Comparative study of wine tannin classification using Fourier transform mid-infrared spectrometry and sensory analysis.
Wine tannins are fundamental to the determination of wine quality. However, the chemical and sensorial analysis of these compounds is not straightforward and a simple and rapid technique is necessary. We analyzed the mid-infrared spectra of white, red, and model wines spiked with known amounts of skin or seed tannins, collected using Fourier transform mid-infrared (FT-MIR) transmission spectroscopy (400-4000 cm(-1)). The spectral data were classified according to their tannin source, skin or seed, and tannin concentration by means of discriminant analysis (DA) and soft independent modeling of class analogy (SIMCA) to obtain a probabilistic classification. Wines were also classified sensorially by a trained panel and compared with FT-MIR. SIMCA models gave the most accurate classification (over 97%) and prediction (over 60%) among the wine samples. The prediction was increased (over 73%) using the leave-one-out cross-validation technique. Sensory classification of the wines was less accurate than that obtained with FT-MIR and SIMCA. Overall, these results show the potential of FT-MIR spectroscopy, in combination with adequate statistical tools, to discriminate wines with different tannin levels.
Fernández
Katherina
K
Department of Chemical Engineering and Bio-Processes, Pontificia Universidad Católica de Chile, Santiago, Chile.
Labarca
Ximena
X
Bordeu
Edmundo
E
Guesalaga
Andrés
A
Agosin
Eduardo
E
D019295:Computational Biology; D016002:Discriminant Analysis; D009812:Odorants; D012684:Sensory Thresholds; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*; D013634:Tannins / Q000032:analysis* / Q000145:classification; D013649:Taste; D027843:Vitis / Q000737:chemistry; D014920:Wine / Q000032:analysis* / Q000145:classification*
D013634:Tannins