Postharvest Quality of Yellow Pear Tomato Cultivated in Aquaponic System
Bibliographic record
Abstract
The production of vegetables in aquaponic systems has high sustainability and conservation of natural resources, but studies that make their cultivation feasible under Brazilian conditions are still incipient. Given the influence that the cultivation system can cause on the postharvest characteristics of fruits and vegetables, this study aimed to evaluate the postharvest quality of yellow pear tomato cultivated in an aquaponic system. Tomato plants were grown in a protected environment, in the experimental area of aquaponics of the Faculty of Agrarian Sciences, belonging to the Federal University of Grande Dourados. The experimental design was completely randomized in a factorial scheme, with two factors: maturity stage at harvest and storage time. Three stages of fruit maturity (green, intermediate and ripe) and two storage times (zero and 35 days) were analyzed. Tomato samples were subjected to the analyses using the whole fruit, evaluated for mass loss, color and firmness, and the fruit pulp, evaluated for soluble solids (SS), titratable acidity (TA), SS/TA ratio, pH and lycopene content. The fruits of yellow pear tomato cultivated in aquaponic system were in satisfactory conditions with respect to the postharvest parameters evaluated, indicating great potential to be cultivated on a commercial scale under Brazilian conditions. The parameters analyzed were similar or superior to the parameters of tomatoes grown in other cropping systems.
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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 | 0.001 | 0.001 |
| 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".