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This paper investigates four different mobile robots with respect to their drivingcharacteristics and soil preservation properties in an agricultural environment.Thereby, robots of classical design from agriculture as well as systems from spacerobotics with advanced locomotion concepts are considered to determine theindividual advantages of each rover concept with respect to the application domain.Locomotion experiments were conducted to analyze the general driving behavior,tensile force, and obstacle‐surmounting capability and ground interaction of eachrobot. Various soil conditions typical for the area of application are taken intoaccount, which are varied in terms of moisture and density. The presented workcovers the specification of the conducted experiments, documentation of theimplementation as well as analysis and evaluation of the collected data. In theevaluation, particular attention is paid to the change in driving characteristics underdifferent soil conditions, as well as to the soil stress caused by driving, since soilquality is of critical importance for agricultural applications. The analysis shows thatthe advanced locomotion concepts, as used in space robotics, also have positiveimplications for certain requirements in agricultural applications, such as maneuver-ability in wet conditions and soil conservation. The results show potential for designinnovations in agricultural robotics that can be used, to open up new fields ofapplication for instance in the context of precision farming.
PEF is an innovative technology to extend the shelf life of fresh liquid food products, mainly juices, with minor impact on the quality. Many lab scale studies have been published, indicating the great potential of PEF for the juice industry. For industrial realization, the PEF systems have been adapted to the industrial requirements, establishing HACCP and hygienic design concept. Important process parameters have been identified from research and integrated in industrial PEF processes. Juice producers are now able to use PEF for their production lines.
Knowledge of the small-scale nutrient status of arable land is an important basis for optimizing fertilizer use in crop production. A mobile field laboratory opens up the possibility of carrying out soil sampling and nutrient analysis directly on the field. In addition to the benefits of fast data availability and the avoidance of soil material transport to the laboratory, it provides a future foundation for advanced application options, e.g. a high sampling density, sampling of small sub-fields or dynamic adaptation of the sampling line during field sampling. An innovative key component is the NUTRI-STAT ISFET sensor module. It measures values for the ions "NO3- ”, “H2PO4- " and "K+ " as well as the pH. The ISFET sensor module was specially developed for soil nutrient analysis. The phosphorus measurement was further developed for the project "soil2data". First results from the ISFET sensor module show a measurement signal settling time of significantly less than 100 seconds and a further consistent stable measurement signal. The measurement signal dynamics of approx. 58 mV per factor 10 of concentration change is given for the measured variables pH and K+. For the measured quantities of NO3- and H2PO4- , the measurement signal dynamics are lower.
Computer-image processing becomes more and more important in the analysis of data in biological and agricultural research and practice. However, robust image processing is highly de pendent on the histogram analysis algorithms used and the quality of the data being processed. The algorithm presented here aims to improve the accuracy of the classification of image data generated under complex boundary situations and inconsistent lighting conditions. Using the example of the determination of nitrogen content of tomato leaves and the qualitative determination of starch con tent of apples on the basis of color image processing, we showed that the developed algorithm is able to perform a robust classification and represents an improvement to simple histogram analysis.
Within the consortium “Experimentation Field Agro-Nordwest”, a practical concept for knowledge and technology transfer of digital competence in agriculture was created. For this purpose, the web-based e-learning system “SensX” was set up, consisting of videos, presentations and instructions. In addition, the classical e-learning concept was extended by data sets, student experiments and sensor data of plants acquired by a remote phenotyping robot. This resulted in a massive open online course (MOOC), which was tested with agricultural and biotechnology students in higher education at the University of Applied Sciences Osnabrück over two years. The evaluation process of “SensX” included an empirical survey, qualitative interviews of the participating students by an external institution and an evaluation of the concept by the lecturers.