Usability of monthly ERFS (Extended Range Forecast System) to predict maize yield using DSSAT (Decision Support System for Agro-technology Transfer) model over Erode District of Tamil Nadu Harinarayanan M.N* Agro Climate Research Centre, Tamil Nadu Agriculture University, Coimbatore (Tamil Nadu), India Manivannan. V Department of Agronomy, Tamil Nadu Agriculture University, Coimbatore (Tamil Nadu), India Ga Dheebakaran Agro Climate Research Centre, Tamil Nadu Agriculture University, Coimbatore (Tamil Nadu), India Guna. M Agro Climate Research Centre, Tamil Nadu Agriculture University, Coimbatore (Tamil Nadu), India *Corresponding author. Email: hariharinz206@gmail.com Article Info https://doi.org/10.31018/ jans.v14iSI.3709 Received: April 19, 2022 Revised: June 21, 2022 Accepted: June 27, 2022 This work is licensed under Attribution-Non Commercial 4.0 International (CC BY-NC 4.0). © : Author (s). Publishing rights @ ANSF. ISSN : 0974-9411 (Print), 2231-5209 (Online) journals.ansfoundation.org Research Article INTRODUCTION Vital monsoons in India are the southwest monsoon season June–September (JJAS) and also northeast monsoon season, October–December (OND). Utmost states of the country meet their heaviest rainfall during the southwest monsoon season except for the south- eastern portion (Tamil Nadu), which receives maximum rainfall during the northeast monsoon (Attri and Tyagi, 2010). India Meteorological Department (IMD) issues weather forecasts for planning and decision-making in agriculture, water management and policymakers dur- ing both monsoon seasons. IMD disseminates weather forecasts at different temporal scales that are short range, medium range, extended range and seasonal scales used for tactical and strategic decisions in agri- culture and allied sectors. Extended Range Forecast Service (ERFS) is highly beneficial for crop planning and midterm correction at the farm level. Another way, it is also useful for the poli- Abstract Extended Range of Forecast Service (ERFS) is highly useful for planning of cropping season and midterm correction at the farm level. The medium-range and long-range forecast validation have many studies, whereas ERF has less that needs to be studied. Maize is an important field crop in India after rice and wheat. Therefore, the prediction of maize yield has significant importance. In the present study, ERFS data were validated by correlation analysis using monthly observed rainfall frequency and intensity. This data was imported to DSSAT (Decision Support System for Agro-technology Transfer) to simulate maize yield of Erode district of Tamil Nadu. The model output and actual yield data from Erode were compared. Forecasted monthly total rainfall was correlated at a rate of 0.97r value with that observed. Yield simulation of maize was done using DSSAT by integrating ERFS data and the observed monthly data. Mean per cent deviation among the yields of observed weather and the disaggregated one tended to be -15.7 %. The average deviation between the yields of ERF forecasted weather data and actual yield was very high ( -29.7 % ) for Erode. Mean % deviation between the yields of observed weather and the actual yield was - 14.7 %. Downscaled and accurate weather forecasts could be facilitated for yield prediction of crops by DSSAT model. Yield prediction by the model under observed weather was convenient and usable. Model under -predicted the yields when using ERF data. Both model and ERF forecast need to be improved further for higher resolution. Keywords: ERFS, DSSAT, Erode district, Rainfall, Maize, Yield prediction How to Cite Harinarayanan, M. N. et al. (2021). Usability of monthly ERFS (Extended Range Forecast System) to predict maize yield using DSSAT (Decision Support System for Agro-technology Transfer) model over Erode District of Tamil Nadu . Journal of Applied and Natural Science, 14 (SI), 244 - 250. https://doi.org/10.31018/jans.v14iSI.3709