Physiological Analysis Reveals the Possible Resistance Mechanisms of Glycine max to Fusarium solani
Bibliographic record
Abstract
Sudden death syndrome (SDS) of soybean is a complex root rot disease caused by the semi-biotrophic fungus Fusarium solani (F. solani) and a leaf scorch disease; caused by toxins produced by pathogen in the roots. However, the mechanism of soybean resistant to F. solani is still poorly understood. Eighteen soybean cultivars were screened for SDS resistance, with one cultivar showing susceptibility and one cultivar showing resistance to F. solani infection. Histochemical analysis with diaminobenzidine (DAB) and Trypan blue staining indicated an accumulation of reactive oxygen species (ROS) and cell death in surrounding area of SDS which was higher in susceptible cultivar than in resistant cultivar. Furthermore, exogenous salicylic acid (SA) application also induced some level of resistance to F. solani by the susceptible cultivar. A biochemical study revealed that the activities of superoxide dismutase (SOD), peroxidase (POD), and enzymes involved in scavenging ROS, increased in susceptible cultivar after SDS infection. In addition, hydrogen peroxide (H2O2) and malondialdehyde (MDA) content also increased in the susceptible cultivar than in resistant cultivar. High-performance liquid chromatography (HPLC) analysis indicated that free and total salicylic acid (SA) content increased in the susceptible cultivar than in resistant cultivar. In addition, a real-time quantitative PCR analysis showed an accumulation of pathogen related (PR) genes in the resistant cultivar than in susceptible cultivar. Our results show that (i). F. solani infection can increase endogenous SA levels, antioxidase activities, ROS and cell death in susceptible soybean cultivar to induce resistance against Fusarium solani. (ii). F. solani infection induced the expression of SA marker genes in resistant soybean cultivar to enhance resistance.
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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 | 0.000 |
| 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 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".