Microbial Metabolomics Interaction and Ecological Challenges of Trichoderma Species as Biocontrol Inoculant in Crop Rhizosphere
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The fungal species belonging to the genus Trichoderma has been globally recognized as a potential candidate of biofertilizer and biocontrol agent to prevent devastating soil-borne fungal pathogens and enhance growth and productivity of agricultural crops. The antagonistic activity of Trichoderma to pathogenic fungi is attributed to several mechanisms including antibiosis and enzymatic hydrolysis, which are largely associated with a wide range of metabolites secreted by the Trichoderma species. Besides suppressing target pathogens, several metabolites produced by Trichoderma species may act against non-pathogenic beneficial soil microbial communities and perform unintended alterations within the structures and functions of microbial communities in the crop rhizosphere. Multiple microbial interactions have been shown to enhance biocontrol efficacy in many cases as compared to bioinoculant employed alone. The key advances in understanding the ecological functions of the Trichoderma species with special emphasis on their associations with plant roots and other microbes exist in the crop rhizosphere, which are briefly described here. This review focuses on the interactions of metabolites secreted by Trichoderma species and plant roots in the rhizosphere and their impacts on pathogenic and non-pathogenic soil microbial communities. The complex interactions among Trichoderma–plants–microbes that may occur in the crop rhizosphere are underlined and several prospective avenues for future research in this area are briefly explored. The data presented here will stipulate future research on sustainably maximizing the efficiency of Trichoderma inoculation and their secondary metabolites in the crop soil ecosystem.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it