The Response of Spring Wheat Cultivars to Arbuscular Mycorrhizal Colonization under Salinity Stresses
Bibliographic record
Abstract
Wheat is an important crop, playing inevitable roles in human life, ranging from major food resource to raw material for biofuel. However, due to the dramatically reduced available arable areas and increasingly severe abiotic and biotic stresses, wheat production nowadays faces extreme challenges.. Many approaches have been explored to increase wheat yield including development of new cultivars. One of the most promising approaches is the application of the naturally existent arbuscular mycorrhiza (AM), a mutualistic symbiosis originated over 400 million years ago. AM have long been known to form mutualistic symbiosis with various plants to enhance yield production and to improve stress tolerance, especially drought and salinity. But the benefits vary among AM strains and plant species. Therefore, the objective of the study was to investigate the influence of four AM strains colonized on four selected spring wheat varieties under three salt concentrations (0, 50, 100 mmol/L). The results demonstrated that wheat inoculated with arbuscular mycorrhizal strains Funneliformis mosseae and Rhizoglomusirregulare mitigated yield losses caused by increased salinity stresses as well as strengthened root growth in comparison with non-inoculated plant controls. Salinity stress, however, had non-significant negative effects on most variables, except for grain yield, root surface area and root dry weight, in which a significant decrease was observed in root surface area and root dry weight with the increasing of saline concentration.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".