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通过挥发性和细胞壁组件的数据科学和风味学来解读来自贵州的蜂蜜甜味的烟草烟草

Risheng Zhong¹, Zhenchun Sun², Liang Feng¹

¹Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Key Laboratory of Flavor Chemistry, Beijing Technology and Business University (BTBU), Beijing, China.

Frontiers in chemistry

|October 17, 2025

概括

烟雾制烟草 (FCT) 的香味因原产地和品种而异. 这项研究使用了机器学习的挥发物和细胞壁组件来识别关键的芳香化合物,成功地区分了FCT的起源和质量.

科学领域:

农业化学农业化学
植物生物化学植物生物化学
感官科学感官科学

背景情况:

烟烟草 (FCT) 的香味受其地理来源和叶子等级的影响.
了解这些差异对于质量评估和市场差异化至关重要.

研究的目的:

用挥发性化合物和植物细胞壁组件 (CWC) 来区分FCT的风味类型和等级.
确定关键的芳香化合物,负责贵州FCT独特的蜂蜜甜味.
开发用于FCT来源和质量评估的机器学习模型.

主要方法:

使用头空间固相微提取气色谱/质谱分析了挥发性物质.
植物细胞壁的成分 (纤维素,半纤维素,点氨酸,素) 被量化.
多变量分析 (PCA,OPLS-DA,LR) 和机器学习模型用于差异化.

主要成果:

上叶烟草 (等级B) 的挥发性水平高于中间叶 (等级C).
确定了27个关键的挥发性物质用于FCT香味分化.
确定β-cyclocitral和1-nonanal是贵州蜜糖FCT的关键芳香化合物.
机器学习模型在区分FCT来源方面达到高达96.5%的准确性.

结论:

这项研究成功地将机器学习与感官科学相结合,以解码FCT香味.
该方法为评估烟草质量和香味特征提供了一种新方法.
确定的挥发性生物标志物将区域地形与贵州FCT独特的风味特征联系起来.

关键词:

分析分析分析气味类型气味类型气味类型细胞壁的组成部分味道味道味道味道烟制烟草的烟制烟草是用烟制成的一个不稳定的波动性.

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