Cost Benefit Analyses in Managing Late Blight Through Trichoderma asperellum Seed Treatment and Ridomil® Application on Potato
Bibliographic record
Abstract
Fungicides overuse in management of late blight has led to increased cost of production and biodiversity issues. To better understand costs and benefits associated with seed treatment to reduce fungicide application, apical cutting and tuber seed crop were pre-treated by either peridermal injection or dipping using T. asperellum suspension at 33%, 66% and 100% concentration and then sprayed separately with Ridomil® (Metalaxyl 4% + Mancozeb 64%) at 21, 14 and 7 (Manufacturer’s Recommended Regime) days interval. Results showed that apical cuttings had 7.5% higher disease severity and 0.2% lower yield than crop from seed tuber. Untreated and 33% T. asperellum were not significant different (p = 0.05) in disease and yield scores. T. asperellum concentration at 66% and 100% reduced disease severity by 26% and 27% resulting to 30% and 29% yield increment respectively. Spray interval of 14 days did not differ significantly from 7 day spray interval in terms of disease score and yield but the regime MRR% was double 7 day spray interval. Maximum yield loss was observed in unprotected plots followed by treatments sprayed at 21 days interval. Combination of 66% and 100% T. asperellum concentration with 14 days interval resulted to higher yield and marginal rate of return compared to any other combination. Seed dipping was four times profitable than injection. The findings suggest that seed treatment at 66% and 100% T. asperellum concentration by dipping in combination with Ridomil® application at 14 days interval significantly reduced late blight epidemics and improved on yield and consequently increased net farm income.
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 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".