A Review of Indicators of Healthy Agricultural Soils with Pea Footrot Disease Suppression Potentials
Bibliographic record
Abstract
The quality of a soil is often viewed in relation to its ability to suppress plant disease and enhance agricultural productivity. A soil is considered suppressive when, in spite of favourable conditions for disease incidence and development, a pathogen cannot become established, or establishes but produces no disease, or establishes and produces disease for a short time and then declines. The interplay of biotic and abiotic factors has long been known to assert disease suppressive capabilities or otherwise. However, the multi-functionality of soil makes the identification of a single property as a general indicator of soil health an uphill task. In this paper, therefore, some indicators of soil health important to agriculture are reviewed with emphasis on pea footrot disease suppression potentials. Findings show that footrot disease due to Nectria haematococca (anamorph Fusarium solani f.sp pisi) is a globally, economically important disease of peas, and an initial inoculum density of ? 100 pathogenic forms of N. haematococca cells would produce an appreciable level of pea footrot disease depending on the relative amount of phosphorus, carbon and nitrogen present in soil. It would be desirable to confirm pea footrot disease models obtained from pot experiments with results from field experiments.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".