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High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis.

Authors :
BAEK, JeongHo
Lee, Eungyeong
Kim, Nyunhee
Kim, Song Lim
Choi, Inchan
Ji, Hyeonso
Chung, Yong Suk
Choi, Man-Soo
Moon, Jung-Kyung
Kim, Kyung-Hwan
Source :
Sensors (14248220). 1/1/2020, Vol. 20 Issue 1, p248. 1p.
Publication Year :
2020

Abstract

Data phenotyping traits on soybean seeds such as shape and color has been obscure because it is difficult to define them clearly. Further, it takes too much time and effort to have sufficient number of samplings especially length and width. These difficulties prevented seed morphology to be incorporated into efficient breeding program. Here, we propose methods for an image acquisition, a data processing, and analysis for the morphology and color of soybean seeds by high-throughput method using images analysis. As results, quantitative values for colors and various types of morphological traits could be screened to create a standard for subsequent evaluation of the genotype. Phenotyping method in the current study could define the morphology and color of soybean seeds in highly accurate and reliable manner. Further, this method enables the measurement and analysis of large amounts of plant seed phenotype data in a short time, which was not possible before. Fast and precise phenotype data obtained here may facilitate Genome Wide Association Study for the gene function analysis as well as for development of the elite varieties having desirable seed traits. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
20
Issue :
1
Database :
Academic Search Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
141128548
Full Text :
https://doi.org/10.3390/s20010248