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• W1836231398 abstract "Banana undergoes significant quality indices and color transformations during shelf-life process, which in turn affect important chemical and physical characteristics for the organoleptic quality of banana. A computer vision system was implemented in order to evaluate color of banana in RGB, L*a*b* and HSV color spaces, and changes in color features of banana during shelf-life were employed for the quantitative prediction of quality indices. The radial basis function (RBF) was applied as the kernel function of support vector regression (SVR) and the color features, in different color spaces, were selected as the inputs of the model, being determined total soluble solids, pH, titratable acidity and firmness as the output. Experimental results provided an improvement in predictive accuracy as compared with those obtained by using artificial neural network (ANN)." @default.
• W1836231398 created "2016-06-24" @default.
• W1836231398 creator A5002026477 @default.
• W1836231398 creator A5007972777 @default.
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• W1836231398 date "2016-02-01" @default.
• W1836231398 modified "2023-10-16" @default.
• W1836231398 title "Prediction of banana quality indices from color features using support vector regression" @default.
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• W1836231398 doi "https://doi.org/10.1016/j.talanta.2015.10.073" @default.
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• W1836231398 hasPublicationYear "2016" @default.
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