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Convective drying of golden delicious apple enhancement: drying characteristics, artificial neural network modeling, chemical and ATR-FTIR analysis of quality parameters by Tolga Kağan TEPE is a Engineering article available to read on EtoBox.

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## Abstract In recent years, many innovative methods have been investigated to provide alternative approaches to the food drying industry, but currently the most widely used method is convective drying. There are difficulties in integrating innovative methods into the food industry due to cost, inapplicability to every food material, or product quality, etc. In addition, it is possible to improve the convective drying method by pre-treating of foods. Thanks to the convective drying method with increased efficiency, shorter drying processes can be achieved. This study investigates the effects of ethanol and citric acid pretreatments on the convective drying process of apple slices and the drying rate, diameter and thickness shrinkage, color properties, total phenolic content (TPC), antioxidant activity (AA), ATR-FTIR spectra, and principal component analysis (PCA) of the dried samples. The results indicate that both ethanol and citric acid pretreatments significantly enhance the drying rate and decrease drying time, with the most favorable outcomes observed for apple slices immersed in an ethanol solution for 20 min. The study employs thin-layer and artificial neural network (ANN) m

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Author

Tolga Kağan TEPE

Publisher

Springer Science and Business Media LLC

Published

2024

Language

EN

Field

Engineering (Physical Sciences)