基于多指标化学组分分析的山葡萄种质资源品质评价研究

项目名称： 基于多指标化学组分分析的山葡萄种质资源品质评价研究

项目编号： No.31500269

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 生物科学

项目作者： 刘炎

作者单位： 中国农业科学院特产研究所

项目金额： 18万元

中文摘要： 山葡萄主要分布于我国东北地区，其浆果含有多种有益成分，具有很高的应用和经济价值。现有的山葡萄品质评价主要从糖度、酸度、单宁含量、色价等方面进行，很难做出快速、精确的质量分析。因此选择现代分析手段，对山葡萄种质资源进行科学的评价与筛选，深度挖掘其品质特性是一项十分有意义的工作。本项目在现有品质评价方法基础上，着眼于山葡萄功能性组分、香气组分、口感组分，采用现代质谱技术、色谱-质谱联用技术、植物化学成分指纹图谱技术并结合化学计量学模式识别分析，对山葡萄从多指标化学成分组成层面进行品质评价。所建立的方法在灵敏度、精确度、稳定性以及重现性等方面均能较现有评价手段有很大程度的技术提升。研究成果能够为山葡萄种质资源的品质评价、发掘以及深度利用提供科学指导，同时能够拓展质谱等现代分析技术在植物资源复杂体系中直接、高通量分析研究的应用，为植物种质资源研究提供新方法。

中文关键词： 山葡萄；种质资源；品质评价；多指标化学组分；指纹图谱

英文摘要： Vitis amurensis Rupr is one kind of wild fruit trees in northeast China, the berries of it contain variety of beneficial ingredients which show the great application and economic value. The routine quality evaluation methods of Vitis amurensis Rupr are from sugar content, acidity, tannins content and colour value, etc. It is very hard to analyze the quality rapidly and accurately. So it is of great significance to apply modern analytical techniques for Vitis amurensis Rupr germplasm resources quality evaluation and variety screening, and to explore the quality characteristics of it deeply. This project is focus on the functional, aroma and flavor chemical components of Vitis amurensis Rupr. By using modern mass spectrometry, HPLC-MS, GC-MS, fingerprints of chemical components, chemometrics and statistics the quality of Vitis amurensis Rupr can be evaluated. Comparing to the existing methods this new developed one could show much better sensitivity, accuracy, stability and repeatability. The achievements of this research will provide the scientific guidances for quality control and evaluation, exploration and utilization of Vitis amurensis Rupr. The application of modern analytical techniques such as MS in the field of plant resources complicated system direct and high throughput analysis is expanded. Some new methods can be provided for the research of plant germplasm resources.

英文关键词： Vitis amurensis Rupr;germplasm resources;quality evaluation;multiple attribute chemical components;fingerprint