This paper presents an experiment making use of the near-infrared spectrum for distinguishing the wines produced in two close provinces of Abruzzo region of Italy. A collection of 32 wines was considered, 18 of which were produced in the province of Chieti, while the other 14 were from the province of Teramo. A conventional dual-beam spectrophotometer was used for absorption measurements in the 1300-1900 nm spectroscopic range. Principal Component Analysis was used for explorative analysis. Score maps in the PC1-PC2 or PC2-PC3 spaces were obtained, which successfully grouped the wine samples in two distinct clusters, corresponding to Chieti and Teramo provinces, respectively. A modelling of dual-band spectroscopy was also proposed, making use of two LEDs for illumination and a PIN detector instead of the spectrometer. These data were processed using Linear Discriminant Analysis which demonstrated satisfactory classification results. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Near-infrared spectroscopy and pattern-recognition processing for classifying wines of two Italian provinces
CICHELLI, Angelo
2014-01-01
Abstract
This paper presents an experiment making use of the near-infrared spectrum for distinguishing the wines produced in two close provinces of Abruzzo region of Italy. A collection of 32 wines was considered, 18 of which were produced in the province of Chieti, while the other 14 were from the province of Teramo. A conventional dual-beam spectrophotometer was used for absorption measurements in the 1300-1900 nm spectroscopic range. Principal Component Analysis was used for explorative analysis. Score maps in the PC1-PC2 or PC2-PC3 spaces were obtained, which successfully grouped the wine samples in two distinct clusters, corresponding to Chieti and Teramo provinces, respectively. A modelling of dual-band spectroscopy was also proposed, making use of two LEDs for illumination and a PIN detector instead of the spectrometer. These data were processed using Linear Discriminant Analysis which demonstrated satisfactory classification results. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
