ICCK

Onyemauche F. Anonye

Nnamdi Azikiwe University, Awka, 420001, Nigeria

Section 01

Academic Profile

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Section 02

Editorial Roles

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Section 03

ICCK Publications

Open Access | Research Article | 05 October 2026
Neuro-Predictive Modelling and Thermo-Energetic Optimization of Convective Drying Kinetics and Mass Transfer Dynamics in Black Bean (Akidi) Seeds
Agricultural Science and Food Processing | Volume 3, Issue 4: 124-141, 2026 | DOI: 10.62762/ASFP.2026.204903
Abstract
Convective drying extends the storage life of legume seeds, but its nonlinear kinetics and energy demand are difficult to predict with conventional models. This study developed and validated an artificial neural network (ANN) to predict the drying kinetics, drying time and energy consumption of black bean (\textit{Vigna unguiculata}) seeds during convective drying at 45-65~\degC, and to identify optimal drying conditions. Fresh seeds had an initial moisture content of 18.84% (wet basis), above the 12-14% safe storage limit. A 2-10-10-3 feedforward network (Levenberg-Marquardt training) used drying time and temperature as inputs and moisture ratio (MR), drying rate (DR) and energy consumption... More >

Graphical Abstract
Neuro-Predictive Modelling and Thermo-Energetic Optimization of Convective Drying Kinetics and Mass Transfer Dynamics in Black Bean (Akidi) Seeds