本文選題：光譜學　切入點：模型　出處：《農業(yè)工程學報》2017年09期 　論文類型：期刊論文

【摘要】：結合太赫茲時域光譜技術和支持向量機對3種典型產地的咖啡豆進行了鑒別。選取埃塞俄比亞(Ethiopia)、哥斯達黎加(Costa Rica)以及印度尼西亞(Indonesia)3個產地咖啡豆樣品進行壓片處理,采用太赫茲透射模式獲取樣品的時域和頻域光譜信號,并用主成分分析法對太赫茲頻域光譜信號進行分析;構造了基于粒子群(partical swarm optimization,PSO)參數尋優(yōu)的支持向量機(support vector machine,SVM)鑒別模型,模型對不同產地咖啡豆樣品的綜合識別正確率達到95%。試驗結果表明,太赫茲作為新型的檢測手段結合模式識別方法可用于咖啡豆的產地鑒別。該文為一類在太赫茲波段下沒有明顯特征吸收峰的農產品/食品安全檢測和產地追溯研究提供了一種快速、準確的方法。
[Abstract]:In combination with terahertz time-domain spectroscopy (THz) and support vector machine (SVM), the coffee beans from three typical areas were identified. The samples from Ethiopia (Ethiopia), Costa Rica (Costa Costa) and Indonesia (Indonesia) were treated by pressing. The time-domain and frequency-domain spectral signals of samples were obtained by terahertz transmission mode, and the spectral signals of terahertz frequency-domain were analyzed by principal component analysis (PCA). A support vector machine (SVM) discriminant model based on particle swarm optimization (PSO) parameters optimization was constructed. The comprehensive recognition accuracy of the model for coffee bean samples from different areas is 95%. The experimental results show that, Terahertz as a new detection method combined with pattern recognition can be used to identify the origin of coffee beans. This paper is a kind of agricultural products / food safety detection and origin traceability research without obvious absorption peak in terahertz band. The research provides a kind of rapidity, An accurate method.
【作者單位】： 合肥工業(yè)大學計算機與信息學院;合肥學院機器視覺與智能控制實驗室;合肥工業(yè)大學食品科學與工程學院;
【基金】：國家重點研發(fā)計劃項目(2016YFD0401104)
【分類號】：S571.2;TP18

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本文編號：1592686