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优化草风味的综合策略:从分子生物合成到数据驱动的质量控制

Qian Luo¹, Ting Li², Huanlu Song²

¹Institute of Quality Standard and Testing Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, PR China; Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, and Laboratory of Risk Assessment for Processed Agro-food Quality and Safety, Ministry of Agriculture (Beijing), Beijing 100193, PR China.

|March 12, 2026

概括

本综述探讨了草风味化合物,挥发性有机化合物 (VOC) 以及如何使用数据驱动的方法稳定它们从农场到餐桌,以确保一致的质量.

科学领域:

* 食品科学与技术 * 食品科学与技术
*植物生物化学 *植物生物化学
* 感官科学感官科学

背景情况:

* 由挥发性有机化合物 (VOC) 驱动的草风味对于消费者接受至关重要,但往往不一致.
*对VOC生物合成和保留的有限理解挑战了整个供应链的风味质量.
*水果发育,遗传学,环境,种植,收获后处理和加工都会影响VOC概况.

研究的目的:

*综合有关草VOC形成,调节和影响因素的当前知识.
* 提出一项综合战略,在整个生产过程中稳定草风味.
*强调基于数据的方法,用于预测性风味管理和实时监控.

主要方法:

* 关于草风味化学和影响因素的科学文献的全面审查.
* 集成高吞吐量分析,机器学习和感官/消费者数据.
*分子标记的应用用于现场风味动态的监测.
* 建议将非挥发性化合物 (NVOC) 纳入整体方法.

主要成果:

* 确定了影响草VOC概况的关键因素,包括本体发生,基因型与环境的相互作用和管理实践.
* 制定了一个产品范围内的干预策略框架,以稳定风味.
* 展示了机器学习和分子标记用于预测性风味管理的潜力.
*强调需要包括NVOC来全面了解风味.

结论:

* 数据驱动的策略,整合化学,技术和消费者感知,可以将经验风味管理转变为可量化和可扩展的范式.
* 稳定草风味需要采用整体方法,从种植到加工,应对各种因素.
*未来的研究应该集中于整合NVOC和先进的分析技术,以精确控制风味.

关键词:

生物合成生物合成味道的保存味道的保存机器学习机器学习多个omics的多个omics.收获后生理学收获后生理学感官分析是一种感官分析.草风味的草味道

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