【作者】 徐贤； 顾振宇；

【Author】 Xu Xian;Gu Zhenyu;College of Food Science and Biotechnology,Zhejiang Gongshang University;

【机构】 浙江工商大学食品与生物工程学院；

【摘要】 本文测定了不同品种(油菜蜜、洋槐蜜、椴树蜜)和不同类型(天然原料蜜、加工成熟蜜、天然成熟蜜)共9种蜂蜜的理化指标和多酚类物质含量,并采集了他们的电子鼻信息。采用主成分分析(PCA)分别对常规指标、电子鼻信息以及他们数据融合之后的整体信息进行了模式识别;偏最小二乘法(PLS)回归分析对电子鼻信息和每个常规指标分别建立数学模型。结果:常规指标可以对不同品种的蜂蜜分类识别;电子鼻技术可以对不同类型的蜂蜜分类识别;常规指标和电子鼻技术数据融合之后可以对本文研究的所有蜂蜜进行分类识别;电子鼻信息与蜂蜜的水分含量、可溶性固形物含量相关性较好。结论:常规指标和电子鼻信息可以用来分类识别不同种类的蜂蜜,这为解决蜂蜜品种鉴别、品质评价提供了重要的参考依据。电子鼻可以直接用来预测蜂蜜的水分含量、可溶性固形物含量等指标。更多还原

【Abstract】 [Objective]Electronic nose technology is applied to discriminate different honeys according to their conventional parameters.[Methods]The discrimination of different honeys was carried out according to some physicochemical parameters and phenolic compounds based on electronic nose technology.A total of9 honeys,which are differed from botanical origin(rape,acacia,linden) and processing methods(raw honey by nature,mature by processing,mature by nature),were analysed.Principal component analysis(PCA) and partial least square(PLS) regression were used to highlight the data structure and to find the relationship between the conventional parameters and electronic nose signals.[Results]Conventional parameters can classify honeys of different botanical origin.Electronic nose technology can identify honeys from different processing methods.All kinds of these honeys can be determined after data fusion.Electronic nose signals have a good correlation with moisture and soluble solids.[Conclusions]It is a powerful reference to fight with honey adulteration.更多还原