Prediction of drying kinetics and energy consumption values of purple carrots dried in a temperature-controlled microwave dryer by decision tree, random forest and ada boost approaches

Abstract

In the literature have focused on modeling data obtained under drying conditions with different methods and comparing them with each other. However, any studies have been found on estimating the behavior of the same material under different drying conditions. Therefore, a study was conducted to predict the behavior of the same material under different drying conditions. In the study, primarily purple carrot slices were reduced from 6.13 ± 0.05 to 0.14 ± 0.018 g moisture/g dry matter value. Among the models, the drying rates were best estimated by the Midilli-Küçük (R²: 0.9993) model. The lowest energy consumption was determined as 0.285 kWh in the drying process at 70 °C. Estimation of intermediate values is very useful because experimental studies can be length and expensive. Sometimes, even if cost is not a concern, long-term experimental studies and the high number of experiment repetitions increase the importance of estimation methods for researchers. The decision tree, random forest and ada boost methods, which are fast operating methods, were used as estimation methods in this study. MAPE and R² success values are expressed for all three methods. The Decision Tree method was found to be the most successful technique with the highest R² value (0.96) and the lowest MAPE value (0.03).