The Roles of Phytoalexin as Responsive Factors in Plant Disease Resistance and Its Benefit on Human Health
Bibliographic record
Abstract
The global challenge of food quality and safety urgently needed reform for safe consumption is closely linked to food insecurity and much emphasis is needed by farmers and plant scientists to understand the roles of phytoalexins and other natural products in the protection of economically important plants against pathogenic attacks.Despite limited experimental evidences and findings it has been suggested that phytoalexins plays major roles in disease resistance as some form of natural products which serves as antimicrobial metabolites of low molecular weight secretion which inhibit the growth of fungi pathogens while some are toxic to bacteria, nematodes and other organisms. This review provides an overview of the roles of phytoalexins a compound in plant defense and their diversity in selected plants families exploring the structural forms of its various groups as well as modes of accumulation from remote precursors through de novo synthesis of enzymes and complex defence mechanisms involving the actions of biotic and abiotic elicitors.. This article further highlight their biosynthesis and mechanisms of action delving into the distinctive metabolic pathways involved in the formation of novel synthetic phytoalexin models, mediated by enzymatic reactions and elicitor influences, shedding light on the complex interactions underlying plant defense strategies. Conclusion is drawn to emphasizes the potential of modern molecular tools in the elucidation of the mechanisms of phytoalexin synthesis and its accumulation,through the manipulation of gene(s) directly involved in their biosynthetic pathways.to produce the compounds for human therapeutic treatment for the promotion of human health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".