Arbuscular mycorrhizal fungi alleviate oxidative stress in pomegranate plants growing under different irrigation conditions
Bibliographic record
Abstract
Drought greatly affects the growth and development of plants. This stressful condition can trigger an increase in reactive oxygen species (ROS) production that, in turn, can induce cellular, anatomical, and morphological changes that improve drought tolerance. A strain of arbuscular mycorrhizal fungi (AMF) is considered efficient when it colonizes roots quickly and extensively, absorbs and transfers nutrients to the plant host, promotes soil aggregation, and protects the host against disease. We evaluated the effect of inoculation of two strains of the AMF Rhizophagus intraradices (N.C. Schenck & G.S. Smith) C. Walker & A. Schüßler (GA5 and GC2) on pomegranate plants (Punica granatum L.) under two irrigation conditions. The response to oxidative stress depended on many factors, including the organism tissue and the degree of stress. Our study showed that, in most cases, mycorrhizal plants increased antioxidant defenses, such as the ROS-scavenging enzymes superoxide dismutase (SOD), catalase (CAT), and ascorbate peroxidase (APX) in shoots under both irrigation levels, whereas the response for roots was ambiguous. AMF inoculation maintained the levels of malondialdehyde (MDA), probably by rapidly increasing antioxidant defenses and preventing lipid damage. We show that early AMF inoculation (particularly with the GC2 strain) in pomegranate propagation protects plants against abiotic stress.
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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) | 0.000 | 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) | 0.001 | 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".