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根据NIRS和MS方法阐明的PDO属性,估计基于matcha的感觉相关代谢物概况

Yan Chen¹, Xiaoyao Xie¹, Zhirui Wen¹

¹Guizhou Key Laboratory of Information and Computing Science, Guizhou Normal University, 116 Baoshan North Rd, Guiyang, Guizhou, 550001, China.

|November 29, 2023

概括

这项研究使用近红外光谱学 (NIRS) 和液体染色学-质谱学 (LC-MS) 来验证受保护原产地名称 (PDO) 匹配的真实性. 这些方法可以准确地预测感官属性,并识别关键的风味化合物,确保抹茶的质量和来源.

科学领域:

食品科学食品科学食品科学
分析化学分析化学
感官科学感官科学

背景情况:

抹茶因其独特的风味和香气而受到全球的重视,正在经历消费者和行业的新兴兴趣,特别是受保护原产地名称 (PDO) 认证的品种.
评估抹茶的独特感官感知存在重大挑战.
验证具有PDO认证的抹茶的原产地和质量对于消费者信任和行业标准至关重要.

研究的目的:

用先进的分析平台来确定来自贵州的PDO认证抹茶的原产地.
根据其化学成分开发matcha感官属性和风味特征的预测模型.
为了确定导致抹茶品质和风味强度变化的关键代谢物.

主要方法:

接近红外光谱 (NIRS) 与竞争性自适应重量化采样-部分最小方程 (CARS-PLS) 结合,用于信息波长选择.
液体染色学-质谱学 (LC-MS) 用于非向的代谢分析.
网络分析以探索感官属性,代谢物和光谱数据之间的相互关联.

主要成果:

对五个感官属性的预测模型的准确度超过0.9,粒子均性达到0.9668.8的验证相关系数.
LC-MS分析确定了与抹茶品质和风味强度相关的主要风味化合物和关键成分.
在感官属性,代谢物和信息波长之间发现了显著的三向相互关联.

结论:

整合NIRS和LC-MS提供了一个强大的框架,用于验证PDO抹茶的真实性,并预测其感官特征.
化学成分数据,当与感觉面板数据相关联时,可以开发可靠的预测模型,用于matcha风味配置文件.
这项研究为抹茶行业的质量控制和原产地验证提供了宝贵的见解.

关键词:

化学测量化学测量化学测量代谢物进行分析.被保护的原产地名称抹茶感官分析是一种感官分析.味觉活性化合物味觉活性化合物

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