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A growing library of work spanning wheat genomics, molecular breeding, bioinformatics, plant disease, and computational agriculture.

18records currently indexed
2research directions
18 research outputsSearchable portfolio library
2024#01
Genomics & breedingGWASWheatPowdery mildew

Genome-wide association study for powdery mildew resistance in CIMMYT's spring wheat germplasm

Bhadana, D., Kaur, P., Kaur, R., Ravat, V.K., Ashutosh, Kumar, R., & Vasistha, N.K. · Plant Pathology, 74(2), 455–464.

Record
—#02
Genomics & breedingGWASGrain qualityWheat

Multi-model GWAS reveals genetic determinants of grain hardness, size and weight in bread wheat (Triticum aestivum L.)

Bhadana, D., Kumar, J., Ahmed, S., Kumari, A., Garg, M., Roy, J., & Kumar, R. · Molecular Genetics and Genomics.

Record
2023#03
Genomics & breedingComparative genomicsVMT genesWheat

Comparative analysis of VMT genes/proteins in selected plant species with emphasis on bread wheat (Triticum aestivum L.)

Sharma, H., Shayaba, Kumar, R., Kumar, J., Bhadana, D., Batra, R., Singh, R., Kumar, S., Roy, J.K., Balyan, H.S., & Gupta, P.K. · Genes & Genomics, 45(11), 1445–1461.

Record
2023#04
Book chapterKASPAllele miningPlant breeding

Allele mining and development of Kompetitive Allele Specific PCR (KASP) marker in plant breeding

Sharma, H., Kumar, S., & Bhadana, D. · Book chapter, IntechOpen.

Record
2021#05
Genomics & breedingWheatNewsletter

Annual Wheat Newsletter

Gupta, P.K., Balyan, H.S., Sharma, P.K., et al., including Bhadana, D. · pp. 16–25.

Record
2023#06
Genomics & breedingGermplasmGenomics

Genoplasmics: Advancing plant germplasm research through genomics

Saha, S., Bhadana, D., Shah, P.K., et al. · International Journal of Plant & Soil Science, 35(21), 106–116.

Record
2023#07
Genomics & breedingBioinformaticsComputational genomics

An overview of bioinformatics and computational genomics in modern plant science

Saha, S., Bhadana, D., Arya, R., et al. · International Journal of Environment and Climate Change, 13(9), 1530–1544.

Record
2024#08
Genomics & breedingBarleyYieldGenetic variability

Unraveling genetic variability, correlation and path analysis for yield and its components in barley (Hordeum vulgare L.)

Saha, S., Kumar, R., Bhadana, D., & Kumar, P. · Plant Cell Biotechnology and Molecular Biology, 25(7–8), 1–10.

Record
—#09
ConferenceVMT genesWheatComparative analysis

Computational identification and analysis of VMT genes and encoded proteins in seven monocots and three dicots with major emphasis on bread wheat

Deepa Bhadana, Shayaba, Hemant Sharma, Sachin Kumar, Rahul Kumar, Harindra S. Balyan, & Pushpendra K. Gupta · International Wheat Conference (China), Abstract No. XM-20349.

Record
2021#10
Computational agricultureDeep learningSeed diseaseVision Transformer

An enhanced deep learning framework integrating Vision Transformers-CNN for accurate seed-borne disease prediction in crops

Bhadana, D. & Purandhar, N. · International Journal of Business Management and Economic Review, 4(2), 260.

Record
2025#11
Computational agricultureVGG16Seed diseaseOptuna

Deep learning approach for seed disease prediction using VGG16 with transfer learning and Optuna optimization

Bhadana, D. & Kurunthachalam, A. · IJARSCT, 604–611.

DOI ↗
2024#12
Computational agricultureGNNPrecision farmingGenomics

FLETO-GNN: A hybrid genomic-aware zoning and fuzzy evolutionary treatment framework for smart precision farming

Bhadana, D. & Rs, A. · International Journal of Multidisciplinary and Current Research, 12.

Record
2022#13
Computational agricultureAgricultureSocio-economic survey

Rural agricultural work experience: Socio-economic survey in Budha Khera Village, Saharanpur, Uttar Pradesh, India

Saha, S. & Bhadana, D. · International Journal of Scientific Research, 11, 585–588.

Record
2023#14
Computational agricultureYOLOSeed diseaseComputer vision

Improving seed disease detection with YOLO and spatial attention mechanisms for agricultural applications

Bhadana, D. · Journal of Engineering and Science Research, 15, 148–159.

Record
2022#15
Computational agricultureXGBoostFusarium wiltCRISPR

Hybrid Autoencoder-XGBoost model for Fusarium wilt resistance using CRISPR-based genomic data

Bhadana, D. & Ganeshan, A.

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2020#16
ConferenceIoTPrecision agricultureZoning

Geo-cognitive smart farming: An IoT-driven adaptive zoning and optimization framework for genotype-aware precision agriculture

Bhadana, D. & Kurunthachalam, A. · Conference/Proceedings.

Record
2019#17
Computational agricultureSmart farmingGenomicsCrop optimization

STAMS-enabled genomic smart farming: A spectrotemporal intelligence framework for adaptive zone treatment and crop optimization

Bhadana, D. & Dr. G, A. · International Journal of Engineering Technology Research & Management, 3, 80–88.

Record
2018#18
Computational agricultureResNetRicePlant disease

Deep learning-based rice leaf disease classification using ResNet

Bhadana, D. · International Journal of Engineering and Technical Research.

Record

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