On-farm production and utilization of arbuscular mycorrhizal fungus inoculum
Bibliographic record
Abstract
Arbuscular mycorrhizal (AM) fungi colonize the roots of the majority of crop plants, forming a symbiosis that potentially enhances nutrient uptake, pest resistance, water relations, and soil aggregation. Inoculation with effective isolates of AM fungi is one way of ensuring the potential benefits of the symbiosis for plant production. Although inocula are available commercially, on-farm production of AM fungus inoculum would save farmers the associated processing and shipping costs. In addition, farmers could produce locally adapted isolates and generate a taxonomically diverse inoculum. On-farm inoculum production methods entail increasing inoculated isolates or indigenous AM fungi in fumigated or unfumigated field soil, respectively, or transplanting pre-colonized host plants into compost-based substrates. Subsequent delivery of the inoculum with seed to the planting hole in the field presents technological barriers that make these methods more viable in labor-intensive small farms. However, a readily available method for utilization of these inocula is mixing them into potting media for growth of vegetable seedlings for transplant to the field. Direct application of these inocula to the field and transplant of seedlings precolonized by these inocula have resulted in enhanced crop growth and yield. Key words: AM fungi, sustainable agriculture, biofertilizer
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".