食品加工中的风湿学分析:机器学习集成的因素,应用和未来前景
Yang Chen1,2, Honglin Zhu2, Yihang Feng2
1Key Laboratory of Food Nutrition and Functional Food of Hainan Province, School of Food Science and Engineering, Hainan University No. 58 Renmin Road Haikou 570228 China zhwm1979@163.com.
RSC advances
|January 26, 2026
概括
食品风湿学,食品流动和变形的研究,通过机器学习 (ML) 得到了增强. 整合ML与食品类病理学,通过先进分析优化产品质量和加工.
科学领域:
- 食品科学与技术 食品科学与技术
- 类风病学 类风病学 类风病学
- 机器学习应用 机器学习应用
背景情况:
- 食品风学对于确定质地,味道,稳定性和整体质量至关重要.
- 复杂的食品生产和市场需求需要先进的表征方法.
- 机器学习 (ML) 为分析复杂的食品系统提供了强大的工具.
研究的目的:
- 审查机器学习与食品风湿学的整合.
- 检查ML在纹理分析中的应用 (大和小变形类风学).
- 总结影响食品风学和成分相互作用的因素.
主要方法:
- 审查现有的关于食品气动学和机器学习的文献.
- 分析风学测量,包括大小变形.
- 机器学习算法的探索,用于rheological数据分析.
主要成果:
- 机器学习可以有效地预测和分析食物的质性质.
- 整合ML与风病学辅助在食品流分析和变形特征.
- ML有助于优化产品配方,过程监控和感官分析.
结论:
- 机器学习显著增强了食品风学的表征和优化.
- 尽管面临着大量数据集和复杂条件的挑战,但ML显示出高效率.
- 进一步开发基于ML的风湿学方法对食品行业有很大的潜力.
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