Soil properties and grape yield affected by rock biofertilisers with earthworm compound
Bibliographic record
Abstract
Grapes are an important crop in several countries, including Brazil.This study was conducted to evaluate the potential of PK rock biofertilisers on grapes (Vitis vinifera) grown in the San Francisco Valley of the Brazilian semi-arid region.Three sources of PK fertilisers, PK soluble fertilisers, PK rock biofertilisers, and powdered PK rocks, which were all mixed with earthworm compound, and a control treatment consisting only of earthworm compound were tested at three rates.The soil pH, available P and K, exchangeable Ca +2 and Mg +2 , soluble S-SO 4 -2 , total Fe and organic carbon were analysed, and the grape yield was evaluated.The soil pH was affected by the fertilisation treatments and was reduced by the application of PK biofertiliser.The available P and K, soluble S-SO 4 -2 , exchangeable Ca and Mg, total Fe and organic carbon in the soil increased with the application of the PK biofertilisers.The soluble fertiliser had a significant effect (p=0.01) on the recommended rate of the grape yield, but no significant difference was observed between the PK soluble fertiliser and biofertiliser at 150% of the recommended rate.Rock biofertilisers may be used as a source of P, K, S-SO 4 -2 and Fe for grape production in soil with low available P and K, especially if applied at a 150% recommended rate.
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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".