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The use of innovative techniques in the classification of dried products for food processing and packaging systems simplifies and brings objectivity to the related processes. In addition, it helps consumers to access quality products. This study aimed to discriminate dried carrot samples subjected to 12 different combinations of drying and pretreatment by using innovative techniques based on chromatic attributes. The drying procedure consists of three different microwave powers (100, 200, 300 W), and pretreatments include 5% gum arabic solution, 5% gum sucrose solution, ultrasound application, and a control (no-pretreatment). The R , G , B , L , a , b , H , S, and V color channels were extracted from dried carrot images, and the exploration of classification models from selected color channels was an innovative aspect of the study. In all color channels, high overall accuracies were obtained with the values of 96.33, 96.50, and 97.00% for the logistic model tree, k-nearest neighbor, and random forest, respectively. The confusion matrix showed the lowest mixing among carrots dried at H-US (300 W + ultrasound) vs. H-C (300 W + control), H-S (300 W + sucrose) vs. H-C (300 W + control), and M-S (200 W + sucrose) vs. H-S (300 W + sucrose). The highest L, a, and b color values for the dried carrot slices were obtained as M-S (75.26), H-GA (30.93), and M-GA (44.75), respectively. In addition, hue values varied between 17.26 and 13.27, whereas saturation values varied between 50.93 and 59.90. The finding revealed that assessment of the effect of pretreatment and drying on carrot slices could be performed by machine learning and image analysis in a practical, rapid, and non-destructive manner. • Eight different machine learning algorithms was applied for classification. • 12 carrot classes subjected to various treatments were distinguished. • Innovative models built based on image textures were developed. • LMT, kNN, and RF was more successful for classification of dried carrot slices. • The developed procedure was non-destructive, objective, and effective. [ABSTRACT FROM AUTHOR]

The effect of fish diet and cooking modality was described for Gilthead sea bream juveniles (Sparus aurata). Three feeds were tested: a control diet containing fish meal (FM>26%) and fish oil (FO>6%) and two diets where FM and FO were replaced with more sustainable alternatives (FM<14%; FO<5%). Fillets were analyzed raw and after cooking at increasing intensities: sous-vide , boiling, roasting and microwave oven baking. The overall quality of fish fillets was assessed by measuring their appearance by Image Analysis, by characterizing their proximate composition, fatty acid profiles, quality indices, and their microstructural features by Magnetic Resonance Imaging and relaxometry. The analysis of experimental data suggested that fish diet specifically characterized the nutritional quality of cooked fillets by affecting their fatty acid profiles, irrespective of the cooking process. Appearance (color, image texture) and muscle microstructure were only influenced by the intensity of cooking, regardless of diet. As cooking intensity increased, water and oil distribution in myofibrils was progressively reorganized and muscle fibers shrunk, causing relevant microstructural changes, especially in roasted and microwave oven baked fillets. The paper provides a useful guide for the production of ready-to-eat meals derived from sustainable aquaculture processes and characterized by high sensory and nutritional quality. [Display omitted] • Magnetic Resonance relaxometry and Image Analysis can guide fish fillet processing. • Fatty acids, color and muscle microstructure of fillets were differentially affected. • Diet affected nutritional quality while cooking mostly color and microstructure. • Combined effect of fish diet and processing on quality is studied for the first time. [ABSTRACT FROM AUTHOR]