Feasibility of using colorimetric devices for whole and ground coffee roasting degrees prediction

Abstract

BACKGROUNCoffee roasting is one of the crucial steps in obtaining a high‐quality product as it forms the product's color and flavor characteristics. Roast control is made by visual inspection or traditional instruments such as the Agtron spectrophotometer, which can have high implementation costs. Therefore, the present study evaluated colorimetric approaches (a bench colorimeter, smartphone digital images, and a colorimetric sensor) to predict the Agtron roasting degrees of whole and ground coffee. Two calibration approaches were assessed, i.e., Multiple Linear Regression (MLR) and Least‐Squares Support Vector Machine (LS‐SVM). For that, 70 samples of whole and ground roasted coffees comprising the Agtron roasting range were prepared.RESULTSThe results showed that all three colorimetric acquisition types were efficient for the model building, but the bench colorimeter and the smartphone digital images generally performed with great determination coefficients and low errors as measured by external validation. For the whole bean coffee, the best model presented an R2 of 0.99 and RMSE of 1.91%, while R2 of 0.99 and RMSE of 0.87% was obtained for ground coffee, both using the colorimeter.CONCLUSIONThe obtained models presented good prediction capability, as assessed by external validation and randomization tests. The obtained findings point to an alternative for coffee roasting monitoring that can lead to higher digitalization and local control of the process, even for smaller producers, due to its lower costs.This article is protected by copyright. All rights reserved.