Dr. Philipp Lottes founded Pheno-Inspect GmbH in January 2020 to raise the technology level of digital phenotyping for agriculture and plant breeding and make it accessible to every practitioner worldwide. He received his Ph.D. in Machine Learning and Computer Vision from the Photogrammetry and Robotics Lab at the University of Bonn in January 2021. He focused on developing crop classification systems for UAVs, agricultural robots such as drones, robots, and tractor-based systems. He received his master’s degree in geodesy and geoinformation in 2016. Before coming to Bonn, he studied surveying engineering at the University of Applied Sciences in Bochum and worked as a surveyor in the Ruhr area for several years.
How do plants grow? Where do stress symptoms occur? What weeds, or plant diseases are present in the field? Which varieties prove themselves under certain environmental or growing conditions? Anyone who grows plants or breeds varieties must spend a lot of time and effort collecting data and evaluating it to answer such questions.Within crop production and plant breeding, phenotyping, i.e., measuring the appearance of the plants, remains a complex and time-consuming, thus expensive process.
Pheno-Inspect GmbH develops state-of-the-art image processing software for the agricultural and plant breeding sector to automate the surveying of plants and digitally record the status and performance of crops in the fields. We develop “digital experts” based on artificial intelligence that analyze plants and support or replace the human eye in the field by exploiting high-resolution RGB, multispectral or hyperspectral image data.