Evaluating the use of plant hormones and biostimulators in forage pastures to enhance shoot dry biomass production by perennial ryegrass (<i>Lolium perenne</i> L.)
Bibliographic record
Abstract
Fertilisation of established perennial ryegrass forage pastures with nitrogen (N)-based fertilisers is currently the most common practice used on farms to increase pasture forage biomass yield. However, over-fertilisation can lead to undesired environmental impacts, including nitrate leaching into waterways and increased gaseous emissions of ammonia and nitrous oxide to the atmosphere. Additionally, there is growing interest from pastoral farmers to adopt methods for increasing pasture dry matter yield which use 'natural', environmentally safe plant growth stimulators, together with N-based fertilisers. Such plant growth stimulators include plant hormones and plant growth promotive microorganisms such as bacteria and fungi ('biostimulators', which may produce plant growth-inducing hormones), as well as extracts of seaweed (marine algae). This review presents examples and discusses current uses of plant hormones and biostimulators, applied alone or together with N-based fertilisers, to enhance shoot dry matter yield of forage pasture species, with an emphasis on perennial ryegrass.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".