Coordinated research on agrometeorology: India perspective
DOI:
https://doi.org/10.54386/jam.v25i2.2128Keywords:
AICRPAM, Weather, Climate, Crop, Pest, Agromet-advisory, DSSAbstract
The All India Coordinated Research Project on Agrometeorology (AICRPAM) was initiated in 1983 to utilize the climatic resource potential for better agricultural planning, enhanced productivity, profitability and sustainable livelihoods. The project has generated valuable research output in the areas of agroclimatic characterization, crop-weather relationship and weather effects on pests and diseases. Such information has been used for developing crop weather calendars, agroclimatic atlases, decision support systems, android apps, software for agromet data analysis, weather-based pest forewarning models, weather triggers for crop insurance etc. These products are being used for preparing agromet advisories and weather-related risk management systems. AICRPAM has completed forty years of its very meaningful existence with significant achievements and recommendations of practical value for the benefit of various stakeholders, particularly farmers. However, in view of the increase in intensity and frequency of the extreme weather events such as heat and cold waves, floods and droughts etc. under changing climatic conditions, the coordinated project envisages characterizing and identifying the hotspots, to minimize risks in crop production.
References
Bal, S.K. and Minhas, P.S. (2017) Atmospheric Stressors: Challenges and Coping Strategies. In: P.S. Minhas et al. (eds) Abiotic Stress Management for Resilient Agriculture. Springer Nature Singapore Pte. Ltd., pp. 9-50. https://doi.org/10.1007/978-981-10-5744-1_2
Bal, S.K., Dhakar, R., Kumar, P.V., Mishra, A., Pramod, V.P., Chandran, M.A., Sandeep, V.M., Subba Rao, A.V.M., Gill, K.K. and Prasad, R. (2021). Temporal trends in frost occurrence and their prediction models using multivariate statistical techniques for two diverse locations of Northern India. Theor. Appl. Climatol., 146(3): 1097-1110.
Bal, S.K., Prasad, J.V.N.S. and Singh, V.K. (2022a). Heat Wave 2022 – Causes, Impacts and Way Forward for Indian Agriculture. ICAR-CRIDA Technical Bulletin 01-2022. 50p.
Bal, S.K., Manikandan, N., Sandeep, V.M., Vijayakumar, P., Lunagaria, M.M., Subba Rao, A.V.M., Pramod, V.P. and V.K. Singh (2022b). Criteria based decisions for determining agroclimatic onset of the crop growing season. Agric. Forest Meteorol., 317: 108903. https://doi.org/10.1016/j.agrformet.2022.108903
Bal, S.K., Sandeep, V.M., Vijaya Kumar, P., Subba Rao, A.V.M., Pramod, V.P., Srinivasa Rao, Ch., Singh, N.P., Manikandan, N. and Bhaskar, S. (2022c). Assessing impact of dry spells on the principal rainfed crops in major dryland regions of India. Agric. Forest Meteorol., 313: 108768. https://doi.org/10.1016/j.agrformet.2021.108768
DTE. (2022). Update overdue: Why climate change should be integrated into crop calendars at the hyper local level. https://www.downtoearth.org.in/news/agriculture/update-overdue-why-climate-change-should-be-integrated-into-crop-calendars-at-the-hyper-local-level-84806 (Accessed on 13 Jan 2023).
Rao, G.G.S.N., Rao, V.U.M., Vijaya Kumar, P. and Rao, A.V.M.S. (2010). 25 years research of AICRP on Agrometeorology. Central Research Institute for Dryland Agriculture, Hyderabad – 500 059, 112p.
Rao, V.U.M., Bapuji Rao, B. and Venkateswarlu, B. (2013). Agroclimatic Atlas of Andhra Pradesh. Central Research Institute for Dryland Agriculture, Hyderabad - 500 059, 270p.
Rao, V.U.M., Rao, B.B., Sikka, A.K., Rao, A.S., Singh, R. and Maheswari, M. (2014). Hailstorm Threat to Indian Agriculture: A Historical Perspective and Future Strategies. Central Research Institute for Dryland Agriculture, Hyderabad - 500 059, 44p.
Rao, V.U.M., Subba Rao, A.V.M., Sarath Chandran, M.A., Prabhjyot Kaur, Vijaya Kumar, P., Bapuji Rao, B., Khandgond I.R., and Srinivasa Rao, Ch. (2015). District Level Crop Weather Calendars of Major Crops in India. Central Research Institute for Dryland Agriculture, Hyderabad – 500 059, 40p.
Rao V.U.M. (2011) Agro-climatic analysis: Weathercock Software, Short Course on Crop Weather Modeling (Sponsored by ICAR) held during 13-22 December 2011, e-publication, Pp 71-78. https://krishi.icar.gov.in/jspui/ bitstream/123456789/31188/ 1/ CWM% 20Lecture%20notes.pdf
Subbarao, A.V.M., Sarath Chandran, M.A., Bal, S.K., Pramod, V.P., Sandeep, V.M., Manikandan, N., Raju, B.M.K., Prabhakar, M., Islam, A. Naresh Kumar, S. and Singh, V.K. (2022). Evaluating area-specific adaptation strategies for maize under future climates of India. Sci. Total Environ., 836: 155511. https://doi.org/10.1016/ j.scitotenv.2022.155511
Subbarao, A. V. M., Arun K. Shanker, Rao, V. U. M, Narsimha Rao, V., Singh A. K, Pragyan Kumari, Singh, C. B., Praveen Kumar Verma, Vijaya Kumar, P. Bapuji Rao, B., Rajkumar Dhakar, M. A. Sarath Chandran, Naidu, C. V., Chaudhary, J. L, Srinivasa Rao and Ch., Venkateswarlu, B. (2015). Predicting Irrigated and Rainfed Rice Yield Under Projected Climate Change Scenarios in the Eastern Region of India, Environ. Model. Assess., 21(1): 17-30. https://doi.org/10.1007/s10666-015-9462-6
Vijaya Kumar, P., Bal, S.K.*, Dhakar, R., Sarath Chandran, M.A., Subba Rao, A.V.M., Sandeep, V.M., Pramod, V.P., Malleswari, S.N., Sudhakar, G., Solanki, N.S., Shivaramu, H.S., Lunagaria, M.M., Dakhore, K.K., Londhe, V.M., Kumari, P., Singh, M., Subbulakshmi, S., Manjunatha, M.S. and Chaudhari, N.J. (2021). Algorithms for Weather Based Management Decisions in Major Rainfed Crops of India: Validation Using Data from Multi-location Field Experiments. Agron. J., 113: 1816-1830. https://doi.org/10.1002/agj2.20518
Vijaya Kumar P., Subba Rao A. V. M., M. A. Sarath Chandran, Venkatesh, H., Rao, V. U. M. and Srinivasa Rao, Ch. (2017). Micro-level Agromet Advisory Services using block level weather forecast – A new concept-based approach. Curr. Sci., 112(2): 227.
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Copyright (c) 2023 SANTANU KUMAR BAL, M.A. SARATH CHANDRAN , A.V. M. SUBBA RAO, N. MANIKANDAN , B.V. RAMANA RAO
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