Collaborative Data Collection in Agriculture - Case Sub-Irrigation On-Farm Experiment

Abstract

Agriculture is increasingly data-intensive. As farmers aim for more informed decisions, they produce growing data volumes that are valuable for the wider farm data ecosystem, particularly in research. Data collection in on-farm experiments benefits the farmer by improving confidence in the experiment results but also provides researchers with data from production-scale environments.Artificial drainage systems can be used for sub-irrigation of crops in open-field farming, in addition to their original use. The effectiveness of this kind of irrigation depends on local soil characteristics and natural groundwater level patterns, necessitating on-site measurements. However, developing a monitoring system required for validating the effect of sub-irrigation can be out of reach of an individual farmer.Over three years, a system for this purpose was collaboratively designed and built during a split-field experiment. This collaboration included the farmer, researchers, extension practitioners and companies. The system proved effective in validating the irrigation's impact on groundwater levels. The experiment helped develop collaboration in the region and provided insight into the requirements and challenges of developing a farm data ecosystem. The system itself provides a basis for long-term monitoring and supports further research, including the use of the data in simulation and AI models for predictive analytics and optimization.