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Updated: Jan 25, 2026

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可解释机器学习集成风味分类与来源归因,用于优化低盐大豆

Xinyun Zhou1, Ting Guo1, Tongquan Li2

  • 1State Key Laboratory of Food Nutrition and Safety, Key Laboratory of Food Nutrition and Safety, Ministry of Education, College of Food Science and Engineering, Tianjin University of Science & Technology, Tianjin 300457, China.

Journal of agricultural and food chemistry
|January 23, 2026
PubMed
概括

开发具有增强风味的低盐大豆 (LSS) 是可能的. 一个集成的triomics模型确定了关键的挥发物和微生物,指导创建一个更健康的LSS,具有理想的感官配置文件.

关键词:
在MMVec中使用.在XGBoost中使用.低盐大豆是一种低盐的汁.机器学习是机器学习.感官挥发性微生物群地图

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