Bertrand Benoît, Villarreal Diana, Laffargue Andréina, Posada Huver, Lashermes Philippe, Dussert Stéphane
CIRAD, UMR RPB, 911 Avenue Agropolis, B.P. 64501, 34394 Montpellier Cedex 5, France.
J Agric Food Chem. 2008 Mar 26;56(6):2273-80. doi: 10.1021/jf073314f. Epub 2008 Feb 27.
The objective of this work was to compare the effectiveness of three chemical families, namely, chlorogenic acids, fatty acids, and elements, for the discrimination of Arabica varieties (traditional versus modern introgressed lines) and potential terroirs within a given coffee-growing area. The experimental design included three Colombian locations in full combination with five (one traditional and four introgressed) Arabica varieties and two field replications. Chlorogenic acids, fatty acids, and elements were analyzed in coffee bean samples by HPLC, GC, and ICP-AES, respectively. Principal component analysis and discriminant analysis were carried out to compare the three methods. Although elements provided an excellent classification of the three locations studied, this chemical class was useless for Arabica variety discrimination. Chlorogenic acids gave satisfactory results, but fatty acids clearly offered the best results for the determination of both varieties and environments, with very high percentages of correct classification (79 and 90%, respectively).
这项工作的目的是比较三大类化学物质,即绿原酸、脂肪酸和元素,用于区分阿拉比卡咖啡品种(传统品种与现代渐渗系)以及特定咖啡种植区域内潜在风土条件的有效性。实验设计包括三个哥伦比亚地区,与五个(一个传统品种和四个渐渗系品种)阿拉比卡咖啡品种进行全面组合,并设置两个田间重复。分别通过高效液相色谱法(HPLC)、气相色谱法(GC)和电感耦合等离子体发射光谱法(ICP - AES)对咖啡豆样品中的绿原酸、脂肪酸和元素进行分析。进行主成分分析和判别分析以比较这三种方法。尽管元素对所研究的三个地区进行了出色的分类,但这类化学物质对区分阿拉比卡咖啡品种毫无用处。绿原酸给出了令人满意的结果,但脂肪酸显然在品种和环境的测定方面都提供了最佳结果,正确分类的百分比非常高(分别为79%和90%)。