Development of ‘Pérola’ Pineapple (Ananas comosus vr. Comosus) Infructescence Under Organic Fertilization
Bibliographic record
Abstract
Pineapple (Ananas comosus vr. Comosus) plants require balanced nutrition to meet fruit’s market quality standards for consumption. The objective of this research was to evaluate the effects of organic and mineral fertilization on the development of the ‘Pérola’ pineapple infructescence produced in Paraíba State, Brazil. The plants were conducted under organic fertilization composed by a mixing of cattle manure and poultry litter n at 0, 50, 75 and 100% of the nitrogen doses recommended (NDR) for pineapple cultivation and mineral fertilization. The evaluation for fresh fruit length, diameter, mass, and crown length was initiated at the 43rd day after the floral induction (DAFI). The use organic fertilizer at 75 and 100% of the NDR provided a higher growth rate of fruits. In general, the length and diameter of the infructescences evolved rapidly until the 73rd DAFI, characterizing the first development phase. At the second phase, it was observed an intense growth rate to about the 103rd DAFI be reached, which was followed by a slower growth rate until around the 118th DAFI. In the third and last phase, from the 118th DAFI the physiological maturity of the fruit was reached and was characterized by the pineapple commercial maturation up to 133rd DAFI, with a quarter of the fruit yellow. Under the experimental conditions, the mixed fertilization in the level of 75% NDR, promoted a greater length and fresh mass than the conventional mineral fertilization for ‘Pérola’ pineapple and can be an alternative for this crop’ family farming production.
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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 | 0.001 |
| 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".