Journal
FOOD CHEMISTRY-X
Volume 14, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.fochx.2022.100325
Keywords
Multispectral imaging; Arabica coffee; Robusta coffee; Authenticity; Adulteration; Substitution
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In this study, multispectral imaging was used to accurately differentiate between Arabica and Robusta coffee beans and predict the level of adulteration between the two.
Arabica coffee beans are sold at twice the price, or more, compared to Robusta beans and consequently are susceptible to economically motivated adulteration by substitution. There is a need for rapid, non-destructive, and efficient analytical techniques for monitoring the authenticity of Arabica coffee beans in the supply chain. In this study, multispectral imaging (MSI) was applied to discriminate roasted Arabica and Robusta coffee beans and perform quantitative prediction of Arabica coffee bean adulteration with Robusta. The Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) model, built using selected spectral and morphological features from individual coffee beans, achieved 100% correct classification of the two coffee species in the test dataset. The OPLS regression model was able to successfully predict the level of adulteration of Arabica with Robusta. MSI analysis has potential as a rapid screening tool for the detection of fraud issues related to the authenticity of Arabica coffee beans.
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