Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots

Abla Bousselma,Dalila Abdessemed,Abdeltif Amrane,Hichem Tahraoui

doi:10.15255/kui.2020.079

Abstract

Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots

Highlights

Apricot is the fruit of the common apricot tree, Prunus armeniaca L., of the Rosaceae family.[1]
The objective of this study was: (1) to monitor the drying kinetics of whole apricots pre-treated by solutions: sucrose, NaCl, and sodium bisulphite in microwave oven at different powers (200, 400, and 800 W), (2) to predict the drying time (DT) and moisture ratio (MR) of drying kinetics of apricot by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), (3) to simulate experimental data by 20 mathematical models, (4) to propose a new mathematical model for drying kinetics of treated whole apricot, (5) to compare the results of time prediction by ANN and ANFIS model, and (6) to compare the results of MR prediction by the three best models simulated in literature, the model which was created by us, the ANN model, and ANFIS
The drying kinetics of microwave-treated apricots were similar to those found by Togrul and Pehlivan.[36]

Summary

Introduction

Apricot is the fruit of the common apricot tree, Prunus armeniaca L., of the Rosaceae family (subfamily Pomoides).[1]. Fruits and vegetables are generally subjected to different pre-treatments, such as blanching, osmotic dehydration in sucrose and salty solutions, and immersion in a sodium bisulphite solution These treatment methods are commonly used to reduce the rate of fruit studies have been reported on the prediction of moisture ratio and drying time for various agricultural products, such as apricot slices,[5] quince,[6] onions,[11] basil seed mucilage,[13] green peas,[14] potatoes,[15] and white mulberry.[16] there is still very little data reported on drying time prediction of apricot slices by ANFIS and genetic algorithm-artificial neural network (GA-ANN).[5] Due to the large-volume production of apricot in Algeria, there are significant losses of this fruit as it is perishable. The objective of this study was: (1) to monitor the drying kinetics of whole apricots pre-treated by solutions: sucrose, NaCl, and sodium bisulphite in microwave oven at different powers (200, 400, and 800 W), (2) to predict the DT and MR of drying kinetics of apricot by ANN and ANFIS, (3) to simulate experimental data by 20 mathematical models, (4) to propose a new mathematical model for drying kinetics of treated whole apricot, (5) to compare the results of time prediction by ANN and ANFIS model, and (6) to compare the results of MR prediction by the three best models simulated in literature, the model which was created by us, the ANN model, and ANFIS

Objectives

Results

Conclusion