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Article

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

1
National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Korea
2
Faculty of Bioscience and Industry, College of Applied Life Science, SARI, Jeju National University, Jeju 63243, Korea
3
National Institute of Crop Sciences, Rural Development Administration (RDA), Wanju-gun 55365, Korea
*
Author to whom correspondence should be addressed.
These authors also contributed equally to this work.
Sensors 2020, 20(1), 248; https://doi.org/10.3390/s20010248
Received: 18 October 2019 / Revised: 25 November 2019 / Accepted: 28 November 2019 / Published: 1 January 2020
(This article belongs to the Section Intelligent Sensors)
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. View Full-Text
Keywords: RGB image; seed morphology; seed color; seed traits; breeding RGB image; seed morphology; seed color; seed traits; breeding
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MDPI and ACS Style

BAEK, J.; Lee, E.; Kim, N.; Kim, S.L.; Choi, I.; Ji, H.; Chung, Y.S.; Choi, M.-S.; Moon, J.-K.; Kim, K.-H. High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis. Sensors 2020, 20, 248. https://doi.org/10.3390/s20010248

AMA Style

BAEK J, Lee E, Kim N, Kim SL, Choi I, Ji H, Chung YS, Choi M-S, Moon J-K, Kim K-H. High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis. Sensors. 2020; 20(1):248. https://doi.org/10.3390/s20010248

Chicago/Turabian Style

BAEK, JeongHo, Eungyeong Lee, Nyunhee Kim, Song L. Kim, Inchan Choi, Hyeonso Ji, Yong S. Chung, Man-Soo Choi, Jung-Kyung Moon, and Kyung-Hwan Kim. 2020. "High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis" Sensors 20, no. 1: 248. https://doi.org/10.3390/s20010248

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