Application of image-based phenotyping for assessing tolerance of rice varieties to combined water and salt stress

2023 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)(2023)

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摘要
This study aims to evaluate the feasible application of image-based phenotyping in evaluating the morphological responses of rice plants to combined abiotic stresses. The study was based on plants of five rice cultivars, namely Ciherang (CH), Inpari 29 (IN29), Inpari 34 (IN34), IR29 (IR29) and Jeliteng (JL). Stress condition factors consist of control (C), drought stress (D), salinity (S), and their combinations (DS). Observations were made on 3 image-derived traits implicated in rice responses to drought and salinity, including the ratio of the area perimeter (PARa), the ratio of plant greenness (GPARa), and the index of atmospheric resistance (VARI). The ANOVA result showed that interaction between genotypes and treatments is affected in GPARa at 105 days after transplantation (DAT; 0.0023) and significantly differentiates control and stress conditions by t-test analysis. Moreover, this trait enabled us to distinguish tolerant (CH, IN29, IN34) and sensitive varieties (IR29 and JL) from stress conditions with exhibits values 46.43% greater in IN29 concerning IR 29. Consequently, the results of this study could pave the way for the application of image-based phenotyping aimed to speed up breeding programs of more resilient rice varieties for individual and/or combined abiotic stresses that are expected to occur more frequently soon due to climate change.
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关键词
Combined abiotic stress,high-throughput phenotyping,resistance traits,RGB image analysis
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