Fluctuations of Production and Quality of Bananas Under Marginal Tropical Climate
Bibliographic record
Abstract
The knowledge of the inter-seasonal fluctuations in characteristics of fruit quality and production is important for management of plants, prediction of yield and marketing strategies. This study aims to evaluate how the climatic conditions prevailing in the month of harvest impact bunch mass and variability of the size and color of the banana fruit ‘Nanica’ and ‘Prata’ cultivated under marginal tropical climate. The experiments were carried in Registro, Ribeira Valley region, São Paulo, Brazil, in a completely randomized design with 24 treatments (months of bunch harvest) and ten replications, for each cultivar. Cyclic seasonal fluctuations in production were found in for the two cultivars, with the lowest bunch mass (BM), fruit size consistently recorded between July and February associated with lower global solar radiation (Rad) and temperature (T) of the harvest month, but not precipitation (Ppt). The extension of monthly fluctuations in BM were similar to ‘Prata’ (18.95±3.31 kg) and ‘Nanica’ (29.51±4.69 kg). Independent of the harvest month, there was a trend of greater variability for fruit length (FL) and lower for fruit diameter (FD) between fruits of the different positions in the bunch. The correlations between Rad or T of harvest month with BM, FL, FD and SL were all positive. For both cultivars, the shelf life (SL) was longer for fruits of the last hand. There were also positive correlations between Rad or T with SL. The decrease of peel color characteristics of the ‘Nanica’ fruit was associated with cold fronts from autumn to spring and chilling injury, with higher intensity in the last hand.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".