Cascos Gema, Lozano Jesús, Montero-Fernández Ismael, Marcía-Fuentes Jhunior Abrahan, Aleman Ricardo S, Ruiz-Canales Antonio, Martín-Vertedor Daniel
Technological Institute of Food and Agriculture CICYTEX-INTAEX, Junta of Extremadura, Avda Adolfo Suárez s/n, 06007 Badajoz, Spain.
Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain.
Foods. 2023 Dec 26;13(1):87. doi: 10.3390/foods13010087.
The aim of this work is to discriminate between the volatile org9anic compound (VOC) characteristics of different qualities of green coffee beans () using two analysis approaches to classify the fresh product. High-quality coffee presented the highest values for positive attributes, the highest of which being fruity, herbal, and sweet. Low-quality samples showed negative attributes related to roasted, smoky, and abnormal fermentation. Alcohols and aromatic compounds were most abundant in the high-quality samples, while carboxylic acids, pyrazines, and pyridines were most abundant in the samples of low quality. The VOCs with positive attributes were phenylethyl alcohol, nonanal and 2-methyl-propanoic acid, and octyl ester, while those with negative attributes were pyridine, octanoic acid, and dimethyl sulfide. The aroma quality of fresh coffee beans was also discriminated using E-nose instruments. The PLS-DA model obtained from the E-nose data was able to classify the different qualities of green coffee beans and explained 96.9% of the total variance. A PLS chemometric approach was evaluated for quantifying the fruity aroma of the green coffee beans, obtaining an RP2 of 0.88. Thus, it can be concluded that the E-nose represents an accurate, inexpensive, and non-destructive device for discriminating between different coffee qualities during processing.
这项工作的目的是使用两种分析方法对新鲜产品进行分类,以区分不同品质的生咖啡豆的挥发性有机化合物(VOC)特征。高品质咖啡的正面属性值最高,其中最高的是果香、草本香和甜味。低品质样品显示出与烘焙、烟熏和异常发酵相关的负面属性。高品质样品中醇类和芳香族化合物含量最高,而低品质样品中羧酸、吡嗪和吡啶含量最高。具有正面属性的挥发性有机化合物是苯乙醇、壬醛、2-甲基丙酸辛酯,而具有负面属性的是吡啶、辛酸和二甲基硫醚。还使用电子鼻仪器区分了新鲜咖啡豆的香气质量。从电子鼻数据获得的偏最小二乘判别分析(PLS-DA)模型能够对不同品质的生咖啡豆进行分类,并解释了总方差的96.9%。评估了一种偏最小二乘化学计量学方法来量化生咖啡豆的果香,得到的决定系数(RP2)为0.88。因此,可以得出结论,电子鼻是一种在加工过程中区分不同咖啡品质的准确、廉价且无损的设备。