The quality of rice grain impacts milling yield, market acceptance, and product value. Physical quality is determined by many traits, such as chalkiness, whiteness, vitreous whiteness, caryopsis length, and width. Breeding for these traits is challenging due to their quantitative nature, environmental effects, and time and labor requirements to evaluate these traits. The digital grain analyzer (S21) equipment determines rice grain physical quality by image-based analysis; however, its use remains restricted. Thus, here we aimed to evaluate S21 efficiency to determine the physical quality of rice grains and estimate the genetic diversity of the trait using a Brazilian panel of 152 irrigated rice genotypes as a working model. We accessed total whiteness, vitreous whiteness, chalkiness degree, chalky grain rate, white belly, grain length, width, and length/width ratio. Our results demonstrated that S21 allowed the characterization of the genotypes according to physical traits, facilitating grouping and separation of accessions and correlation analyses between quality traits. It was also possible to estimate the heritability of quality traits. S21 was efficient in characterizing the physical quality of rice grains and determining their genetic diversity. The equipment is an effective tool exhibiting potential application by breeder programs.
Perleberg et al. (Fri,) studied this question.