HARVEST INDEX OF PEA PLANT AND SOIL PROPERTIES INFLUENCED BY A TWO-YEAR AMENDMENT OF BIOCARBONS UNDER MUNICIPAL WASTEWATER IRRIGATION IN ARID CLIMATE
Bibliographic record
Abstract
In this study, the influence of biochars, produced from cow manure and wood, on the harvest index of pea plants (Pisum sativum L.) and soil properties under groundwater and municipal wastewater irrigation was investigated.Biochars were applied at 5, 10 and 15 t ha -1 rates for two years.Yield biomass (pods) was higher under groundwater irrigation.As compared to control, amendment of biochar did not influence harvest index for both years, under irrigation treatments; however, as compared to wastewater irrigation, harvest index tended to be higher under groundwater irrigation.Soluble phosphorus level was higher in response to manure derived biochar under groundwater irrigation and nitrogen level was higher in response to lower rate of manure derived biochar under wastewater irrigation as compared to groundwater-irrigated soil.Under wastewater, macroaggregate stability was significantly increased within the soil as compared to groundwater irrigation, while; macroaggregates stability was observed in response of wood-derived biochar at higher rate under groundwater irrigation.Bacterial diversity was two-fold higher in the soil irrigated with groundwater as compared to the soil irrigated with wastewater.
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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) | 0.000 | 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 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".