The concept of precision farming is wide, and it represents the efficiency which is achieved with the help of precision. For the navigation of field machines, the RTK (Real Time Kinematic) navigation is needed. In order to verify the positive effects in practice, RTK navigation system equipped with Fentd 828 was applied to test the width of overlap, and fuel and time that could be saved compared with manual driving. The experiment was conducted on two areas of land size of 172 m × 58 m with two working machines width 3 m and 6 m. Results indicated that 15.7% of the time and 8.66% of the fuel were saved on a working machine of 3 meters width, and 12.6% of the time and 8.28% of the fuel were saved on a working machine of 6 m width. The width of the overlap represent 10% of the working width of the machine, and with the method of turning, which RTK navigation allows, additional time was saved. Ecological footprint, CO2 emissions and global warming potential (GWP) was estimated under different guiding systems. The largest footprint was related to manual tillage with 3 m width working machine, while estimation on CO2 (kg) emissions and GWP obtained the same result. The use of precision agriculture technologies allows better planning and analyzing of working procedures. The air, water and soil pollution are less intensive. Keywords: precision farming, RTK technology, ecological footprint, environmental pollution, tillage DOI: 10.25165/j.ijabe.20191205.4932 Citation: Kelc D, Stajnko D, Berk P, Rakun J, Vindiš P, Lakota M. Reduction of environmental pollution by using RTK-navigation in soil cultivation. Int J Agric & Biol Eng, 2019; 12(5): 173–178.

This paper describes a computer vision system based on image processing and machine learning techniques which was implemented for automatic assessment of the tomato seed germination rate. The entire system was built using open source applications Image J, Weka and their public Java classes and linked by our specially developed code. After object detection, we applied artificial neural networks (ANN), which was able to correctly classify 95.44% of germinated seeds of tomato (Solanum lycopersicum L.).

Growth and glucosinolate profiles of Eruca sativa (Mill.) (rocket salad) and Diplotaxis tenuifolia (L.) DC. under different LED lighting regimes | Denis Stajnko, Peter Berk, Andrej Orgulan, Marko Gomboc, Damijan Kelc, Jurij Rakun | Agricultural Journals

The fourth industrial revolution, which has begun couple of years ago, covers not only "smart" and interconnected machines and systems. It also coincides with further discoveries in various areas, from determining the genome sequence to nanotechnology and from renewable sources to quantum computing. The correlation between these technologies and their interaction in the physical, digital and biological field is what makes the fourth industrial revolution significantly different from the previous ones. The events should be faster, more extensive and radical, which will require the transformation of entire systems through (and within) countries, businesses, industries and society as a whole. We are already talking about switching from financing innovative projects to Comprehensive Innovation Ecosystems (AKIS). The paper describes some important research work from the field of automatization and digitalization of slovenian agriculture.

ISHS VII International Symposium on Modelling in Fruit Research and Orchard Management APPLICATION OF THERMAL IMAGING FOR VISUALIZATION OF HIGH DENSITY ORCHARDS AND COUNTING APPLE FRUITS