Development of image-based phenotyping for selection characters of rice adaptability on the seedling salinity screening


M F Anshori, - and M Farid, - and Nasaruddin, - and Y Musa, - and H Iswoyo, - and A I Sakinah, - and M Arifuddin, - and A A Laraswati, - (2021) Development of image-based phenotyping for selection characters of rice adaptability on the seedling salinity screening. IOP Conf. Series: Earth and Environmental Science.

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Abstract (Abstrak)

Development of image-based phenotyping for selection characters of rice adaptability on the seedling salinity screening Development of adaptability rice under salinity stress needs effective and selective methods in the screening process. The seedling screening method is a general method used in salinity screening. However, this screening method often uses conventional observation in its screening process. This observation is rated that has a high error level. Therefore, the development of a digital approach through image-based phenotyping expected could minimize the error in the adaptability screening. This study was designed with a nested randomized complete group design, where replications were nested in a stressful environment. The environment in this study was normal (0 mM NaCl) and salinity stress (120 mM NaCl). The genotype used consisted of 8 genotypes which were repeated three times. The number of characters observed was nine image-based phenotyping. The results of this study showed that green percentage, the 3rd leaf length, and total area were the selection characters of image-based phenotyping under seedling salinity screening. Besides that, the used adaptability index in salinity screening became a good approach in considered and distinguished tolerance responses among varieties, especially to Pokkali (tolerant control variety) and IR 29 (sensitive control variety). Based on this study, the application of image-based phenotyping recommended in the screening process of line adaptability under salinity stress.

Item Type: Article
Subjects: S Agriculture > S Agriculture (General)
Depositing User: - Andi Anna
Date Deposited: 08 Oct 2021 03:03
Last Modified: 08 Oct 2021 03:03
URI: http://repository.unhas.ac.id:443/id/eprint/7883

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