Development of a Simple and Rapid Method for Color Determination in Beers Using Digital Images

摘要

Color is an important sensory parameter required for the quality control of beers. A new multivariate image analysis method for the color determination of beers was proposed and validated. Reference color values were determined using the SRM (standard reference method) system, which is based on absorbance measurements at 430 nm. Digital images were obtained with an iPhone 7 smartphone. The obtained RGB histograms were used for building partial least squares (PLS) models. The developed method is direct, simple, and rapid, not requiring sample pretreatment steps as the reference method. Beer samples of different styles, brands, and brewery companies were obtained in a large variety, totalizing 128 samples and comprising a range from 3 to 130 SRM units. A global PLS model built with all the beer samples presented too large prediction errors for some samples in the lower part of the SRM scale (below 12 units). Thus, considering the requirement of dilution prescribed by the reference method for samples with absorbances higher than 1.0, two local calibration models were built: for high SRM range (above 12 units) and low SRM range (equal or below 12 units) samples. A previous PLS discriminant analysis (PLS-DA) model was used to assign the beer samples to these two classes, resulting in 78 and 50 samples in the high- and low-range models, respectively. These two models were validated according to the Brazilian and international guidelines, being considered linear, accurate, precise, and unbiased. Uncertainties were also calculated for estimating confidence intervals for the predictions of the validation samples. The developed method could be easily adapted in a mobile platform, spreading its use and opening the possibility for the commercial production of a dedicated equipment.