Discussion on the Symbiotic Relationship between Legume Crops and Soil Microorganisms and Their Ecological Benefits
Bibliographic record
Abstract
Leguminous crops form a unique symbiotic system with soil microorganisms (especially nitrogen-fixing rhizobia and arbuscular mycorrhizal fungi), which plays an important role in agricultural ecosystems. This study reviews the biological basis of leguminous crop-microorganism symbiosis and its significance to soil microecology and agricultural sustainable development, introduces the mechanism of symbiotic nitrogen fixation, discusses how leguminous crops promote soil microecological balance by increasing soil organic matter, improving soil enzyme activity and improving soil physical and chemical properties, and explains the supporting role of microbial symbiosis on nutrient absorption and stress resistance of leguminous plants, such as improving nitrogen fixation efficiency, enhancing plant drought and salt tolerance, inducing plant immunity and biological control potential. Furthermore, from the perspective of ecological benefits, the contribution of leguminous-microorganism symbiosis in reducing fertilizer dependence and greenhouse gas emissions, restoring degraded soil functions and enhancing the stability of agricultural ecosystems is analyzed, and illustrated by cases such as soybean-rhizobium, peanut inoculants and leguminous rotation. This study hopes to provide a theoretical basis and practical reference for the role of leguminous crops and soil microbial symbiosis in sustainable agriculture.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".