Böcker av Kamal Batra

To sustain the need of food security, there is a strain on food producers and researchers to use the technology especially Information Technology in such a way that it should cater to all the demands by making a judicious use of the available resources. Over the years, it has been observed that, despite the availability of best varieties and associated inputs, the attainable yield of many crops is below the expected levels. To overcome this gap, proper policy may be framed using IT techniques in the area of agriculture. Therefore, Information and Communications Technology (ICT) based decision support in the area of forecast must be visualized. In agriculture, forecast and decision support system helps a farmer to get proper information provided by the area experts, making a farmer use it for proper and in advanced planning for his crop. There are lots of unknown variables/factors such as weather, crop production etc. which directly or indirectly affect the prices of the crops and can often lead to unexpected losses to the farmers. One of the major cost contributors in agriculture is irrigation water. The moisture loss due to evaporation can add to the cost of irrigation and can have an overall impact of cost efficiency in agriculture. The water losses from the primary water resources/water bodies thus, needs to be estimated accurately for planning the requirement of water resources for a particular crop. Under this situation, an attempt has been made to study ICT based forecasting (backed by Artificial Neural Network (ANN) model) and Decision Support System (DSS) in agriculture to find out the irrigation requirement of a particular crop based on the water losses due to evaporation. The ANN model-based evaporation prediction aids the decision support system to forecast the requirement of irrigation water according to the selected crop in a particular agro-ecological zone. This will not only provide the valuable information and guidance to the farmers, but it also has become a must to make agriculture as a viable business. Agriculture being complex in nature, a simple forecasting model and decision support system may not address the purpose of dynamic decision making. The web based DSS utilizing forecast model based on data mining technique (Neural Network and Hybrid model) is a viable and appropriate alternative option and are becoming indispensable to disseminate this information efficiently and effectively and may reduce the cost of cultivation of the farmers.To improve the estimation, the new data mining techniques especially Artificial Neural Networks (ANN) techniques are being used for estimating the evaporation more accurately. Recently, ANN techniques are getting more attention as compared to the traditional models as it learns from the exemplar data and predict the pattern using supervised learning.