Harnessing Trichoderma in Agriculture for Productivity and Sustainability
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
Increased agricultural activities driven by rising food demand have led to environmental problems mostly arising from the high levels of external inputs and resources that are required. Additionally, environmental changes, such as global warming, can lead to various biotic and abiotic stresses, which have negative impacts on crop production. Numerous solutions and agricultural strategies have been introduced to overcome these problems. One of the ways to improve plant production as well as to increase resistance towards biotic and abiotic stresses is by utilizing beneficial microbes as soil inoculants. A better understanding of the ability of Trichoderma to enhance crop production and the mechanisms that are involved are important for deriving maximum benefits from their exploitation. These versatile fungi hold great promise for the development of viable commercial products that can be used widely in agriculture for increasing crop productivity in a more sustainable way. Many previous reviews on Trichoderma have tended to focus on the mechanisms of Trichoderma in enhancing plant growth and yield. This current review discusses the sustainability aspect of using Trichoderma as plant growth regulators, the impact on plant growth and yield as well as their effects in regulating biotic and abiotic stresses.
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.
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) | 0.000 | 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