DigiVine – Optics and Image Exploitation for Digitalization in Viticulture

Short description of the project

The project promotes the interaction of research and development, consulting and practice to penetrate and master the multi-layered process of grape production by means of Digitalization. It develops tailor-made services and recommendations for action for winegrowers and increases the efficiency of work and resources as well as legal security.

Our competences

Online quality control in the tank of the grape harvester:

The goal in this use case is to continuously record the quality (e.g. sugar and acid content) of the harvested grapes in the full harvest tank using suitable optical sensors. Laboratory systems are already being converted to and used as spectrometer systems in harvesting vehicles. Despite yield improvements, the technology's spread is inhibited by its enormous cost.

By using auto-calibration techniques and fusion of different sensors, miniaturized optical sensors, will be developed into a cost-effective alternative in this project. For this purpose, optical sensors will be attached to the tank of the grape harvester and tested.

Selective harvesting with the grape harvester:

The sensor-based detection of healthy canes and healthy harvesting material enables selective mechanical harvesting. In this process, the beating mechanism of the grape harvester can be completely switched off or reduced (unripe grapes or berries from diseased vines thus do not enter the grape harvester) or possibly the parameters can be changed so that unripe berries remain on the vine. Imaging spectroscopy by hyperspectral camera systems is an established research method for material detection in a wide variety of applications from microscopy to remote sensing. Due to the enormous cost of the equipment, applications are mainly found in research projects. However, significant spectral ranges can be identified by evaluating hyperspectral images. With the help of optical bandpass filters, low-cost imaging systems for special product characteristics can be developed (see GrapeSort project).

Project goals

The intended internal digital networking and visualization of data from the process chain allows targeted intervention in natural variations (varieties, soil, weather) and, in the medium term, a data-based response to climate change, the realization of natural and environmentally friendly viticulture (sustainability) and, with simultaneous resource and cost savings, increased work efficiency.