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Food Analytical Methods

, Volume 13, Issue 1, pp 303–312 | Cite as

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

  • Ana Carolina C. Fulgêncio
  • Vinícius P. T. Araújo
  • Hebert V. Pereira
  • Bruno G. Botelho
  • Marcelo M. SenaEmail author
Article
  • 83 Downloads

Abstract

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.

Keywords

RGB histograms Image analysis PLS Multivariate calibration Beer quality control Chemometrics 

Notes

Acknowledgments

The authors want to thank the Brazilian agencies CNPq, CAPES (Finance Code 001), and FAPEMIG for financial support. A. C. C. F., H. V. P., and V. P. T. A. particularly acknowledge fellowships from CAPES and CNPq.

Compliance with Ethical Standards

Conflict of Interest

Ana Carolina da Costa Fulgêncio declares that she has no conflict of interest. Vinícius Pires Teixeira Araújo declares that he has no conflict of interest. Hebert Vinícius Pereira declares that he has no conflict of interest. Bruno Gonçalves Botelho declares that he has no conflict of interest. Marcelo Martins Sena declares that he has no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed Consent

Not applicable.

Supplementary material

12161_2019_1634_MOESM1_ESM.docx (591 kb)
ESM 1 (DOCX 590 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Departamento de Química, ICExUniversidade Federal de Minas GeraisBelo HorizonteBrazil
  2. 2.Instituto Nacional de Ciência e Tecnologia em Bioanalítica (INCT Bio)CampinasBrazil

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