Editorial: Horticultural crops: Interaction with fungal community
Bibliographic record
Abstract
Horticultural crops: Interaction with fungal communityHorticultural crops such as vegetables, fruits, or ornamentals are used to increase the diversity of diet nutrient, improve health, and beautify our living environment.They are prone to interact with various fungi and other microbes during multiple developmental stages of growth.These fungal pathogens cause significant yield and economical losses in horticultural crops annually.For example, fungal pathogens along with the mechanical wounds and environmental factors cause up to 90% of total post harvest losses in citrus species (Perez et al., 2017;Zhu et al., 2017;Lin et al., 2019).Besides the pathogenic effect of fungi pathogens, beneficial plant-microbe interactions also play a role in horticultural crops.Trichoderma species, e,g., are widely used as bio-fertilizer and bio-fungicide (Kubheka and Ziena, 2022;Modrzewska et al., 2022).Plant-microbe interactions have been extensively studied in crops such as rice, wheat, corn and others in last two decades.However, there are knowledge gaps in the molecular mechanisms, integrated pest management, fungal genetics and biology, and beneficial microbes in horticultural crops.Thus, this research topic tried to update the recent knowledge and progress on the following questions: (1) how the beneficial microbes including fungi interact and promote horticultural crop growth; (2) how the fungal pathogens attack horticulture plants; (3) how to dig out more resistance from plants against fungal pathogens.To address these questions, a research topic was initiated aiming to identify additional genetics resistance to pathogens, beneficial bio-agents, and to reveal the mechanisms between horticultural crops and microbe interactions.These findings will facilitate integrated pest management in horticultural crops.After rigorous peer review, we collected four research and one review articles covering horticultural crops as oilseed rape (Brassica napus), citrus, Panax ginseng (Panax ginseng C.A. Meyer), Artemisia selengensis, etc.We hope these research objectives on plant and microbe interactions in different plant species can benefit each other, since these studies applied various methodologies such as genome wide identification, gene expression analysis, strain 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 | 0.004 | 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 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.020 | 0.017 |
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".