Analysis of Influencing Factors and Decision Criteria on Infield-Logistics of different Farm Types in Germany

Michael Mederle, Heinz Bernhardt


In future increasing production efficiency in agriculture will not only be achieved by rising machinery working widths but more and more by optimization of entire production process chains. The more machines are interacting the higher will be the specific optimization potential.

Navigation not only to the fields but also within the fields will certainly contribute to make use of these efficiency reserves. Necessary therefore is the knowledge of potential influences on infield-logistics to be able to navigate agricultural machinery in the fields effectively and process optimized.

Preliminary studies based on GPS-lane analysis in different German agricultural regions and in Central Canada show that decisions on specific infield patterns to a certain degree depend on unchangeable factors such as field geometry or field access points. Nevertheless regarding infield-logistics farm managers and staff members mostly act farm specifically as well as depending on technology or situation and furthermore often intuitive.

The examination is based on expert interviews with farmers of all agricultural regions in Germany. Rural mixed farms with simple machinery are considered as well as large agricultural cooperatives which farm thousands of hectares using track guidance and other electronic assistance systems. By aerial images of their arable land the individual decision behavior should be analyzed to specify the “soft” influencing factors.

First results show that farm managers using guidance tracking or SectionControl increasingly attune their infield-logistics to direction giving obstacles such as power lines. Livestock farmers rather focus on the application of organic manure, where road conditions and possible field access points become important due to the required supply logistics. Sugar beets make great demands on infield patterns because of relatively low bunker sizes compared to the mass to be transported as well as the positioning of the beet clamp.

Afterwards the obtained influences can be integrated into a navigation tool for optimizing infield logistics. Thus process efficiency can be further increased.


Agricultural logistics, process optimization, infield navigation, vehicle guidance, decision criteria

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