Development of FT-NIR Technique to Determine the Ripeness of Sweet Cherries and Sour Cherries

The FT-NIR technique was used for the rapid and non-destructive determination of sweet cherry and sour cherry ripeness. Titratable acidity (A), water-soluble total solids (SSC), total anthocyanin (TA) content and calculated maturity index (SSC/A = MI) were used as reference values. PLS correlations were validated by seven-fold cross-validation (RMSECV for different parameters: DM = 1.25%, w/w; A = 0.14%, w/w; SSC = 0.97%, w/w; TA = 17.5 g/100 mL; MI = 1.66) and testvalidation (RMSEP for different parameters: DM = 1.46%, w/w; A = 0.19%, w/w; SSC = 0.99%, w/w; TA = 17.5 g/100 mL; MI = 1.59). Different discriminant analyses and support vector machine (SVM) classifications were performed for each parameter. The quadratic discriminant analysis (QDA) was found to be the best pattern recognition method. A maturity degree (MD) was developed based on the reference values, which classified the samples into mature and immature categories with an accuracy of 98.44%.

Automated summary

The FT-NIR technique was applied to determine the ripeness of sweet cherry and sour cherry rapidly and non-destructively. Titratable acidity, water-soluble total solids, total anthocyanin content, and calculated maturity index were used as reference values. The study validated the PLS correlations through cross-validation and test-validation methods and performed different discriminant analyses and support vector machine classifications. Quadratic discriminant analysis was found to be the best pattern recognition method. Additionally, a maturity degree was developed for accurate classification of mature and immature samples.