Karadeniz Fen Bilimleri Dergisi, cilt.14, sa.1, ss.168-193, 2024 (Hakemli Dergi)
This study focused on the impact of citric acid, hot water blanching, and ultrasound pretreatment on the drying of zucchini
slices, color properties, and the comparison of artificial neural network (ANN) and thin-layer modeling. The pretreatments
enhanced the drying rate and reduced drying time. Ultrasound pretreatment was observed as the most effective, with a
reduction rate of the drying time as 40%. Besides, mass transfer and moisture diffusion phenomena were positively
affected by pretreatments, depending on the increment of the drying rate. The highest mass transfer coefficient (hm),
moisture diffusivity (D) by the Dincer and Dost model, and effective moisture diffusivity (Deff) by the Crank equation
were obtained with ultrasound pretreatment. On the other hand, Midilli and Kucuk, Parabolic, and Page gave the best
predictions among the thin-layer models. However, ANN modeling had a better performance than thin-layer modeling
due to a higher determination coefficient (R2
) and lower root mean square error (RMSE) values. Color properties of the
zucchini slices were affected by drying processes. In general, the redness and yellowness of the zucchini slices increased;
however, lightness did not show statistical significance. Additionally, citric acid pretreatment gave the lowest total color
difference (∆E).