A challenge in modern farming is to find a sustainable way of achieving sufficient production. Precision in dosage, timing and allocation of water, biocides, fertilizer and other inputs is essential, as are such management actions as harvesting, pruning and weeding. Despite the increasing availability of sensor and actuator technologies, decision-making is still largely left to the farmer. This is creating a strong demand for support in operational management. This paper presents an overview of methods involving the use of technology and data to develop model-based management support and automation for productive and input-efficient farming. For each method, the main advantages and drawbacks relating to typical farm characteristics are discussed and summarized. Three case studies are presented, to illustrate the design steps involved in developing a model, observer and controller. The overall design procedure is summarized in a flowchart, and serves as a basic guide for method selection and model development.
- Precision farming