Macronutrients Use Efficiency and Phosphorus Exportation by Melon Plants in Response to Fertilization
Bibliographic record
Abstract
This study aimed to evaluate macronutrients use efficiency and phosphorus accumulation, partition and partial balance in the melon hybrid Goldex F1, in response to mineral and organic fertilizers. The following fertilizations were evaluated: mineral fertilizer; bovine manure; bovine manure associated with mineral fertilizer; poultry litter; and poultry litter associated with mineral fertilizer. Plants were collected and separated into leaves, stem, and flowers and, when there were, unripe and ripe fruits for chemical analysis. Phosphorus accumulation increased along the melon crop cycle. Phosphorus partition between leaves + stems + flowers and unripe fruits + ripe fruits showed that about 80% of P was allocated to the fruits. The decreasing order of use by the plant was S > P > Mg > Ca > N > K. Only the treatment with poultry litter was within the range considered as adequate for P recovery. Mineral and organic fertilizers did not interfere with nutrient accumulation and P partition by the melon plants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".