Drying characteristics of yam slices (Dioscorea rotundata) in a convective hot air dryer: application of ANFIS in the prediction of drying kinetics

Abstract

This study applied Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict the moisture ratio (MR) during the drying process of yam slices (Dioscorea rotundata) in a hot air convective dryer. Also the effective diffusivity, activation energy, and rehydration ratio were calculated. The experiments were carried out at three (3) drying air temperatures (50, 60, and 70 C), air velocities (0.5, 1, and 1.5 m/s), and slice thickness (3, 6, and 9 mm), and the obtained experimental data were used to check the usefulness of ANFIS in the yam drying process. The result showed efficient applicability of ANFIS in predicting the MR at any time of the drying process with a correlation value (R 2 ) of 0.98226 and root mean square error value (RMSE) of 0.01702 for the testing stage. The effective diffusivity increased with an increase in air velocity, air temperature, and thickness and the values (6.382E -09 to 1.641E -07 m 2 /s). The activation energy increased with an increase in air velocity, but fluctuate within the air temperatures and thickness used (10.59-54.93 KJ/mol). Rehydration ratio was highest at air velocityÂair tem-peratureÂthickness (1.5 m/sÂ70 C  3 mm), and lowest at air velocity  air temperatureÂthickness (0.5 m/ sÂ70 C  3 mm). The result showed that the drying kinetics of Dioscorea rotundata existed in the falling rate period. The drying time decreased with increased temperature, air velocity, and decreased slice thickness. These established results are applicable in process and equipment design, analysis and prediction of hot air convective drying of yam (Dioscorea rotundata) slices.

Energy and exergy analyses of okra drying process in a forced convection cabinet dryer

“…at 400, 300 and 200 g, respectively. Ojediran et al (2020) and Aviara et al (2014) obtained similar results when drying yam slices and drying native cassava starch, respectively . ment, and that level decreased over time due to the faster moisture transfer.…”

“…Hot air drying, which has two major important facts related to it; the efficient removal of the surface water and a low operating cost. Hot air drying involves blowing heated air over food materials to remove moisture, which has been used frequently in food dehydration (Omari et al 2018;Ojediran et al 2020). However, the dehydration of vegetables and other food crops by traditional methods of open-air sun drying is not satisfactory, because the products deteriorate rapidly (Adekanye et al 2019).…”

Optimization and Prediction of the Drying and Quality of Turnip Slices by Convective-Infrared Dryer under Various Pretreatments by RSM and ANFIS Methods

“…In RSM optimization, input variables are defined as the independent ones and their influence on the response (dependent) variable is explored. Numerous researchers have used RSM and ANFIS to model and optimize the quality and drying process of various crops including okra [ 22 ], quince [ 23 ], yacon [ 24 ], lavender leaves [ 25 ], and rough rice [ 26 ] for RSM and blackberries [ 8 ], almond [ 20 ], and yam slices [ 27 ] using the ANFIS method.…”

The Influence of Xanthan and Balangu Seed Gums Coats on the Kinetics of Infrared Drying of Apricot Slices: GA-ANN and ANFIS Modeling

“…Lertworasirikul (2008) performed a comparative study on the drying kinetics of semi-finished cassava crackers using empirical, ANN, and ANFIS models, and predicted the dynamic drying parameters. In another study, Ojediran et al (2020) used ANFIS to predict the drying kinetics during the drying of yam slices in a convective hot air dhoryer. In this study, the experiments were done at various drying air temperatures (50, 60, and 70°C), air velocities (0.5, 1.0, and 1.5 m/s), and yam slices thickness (3, 6, and 9 mm), and the obtained experimental data were used to model and check the advantage of ANFIS approach.…”