Sangram Chavan

About

Dr. Sangram Chavan was born on 7 December 1987 in Karad, Maharashtra, India. He earned his Ph.D. in Forestry from CCS Haryana Agricultural University, Hisar (2019), M.Sc. (Forestry) from FCRI, TNAU, Coimbatore (2011), and B.Sc. (Forestry) from Dr. BSKKV, Dapoli (2009).

He joined the Agricultural Research Service (ARS) of ICAR in 2013 and served as a Scientist (Forestry) at ICAR-Central Agroforestry Research Institute, Jhansi, before moving to ICAR-National Institute of Abiotic Stress Management, Baramati, in 2020. His research focuses on agroforestry, biomass and carbon modeling, climate change, bioenergy, tree improvement, and livelihood security.

Dr. Chavan contributed to quantifying India’s agroforestry area and carbon sequestration potential, developed android-based applications “FarmTree” and “Wood Bazaar” for agroforestry stakeholders, and guided postgraduate students. He served as Organizing Secretary for the National Seminar on Millets (August 2023), co-organized the 3rd World Congress on Agroforestry, and is an editorial board member and reviewer for several reputed journals.

Employment

• National Research Centre for Agroforestry Scientist (Forestry)
  2013 - Present
• National Institute of Abiotic Stress Management Scientist (Forestry/Agroforestry)

Education

• Chaudhary Charan Singh Haryana Agricultural University Ph D FORESTRY
  2016 - Present
• Tamil Nadu Agricultural University MSc Forestry
  2009 - 2011

Projects & Funding

Projects & funding information is unavailable.

Publications (77)

• Tree shade mitigates stress and enhances chickpea productivity: Insights from an Emblica officinalis-based agroforestry system in semi-arid shallow Basaltic Deccan Plateau, India
  Trees, Forests and People 2026 DOI: 10.1016/j.tfp.2026.101164
  +Save
• Estimating carbon sequestration in orchards of semi-arid tropics: A modeling approach
  Biomass and Bioenergy 2026 DOI: 10.1016/j.biombioe.2025.108610
  +Save
• Grape vine (Vitis vinifera) yield prediction using optimized weighted ensemble machine learning approach
  Smart Agricultural Technology 2025 DOI: 10.1016/J.ATECH.2025.101151
  +Save
• Soil- and Moisture-Saving Techniques Improve Rain-Fed Sapota Tree Growth, Productivity, and Fruit Quality in Semi-Arid Degraded Ravine Lands
  Applied Fruit Science 2025 DOI: 10.1007/S10341-025-01445-0
  +Save
• Optimizing tree shade gradients in Emblica officinalis-based agroforestry systems: impacts on soybean physio-biochemical traits and yield under degraded soils
  Agroforestry Systems 2025 DOI: 10.1007/S10457-024-01123-2
  +Save
• Nature-based solutions for enhancing CO2 sequestration and rehabilitating degraded lands through silvo-aromatic system and soil moisture conservation techniques
  Journal of Environmental Management 2025 DOI: 10.1016/J.JENVMAN.2025.124904
  +Save
• Integrating ecosystem services through sustainable land use approach in multifucntional agroforestry: The case of Tamil Nadu, Southern India
  Environmental and Sustainability Indicators 2025 DOI: 10.1016/J.INDIC.2025.100998
  +Save
• Fruit tree-based restoration strategy to mitigate greenhouse gas emissions, and enhance the profitability of degraded land in semi-arid tropics
  Science of the Total Environment 2025 DOI: 10.1016/J.SCITOTENV.2025.180409
  +Save
• Effects of Deficit Irrigation and Growth Regulators on Physio-Biochemical Changes, Yield, Fruit Quality and Water Productivity in Pomegranate (Punica granatum) Growing in Shallow Basaltic Soils
  Irrigation and Drainage 2025 DOI: 10.1002/IRD.70044
  +Save
• Editorial: Agroforestry for biodiversity and ecosystem services
  Frontiers in Forests and Global Change 2025 DOI: 10.3389/FFGC.2025.1616451
  +Save