Trend Pattern Analysis of Cotton Using Linear and Non-linear Models

This paper investigates the trend patterns in area, production, and yield of cotton in India using secondary time series data from 2001-2023. Trend values are estimated by fitting linear, exponential, quadratic, and cubic models to the data. The accuracy of these models is evaluated using statistical measures, including the coefficient of determination ( ), root mean square error (RMSE), and relative mean absolute percentage error (RMAPE). The findings reveal that all applied models effectively represent the trends, with the cubic model exhibiting the highest accuracy. This makes it a reliable choice for forecasting the future scenario of cotton production in India. The findings offer valuable insights for policymakers in formulating strategies to enhance cotton production and strengthen its position in global trade.