Volatile compounds from 90 Italian citrus honeys of different varieties (lemon, Citrus limon (L.)30 Burm., orange, Citrus sinensis (L.) Osbeck, and citrus, Citrus spp.), 30 provided by CRA-API31 (Consiglio per la Ricerca e la Sperimentazione in Agricoltura-Unità di ricerca di apicoltura e32 bachicoltura) (Bologna, Italy) and 60 purchased on the local markets, were analysed in order to33 classify them according to the characteristic aroma profiles. The HS-SPME-GC method previously34 developed and validated in our laboratory was applied. Factor Analysis and General Discriminant35 Analysis were carried out on peaks and intensity data for the honey samples classification.36 Statistical analyses revealed a good separation between honey samples, the best model indeed37 shows a 66.5% of total variance explained by the first canonical function (CF1) and a predictive38 capacity of 78.9%. The most significant compounds responsible for the observed separation were39 assigned to lilacaldehyde isomers, 1-p-menthen-9-al isomers, dill ether, limonene, limonen-10-ol40 and undecanal.
Use of HS-SPME-GC-MS for the classification of Italian lemon, orange and citrus spp. honeys / Papotti, Giulia; Bertelli, Davide; Plessi, Maria. - In: INTERNATIONAL JOURNAL OF FOOD SCIENCE & TECHNOLOGY. - ISSN 0950-5423. - STAMPA. - 47:11(2012), pp. 2352-2358. [10.1111/j.1365-2621.2012.03109.x]
Use of HS-SPME-GC-MS for the classification of Italian lemon, orange and citrus spp. honeys
PAPOTTI, GIULIA;BERTELLI, Davide;PLESSI, Maria
2012
Abstract
Volatile compounds from 90 Italian citrus honeys of different varieties (lemon, Citrus limon (L.)30 Burm., orange, Citrus sinensis (L.) Osbeck, and citrus, Citrus spp.), 30 provided by CRA-API31 (Consiglio per la Ricerca e la Sperimentazione in Agricoltura-Unità di ricerca di apicoltura e32 bachicoltura) (Bologna, Italy) and 60 purchased on the local markets, were analysed in order to33 classify them according to the characteristic aroma profiles. The HS-SPME-GC method previously34 developed and validated in our laboratory was applied. Factor Analysis and General Discriminant35 Analysis were carried out on peaks and intensity data for the honey samples classification.36 Statistical analyses revealed a good separation between honey samples, the best model indeed37 shows a 66.5% of total variance explained by the first canonical function (CF1) and a predictive38 capacity of 78.9%. The most significant compounds responsible for the observed separation were39 assigned to lilacaldehyde isomers, 1-p-menthen-9-al isomers, dill ether, limonene, limonen-10-ol40 and undecanal.File | Dimensione | Formato | |
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