Muhammad Anas Asy-Syaqiq

This study aimed to investigate the drying kinetics of cardamom ( Amomum compactum ) in a desiccant‐assisted fluidized bed dryer (FBD) and optimize its thermodynamic performance. The experiments evaluated drying air temperature (45°C–75°C) and zeolite mass (50–150 g). Kinetic analysis revealed that cardamom drying occurred entirely within the falling‐rate period, with the Midilli thin‐layer model providing the most precise fit for moisture ratio decline ( R ² > 0.991, RMSE < 0.021). While response surface methodology (RSM) successfully modeled drying efficiency ( p < 0.05), it failed to generate statistically predictive models for non‐linear kinetic responses (moisture content and drying rate). To overcome this, artificial neural network (ANN) modeling was deployed. A static ANN outperformed RSM in predicting simultaneous endpoint responses (overall R ² = 0.9300), while a dynamic time‐series ANN mapped the continuous moisture ratio decline with exceptional precision ( R ² = 0.9717). Finally, a hybrid ANN‐particle swarm optimization (ANN‐PSO) algorithm was applied to scientifically refine the optimal operational boundary. The ANN‐PSO discovered a superior global optimum at 45.35°C and 170.71 g of zeolite, achieving a predicted drying efficiency of 3.79% while maintaining rapid moisture diffusivity (1.74 × 10 ⁻⁸ m ² /min). These findings demonstrate that integrating machine learning with metaheuristic optimization provides a more rigorous framework for scaling up spice drying processes than conventional empirical polynomials.

This study compares the drying characteristics and the heat and mass transfer phenomena while drying turmeric slices using a photovoltaic ventilation direct solar dryer and open sun drying. Turmeric slices of varying thicknesses—5, 7, and 10 mm—were dried from 83.48% to a final moisture content of 5–6% to ensure safe storage conditions. The drying times required were 1440, 1800, and 2160 min for the direct solar dryer, and 2220, 2520, and 2880 min for open sun drying at 5, 7, and 10 mm thicknesses, respectively. Drying Turmeric slices using the direct solar dryer at thinner thicknesses showed a faster drying rate, with the highest average drying rate observed for the 5 mm slices at 0.287 g/min. Similarly, drying efficiency was higher for thinner slices. The Midilli model provided the best fit for experimental and predicted data in describing the drying kinetics of turmeric slices. The effective moisture diffusivity obtained in this study was 1.65 × 10⁻⁸, 2.66 × 10⁻⁸, and 4.11 × 10⁻⁸ m2/s for the direct solar dryer, and 0.89 × 10⁻⁸, 1.52 × 10⁻⁸, and 2.38 × 10⁻⁸ m2/s for open sun drying at 5, 7, and 10 mm thicknesses, respectively. Higher heat and mass transfer coefficients were observed for drying thinner turmeric slices using the direct solar dryer. The convective heat transfer and evaporative heat transfer coefficients decreased as the moisture content was reduced. In contrast, the mass transfer coefficient increased as the drying time progressed.

A novel mixed-mode air recirculation solar dryer was developed and tested for drying sweet corn kernels. The air recirculation system was combined with an evacuated tube solar collector installed on a mixed-mode solar dryer. Performance parameters such as the drying kinetics and drying efficiency were investigated. The time required to dry sweet corn kernels with open sun drying was 21.5 h, whereas using the mixed-mode solar dryer was much faster, taking about 12–16 h to reduce the moisture content from an initial 77.12% to a final 12.34 – 14.2%. The drying efficiency ranged from 9.8479 to 14.3776%, with the SEC ranging from 10.1733 kWh/kg to 12.7867 kWh/kg. The ETSC efficiency ranged from 48.9754 to 61.9727% and could heat water to 62 °C. Overall, drying at a 50% air recirculation ratio showed the best performance.

