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Assessment of yerba mate quality based on branch content via digital image analysis
Thyago Mellinger Silva1, Sheila Catarina de Oliveira1, Paulo Henrique Gonçalves Dias Diniz2
1Group of Chemical Analysis and Chemometrics, Department of Chemistry, Federal University of Paraná, P.O. Box: 19032, Curitiba, PR 81531-980, Brazil.
None:
Yerba mate, a key crop in South America, is prized for its pleasant taste and high organoleptic quality, often linked to lower branch content. To quantify branch content and authenticate high-quality samples (less than 30 % m/m branch content), a Chemometrics-assisted Color Histogram-based Analytical System (CACHAS) was employed. Using Hue-Saturation-Value (HSV) histograms, Partial Least Squares (PLS) demonstrated excellent predictive performance, achieving a root mean square error (RMSEP) of 4.05 % m/m, a correlation coefficient (rpred) of 0.96, a performance-to-deviation ratio (RPD) of 3.64, and a relative error of prediction (REP) of only 10.79 %. Additionally, Data-Driven Soft Independent Modeling of Class Analogy (DD-SIMCA) yielded a sensitivity of 100 % and specificity of 91.2 % in the test set, with an overall efficiency of 96.4 %. In line with Green Chemistry principles, CACHAS emerged as an effective, environmentally friendly tool for the quality assessment and authentication of yerba mate.
