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江西安兴白生产的数字化转型:整合风味化合物分析,机器学习识别和遗传算法混合多轮的混合

Xiaotong Lyu¹, Qi Jiang¹, Kemin Linghu¹

¹State Key Laboratory of Food Nutrition and Safety, Key Laboratory of Industrial Fermentation Microbiology, Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, College of Biotechnology, Tianjin University of Science and Technology, Tianjin 300457, PR China.

Food research international (Ottawa, Ont.)

|March 7, 2026

概括

这项研究介绍了江西安兴白江的数字混合,使用风味和智能模型. 一种遗传算法模型优化了混合,以获得一致的风味配置.

科学领域:

食品科学食品科学食品科学
分析化学分析化学
计算化学计算化学

背景情况:

江西安兴的Baijiu混合依赖于传统方法,具有复杂的风味变化.
了解挥发性和非挥发性化合物对于一致的风味概况至关重要.

研究的目的:

开发数字辅助的混合方法,用于江西安兴 Baijiu.
识别特征性风味描述符并分析化合物变异.
创建智能模型,以准确识别和优化混合.

主要方法:

在不同的蒸轮中进行了感觉分析和风味分析.
使用了8个传感器的电子鼻子和染色学数据.
机器学习和基于遗传算法的模型被开发用于识别和混合优化.

主要成果:

确定了特有的风味描述符.
风味组学分析揭示了化合物类型,度和变化模式.
一个机器学习模型准确地识别了蒸轮,一个遗传算法模型优化了混合.

结论:

经过感官和染色学分析验证的遗传算法模型对于江西兴白混合来说是优越的.
这项研究为数字化改造传统的Baijiu混合技术提供了科学基础.

关键词:

州混合混合的混合物电子鼻子电子鼻子遗传算法遗传算法遗传算法江西安兴市江西安兴市机器学习机器学习不易挥发的化合物不易挥发的化合物挥发性化合物挥发性化合物

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