Wheat yield prediction in relation to climatic parameters using statistical model for Ludhiana district of central Punjab

• Published in: Journal of agrometeorology Vol. 23; no. 1; pp. 122 - 126
• Main Authors: Singh, Mahesh Chand, Pal, Vajinder, Singh, Sompal, Satpute, Sanjay
• Format: Journal Article
• Language: English
• Published: Anand Association of Agrometeorologist 01.03.2021; Association of agrometeorologists
• Subjects: 21st century; Agricultural policy; Agricultural production; Cereal crops; climate; Climate change; Climate models; Climatic conditions; Climatic data; Climatic zones; Crop growth; Crop production; Crop yield; Crops; Growth patterns; Historical account; History; Humidity; Mathematical models; Production management; Rain; Regression analysis; Statistical analysis; Statistical model; Statistical models; Statistical prediction; Wheat; Wheat yield; Yield forecasting; India
• ISSN: 0972-1665; 2583-2980
• DOI: 10.54386/jam.v23i1.97

Climate change which is one of the main determinants of agricultural production has started affecting the crop growth pattern and yield from past couple of decades in various agro-climatic zones globally. Under such scenario, the prior forecasting of yield of field crops such as wheat via modeling techniques can help in simplifying the crop production management system starting from farmer’s level to policy makers. The present study was thus undertaken to model the wheat yield of Ludhiana district of  Indian Punjab through regression analysis of historical data (1993-2017) of wheat yield and climatic conditions in the area. The developed model was successfully validated with a strong positive correlation (R2=0.81) between predicted and observed data. Both observed and predicted yields were having similar trend with a minimum and maximum absolute differential error of 0.1 and 13.9% respectively. The developed model may serve as a powerful tool for predicting the future yield of wheat crop with available futuristic climatic data of the study area.