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"Byungsoo Chae"

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"Byungsoo Chae"

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A statistical analysis of 9,771 non-glutinous rice in breeding line germplasm collected from Korea (2,836), China (2,136), Japan (1,219), and the Philippines (1,213) was conducted using normal distribution, variability index value (VIV), analysis of variation (ANOVA) and Ducan’s multiple range test (DMRT) based on the data obtained from NIRS analysis. According to the normal distribution, the average protein content was 7.9%, and non-glutinous rice ranging over 10% amylose had 23.6% average content. Most resources were between 5.3 and 10.5% in protein content, and 15.7 and 31.5% in amylose content. The VIV was 0.54 for protein, and 0.83 for amylose. The average amylose content was 25.18%, 24.54%, 22.08%, and 21.47% in Filipino, Chinese, Korean, and Japanese resources, respectively, wheereas the average protein content was found to be 8.19%, 7.79%, 7.58%, and 7.42% in Filipino, Chinese, Korean, and Japanese resources, respectively. The ANOVA of amylose and protein content showed significant differences at the level of 0.01. The F-test value was 412.2 for amylose content, and 108.4 for protein when compared with the critical value of 3.78. The DMRT of amylose and protein content showed significant differences (p<0.01) among resources from different countries. The Filipino resources had the highest level of amylose and protein content, whereas; the lowest level of amylose and protein content were found in Japanese when compared with resources of other origins. These results are recommended as helpful materials in the field of breeding.

Citations

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  • Year-independent prediction of rice grain protein content using machine learning with agronomy-aligned multi-year field data
    Hyun-Jin Jung, Yun-Ho Lee, ChungGen Lee, Seong-Woo Cho, Tae-Young Hwang
    Frontiers in Plant Science.2026;[Epub]     CrossRef
  • Characterization of Quality-Related Traits and Pasting Properties of Early Maturing Rice Varieties by Cultivation Times in the Honam Plain, Korea
    Hyun-Su Park, Man-Kee Baek, Chang-Min Lee, Suk-Man Kim, Jung-Pil Suh, O-Young Jeong, Young-Chan Cho
    Korean Journal of Breeding Science.2021; 53(1): 1.     CrossRef
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