A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control

Abstract Background Low temperature freezing stress has adverse effects on wheat seedling growth and final yield. The traditional method to evaluate the wheat injury caused by the freezing stress is by visual observations, which is time-consuming and laborious. Therefore, a more efficient and accura...

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Autores principales:	Xiuqing Fu, Yang Bai, Jing Zhou, Hongwen Zhang, Jieyu Xian
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	RGB imaging Wheat freezing injury Freezing injury phenotype Vegetation coverage Frost damage grade Plant culture SB1-1110 Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/a2cdc85600f94d99bec6a94848b4c4fd
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spelling	oai:doaj.org-article:a2cdc85600f94d99bec6a94848b4c4fd2021-11-28T12:09:16ZA method for obtaining field wheat freezing injury phenotype based on RGB camera and software control10.1186/s13007-021-00821-71746-4811https://doaj.org/article/a2cdc85600f94d99bec6a94848b4c4fd2021-11-01T00:00:00Zhttps://doi.org/10.1186/s13007-021-00821-7https://doaj.org/toc/1746-4811Abstract Background Low temperature freezing stress has adverse effects on wheat seedling growth and final yield. The traditional method to evaluate the wheat injury caused by the freezing stress is by visual observations, which is time-consuming and laborious. Therefore, a more efficient and accurate method for freezing damage identification is urgently needed. Results A high-throughput phenotyping system was developed in this paper, namely, RGB freezing injury system, to effectively and efficiently quantify the wheat freezing injury in the field environments. The system is able to automatically collect, processing, and analyze the wheat images collected using a mobile phenotype cabin in the field conditions. A data management system was also developed to store and manage the original images and the calculated phenotypic data in the system. In this experiment, a total of 128 wheat varieties were planted, three nitrogen concentrations were applied and two biological and technical replicates were performed. And wheat canopy images were collected at the seedling pulling stage and three image features were extracted for each wheat samples, including ExG, ExR and ExV. We compared different test parameters and found that the coverage had a greater impact on freezing injury. Therefore, we preliminarily divided four grades of freezing injury according to the test results to evaluate the freezing injury of different varieties of wheat at the seedling stage. Conclusions The automatic phenotypic analysis method of freezing injury provides an alternative solution for high-throughput freezing damage analysis of field crops and it can be used to quantify freezing stress and has guiding significance for accelerating the selection of wheat excellent frost resistance genotypes.Xiuqing FuYang BaiJing ZhouHongwen ZhangJieyu XianBMCarticleRGB imagingWheat freezing injuryFreezing injury phenotypeVegetation coverageFrost damage gradePlant cultureSB1-1110Biology (General)QH301-705.5ENPlant Methods, Vol 17, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	RGB imaging Wheat freezing injury Freezing injury phenotype Vegetation coverage Frost damage grade Plant culture SB1-1110 Biology (General) QH301-705.5
spellingShingle	RGB imaging Wheat freezing injury Freezing injury phenotype Vegetation coverage Frost damage grade Plant culture SB1-1110 Biology (General) QH301-705.5 Xiuqing Fu Yang Bai Jing Zhou Hongwen Zhang Jieyu Xian A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control
description	Abstract Background Low temperature freezing stress has adverse effects on wheat seedling growth and final yield. The traditional method to evaluate the wheat injury caused by the freezing stress is by visual observations, which is time-consuming and laborious. Therefore, a more efficient and accurate method for freezing damage identification is urgently needed. Results A high-throughput phenotyping system was developed in this paper, namely, RGB freezing injury system, to effectively and efficiently quantify the wheat freezing injury in the field environments. The system is able to automatically collect, processing, and analyze the wheat images collected using a mobile phenotype cabin in the field conditions. A data management system was also developed to store and manage the original images and the calculated phenotypic data in the system. In this experiment, a total of 128 wheat varieties were planted, three nitrogen concentrations were applied and two biological and technical replicates were performed. And wheat canopy images were collected at the seedling pulling stage and three image features were extracted for each wheat samples, including ExG, ExR and ExV. We compared different test parameters and found that the coverage had a greater impact on freezing injury. Therefore, we preliminarily divided four grades of freezing injury according to the test results to evaluate the freezing injury of different varieties of wheat at the seedling stage. Conclusions The automatic phenotypic analysis method of freezing injury provides an alternative solution for high-throughput freezing damage analysis of field crops and it can be used to quantify freezing stress and has guiding significance for accelerating the selection of wheat excellent frost resistance genotypes.
format	article
author	Xiuqing Fu Yang Bai Jing Zhou Hongwen Zhang Jieyu Xian
author_facet	Xiuqing Fu Yang Bai Jing Zhou Hongwen Zhang Jieyu Xian
author_sort	Xiuqing Fu
title	A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control
title_short	A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control
title_full	A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control
title_fullStr	A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control
title_full_unstemmed	A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control
title_sort	method for obtaining field wheat freezing injury phenotype based on rgb camera and software control
publisher	BMC
publishDate	2021
url	https://doaj.org/article/a2cdc85600f94d99bec6a94848b4c4fd
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A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control

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