Corn is a widely produced and consumed agricultural product, used as fuel, staple food, and livestock feed. The high level of corn production can lead to potential post-harvest food losses. Drying methods offer a solution to extend the shelf life of a substance. Hybrid solar drying, which combines solar drying with additional heating, particularly using liquefied petroleum gas (LPG), was introduced in this research to ensure faster and more efficient drying processes. The three drying methods compared in this study consist of open sun drying, natural solar drying, and hybrid solar drying. The research results show an average corn grain moisture content of 13.95% over 10.5 hrs, 13.75% over 6 hrs, 13.65% over 7 hrs, 13.45% over 5 hrs, and 13.65% over 4.5 hrs in open sun drying, natural solar drying, and hybrid solar drying with temperature variables of 40°C, 50°C, and 60°C. The average drying rates were 0.212 g/min, 0.364 g/min, 0.318 g/min, 0.439 g/ min, and 0.477 g/min, respectively. The average drying efficiency values for each variable were 2.968%, 4.719%, 5.358%, 5.271%, and 6.037%. In the proximate test, the corn grain moisture content in the hybrid solar drying variable at 60°C was 13.8%, ash was 1.24%, protein was 7.76%, fat was 4.40%, and carbohydrate was 72.8%. For the corn grain color test, the average values obtained were L = 46.48, a = 4.58, and b = 25.37. Meanwhile, the aflatoxin test for dried corn grains showed values of aflatoxin B1, B2, G1, and G2 <0.5 with a total aflatoxin content <2.00. Therefore, hybrid solar drying is recommended over open sun drying and natural solar drying because of its ability to operate even in unfavorable weather conditions, its temperature control capability, its ability to accelerate the drying process, and its capacity to maintain the quality of the material.

The world's population is projected to increase, impacting a 60% rise in food production demand by 2050, including the demand for maize. Currently, maize production is estimated to reach 1510 million tons in 2023, necessitating suitable methods for preserving maize kernels to maintain quality and reduce post‐harvest agricultural losses. Although drying methods present a viable solution to address this issue, the majority of farmers in Indonesia still use conventional drying methods, such as open sun drying, which has several drawbacks. Hence, solar drying systems aim to overcome these limitations by harnessing renewable, clean, sustainable, and eco‐friendly energy to support the sustainable development goals (SDGs). This research comprehensively reviews the progress of solar drying technology, providing insights into its working principles, innovative designs, and operational modes across various types of solar dryers. The 4E + Q analysis provides information regarding the performance of solar drying systems, including energy analysis to determine the quantity of energy utilized and exergy analysis to demonstrate irreversibility in thermodynamic processes. Additionally, this analysis highlights environmental impacts such as CO₂ emissions and mitigation efforts, while considering economic aspects through lifecycle assessment and payback period methods. The quality assessment of dried maize kernels according to the standards set by the Indonesian National Standard (SNI) is conducted, including proximate analysis, aflatoxin levels, color measurements, and internal cracking analysis.Practical applications: Drying technology is essential for the food preservation process, enabling the maintenance of product quality and extending storage life by reducing the moisture content to eliminate the activities of microbial agents. The application of solar drying technology harnesses solar radiation as the primary energy source, making it well‐suited for crops like paddy, maize, cassava, etc. The development of solar dryers continues through modifications and the addition of auxiliary systems to achieve more efficient, economical, and sustainable technologies. The hope is that in the future, these technologies can be adopted by farmers on an industrial scale due to low operational costs, ease of operation, and controllable operating conditions. The methodological approach is necessary to evaluate the performance of solar dryers and the quality of dried products through a 4E + Q analysis, it provides information on energy consumption, exergy flow, economic considerations, environmental aspects, and quality assessments against national quality standards (SNI).

AArea (m2)CpSpecific heat capacity (kJ/kg.oC)DRDrying rate (g/min)EEnergy consumption (kW)EfanEnergy consumption of fan (kW)EUREnergy utilisation ratioExExergy rate (kJ/s)ExRExergy of solar radiati...