Occurrence of Black Scurf Disease of Potato in Multan (Punjab) Alongwith Its in vitro Chemical and Biotic Elicitor Mediated Management
Bibliographic record
Abstract
Black scurf disease of potato, caused by fungus Rhizoctonia solani, is the most common and one of the oldest diseases of potato affecting stem and stolons. In recent years, the disease is reportedly present in the fields of potato in Pakistan especially in Punjab. Survey of different locations viz. Narangaabad, Band Bosan, Kaian Pur, Kotla Abdul-Fateh and Dhillun was conducted to assess the prevalence of disease in Multan region. Maximum disease incidence and severity of 95.00% and 3.1 rating, was recorded in Kotla Abdul-Fateh respectively. Sclerotial pieces showing characteristic symptoms of black scurf were detached from tuber surface and the fungus was isolated on potato dextrose agar medium. For in-vitro chemical and biotic elicitor testing, three different fungicides viz., Monceren, Topsin-M, and Triton were evaluated using poisoned food technique and antagonistic effect of two accessions of Triochoderma spp. viz. Trichoderma harzianum and Trichoderma viridae was determined against the sensitivity of fungus. Triton was found to be superior at all concentrations in inhibiting the radial mycelial growth of the fungus followed by Topsin-M and Monceren. Satisfactory results were obtained by the antagonistic effect of Trichoderma harzinaum and Trichoderma viridae with 70.00% and 66.00% respectively under in-vitro conditions. Although the fungicide chemistries exclusively control the fungus yet the evaluation of bioagents also remained prolific towards antagonism against Rhizoctonia solani. These investigations provide fresh information on the current status of black scurf disease of potato in fields of Multan and regarding the biochemical management against Rhizoctonia solani under in-vitro conditions and serve as a guide for the future prospects against this holistic disease.
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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 | 0.001 |
| 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".