Editorial: Arbuscular mycorrhiza-mediated augmentation of plant secondary metabolite production
Bibliographic record
Abstract
Arbuscular mycorrhiza-mediated augmentation of plant secondary metabolite productionThe health promoting properties of plant products have increasingly gained acceptance.Besides several factors such as plant genotype, cultivation practices, environmental conditions, abiotic and biotic stress, symbiotic association of plant roots with soil-dwelling fungi namely arbuscular mycorrhizal (AM) fungi (AMF) is known to influence the content and range of phytochemicals produced by plants (Sbrana et al., 2014;Kapoor et al., 2017;Fokom et al., 2019;Thokchom et al., 2020;Javanmard et al., 2022;Zhao et al., 2022).The literature is overwhelmed with studies that deliberate on the effect of AMF on plants' metabolism, however knowledge on the underlying mechanisms thereof remains fragmentary.The four articles hosted in this special issue consolidate our understanding on the wide range of effects of AMF on plant metabolism and implication it holds on the overall growth and performance of the plant.Although AMF are restricted morphologically to the roots, AMF-induced physiological and metabolic alterations in the root also influence the physiology of the entire plant (Schweiger and Muller, 2015).Since the fungal symbionts are dependent upon plant-derived photosynthates (carbohydrates) and fatty acids, they act as strong carbon sink in roots.Consequently, the carbon balance in plants is maintained by regulation of photosynthesis and leaf primary metabolism (Kaschuk et al., 2009;Kogel et al., 2010).Alteration in the secondary metabolite profile of plant is an inevitable consequence of the changes in primary metabolism.While AMF-mediated effects on plant primary metabolism have been a subject of landscape of studies, relatively little is known vis-à-vis modifications in secondary metabolism in the systemic tissues.Furthermore, a comparative analysis of Frontiers in Plant Science frontiersin.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.030 | 0.018 |
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".