Abstract:
Maize plays a critical role as a staple food and income source in Kenya, yet a significant annual loss of 12% to 20% of the national output occurs due to high moisture content. To mitigate this, drying maize to a safe moisture level of 13.5% (dry basis) before storage is essential. However, drying processes are energy intensive, consuming about 60% of the total invested energy. This emphasizes the need for appropriate technology which is the vertical pneumatic maize grain dryer (PMGD). The objectives of this research were to validate simulation models for mass flow rate (MFR) of maize grain, determine the effect of moisture content (MC), air temperature (Ta), and MFR on moisture removal rate (MRR) and energy used (EU) in drying, and optimise energy proportioned for the grain drying (Ea) and transportation (Eg) to maximise MRR. Furthermore, optimise MC, Ta, and MFR to enhance MRR and minimise EU through Taguchi's method. The Beverloo (BEV), British Code of Practice (BCP), Tudor (TUD), and New simulation model (QN) were validated using actual MFR data obtained from maize grain flow through horizontal circular orifices of diameters ranging from 0.040 m to 0.056 m. The experimental conditions included MC levels of 20%, 25%, and 30% (wet basis), Ta of 60°C, 70°C, and 80°C, and MFR of 720 kg/h, 771 kg/h, and 864 kg/h, while maintaining an air MFR of 547 kg/h during 2 hours drying period for 70.0 kg of the grain. The actual MFR ranged from 720 kg/h to 1735 kg/h, 650 kg/h to 2006 kg/h for BEV, 851 kg/h to 2378 kg/h for BCP, 867 kg/h to 2010 kg/h for TUD and 706 kg/h to 1757 kg/h for QN model. The Student’s t-test results showed significant difference (P < 0.05) between the actual and models MFR except QN (P > 0.05). The effect of MC on MRR was significant (P < 0.05). However, MC did not have significant (P > 0.05) effect on Ea and Eg. The effect of Ta on MRR and Ea was significant (P < 0.05) except Eg (P > 0.05). The effect of MFR on MRR, Ea and Eg was not significant (P > 0.05). The optimum Ea and Eg for MRR were 7.3 kWh and 2.2 kWh, respectively. Additionally, the optimum MC, Ta and MFR for MRR were 20%, 80°C and 720 kg/h while that for EU was 20%, 60°C and 720 kg/h, respectively. The Page model with coefficient of determination of 0.99 and root mean square error of 0.0049 was suitable for describing variation of moisture ratio with time in maize grain drying. The availability and use of the optimised PMGD would provide applicable solutions to energy challenges in maize grain drying, ultimately leading to reduced postharvest losses and enhanced food security and income for farmers. This would contribute to the attainment of sustainable development goals, particularly in eradicating hunger and poverty.
