Impact Analysis of Lockdown in COVID-19 on agriculture using Machine Learning Regression model

Document Type : Primary Research paper


1 Associate Professor-Computer Science & Engineering, Women Institute of Technology (Govt.), Dehradun, India

2 Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

3 Assistant professor, Govt. Engineering College, Bharatpur, Rajisthan, India

4 Assistant Professor, Dept. of Computer Science & IT, MJP Rohilkhand University, Bareilly, India

5 Director, Women Institute of Technology, Dehradun, India

6 Professor, Computer Science and Engineering, Chandigarh University, Punjab, India


COVID-19, which emerged in January 2020, has affected almost all sectors of the economy. Agriculture sector also contributes in controlling the economy on a large scale. Social distancing is the only effective way to prevent the corona virus. In order to implement social distancing, more than 80 countries around the world have implemented the provision of lockdown. The lockdown has affected almost all sectors of the world, such as education, travel and hospitality, and agricultural imports and exports. This paper calculates the impact on the agriculture sector due to the lockdown under COVID-19 using a machine learning regression model. To understand the impact of COVID-19 on agriculture, we took a case study of one of the major agricultural countries, INDIA, and studied the impact using datasets collected from various sources. A significant positive relationship between food inflation, import goods and export commodities has been revealed by the results of data collision. This indicates that the decline in imports and exports of goods has led to a spurt in food inflation.