Drying Kinetics of Sliced Pineapples in a Solar Conduction Dryer
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Bibliographic record
Abstract
As a means of adding value to pineapple production and minimising post-harvest losses, sliced pineapples were dried using a Solar Conduction Dryer (SCD) and appropriate thin layer drying models to predict drying were developed whilst the performance of the SCD was also investigated. For the period of the experiment, ambient temperature and temperature in the dryer ranged from 24 to 37 °C and 25 to 46 ℃ respectively. The performance of the dryer was compared to open sun drying using pineapple slices of 3-5 mm in thickness where the slices were reduced from an average moisture content of 85.42 % (w.b.) to 12.23 % (w.b.) by the SCD and to 51.51 % (w.b.) by the open sun drying in 8 hours effective drying time. Pineapple slices of thicknesses 3 mm, 5 mm, 7 mm and 10 mm were simultaneously dried in the four drying chambers of the SCD and their drying curves simulated with twelve thin layer drying models. The Middilli model was found as the best fitted thin layer drying model for sliced pineapples. The optimum fraction of drying tray area that should be loaded with pineapples was also investigated by simultaneously loading 7 mm slices of pineapples at 50, 75, and 100 percent of drying tray area. Loading the slices at 50, 75 and 100 percent of drying tray area gave overall thermal efficiencies of 23, 32 and 44 percent, respectively, hence loading pineapple slices at 100 percent drying tray area was recommended as the best.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it