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Anurag

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Open access Aug 2026

Deciphering Genetic Variability and Stability for Yield Improvement in Mungbean (Vigna radiata)

Mungbean [Vigna radiata (L.) R. Wilczek] is an important short-duration and widely adaptable pulse crop known for its nutritional andsoil-ameliorative properties. However, its productivity still lags due to photo- and thermo-period sensitivity, the seasonal specificity ofthe available cultivars, and susceptibility to a wide range of biotic and abiotic factors. Therefore, breeding for developing stable elitecultivars is urgently required to improve productivity. A total of 55 genotypes of mungbean, including released varieties and elitelines, were tested over a period of three years to identify the stable elite lines for high yield. A wide range of variability was recorded for seed yield per plant (SYP) and its key component traits. Based on correlation coefficient analysis, PL and NSP were found to be keycomponents. The significant interaction of genotype × year indicated the crucial role of the environment on SYP. The correlationcoefficient analysis revealed that pod length (PL) and number of seeds per pod (NSP) were key yield contributing traits. GGE biplotanalysis demonstrated that five genotypes, i.e. G42 (BMS 19-3), G17 (Shikha), G49 (ML 134), G18 (TRAM-18), and G27 (BMS 18-4), werefound most stable and high-yielding genotypes over the year. Further, the molecular characterisation of these selected genotypeswith SSR and functional markers opens the scope for their effective utilization in the mungbean breeding programme

Chandra Mohan Singh, Mukul Kumar, H. Kumar et al. · 0 citations
Open access 2026

Explainable Hybrid Transformer Model Based Fake News Detection System

This paper presents an extensive study of fake news detection, which involves manually curated linguistic features, classic machine learning techniques, DL, transfomer, and fusion multimodal, and examines the key multimodal benchmark, the Fakeddit dataset.

Anurag, Amandeep · 0 citations