Moisture-Dependent Airflow Resistance and Predictive Modeling of Bulk Camelina Seeds for Drying and Aeration Design

Reliable airflow-resistance data are essential for designing efficient drying, aeration, and storage systems for bulk seeds. However, airflow resistance of camelina remains largely unknown despite its growing importance as an oilseed crop for biofuel production. This study evaluated the effects of airflow rate, bed depth, filling method, and moisture content on pressure drop through bulk camelina seeds and assessed established airflow-resistance models. Seeds were conditioned to 6, 8, 11, and 14% moisture content (w.b.) and tested at airflow rates of 0.02–0.50 m3 s−1 m−2 across five bed depths under loose- and dense-fill conditions. Ergun, Hukill and Ives, and Shedd models were applied to the experimental data. Results indicated that pressure drop increased significantly (p < 0.05) with airflow rate and bed depth, was greater under dense-fill conditions, and decreased with increasing moisture content. All models adequately described the experimental data (R2 = 0.981–0.989), with the Shedd model providing the best overall performance. A moisture-dependent modified Shedd model was developed to incorporate moisture effects and described the observed pressure-drop trends (R2 = 0.975; RMSE = 54.87 Pa m−1). This model was calibrated and evaluated using the same experimental dataset and has not yet been validated with independent data. The results provide crop-specific parameters for predicting airflow resistance and support fan sizing, energy-efficient aeration, and drying-system design for camelina seeds.