Time Series Analyses of Groundnut (Arachis Hypogaea L.,) in the Selected Sites of Karnataka State

Abstract

Background: India is one of the leading global producers of groundnut, with the states of Gujarat, Madhya Pradesh, and Tamil Nadu at the forefront. However, the area dedicated to groundnut cultivation and its production in India has experienced significant fluctuations over the years, leading to challenges in agricultural planning.
Methods: This research seeks to examine the trends in both area and production of groundnut in selected districts of Karnataka, specifically Tumkur and Chitradurga was major purposively selected for the study , because due to production and productivity is more for last five years. The study employs various time series models, including linear, quadratic, cubic, exponential, and logistic regression models were formulated, utilizing a dataset spanning twenty-five years (1997- 2022).
Results: The results indicate that, the cubic model is the most appropriate for assessing the area under cultivation, while the quadratic model is deemed to be most robust for analyzing production trends of groundnut in different agro climatic zones. Additionally, the study addressed various challenges and risks associated with groundnut production in Karnataka. Linear, quadratic and exponential models were fitted .Asper the results , the cubic and logistic models were found to be insignificant. Additionally, the Run’s test and Shapiro-Wilk test statistics were found to be non-significant for quadratic model. Therefore, the data on groundnut production in Tumkur district during the study period was well-fitted by the quadratic model as compared with rest of the study sites.
Conclusion: The findings aim to enhance the understanding of different oilseed production trends, thereby aiding farmers and government stakeholders in making informed decisions to ensure stable production across larger areas.