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Research Article Open access CC BY 4.0

Mycelial Compatibility Groups among Sclerotium rolfsii Isolates Associated with Collar Rot of Chickpea in Telangana, India

Niharika, D., Yella Goud, T., Ameer Basha, Laxmi Prasanna

Journal of Scientific Research and Reports · pp. 473–480 · Published 20 Jan 2026

10.9734/jsrr/2026/v32i13913

Abstract

Chickpea (Cicer arietinum L.) is one of the most important pulse crops cultivated extensively in India. Despite its immense potential and superior nutritional value, chickpea productivity remains low due to several biotic stress factors. Among the various diseases, collar rot caused by Sclerotium rolfsii (Sacc.) is the most destructive and leads to plant mortality ranging from 10% to complete crop loss. Considering the importance of the crop and the highly destructive nature of the pathogen, mycelial compatibility studies were undertaken. Thirteen S. rolfsii isolates isolated from collar rot–infected chickpea fields of Telangana were used in the present investigation. Mycelial compatibility among the isolates was assessed by dual culture and classified based on an aversion scale (0–4). Out of 78 isolate combinations, 44 showed complete mycelial compatibility (scale 0). All isolates were self-compatible, indicating the absence of self-incompatibility. Among the isolates, CSR-2, CSR-10 and CSR-12 showed incompatibility with seven other isolates (38.46%) indicating the highest level of incompatibility, whereas CSR-7 and CSR-13 were the most compatible (84.62%) each showing incompatibility with only one isolate. Despite the presence of several incompatible pairings (aversion levels 1–4), all isolates were interconnected through at least one fully compatible interaction. The results identified a single mycelial compatibility group (MCG) among the chickpea isolates, indicating low genetic variability and suggesting that control measures evaluated against a representative isolate may be effective across the region.

Chickpea Sclerotium rolfsii Collar rot mycelial compatibility group genetic variability disease management

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