Generating recommendatins for agricultural crop production

Abstract

Agricultural Productivity depends on large number of parameters such as climatic conditions, soil quality, socio-economic factors, cultural practices, cultivation factors, technological innovations etc. The change in climate has a significant impact on the crop production. Scientists all over the world are trying to model the change in climate and various parameters affecting it. A huge amount of spatial data is available regarding climatic conditions, agricultural productivity etc. The data is available at varying resolutions. Applications of spatial data analysis in generating the rec-ommendations for farmers is considered. We specifically consider for cotton crop in North Gujarat region. A recommendation system is developed which helps farmers in various stages of farming. An extensive knowledge base in the form of ontology is also developed to provide support for better reasoning. The future extensions of the work includes the development of web based interfaces and a service oriented architecture to access the system in a platform independent manner. The recommendations would typically help the farmers choose the appropriate fertilizers, pesticides, cultural methods etc.