The project “Experimentierfeld Südwest” (https://ef-sw.de/) is a digitalisation project, which aims to promote cross-industry and inter-farm data management to support agricultural value systems.
In eight different sup-projects, the project consortium works on digital solutions for arable farming, viticulture, bee-keeping and fruit-growing in Rhineland-Palatinate. The research is accompanied by an Open data farm and a Living Lab at the Hofgut Neumühle as well as the knowledge transfer platform ‘Farmwissen’ (https://farmwissen.de/).
Our sub-project is focused on sensor-use in fruit-growing and digital decision support tools for fruit-growers.
Modern sensors offer numerous possibilities for digitally supporting agriculture. How modern sensor technologies can be integrated into fruit growing in the future is one of the central questions in this project. We are using a sensor platform, developed at University of Wageningen, consisting of three RGB-D cameras, a LiDAR sensor and a built-in RTK-GPS antenna, which allows to add GPS coordinates to the sensor data. We will test how well the sensors are suited for practical use in fruit growing, e.g. for detection of the blossom attachment for thinning or the counting of the fruits on the tree for yield estimation.
In addition to testing the sensor system, we will also analyse the suitability of various tree training systems for digitally assisted apple cultivation. It will be investigated whether the tree shape has an influence on how well such sensors can detect plant structures, such as blossoms or fruits. Besides support through new sensor technologies, fruit-growers are more and more in the need of tools that support their operational decisions. Fruit-growing underlies an increasing economic pressure due to increasing labour, energy cost and difficulties in the recruitment. At the same time, climate change bears additional challenges for orchard systems. These complex influences reinforce the need of holistic decision support tools for fruit-growers. Based on the decision analysis approach, we develop two decision models – one to advise fruit-growers on investments in frost protection and the second to evaluate the economic and physiologic viability of a system change from standard spindle training to a narrow fruit wall in apple cultivation. In addition, we are developing a quality forecast for apples using the decision analysis methodology, which will help to estimate the fruit quality at harvest time early in the year and to take the appropriate management measures.
Contact sub-project ‘Fruit-growing’
Until 31th of January 2023 (probably extended until 31 of January 2025)
Federal Ministry for Food and Agriculture (BMEL)