a78
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spelling	oai:doaj.org-article:edf27e728e404980b7d9d01c9ca71a782021-12-02T20:08:28ZRGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.).1932-620310.1371/journal.pone.0256978https://doaj.org/article/edf27e728e404980b7d9d01c9ca71a782021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0256978https://doaj.org/toc/1932-6203Kenaf (Hibiscus cannabinus L.) is an industrial crop used as a raw material in various fields and is cultivated worldwide. Compared to high potential for its utilization, breeding sector is not vigorous partially due to laborous breeding procedure. Thus, efficient breeding methods are required for varieties that can adapt to various environments and obtain optimal production. For that, identifying kenaf's characteristics is very important during the breeding process. Here, we investigated if RGB based vegetative index (VI) could be associated with traits for biomass. We used 20 varieties and germplasm of kenaf and RGB images taken with unmanned aerial vehicles (UAVs) for field selection in early and late growth stage. In addition, measuring the stem diameter and the number of nodes confirmed whether the vegetative index value obtained from the RGB image could infer the actual plant biomass. Based on the results, it was confirmed that the individual surface area and estimated plant height, which were identified from the RGB image, had positive correlations with the stem diameter and node number, which are actual growth indicators of the rate of growth further, biomass could also be estimated based on this. Moreover, it is suggested that VIs have a high correlation with actual growth indicators; thus, the biomass of kenaf could be predicted. Interstingly, those traits showing high correlation in the late stage had very low correlations in the early stage. To sum up, the results in the current study suggest a more efficient breeding method by reducing labor and resources required for breeding selection by the use of RGB image analysis obtained by UAV. This means that considerable high-quality research could be performed even with a tight budget. Furthermore, this method could be applied to crop management, which is done with other vegetative indices using a multispectral camera.Gyung Doeok HanGyuJin JangJaeyoung KimDong-Wook KimRenato RodroguesSeong-Hoon KimHak-Jin KimYong Suk ChungPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0256978 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Gyung Doeok Han GyuJin Jang Jaeyoung Kim Dong-Wook Kim Renato Rodrogues Seong-Hoon Kim Hak-Jin Kim Yong Suk Chung RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.).
description	Kenaf (Hibiscus cannabinus L.) is an industrial crop used as a raw material in various fields and is cultivated worldwide. Compared to high potential for its utilization, breeding sector is not vigorous partially due to laborous breeding procedure. Thus, efficient breeding methods are required for varieties that can adapt to various environments and obtain optimal production. For that, identifying kenaf's characteristics is very important during the breeding process. Here, we investigated if RGB based vegetative index (VI) could be associated with traits for biomass. We used 20 varieties and germplasm of kenaf and RGB images taken with unmanned aerial vehicles (UAVs) for field selection in early and late growth stage. In addition, measuring the stem diameter and the number of nodes confirmed whether the vegetative index value obtained from the RGB image could infer the actual plant biomass. Based on the results, it was confirmed that the individual surface area and estimated plant height, which were identified from the RGB image, had positive correlations with the stem diameter and node number, which are actual growth indicators of the rate of growth further, biomass could also be estimated based on this. Moreover, it is suggested that VIs have a high correlation with actual growth indicators; thus, the biomass of kenaf could be predicted. Interstingly, those traits showing high correlation in the late stage had very low correlations in the early stage. To sum up, the results in the current study suggest a more efficient breeding method by reducing labor and resources required for breeding selection by the use of RGB image analysis obtained by UAV. This means that considerable high-quality research could be performed even with a tight budget. Furthermore, this method could be applied to crop management, which is done with other vegetative indices using a multispectral camera.
format	article
author	Gyung Doeok Han GyuJin Jang Jaeyoung Kim Dong-Wook Kim Renato Rodrogues Seong-Hoon Kim Hak-Jin Kim Yong Suk Chung
author_facet	Gyung Doeok Han GyuJin Jang Jaeyoung Kim Dong-Wook Kim Renato Rodrogues Seong-Hoon Kim Hak-Jin Kim Yong Suk Chung
author_sort	Gyung Doeok Han
title	RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.).
title_short	RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.).
title_full	RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.).
title_fullStr	RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.).
title_full_unstemmed	RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.).
title_sort	rgb images-based vegetative index for phenotyping kenaf (hibiscus cannabinus l.).
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/edf27e728e404980b7d9d01c9ca71a78
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RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.).

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