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Recent technology advances in information technology and other engineering fields provide new opportunities for research and practices in precision agriculture. Using these technologies, field operators can collect voluminous data from a heterogeneous network of devices that provides real-time and multiple-factor measurement of field conditions with much finer granularity. A major challenge in precision agriculture today is how to analyze these data efficiently and use them effectively to improve farming decisions. We propose an extensible and integrated software architecture for data analysis and visualization in precision agriculture, with three distinctive features: (a) a meta-data-model-based data importation component capable of importing data in various formats from a variety of devices in different settings; (b) a data-flow-driven data processing subsystem in which a user can define his/her own data processing workflows and add custom-defined data processing operators for a specific application; (c) an overall architecture design following a client-server model that supports a variety of client devices, including mobile devices such as the Apple iPad. We implemented the software architecture in an open-source decision support tool for precision agriculture. The tool has been successfully used in a USDA-sponsored project on canopy management for specialty crops. [ABSTRACT FROM PUBLISHER]