Linear discriminant analysis of grain quality traits in rice (Oryza sativa L.) using the digital imaging technique

Abstract

Rice (Oryza sativa L.) is the most important food crop in India, and aromatic rice (Basmati and non-basmati) occupies an important place due to its demand in the domestic and international markets. Despite its economic value, it is cultivated mainly in North-western India, whereas cultivation is limited in other rice-growing regions of India, particularly southern Indian states. Aromatic rice is determined based on aroma content, grain quality traits, and the conventional methods for measuring grain quality traits are time-consuming and laborious. In this study, 21 hybrids were obtained from 10 rice cultivars (Aromatic and non-aromatic), using a line × tester fashion mating design. Further, the grain quality traits were evaluated [i.e., grain size and grain type] with the support of digital imaging technique (DIT) and then assessed the gelatinization temperature, and aroma. The mean values of all the traits from 10 parents and their 21 hybrids were subjected to linear discriminant analysis (LDA). The precise classification of grain size into short, medium, and long-grained groups with higher accuracy levels was observed rather than by grain type, gelatinization temperature, and aroma. The percentage of separation by LD1 was 98.91%, and LD2 was 1.09%. In addition, we evaluated the agronomic traits of the hybrids, revealing the agronomically superior aromatic hybrids (i.e., CO 51 × Jeeragasamba and MDU 6 × Jeeragasamba). Taken together, the present study shows the efficiency of DIT in obtaining accurate classifications of rice genotypes. The newly developed lines could serve as potential resources to further develop aroma-type rice genotypes and could provide genetic stock for use in breeding programs.