Arbuscular mycorrhizal fungi elevate maize plant tolerance to Antimony, enhancing the nutritive value of seeds
Bibliographic record
Abstract
Abstract The rise in industrial activity has resulted in an escalating threat antimony (Sb) buildups and biomagnifications in both plants and humans. Arbuscular mycorrhizal fungi (AMF) have been thoroughly investigated as a soil enhancement due to their ability to decrease the accumulation of many heavy metals in plant tissues. However, a quantitative and data-based consensus has yet to be reached on the effect of AMF application on maize plants, focusing on plant growth, nutrient content, and antioxidant properties in maize grains subjected to antimony treatment. A notable decrease in AMF-related parameters, including colonization, hyphal length, and arbuscules, was noted when AMF was combined with Sb compared to AMF alone. The AMF treatment alone enhanced plant growth, as indicated by the increased fresh and dry biomass, while Sb treatment alone reduced substantially the total fresh (66%) and dray weight (65%). However, combining AMF with Sb resulted in significant variations in macro- and micronutrients in maize grains. Notably, the combined AMF and Sb treatment influenced the nutritional value of maize grains, showing increased levels of organic acids, amino acids, and fatty acids compared to control. Furthermore, antioxidant activity of maize grains was enhanced by AMF inoculation, as indicated by high levels of polyphenols (39%), flavonoids (63%), ascorbic acid (ASC) (71%), and glutathione (GSH) (28%) content as response to Sb application. Also, a 33% rise in total tocopherol was noted, reflecting comparable upward trends. These findings suggest that the co-application of AMF and Sb can positively influence maize nutritional quality and antioxidant properties of maize grains, offering benefits for sustainable agricultural practices.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".