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Due to lack of an integrating system in existing agriculture system, the system is taking longer time and is difficult to handle dynamic needs of user which leads to customer dissatisfaction. Sorensen et al. 46 identified various functional requirements of FMIS and information model is presented based on these requirements to refine decision processes. They acknowledged that intricacy of FMIS is increasing with increase in functional requirements and create that there is a need of autonomic system to reduce complexity. The study conducted by 47 proposed WASS (Web-based Agricultural Support System) and recognized functionalities (information, collaborative work and decision support) and features of WASS. Based on features, authors divided WASS into three subsystems: production, research-education and management.
Reddy at el. 48 proposed GIS based DSS (Decision Support System) framework in which spatial DDS has been designed for watershed management and management of crop productivity regional and farm level. GIS is used to gather and analyze the graphical images for making new rules and decisions for effective management of data. Shitala et al. 49 presented mobile computing-based framework for agriculturists called AgroMobile for cultivation, marketing and analysis of crop images. Further, AgroMobile is used to detect the disease through image processing and also discussed how dynamic needs of user affects the performance of system. Seokkyun et al. 50 proposed cloud-based Disease Forecasting and Livestock Monitoring System (DFLMS) in which sensor networks has been used to gather information and manages virtually. DFLMS provides an effective interface for user, but due to temporary storage mechanism used, it is unable to store and retrieve data in databases for future use. Renaud et al. 51 presented cloud-based weather forecasting system to collect and analyze the weather data replication and ensures load balancing for management of resources.
The study conducted by Peter et al. 1, have proposed as a study which is conducted at majority of farmers in Kenya who are not able to sell their produce at market price due to lack of sufficient information available. Also, the agricultural productivity is being lessen due to the lack of information and resistance developed by the agricultural universities. For such farmers to produce and sell their products at market based competitive prices, information communication technologies (ICT) tools have be availed to them. This is because the development of agriculture is dependent on how fast and relevant information is provided to the end users.

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