Compost Tea and Poultry Litter Extract: Alternative Organic Management Approaches for Stem Canker of Potato Caused by Rhizoctonia solani
Bibliographic record
Abstract
An experiment was conducted in the field laboratory, Department of Plant pathology, Bangladesh Agricultural University, Mymensingh to know the efficacy of compost tea and poultry litter extract in controlling stem canker of potato under natural infection condition. Significant effect of different treatments was observed on the incidence of stem canker of potato as compared to control. The results evidently showed the lowest stem canker incidence recorded in plots when IPM Lab Biopesticde was applied followed by foliar spray of Ridomil, compost tea, and BAU-Biofungicide while the highest stem canker incidence was recorded in untreated control plot. However, the soil drenching of compost tea and poultry litter extract also performed better as compared to control in reducing the incidence of stem canker. Significant effect of the treatments was observed on the plant height and yield except number of plant raised per tuber. Foliar and soil application of compost tea, poultry litter and mustard oil cake showed better performance in increasing the plant height and yield as compared to all other treatments. Benefit cost analyses of the treatments revealed that foliar application of compost tea showed highest BCR (65.20) followed by Soil application of IPM Lab Biopesticide with BCR 54.38. The treatments viz. foliar spray of Ridomil and BAU-Biofungicide resulted 35.31 and 38.88 BCR, respectively which were the second best treatments as compared to untreated control. The results indicated that an investment of Tk. 1.00 may lead to a profit up to Tk. 65.20 by foliar application of compost tea which shows the maximum profit in the present study. Therefore, compost tea as foliar spray may be used as an alternative environment-friendly approach to control stem canker of potato along with other biological means with maximum economic return.
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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 | 0.000 | 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) | 0.001 | 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 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".