摘要
【目的】利用电子鼻技术对不同贮藏时间的沃柑进行检测分析,为快速判断沃柑的新鲜度及建立沃柑品质快速评价体系提供技术支持。【方法】利用PEN3电子鼻系统获取不同贮藏时间沃柑的气味特征值,通过载荷分析法分析传感器对沃柑芳香物的相对重要作用,采用主成分分析(PCA)和线性判别分析(LDA)对气味特征值进行分析并建立预测模型,并以样品果对预测模型进行验证。【结果】不同贮藏时间的沃柑会产生不同气味响应信号,经载荷分析发现传感器7(W1W)、9(W2W)、6(W1S)、2(W5S)和8(W2S)在沃柑贮藏期识别中影响最大;建立模型时选取90～92 s时的稳定响应值作为特征值;采用PCA无法对贮藏间隔5 d的沃柑进行区分,而应用LDA能很好地区分不同贮藏时间的沃柑,总贡献率85.12%。预测模型能对样品果进行贮藏时间的初步判别,平均准确率达98.23%。【结论】电子鼻结合LDA的无损检测方法能对不同贮藏时间的沃柑气味特征进行识别并区分,可应用于沃柑贮藏时间快速判断。
【Objective】The electronic nose technique was used to detect the Orah of different storage times,and to provide technology support for the judgment of freshness degree of Orah and establishment of a rapid evaluation system for Orah quality.【Method】PEN3 electronic nose was used to obtain aroma characteristic value of Orah with different storage times.The relative important effects of sensors on Orah aromatic substance were analyzed by load analysis.Principal component analysis(PCA)and linear discriminant analysis(LDA)were applied to investigate the aroma characteristic values and establish the prediction model,then the prediction model was verified with samples.【Result】At different storage times,Orah produced different aroma response signals.It was found that sensor 7(W1W),9(W2W),6(W1S),2(W5S)and 8(W2S)had the largest effects on identification of Orah storage time by load analysis.The stable response value of 90-92 s was selected as the eigenvalue of the model.The PCA could not be used to distinguish Orah with a storage interval of 5 d.The LDA method could better distinguish the Orah with different storage times,and the total contribution rate was 85.12%.The prediction model could be used for the preliminary determination of sample fruit storage time,with an average accuracy of 98.23%.【Conclusion】Electronic nose combined with LDA nondestructive detection method can identify and distinguish the aroma characteristics of Orah at different storage times,which can be applied to rapid determination of Orah storage time.
作者
黎新荣
LI Xin-rong(Guangxi Subtropical Crops Research Institute,Nanning 530001,China)
出处
《南方农业学报》
CAS
CSCD
北大核心
2018年第9期1827-1832,共6页
Journal of Southern Agriculture
基金
广西创新驱动发展专项项目(桂科AA17204038)
