OPTIMIZATION OF STRAWBERRY DRYING PROCESS UNDER DIFFERENT PRETREATMENTS AND GEOMETRIES AT LOW TEMPERATURES
Bibliographic record
Abstract
The drying kinetics of strawberry were investigated and optimized. They affected by the strawberry geometries and the drying temperature in addition to the pretreatments including the thermal treatments and osmotic dehydration. Three geometries (whole, halve and quarter), two thermal pretreatments (hot water and microwave), osmotic dehydration (sucrose + calcium chloride and glucose + calcium chloride) and three temperatures (40, 50 and 60°C) were evaluated. The initial moisture content of the fresh strawberry samples was varied between 93.4 and 77 % (w.b). The results indicated that thehalf that treated by sucrose, Whole that treated by sucrose and hot water (80 °C) for 10 sec and half that treated by glucose, microwave (1100 W) for 10 sec at 40ºC. Also, half that treated by glucose, whole that treated by sucrose and hot water (80 °C) for 10 sec and whole that treated by sucrose, microwave (1100 W) for 10 sec at 50ºC. The optimum conditions at the highest temperature 60 ºC were half that treated by sucrose, whole that treated by sucrose and hot water (80 °C) for 10 sec and whole that treated by sucrose, microwave (1100 W) for 10 sec.
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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) | 0.001 | 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) | 0.001 | 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".