Application of Mathematical Models in Agriculture- A Review

Abstract : Application of mathematical models are for solving problems in agriculture for a scientific understanding, quantitative expression and to take strategic decisions. Mathematical models include mechanistic, empirical, deterministic, and stochastic approaches. It has dynamic models with differential equations, static models with algebraic for a specific set of conditions, deterministic models suggest solutions, stochastic model deals with defined by probability functions, mechanistic model deals with theory or hypothesis, and empirical models uses existing data to explain the relationship between one or two variables. Mathematical models have been developed to investigate specific issues limited to mathematical formulation and the added complexity inherent of integrated models. Mathematical methods of resource utilization optimization have been used in practice and the first mathematical programming approaches include the method of linear programming (simplex method). Linear approach to modeling establishes the relationship between a dependent variable and one or more independent variables. In the linear equation, dependent and independent variables, coefficients, intercept or the bias coefficient and degree of freedom have been used. The application of mathematical models in agriculture portrays the main methods of various mathematical tools like analytical, simulation and empirical. This paper aims at application of Mathematical Models in agriculture.