使用氣相層析質譜技術為基礎，配合 LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) 電腦語言程式，使用模式識別 (pattern recognition) 的方法，開發出成功識別相似度的程式，可用以研究咖啡產區的辨識。透過計算參考樣品和標準樣品彼此之間的交叉相關係數 (cross correlation factor , CCF) 來估量相似度的值。在本程式中定義兩組圖譜的相似度， A 圖譜為標準品， B 圖譜為對照圖，相似度會在0%到100%之間。當 (A⋂B)/(A⋃B)=1 時，相似度為 100% ；當 (A⋂B)/(A⋃B)=0 時，相似度為 0% 。比對市面上5種咖啡豆在三種烘焙度下，同條件的情況下的氣相層析圖，發現在淺烘及深烘下，地區相近的咖啡豆有較高的相似度。自行開發的程式具有將相似度量化、簡單操作、快速得出結果等優點，且已成功應用在氣相層析圖譜的比對上。揮發性有機氣體在深烘焙下的滯留時間較長，煙霧產出的速度比揮發性有機氣體還快，並且似乎沒有同時夾帶揮發性有機氣體。

Using gas chromatography mass spectrometry technology as the basis, in conjunction with LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) computer language program, using pattern recognition method, developed a program to successfully identify similarity, which can be used to study the identification of coffee production areas . The similarity value is estimated by calculating the cross correlation factor (CCF) between the reference sample and the standard sample. In this program, define the similarity of two sets of maps. A-spectrum is the standard product and B-spectrum is the control image. The similarity will be between 0% and 100%. When (A⋂B)/(A⋃B)=1, the similarity is 100%; when (A⋂B)/(A⋃B)=0, the similarity is 0%. Taking the gas chromatogram of Arabica variety Kenya coffee beans as the standard spectrum, comparing the gas chromatogram of five kinds of coffee beans on the market under three roasting degrees and under the same conditions, it was found in light roasting and Under deep roasting, coffee beans in similar regions have a high degree of similarity. The self-developed program has the advantages of quantification of similarity, simple operation, and quick results, and has been successfully applied to the comparison of gas chromatogram. The residence time of volatile organic gas in deep roasting is longer, the smoke production rate is faster than that of volatile organic gas, and it does not seem to entrain volatile organic gas at the same time.

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