Non-Destructive Determination of Adulteration Rate in Ground Coffee (Coffea arabica) using Chromameter Combined with Chemometrics

Authors : Yunus Emre Şekerli, Ahmet Zafer Aslan

Pages : 766-773

Doi:10.47115/bsagriculture.1765001

View : 85 | Download : 199

Publication Date : 2025-11-15

Article Type : Research Paper

Abstract :Roasted and ground coffee, owing to its high demand and commercial value, is often adulterated with cheaper materials to offset shortages or reduce costs. However, adulteration that could harm consumers economically or health-wise cannot be detected with the naked eye. For this reason, standard chemical analytical methods are generally preferred for detecting substances added to coffee for adulteration purposes. However, these methods also have some fundamental problems, such as being time-consuming, requiring pretreatment, requiring chemicals, being subjective, and often producing conflicting results. In this study, the success of determining the proportions of Robusta coffee, roasted soybeans, and carob flour mixed into Arabica coffee using color values was investigated in a practical, non-destructive, and objective manner without the need for chemical analysis methods. For samples adulterated with soy, L*a*b* values were used (RMSEP = 4.44%, R2val = 0.98), for samples adulterated with carob, L*a*b*C*h values were used (RMSEP=3.92%, R2val=0.98), and L*a*b*C*h values were used for samples adulterated with Robusta coffee (RMSEP=8.94%, R2val=0.91), resulting in successful prediction models. When the prediction models were evaluated in terms of RPD values, it was determined that all models had RPD values greater than 3, meaning that the prediction success rate for adulteration could be considered excellent. Based on the results obtained, it was observed that the proportions of soy, carob, and Robusta coffee added to Arabica coffee could be successfully determined in a short time using a colorimeter without causing any damage.
Keywords : Coffee, Adulteration, Chromameter, Proximal sensing, PLSR

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