Drying Time, Energy and Exergy Efficiency Prediction of Corn (Zea mays L.) at a Convective-Infrared-Rotary Dryer: Approach by an Artificial Neural Network

Abbaspour-Gilandeh, Yousef; Zadhossein, Safoura; Kaveh, Mohammad; Szymanek, Mariusz; Hassannejad, Sahar; Wojciechowska, Krystyna

doi:10.3390/en18030696

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Drying Time, Energy and Exergy Efficiency Prediction of Corn (Zea mays L.) at a Convective-Infrared-Rotary Dryer: Approach by an Artificial Neural Network

by

Yousef Abbaspour-Gilandeh

^1,*

,

Safoura Zadhossein

¹,

Mohammad Kaveh

²

,

Mariusz Szymanek

^3,*

,

Sahar Hassannejad

⁴

and

Krystyna Wojciechowska

⁵

¹

Department of Biosystems Engineering, College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran

²

Department of Petroleum Engineering, College of Engineering, Knowledge University, Erbil 44001, Iraq

³

Department of Agricultural, Forest and Transport Machinery, University of Life Sciences in Lublin, Głeboka 28, 20-612 Lublin, Poland

⁴

Department of Medical Laboratory Science, College of Science, Knowledge University, Erbil 44001, Iraq

⁵

Department of Strategy and Business Planning, Faculty of Management, Lublin University of Technology, 20-618 Lublin, Poland

^*

Authors to whom correspondence should be addressed.

Energies 2025, 18(3), 696; https://doi.org/10.3390/en18030696 (registering DOI)

Submission received: 27 December 2024 / Revised: 21 January 2025 / Accepted: 30 January 2025 / Published: 3 February 2025

(This article belongs to the Section K: State-of-the-Art Energy Related Technologies)

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Abstract

Energy consumption in the drying industry has made drying an energy-intensive operation. In this study, the drying time, quality properties (color, shrinkage, water activity and rehydration ratio), specific energy consumption (S.E.C), thermal, energy and exergy efficiency of corn drying using a hybrid dryer convective-infrared-rotary (CV-IR-D) were analyzed. In addition, the energy parameters and exergy efficiency of corn were predicted using the artificial neural network (ANN) technique. The experiments were conducted at three rotary rotation speeds of 4, 8 and 12 rpm, drying temperatures of 45, 55 and 65 °C, and infrared power of 0.25, 0.5 and 0.75 kW. By increasing drying temperature, infrared power and rotary rotation speed, the drying time, S.E.C and water activity decreased while the D_eff, energy, thermal and exergy efficiency increased. In addition, the highest values of rehydration ratio and redness (a*) and the lowest values of shrinkage, brightness (L*), yellowness (b*) and color changes (ΔE) were obtained at an infrared power of 0.5 kW, air temperature of 55 °C and rotation speed of 8 rpm. The range of changes in S.E.C, energy, thermal and exergy efficiency during the corn drying process was 5.05–28.15 MJ/kg, 3.26–29.29%, 5.5–32.33% and 21.22–55.35%. The prediction results using ANNs showed that the R for the drying time, S.E.C, thermal, energy and exergy data were 0.9938, 0.9906, 0.9965, 0.9874 and 0.9893, respectively, indicating a successful prediction.

Keywords: corn; energy efficiency; exergy efficiency color; rehydration ratio

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MDPI and ACS Style

Abbaspour-Gilandeh, Y.; Zadhossein, S.; Kaveh, M.; Szymanek, M.; Hassannejad, S.; Wojciechowska, K. Drying Time, Energy and Exergy Efficiency Prediction of Corn (Zea mays L.) at a Convective-Infrared-Rotary Dryer: Approach by an Artificial Neural Network. Energies 2025, 18, 696. https://doi.org/10.3390/en18030696

AMA Style

Abbaspour-Gilandeh Y, Zadhossein S, Kaveh M, Szymanek M, Hassannejad S, Wojciechowska K. Drying Time, Energy and Exergy Efficiency Prediction of Corn (Zea mays L.) at a Convective-Infrared-Rotary Dryer: Approach by an Artificial Neural Network. Energies. 2025; 18(3):696. https://doi.org/10.3390/en18030696

Chicago/Turabian Style

Abbaspour-Gilandeh, Yousef, Safoura Zadhossein, Mohammad Kaveh, Mariusz Szymanek, Sahar Hassannejad, and Krystyna Wojciechowska. 2025. "Drying Time, Energy and Exergy Efficiency Prediction of Corn (Zea mays L.) at a Convective-Infrared-Rotary Dryer: Approach by an Artificial Neural Network" Energies 18, no. 3: 696. https://doi.org/10.3390/en18030696

APA Style

Abbaspour-Gilandeh, Y., Zadhossein, S., Kaveh, M., Szymanek, M., Hassannejad, S., & Wojciechowska, K. (2025). Drying Time, Energy and Exergy Efficiency Prediction of Corn (Zea mays L.) at a Convective-Infrared-Rotary Dryer: Approach by an Artificial Neural Network. Energies, 18(3), 696. https://doi.org/10.3390/en18030696

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Drying Time, Energy and Exergy Efficiency Prediction of Corn (Zea mays L.) at a Convective-Infrared-Rotary Dryer: Approach by an Artificial Neural Network

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