Aeration is a key post-harvest grain processing operation that forces air through the pore volume of the grain bulk to establish favorable conditions to maintain grain quality and improve its storability. However, during storage, grain bulk experiences self-compaction due to its dead weight, which alters the bulk properties and impedes the uniform flow of air during aeration. Thus, this study focused on investigating the effect of self-compaction on the pressure drop ΔP of wheat bulk (Triticum aestivum L., cv. ‘Pionier’, X = 0.123 kg·kg−1 d.b.) accommodated in a laboratory-scale bin (Vb = 0.62 m3) at a coherent set of airflow velocities va. Pressure drop ΔP was measured at bulk depths Hb of 1.0, 2.0, 3.0 and 3.4 m and storage times t of 1, 65, 164 and 236 h. For the semi-empirical characterization of the relationship between ΔP and va, the model of Matthies and Petersen was used, which was proficient in describing the experimental data with decent accuracy (R2 = 0.990, RMSE = 68.67 Pa, MAPE = 12.50%). A tailored product factor k was employed for the specific grain bulk conditions. Results revealed a reduction of in-situ pore volume ε from 0.413 to 0.391 at bulk depths Hb of 1.0 to 3.4 m after 1 h storage time t and from 0.391 to 0.370 after 236 h storage time t, respectively. A disproportional increase of the pressure drop ΔP with bulk depth Hb and storage time t was observed, which was ascribed to the irreversible spatio-temporal behavior of self-compaction. The variation of pore volume ε was modeled and facilitated the development of a generalized model for predicting the relationship between ΔP and va. The relative importance of modeling parameters was evaluated by a sensitivity analysis. In conclusion, self-compaction has proven to have a significant effect on airflow resistance, therefore it should be considered in the analysis and modeling of cooling, aeration and low-temperature drying of in-store grain bulks.
The management of moisture is one of the main challenges in anticipating and averting food decay and food losses during postharvest processing and storage. Hence, it is imperative to reduce the moisture of freshly harvested products to safe-storage limits in order to inhibit the occurrence of diverse biochemical, microbiological and other moisture-related deteriorative reactions which can contribute to quality degradation. A viable alternative to conventional hot-air drying is the application of low temperatures for drying, which has scarcely been investigated. In this regard, experimental-based modeling is a requisite to gain insights into drying processes. Thus, this study focused on investigating the drying kinetics of wheat (Triticum aestivum L.) cv. ‘Pionier’ under a coherent set of drying air temperatures (T = 10–50 °C), relative humidity (RH = 20–60%), and airflow velocity (v = 0.15–1.00 ms−1). A robust and automated measurement system using a high precision balance was utilized as a basis for the real-time and continuous acquisition of drying data. The analysis of the experimental results facilitated the establishment of generalized drying model for low temperatures able to describe at a high accuracy the behavior of moisture ratio X* (R2 = 0.997, RMSE = 1.285 × 10−2, MAPE = 6.5%). An analytical model for predicting the effective diffusion coefficients D (R2 = 0.988, RMSE = 4.239 × 10−2, MAPE = 7.7%) was also developed. In conclusion, the anticipated drying model has demonstrated the capability of modeling the drying behavior of wheat at low temperatures with a high temporal resolution and should be employed in the design, analysis and modeling of cooling, aeration and low-temperature drying processes of wheat bulks.
Small-scale farmers in developing Asian countries have minimal agricultural mechanisms available to them. In the Philippines, postharvest losses in rice production can reach about 36% in the drying process alone. Thus, the inflatable solar dryer (ISD) was developed through the collaboration of the University of Hohenheim, the International Rice Research Institute, and GrainPro Philippines Inc. Although the ISD was successfully tested with different agricultural products, further characterization of the ISD design is required for predicting the drying performance. To this end, the airflow behavior in the ISD was simulated using computational fluid dynamics (CFD) via ANSYS Fluent. Moreover, a thermal model was developed in MATLAB/Simulink by taking into account heat transfer in the heating area and coupled heat and mass transfer within the drying area. Three batches of drying experiments were performed and airflow measurements were taken inside the dryer to validate the models. The MATLAB/Simulink model was further used to predict the drying performance under various weather conditions spanning 10 years. The simulated temperatures and moisture content in the ISD showed high accuracy (mean absolute percentage error (MAPE) < 10%) with the experimental data. The proposed dynamic model provides an efficient computational tool that can be applied to predict the drying performance and to optimize the ISD design.
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