Weather Based Cotton Yield Forecasting Models for South Gujarat Region

Pravinsinh K. Parmar *

Department of Agricultural Engineering, Agricultural Meteorological Cell, N. M. College of Agriculture, Navsari Agricultural University, Navsari –396 450, (Gujarat), India.

Narendra Singh

Department of Soil Science, Navsari Agricultural University, Navsari-396450, (Gujarat), India.

Vibha Tak

Department of Agricultural Engineering, Agricultural Meteorological Cell, N. M. College of Agriculture, Navsari Agricultural University, Navsari –396 450, (Gujarat), India.

Khyati Sabhani

Department of Agricultural Engineering, Agricultural Meteorological Cell, N. M. College of Agriculture, Navsari Agricultural University, Navsari –396 450, (Gujarat), India.

Abhinav N. Patel

District Agrimet Unit, Krishi Vigyan Kendra, Navsari Agricultural University, Surat ,(Gujarat), India.

*Author to whom correspondence should be addressed.


Abstract

An attempt has been made to developed the pre - harvesting forecasting models for cotton yields using (1995-2020) weather and yield data for Bharuch and Surat districts respectively. Models were validated for three years (2018-2020). Good agreements have been realized between actual and predicted yield with similar trends of deviation at pre - harvest stage. R2 values were 0.78 to 0.93 for both districts and stages respectively. Hence, these models can be used for forecasting cotton yield in mid – season (F1) and pre - harvest stage (F2) which is very useful to government authorities to plan the sugarcane production more efficiently. The estimated cotton yields during kharif, the year 2022 were 769 kg/ha and 870 kg/ha for F1 & F2 stage in Bharuch district and 1209 kg/ha and 1454 kg/ha for F1 & F2 stage in Surat district, respectively.

Keywords: Cotton, weather parameter, yield forecast


How to Cite

Parmar , Pravinsinh K., Narendra Singh, Vibha Tak, Khyati Sabhani, and Abhinav N. Patel. 2023. “Weather Based Cotton Yield Forecasting Models for South Gujarat Region”. International Journal of Environment and Climate Change 13 (9):3200-3204. https://doi.org/10.9734/ijecc/2023/v13i92564.