Crop diseases threaten yields in the field. Pests and parasitic weeds cause high crop losses of up to 30 percent every year.

In the FarmerSpace project, the Fraunhofer Institute for Optronics, System Technologies and Image Exploitation IOSB in Ilmenau is working together with partners to investigate the use of digital technologies for crop protection. The aim is to detect leaf diseases and the spread of weeds at an early stage and to initiate targeted protective measures using sensors, robotics and data-driven solutions.

Targeted crop protection is critical in agriculture. It ensures that plants are protected from diseases, pests and weeds. A healthy supply of nutrients to wheat, corn and the like influences the quality of the food and prevents crop losses. In the FarmerSpace digital experimental field, the project partners are exploring the potential of digital technologies to detect crop diseases at the right time and place in the field.

The platform for practical experiments offers players from research, practice and industry the opportunity to test sensor and data transmission systems, radio sensor networks, optical and machine-supported sensors, drone technology, robotics and machine learning methods in the fight against crop parasites.

In addition, machine learning methods create the prerequisite for evaluating the variety of data collected. In a common data room, all field-relevant data is to be recorded synchronously in terms of time and space, so that models can subsequently be trained that provide forecasts for further action required.

> Source: PHYS.ORG