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Updated: Jul 8, 2025

Author Spotlight: Streamlining Rice Breeding with CRISPR/Cas for Obtaining Optimal Phenotypic and Agronomic Traits
Published on: January 3, 2025
Screen for low-arsenic-risk rice varieties based on environment-genotype interactions by using GGE analysis
Kai-Wei Juang1, Ting Tsai1,2, Chien-Hui Syu3
1Department of Agronomy, National Chiayi University, Chiayi County, Taiwan.
Abstract:
Arsenic (As) accumulation in rice is a global health concern that has received increased attention in recent years. In this study, 12 rice genotypes were cultivated at four As-contaminated paddy sites in Taiwan. According to the different crop seasons and As levels in the soil, the sites were further divided into 18 environmental conditions. For As in soils, results showed that 67% of the studied environments were likely to represent As contamination. For As in rice, the mean total As concentration in brown rice grains ranged from 0.17 to 0.45 mg kg-1. The analysis of variance for the environment effect indicated that grain As concentration was mainly affected by the environmental conditions, suggesting that there was a remarkable degree of variation across the trial environments. According to the combination of the GGE biplot and cumulative distribution function of order statistics (CDFOS) analysis, five genotypes-TCS17, TCS10, TT30, KH139, and TC192-were regarded as stable, low-risk genotypes because the probability of grain As concentration exceeding the maximum permissible concentration (MPC) was lower for these genotypes across all environmental conditions. Particularly, TCS17 was recommended to be the safest rice genotype. Thus, grain As levels in the selected genotypes were applied to assess the health risk to Taiwanese residents associated with As exposure through rice consumption. Results showed that the upper 75th percentile values of the hazard quotient were all less than unity. This suggested that the health risk associated with consuming the selected rice genotypes was acceptable for most of the residents. The methodology developed here would be applicable to screen for stable, low-As-risk rice genotypes across multiple field environments in other regions or countries.
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