纳米卟啉多元光谱阵列传感器可控制备及对名优绿茶风味品质协同调控研究

Contraposing some key scientific problems existed in flavor quality control of famous green tea, such as unclear dose-effect synergistic relationship in flavor multi-components, ambiguous correlation between aroma type and taste characteristics, and difficulty in accurately identifying and simultaneous quantifying for trace components with similar structures of green tea. To tackle such problems, the current project aims to prepare a nano-porphyrin multivariate spectral array sensor with high sensitivity, selectivity and resolution properties, which can produce accurate response signals for the differences of flavor component clusters in famous green tea. And the pattern recognition methods and high-order calibration methods with function of mathematical separation can be adopted to interpret the combined sensor signals, which will help to achieve simultaneous identification and direct quantification for flavor multi-components of the famous green tea, further expound the dose-effect relationship of synergized flavor-influencing multi-components and the correlation between aroma type and taste characteristics, and reveal the dose-effect and composition-activity rule for the flavor quality of famous green tea. It can be used to guide the simulation and reconstruction of flavor characteristics, facilitating effective regulation and control of aroma and the taste of famous green tea. The research content has not been reported previously and the results can contribute to clarify the regulation of qualitative and quantitative synergistic control for inherent multi-components and external characteristics of the famous green tea, which will enrich and develop the theories on compounding of fine chemicals as well as quality regulation and control, and promote the cross-industry application of characteristic green tea aroma and flavor control to the food and fine chemical industries.

针对目前名优绿茶风味品质调控研究中存在风味成分群协同量效关系不清楚、香型和滋味特征间相关性不明确，难以准确识别和同时定量结构相似的微痕量风味成分等关键科学问题，本项目通过设计制备一种兼具高灵敏度、高选择性、高分辨力的纳米卟啉多元光谱阵列传感器，使其对名优绿茶特征风味成分群差异产生准确的响应信号，再借助模式识别和具有数学分离功能的高阶校正方法对其传感组合信号进行解析，实现名优绿茶特征风味成分群的同时识别与快速定量，探明名优绿茶特征风味差异的内在成分群协同量效关系及香型和滋味特征间的相关性，揭示名优绿茶风味品质的量效-组效规律，并用其指导风味特征模拟与重构，实现名优绿茶风味品质有效调控，阐明名优绿茶风味内在成分组群和外在特征品质定性定量协同调控的规律。该思路尚未见文献报道。其研究结果有助于丰富和发展精细化工产品复配和品质调控的理论，促进绿茶特征香气和风味调控在食品、精细化工等行业中的跨界应用。

针对目前名优绿茶风味品质调控研究中存在风味成分群协同量效关系不清楚、香型和滋味特征间相关性不明确，难以准确识别和同时定量结构相似的微痕量风味成分以及影响绿茶安全性的农药和重金属等问题。本项目在GC-MS、HPLC-MS、UPLC-QTOF-MS等现代分离分析技术进行鉴定和定量分析基础上，开发了基于局部极小值结合稳健统计分析（LMV-RSA）的自动背景漂移校正、多尺度高斯平滑（MGSPE）色谱峰的自动提取、自动非靶标代谢谱分析（anTMPA）、自动数据分析策略（AntDAS）等新方法并将其用于绿茶风味成分群研究，通过量子化学计算模拟卟啉分子对接模型，设计制备一种高灵敏度、高选择性、高分辨力的纳米卟啉多元光谱阵列传感器，使其对名优绿茶特征风味成分群差异以及影响绿茶的农药和重金属产生准确的响应信号，利用化学计量学方法结合色谱/光谱数据对响应信号进行解析，探明名优绿茶特征风味差异的内在成分群协同量效关系。研究结果表明，10种特征香气成分对绿茶香气品质起主导作用，总贡献率达到98.00%；8种特征呈味成分对绿茶呈味品质起主导作用，总贡献率达到84.51%；12种特征风味成分对绿茶风味品质起主导作用，总贡献率达到93.06%。该研究结果促进了食品、精细化工等领域中物质的特征香气和风味调控及应用。本项目已完成研究计划中规定的各项任务，研究经费全部符合基金项目的财务要求。受本项目自助，已发表学术论文43篇，其中SCI收录论文39篇；授权中国发明专利10件；授权登记软件著作权5部，培养硕士毕业生5名（荣获校级优秀硕士学位论文4篇，并获得参评省级优秀硕士学位论文）；尚有4篇已撰写完成的论文拟投稿到SCI期刊。.本项目具体研究成果主要包括：（1）开发了多种色谱数据分析新方法；（2）制备了一种纳米卟啉多元光谱阵列传感器；（3）阐明名优绿茶风味成分群与风味品质协同量效-组效关系，明确绿茶风味品质调控机制。本项目研究结果为食品、精细化工等领域中的物质特征香气和风味调控研究提供了一种新的分析应用模式。