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This study was carried out to verify the influence of drying parameters on phenolic and flavonoid compounds of apricots (Prunus armeniaca L.) treated with sucrose, NaCl, and sodium bisulphite solutions dried by microwave at different powers (200, 400, and 800 W). We used two extraction methods, namely, cold soaking and ultrasound-assisted extraction (UAE). Total phenolics and flavonoids in fresh and dried apricots and apricot dough were estimated using the Folin-Ciocalteu reagent and the aluminium trichloride method, respectively. Fresh apricot contained considerable amounts of polyphenols and flavonoids by the cold soaking and UAE (285.43 and 165.49 mg GAE/100 g DM and 48.57 and 12.11 mg QE/100 g DM, respectively). Analysis of the data showed that the decrease in polyphenol and flavonoid contents of the dried treated apricots compared to the fresh material was significant. The greatest losses of these nutrients were recorded when applying the ultrasonic extraction method.

The objective of this study was to evaluate the antioxidant (AA), antibacterial, and antifungal activity of fresh and pre-treated apricot extracts, dried by microwave at different powers (200, 400, and 800 W), extracted by the cold soaking method, and ultrasound-assisted extraction (UAE). Biological activity (bacterial and fungal) was estimated by agar disk diffusion test against four bacterial strains (Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Streptococcus sp.), and two fungal strains (Candida spp. and Geotrichum capitatum). Methanolic extracts of apricot fruits: fresh, dried processed, and apricot dough extracted by cold soaking showed a higher AA ranging from 34.22 to 96 % than the other extracts extracted by UAE with values ranging from 14.37 to 66.88 %. The results of tested extracts from fruits (Prunus armeniaca L.) extracted by both extraction methods showed the highest inhibitory activity against most of the tested bacterial and fungal strains with inhibition zones ranging from 4 to 45 mm. The biological activity (antibacterial and antifungal activity) has been improved using different treatments and microwave powers for drying apricots. In addition, the results of the biological activity of the extracts obtained by UAE are the best compared to cold soaking. However, it was determined that the UAE extraction method of cold soaking and drying of apricot fruits was more appropriate for the food industry due to the obtaining of extracts with good antibacterial and antioxidant potential, and their incorporation in foods would increase their production and uses, thus leading to the development of superior biofunctional foods, and the use of bio-solvent, such as methanol, which is easily available in high purity, highly safe, and completely biodegradable.

This study involved monitoring and modelling the drying kinetics of whole apricots pre-treated with solutions of sucrose, NaCl, and sodium bisulphite. The drying was performed in a microwave oven at different power levels (200, 400, and 800 W). Two artificial intelligence models were used for the prediction of drying time (DT) and moisture ratio (MR): artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS). On the other hand, the MR prediction was also done with 21 semi-empirical models, one of which we created. The results showed that the drying time decreased with the increase in microwave oven power for the three treatments. The treatment with NaCl was the most suitable for our work. The correlation coefficients of drying time (0.9992) and moisture ratio (0.9997) of ANN were high compared to the ANFIS model, which were 0.9941 and 0.9995, respectively. Among twenty semi-empirical models that were simulated, three models were fitted to our study (Henderson & Papis modified, Henderson & Pabis, and Two Terms). By comparing the three models adapted to our work and the model that we proposed, as well as ANN for MR prediction, it was observed that the model that we created was the most appropriate for describing the drying kinetics of NaCl-treated apricot. This solution opens the prospect of using this potential model to simulate fruit and vegetable drying kinetics in the future.