The present work aimed to carry out a preliminary study to verify the possibility of employing an optical, portable and inexpensive non-destructive device, based on vis/NIR, spectroscopy, directly on the production line of craft beer. Three types of craft beer were analyzed. For each type of craft beer, transflectance spectra were acquired in the wavelength range of 450-980 nm and at different stages of fermentation. Spectral sampling for each craft beer was conducted on filtered and non-filtered samples. The vis/NIR device was tested for the quick evaluation of soluble solid content (SSC) and pH. Spectra were elaborated in order to perform principal component analysis (PCA) and to build partial least square (PLS) regression models. The PCA results show that vis/NIR spectroscopy could be effective in discriminating between non-filtered (condition in the process line) and filtered samples. PLS models are promising for both the prediction of SSC and pH.

Rapid evaluation of craft beer quality during fermentation process by vis/NIR spectroscopy / V. Giovenzana, R. Beghi, R. Guidetti. - In: JOURNAL OF FOOD ENGINEERING. - ISSN 0260-8774. - 142(2014 Dec), pp. 80-86. [10.1016/j.jfoodeng.2014.06.017]

Rapid evaluation of craft beer quality during fermentation process by vis/NIR spectroscopy

V. Giovenzana
;
R. Beghi
Secondo
;
R. Guidetti
Ultimo
2014

Abstract

The present work aimed to carry out a preliminary study to verify the possibility of employing an optical, portable and inexpensive non-destructive device, based on vis/NIR, spectroscopy, directly on the production line of craft beer. Three types of craft beer were analyzed. For each type of craft beer, transflectance spectra were acquired in the wavelength range of 450-980 nm and at different stages of fermentation. Spectral sampling for each craft beer was conducted on filtered and non-filtered samples. The vis/NIR device was tested for the quick evaluation of soluble solid content (SSC) and pH. Spectra were elaborated in order to perform principal component analysis (PCA) and to build partial least square (PLS) regression models. The PCA results show that vis/NIR spectroscopy could be effective in discriminating between non-filtered (condition in the process line) and filtered samples. PLS models are promising for both the prediction of SSC and pH.
Vis/NIR spectroscopy; Craft beer; Quick quality evaluation; Chemometrics
Settore AGR/09 - Meccanica Agraria
dic-2014
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/236717
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