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Screening new breeding japonica rice varieties by rice quality, three processing characteristics, and odor characteristics.

Sailimuhan AsimiRen XinZhang MinLi SixuanQixin LvMeng Lingqi
Published in: Journal of food science (2022)
Rice's yield, cooking, and sensory quality are primary considerations in selecting new breeding rice varieties, which are determined by the rice eating quality such as processing and flavor characteristics. Thus, in this study, to advance the breed of new superior japonica rice varieties, the differences in the rice quality, processing characteristics, and flavor characteristics between 12 newly-bred varieties (H2-36, H2-42, H2-53, H2-59, H2-63, H2-73, H2-74, H2-79, H2-81, H2-82, H2-89, and H2-91) and 1 commercial variety (Kenyu38) were analyzed. The results indicated that H2-42 has a reasonable length-to-width ratio (1.51), high rice yield, good color, reasonable amylose, protein content, excellent water existence index, accessible storage, and the highest taste value. Electronic nose results showed significant differences in aldehydes, ketones, and alcohols among 13 rice varieties. Aroma analysis results showed that H2-42 had the highest n-hexanal (14.63 µg/kg), (E,E)-2,4-nonadienal (37.24 µg/kg), nonanal (19.93 µg/kg), and decanal (4.81 µg/kg); those were important aroma components in cooked rice. The Pearson correlation analysis showed that hardness, springiness, cohesiveness, trough viscosity, peak time, and pasting temperature were the crucial factors that affected rice quality. According to partial least squares regression analysis, total color change, final viscosity, setback, (E)-2-heptenal, and 2-methyl-undecanol were the most important factors that distinguished the rice quality. In conclusion, H2-42 rice was better apparent quality, processing characteristics, and aroma compounds. Therefore, H2-42 has the potential for identification and promotion. PRACTICAL APPLICATION: The results from this study will provide data support for the cultivation, application, and quality improvement of high-quality rice varieties. In addition, it gives new ideas and methods for studying rice eating quality.
Keyphrases
  • quality improvement
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  • magnetic resonance imaging
  • machine learning
  • weight loss
  • small molecule
  • electronic health record
  • big data
  • climate change
  • artificial intelligence