Optimization of the acquisition of NIR spectrum in grape must and wine
The characterization of chemical compounds related with quality of grape must and wine is relevant for the viticulture and enology fields. Analytical methods used for these analyses require expensive instrumentation as well as a long sample preparation processes and the use of chemical solvents. On the other hand, near-infrared (NIR) spectroscopy technique is a simple, fast and non-destructive method for the detection of chemical composition showing a fingerprint of the sample. It has been reported the potential of NIR spectroscopy to measure some enological parameters such as alcohol content, pH, organic acids, glycerol, reducing sugars and phenolic compounds.
This work focuses on the evaluation of the optimal parameters and pathlengths for fast measurement of the UV/VIS/NIR/MIR spectra in grape must and wine. The study was carried out with three different type of samples: (i) red wine cv Mencía, (ii) white wine cv Albariño, and (iii) grape must cv Albariño. Absorbance spectra were collected in rectangular quartz cuvettes of different optical pathlengths (1, 2, 5, and 10 mm) where different bandwidth parameters were tested.
The results indicated that increasing the optical pathlengths of the cuvettes increases the absorption intensity up to a saturation level (absorbance >2.5 units) at long wavelengths using long pathlengths (5 and 10 mm). The interpretation of the spectra also improves with 1 and 2 mm pathlengths. The bandwidth parameters evaluated indicated that using higher values, the spectrum appeared more defined, and the range of analysis was increased, reaching the MIR part of the spectrum. In conclusion, the best combination of pathlength and bandwidth for the measurement of grape must and wine in the UV/VIS/NIR/MIR range is 1 mm of pathlength cuvette with the bandwidth set at 40 nm.
Issue: ICGWS 2023
1 Instituto de Ciencias de la Vid y el Vino-ICVV (CSIC, UR, GR) 26007 Logroño (España)
2 Centre for Nutrition and Food Sciences (CNAFS), Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Brisbane, QLD 4072, (Australia)
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NIR, wine, must, cuvette, bandwidth