Forecasting the Production and Area of Mango (Mangifera indica L.) in Himachal Pradesh by using Different Statistical Models - Kumar, Arun; Gupta, R. K. (International Journal of Bio-resource and Stress Management, 2020)
A statistical model is a formulization of relationships between variables in the form of the mathematical equation or set of mathematical equations. Statistical model provides tools for investigating the dependence and nature of relationship among the variables of interest. Different statistical models were used for forecasting the production of vegetables and fruits. Forecasts of agricultural production are intended to be useful for farmers, governments, and agribusiness industries. Because of the special position of food production in a nation’s security, governments have become both principal suppliers and main users of agricultural forecasts. They need internal forecasts to execute policies that provide technical and market support for the agriculture sector. Government publications routinely provide private decision makers with commodity price and output forecasts at regional and national levels and at various horizons The present investigation were conducted in the Department of Basic Science, Dr Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan (173 230) (H.P.) during 2013-2015.Secondary data on area (ha) and production (MT) for mango for last eighteen years was used and different prediction models viz. autoregressive, straight line, second degree parabola, exponential, modified exponential and gompertz were fitted & tested by using Adj. R2, Root mean square error and Thiel’s inequality coefficient. Second degree parabola and autoregressive models were found to be best models to forecast the area and production of mango crop as per Adj. R2, Root mean square error and Thiel’s inequality coefficient (U).