Sucheta Panda
Papers
1
Total Citations
3
H-Index
1
About
Sucheta Panda is a researcher whose work sits at the intersection of agricultural technology and artificial intelligence, with a particular focus on applying machine learning to plant disease detection. Her most-cited paper, "A Machine Learning Approach for Classification of Lemon Leaf Diseases" (2022), has garnered 3 citations and exemplifies her core contribution: developing accessible, data-driven methods for early and accurate identification of crop diseases. This work is vital for improving food security and reducing pesticide overuse, as it empowers farmers with rapid diagnostic tools. While her citation count is still growing, the practical relevance of her research—targeting a specific, high-value crop like lemons—demonstrates a clear commitment to solving real-world agricultural challenges. Panda’s approach combines rigorous algorithmic design with domain-specific knowledge, making her a promising voice in precision agriculture. Her efforts highlight how even modestly cited papers can have significant applied impact, especially in fields where technology is being adapted for grassroots use. For students and researchers, her work serves as a model for how machine learning can be tailored to niche, high-impact problems in sustainable farming.
Research Focus
Key Achievements
Top Papers
- 1A Machine Learning Approach for Classification of Lemon Leaf Diseases3 citations · 2022