Preservation of Chayote (Sechium Edule L) Using Different Drying Methods
Bibliographic record
Abstract
Chayote (Sechium edule L) has a short shelf life due to its high moisture content (87-95%). This study aimed at prolonging the shelf life of chayote by using different drying methods: convective hot oven drying (OV), and osmo-dehydration (OD) with salt or sugar. Dried samples (at 20% moisture content) were analysed for their nutritional, rehydration, textural and sensory properties. Dried chayote was stored for three months while determining total plate count (TPC), coliforms, Staphylococcus, yeasts and moulds and sensory acceptability. The time to attain 20% moisture in chayote varied significantly (p < 0.05) from 9 h (OV and OD sugar) and 12h for osmo-dried chayote in salt. Ash, total sugar, starch and fiber increased significantly (p ˂ 0.05) from fresh sample as follows 5.2 - 28.3 g/100g (OD salt), 5.8 - 18.5 g/100g (OD sugar), 18.4 - 21.3 g/100g (OD sugar), 49.1 - 52.9 g/100g (OD sugar), respectively after drying. Vitamin C decreased from 232.5 - 38.4 mg/100g (OV) whereas zinc decreased from 1442.9 - 29.5 mg/100g (OV). Rehydration ratio varied from 2.0 ± 0.26 (OD salt after 30 min) to 2.9 ± 0.05 (OV after 20 min). Osmotically dehydrated samples were softer than air dried samples after rehydration and cooking. Total plate counts decreased from log 5.14 to non-detected. Staphylococcus aureus counts decreased from log 4.29 to non-detected. Coliform counts deceased from log 4.91 non detected respectively. Osmotic dehydration contributed to the preservation of the nutritional, textural and sensory properties of dried chayote with salt achieving better preservation than sugar. Drying increased the shelf life of chayote from days to three months with high microbial quality and sensory acceptability.
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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 | 0.000 |
| 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".