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Exploratory and discriminative studies of commercial processed Brazilian coffees with different degrees of roasting and decaffeinated

机译:探索性和区分性研究对不同程度烘烤和脱咖啡因的巴西商业加工咖啡

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The fingerprints of the volatile compounds of 21 commercial Brazilian coffee samples submitted to different industrial processing i.e. decaffeinated or different roasting degrees (traditional and dark) were studied. The volatiles were collected by headspace solid phase microextraction (HS-SPME) and analyzed by GC-FID and GC-MS. The chromatographic data matrices (fingerprints) obtained were explored by the principal component analysis (PCA) and partial least squares - discriminative analysis (PLS-DA). Initially the chromatographic profiles were aligned by the algorithm correlation optimized warping (COW). The PCA showed the discrimination of the decaffeinated coffees from the others with both the SPME fibres used. This separation probably occurred due to the loss of some volatile precursors during the decaffeination process, such as sucrose. For both the fibres tested, PDMS/DVB and CX / PDMS SPME, the PLS-DA models correctly classified 100% of the samples according to their roasting degree: (medium and dark), the main differences being the concentrations of some of the volatile compounds such as 2-methyl furan, 2-methylbutanal, 2,3-pentanedione, pyrazine, 2-carboxyaldehyde pyrrole, furfural and 2-furanmethanol.
机译:研究了21种巴西咖啡样品中挥发性化合物的指纹图谱,这些样品经过了不同的工业处理,即脱咖啡因或不同的烘烤程度(传统和深色)。通过顶空固相微萃取(HS-SPME)收集挥发物,并通过GC-FID和GC-MS分析。通过主成分分析(PCA)和偏最小二乘-判别分析(PLS-DA)探索获得的色谱数据矩阵(指纹)。最初,色谱轮廓通过算法相关优化翘曲(COW)进行对齐。 PCA显示使用两种SPME纤维都可以将脱咖啡因的咖啡与其他咖啡区别开来。这种分离可能是由于在脱咖啡因过程中损失了某些挥发性前体(例如蔗糖)而发生的。对于被测试的两种纤维,PDMS / DVB和CX / PDMS SPME,PLS-DA模型根据其焙烧程度(中等和深色)正确分类了100%的样品:主要区别在于某些挥发性物质的浓度化合物,例如2-甲基呋喃,2-甲基丁醛,2,3-戊二酮,吡嗪,2-羧醛吡咯,糠醛和2-呋喃甲醇。

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