Dr. Prameela Krishnan

Dr. Prameela Krishnan is a Principal Scientist at ICAR-Central Institute of Brackishwater Aquaculture. She is former Head & Professor, Division of Agricultural Physics, IARI, New Delhi. She has earned a Masters from Department of Biophysics, University of Madras and a Ph D from Agricultural Physics, IARI, New Delhi.  She has Post Doctoral Experiences from University of Oxford, UK  and Climate Change Lab, USDA, USA. With more than 34 years of experience in ICAR, Dr. Krishnan has consistently demonstrated the application of principles and laws of Physics in agriculture, bridging fundamental science with real‑world challenges. Her work has empowered farmers, enlightened policymakers, enriched scientific communities, and inspired students, making her contributions deeply societal, advancing food security, sustainability, climate resilience, AI-driven farming, with emphasis on simulation, Forecasting, regenerative practices, and digital technologies for future generations.

At CIBA her work focuses on AI based simulation modelling and image analysis for Aquatic Animal Health and Environment.

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1. Fellow - National Academy of Agricultural Sciences (NAAS), New Delhi - 2021
2. ICAR - Punjabrao Deshmukh Outstanding Woman Scientist Award - 2014 by Indian Council of Agricultural Research, New Delhi
3. Fulbright Senior Research Fellowship (USA) 2009-2010 by J William Fulbright Foreign Scholarship Board and Cultural affairs of the United States of Department of State (USDA), Washington DC, USA, visited Global Climate change Laboratory, USDA, Maryland, USA
4. BOYSCAST (2003-2004) Fellowship by Department of Science and Technology (DST), Government of India, visited the Laboratory of NMR, Department of Plant Sciences, University of Oxford, UK
5. Fellow - Indian Society of Plant Physiology (ISPP) - 2014, New Delhi

1. Krishnan P*, R K Sharma, Anchal Das, Ankur Kukreja, Ravi Srivastava, Ruchika Jain Singhal, K. K. Bandyopadhyay, Khajanchi Lal, K. M. Manjaiah, R. S. Chhokar and S. C. Gill (2016) Web-based crop model: Web InfoCrop - Wheat to simulate the growth and yield of wheat. Computers and Electronics in Agriculture 127: 324-335. (IF -8.9) [NAAS 2026, 14.9] https://doi.org/10.1016/j.compag.2016.06.008
2. Koushik Banerjee and P. Krishnan* (2020) Normalized Sunlit Shaded Index (NSSI) for characterizing the moisture stress in wheat crop using classified thermal and visible images. Ecological Indicators. 110: 105947 (IF – 7.4) [NAAS 2026, 13.4] https://doi.org/10.1016/j.ecolind.2019.105947
3. Koushik Banerjee; Prameela Krishnan* and B Das (2020) Thermal imaging and multivariate techniques for characterizing and screening wheat genotypes under water stress condition. Ecological Indicators. 119: 106829 (IF – 7.4) [NAAS 2023, 13.4] https://doi.org/10.1016/j.ecolind.2020.106829
4. Krishnan P*, Swain D K, Baskar C, Nayak S K and Dash R N (2007) Impact of elevated CO₂ and temperature on rice yield and methods of adaptation as evaluated by crop simulation studies. Agriculture, Ecosystems & Environment, 122(2): 233-242. (IF - 6.4) [NAAS 2026, 12.4] https://doi.org/10.1016/j.agee.2007.01.019
5. Victor Banerjee, P Krishnan*, Bappa Das, A P S Verma and E Varghese (2015) Crop Status Index as an indicator of wheat crop growth condition under abiotic stress situations Field Crops Research 181, 16–31. (NAAS 2026, F010, 12.4) https://doi.org/10.1016/j.fcr.2015.06.009

1. Monika Kundu, Ananta Vashisth & Prameela Krishnan, (2026), Instrumental detection of fish freshness in research and food industry: a review. Journal of Food Science and Technology 63 (1), 22-50. https://doi.org/10.1007/s13197-025-06497-4 [NAAS 2026, 9.3]
2. Deepti Joshi, Prameela Krishnan*, Ananta Vashisth, Monika Kundu, Alka Rani & Tusar Kanti Bag (2025) AI-Based Machine Learning and Multiple Linear Regression Approach to Simulate the Effect of Weather on the Crop Age at First Appearance of Potato Late Blight  (Phytophthora infestans (Mont.) de Bary) Disease. Potato Research 68, 1825–1848. https://doi.org/10.1007/s11540-024-09795-0
3. Tarun kumar, Prameela Krishnan*, Sona Kumar, Amrender Kumar & Anju Mahendru Singh (2025), Identification of the cultivars of the wheat crop from their seed images using deep learning: convolutional neural networks. Genetic Resources and Crop Evolution 72, 1633–1648. https://doi.org/10.1007/s10722-024-02042-y