基于电子鼻技术鉴别陇南初榨橄榄油

为了快速简便地鉴别同一品种不同果实成熟度和不同品种同一果实成熟度的初榨橄榄油，运用电子鼻传感器分析技术结合Loadings负荷加载分析、线性判别分析（LDA）等数据处理技术对结果图谱进行解析，并通过欧氏距离分析（EDA）、相关性分析（CA）、马氏距离分析（MDA）和判别函数分析（DFA）验证模型的准确性。结果显示：电子鼻响应值雷达图及Loadings负荷加载分析均表明W5S、W2W、W1W、W1S传感器对样品有较好的信号响应，通过LDA分析建立的特征图谱可有效鉴别区分被试样品，其识别确定性大于96%，所建模型准确可靠，电子鼻技术可用于同一品种不同果实成熟度和不同品种同一果实成熟度初榨橄榄油的识别。

Identification of Longnan Virgin Olive Oil Based on Electronic Nose Technology

In order to more quickly and effectively identify virgin the olive oil with different fruit maturities of the same variety and the same fruit maturity of different varieties, the electronic nose sensor technology combined with loadings analysis and linear discriminant analysis (LDA) were used to parse the results mapping data. The accuracy of the models was verified by Euclidean distance analysis (EDA), correlation analysis (CA), Mahalanobis distance analysis (MDA) and discriminant function analysis (DFA). The radar graph of electronic nose response value and loading analysis showed that electronic nose sensor of W5S, W2W, W1W, W1S had excellent response signals to the olive oil samples. The feature map model established by LDA could effectively distinguish and identify the participant sample, and the identification certainty was greater than 96%. The established model is accurate and reliable. Electronic nose technology can be used for the identification of virgin olive oil with different fruit maturities of the same variety and the same fruit maturity of different varieties.