Computational modeling and emerging trend in agriculture

Computational modelling with the use of intelligence techniques for computing the agricultural output by providing minimum input data to lessen the time through cutting down the multi locational field trials and also the labours and other inputs is getting momentum. Development of locally suitable integrated farming systems (IFS) is the utmost need of the day, particularly in India where about 95% farms are under small and marginal holding size. The computational models are developed through incorporation of all independent variables which affect directly or indirectly the output of a system. Models can also be useful in teaching processes involved in the systems and its behaviour in response input variables. Calibration, verification, and validation are very important procedure to produce accurate simulation models. Computer simulations are good at portraying and comparing theoretical scenarios, but in order to accurately model actual case studies they have to match what is actually happening today. It is the research tools which can be used to curtail the huge expenditure in conducting the multiple experiments either in the field or laboratory. Computational modelling is increasingly effective for designing and analysis of the system. This is very important tool to analyses the effect of different scenarios on the systems and its interaction among themselves.