Modelling of microwave assisted hot-air drying and microstructural study of oilseeds
Bibliographic record
Abstract
Abstract: A modelling study was performed to solve the heat and mass transfer problems between grain and the ambient air encountered during drying by microwave assisted hot-air dryer, under low microwave (MW) density of 0.2 W/g. Canola (Brassica napus), soybean (Glycine max) and corn (Zea mays) seeds were chosen due to their inherent high oil content. Scanning electron microscopy (SEM) was used to study the effect of drying conditions on the structural characteristics of these oilseeds. A mathematical model was adapted to simulate drying of one seed of canola, soybean and corn. The process of water transfer was modelled based on the effect of vapour pressure on the water molecules inside the seed. It was observed that when the difference between the vapour pressure inside the grain and the surrounding air was higher than, the drying rate increased which led to cracks in the grain. Results showed that the drying rate decreased when the temperature of air inside the cavity of the microwave increased for all the oilseeds studied, because of the reduced differential vapour pressure between the grain and the ambient air. On the other hand, the drying rate increased if the temperature of the inlet air was reduced because the difference between the two pressures increased. It was concluded that by controlling the ambient air, the grains could be protected against popping and cracking because of lower vapour pressure differential during MW assisted hot-air drying. Keywords: mathematical modelling, oilseeds, MW assisted drying, drying rate, SEM images DOI: 10.3965/j.ijabe.20160906.2442 Citation: Hemis M, Choudhary R, Becerra-Mora N, Kohli P, Raghavan V. Modelling of microwave assisted hot-air drying and microstructural study of oilseeds. Int J Agric & Biol Eng, 2016; 9(6): 167－177.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".