A semidwarf and late-flowering isogenic Kosihihikari d60Hd16: development, productivity, and regional suitability revealed by correlation-based network analysis.

Abstract

Breeding rice varieties that are tolerant to weather variability and optimizing cultivation methods for each developed variety are challenging issues for global food problems. In this study, the late-flowering gene Hd16 of Koganebare was introduced into Koshihikari through backcrossing to create Koshihikari Hd16. It was then crossed with Koshihikari d60 to develop an isogenic Koshihikari containing both Hd16 and d60. Productivity tests were conducted in nine prefectures in Japan for two homogeneous rice genotypes, Hd16 (late flowering) and d60Hd16 (short culm and late flowering). By analyzing the relationship between genotype, traits, and accumulation temperature, we reexamined the characteristics of each genotype and inferred the optimal growing areas. Correlation-based network analysis among yield, grain quality, and value of taste and traits showed that quality was positively correlated with panicle length and 1000-grain weight, and yield was strongly positively correlated with 1000-grain weight. d60 genotype was negatively correlated with culm length and lodging degree. These correlations were supported by partial correlation analysis and significant differences compared to the wildtype was identified. Principal component analysis of d60Hd16 revealed that Yamanashi and Ehime, which have longer panicle length and culm length, were suitable in terms of yield and quality, while Shimane, which is warmer and has shorter panicle length and culm length, was suitable in terms of eating quality. Moreover, Koshihikari d60Hd16 could express traits that are less prone to lodging degree while maintaining the same quality and yield as the wild type in cultivation of late-flowering strains. Thus, the d60 and H16 genotypes express stable traits adapted to a wide range of Japanese climatic conditions and growing environments. This study provides fundamental information for promoting new smart agriculture, in which improved varieties are deployed in different regions with different climatic conditions.