Figures & data
Figure 1. The value of percentage variability for each individual nutritional component in rice grains
![Figure 1. The value of percentage variability for each individual nutritional component in rice grains](/cms/asset/ade09934-4335-4fad-b76c-7b05885cf956/kgmc_a_1893624_f0001_oc.jpg)
Table 1. Analysis of similarities (ANOSIM) results between two effect factors in rice composition
Table 2. Results of the PERMANOVA analysis for the nutrition categories of rice grains, using plant cultivation year, cultivation site, genotype, and their interaction as the source of variation
Figure 2. Average dissimilarity in the composition of proximates (a), amino acids (b), lipid acids (c), minerals (d), vitamins (e), and antinutrients (f) among cultivation factors and among genotype factors by SIMPER analysis
![Figure 2. Average dissimilarity in the composition of proximates (a), amino acids (b), lipid acids (c), minerals (d), vitamins (e), and antinutrients (f) among cultivation factors and among genotype factors by SIMPER analysis](/cms/asset/204f2182-69f5-4dd5-9fb8-26e54eba5141/kgmc_a_1893624_f0002_oc.jpg)
Figure 3. Results of SIMPER comparison among cultivation factors and among genotype factors for all rice components. SIMPER analysis was operated using a two-way crossed layout, opting for the Bray-Curtis dissimilarity matrix, and setting the cutoff at 80%. Abbreviation: Carbo, carbohydrate; Trypsin IH, Trypsin inhibitor
![Figure 3. Results of SIMPER comparison among cultivation factors and among genotype factors for all rice components. SIMPER analysis was operated using a two-way crossed layout, opting for the Bray-Curtis dissimilarity matrix, and setting the cutoff at 80%. Abbreviation: Carbo, carbohydrate; Trypsin IH, Trypsin inhibitor](/cms/asset/94c52b78-6cb1-47d3-8c37-3d9e1c73e768/kgmc_a_1893624_f0003_oc.jpg)