Fifteen micro-fermentation trials were conducted during the 2008 vintage harvest in the Valtellina (Northern Italy) viticultural area. During fermentation, the spectra were achieved in the near and mid-infrared region by a FT-NIR spectrometer and a FT-IR spectrometer, respectively. Samples were also analysed by using chemical methods to evaluate sugars (glucose and fructose), alcohols (ethanol and glycerol) and phenolic compounds (total phenolics, total anthocyanins and total flavonoids). The pretreated spectral data were processed using principal component analysis. After feature selection by the algorithm SELECT, linear discriminant analysis (LDA) was applied to spectral data as a classification technique, to predict the fermentation stage from initial to final phase. Moreover, partial least square regression was used to predict sugar content, ethanol, glycerol and phenolic compounds simultaneously. LDA results, characterised by a high percentage of correct classification (87% and 100% as average value in prediction for NIR and MIR spectroscopy, respectively), showed that samples belonging to a particular fermentation step could be correctly classified. Good calibration models for the prediction of the main compositional changes during alcoholic fermentation were obtained with both FT-NIR and FT-IR, suggesting that either instruments could be used to evaluate online and simultaneously these compounds in red wine.
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The authors wish to express their sincere thanks to Fondazione Fojanini (Sondrio) for carrying out the micro-fermentation trials and to Regione Lombardia for financial support of this project (VALORVI’, Valorizzazione e ottimizzazione delle filiere viticola e frutticola valtellinesi attraverso sistemi innovativi in postraccolta e trasformazioni ad alta qualità).
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Di Egidio, V., Sinelli, N., Giovanelli, G. et al. NIR and MIR spectroscopy as rapid methods to monitor red wine fermentation. Eur Food Res Technol 230, 947–955 (2010). https://doi.org/10.1007/s00217-010-1227-5
- Alcoholic fermentation
- NIR spectroscopy
- MIR spectroscopy
- Red wine
- Process monitoring