Physio-Biochemical Mechanisms of Arbuscular Mycorrhizal Fungi Enhancing Plant Resistance to Abiotic Stress
Bibliographic record
Abstract
Agricultural innovations in the past decades have addressed the mounting challenges of food, feed, and biofuel security. However, the overreliance on synthetic fertilizers and pesticides in agriculture has exacerbated biodiversity loss, environmental degradation, and soil health deterioration. Leveraging beneficial soil microorganisms, particularly arbuscular mycorrhizal (AM) fungi, offers an emerging solution to reduce dependence on synthetic agrochemicals in crop production. Understanding the mechanisms can help maximize AM fungi’s benefits in response to abiotic stresses. In this review, we explore the main mechanisms of AM fungi in promoting soil nutrient mobilization and uptake, increasing water absorption, stimulating antioxidative enzyme activities, altering morphophysiological structure, and performing hormonal crosstalk when mycorrhizal plants face an abiotic stressor. Also, we highlight the necessity of innovating practical ways to cope with variations in AM fungal species, diversity in host species, soil, and environmental conditions, as well as difficulties in mass multiplication for commercialization. Understanding the mechanisms and limitations may help explore the biofertilizer potential of AM fungal symbiosis, benefiting crop production while addressing the environment and soil health issues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".