Tag Archives: GPS

41-53 J. Kaivosoja and R. Linkolehto
Spatial overlapping in crop farming works
Abstract |
Full text PDF (791 KB)

Spatial overlapping in crop farming works

J. Kaivosoja* and R. Linkolehto

Natural Resources Institute Finland (LUKE), Green Technology, Vakolantie 55, FI 03400 Vihti, Finland
*Correspondence: jere.kaivosoja@luke.fi

Abstract:

A good driving accuracy and a proper machine input control are essential in sustainable farming. The goal is to work on the field exactly according to the plan, for example spraying a certain amount of fungicides evenly to the field. However, without modern assisting systems the farmers tend to overlap their driving lines. So far there have not been quantitative tests to present how mark able this overlapping is in real conditions. To solve this, we collected data from regular farming practices during four years in 17 different fields by recording GNSS (Global navigation satellite system) positions and a relative working status of the implement. We developed data mining methods of finding out the average overwork percentages of regular crop farming practices within different complete field plots. Based on the cumulative work distance, we measured the minimum overlapping percentage of different field works. The average minimum overlapping percentages for different machinery were: sprayer 15.7%, combine driller 7.7%, combine harvester 1.7%, spin disk fertilizer 9.5%, cultivator 19% and roller 59%. To understand reasons for great deviation between similar works, we determined different overlapping components for the spraying work: 2/3 of the spraying overlap was because of the driving line inaccuracies while the remaining 1/3 happens in the headland turns. This detected overlapping leads to the over consumption of pesticides, seeds, fertilizers, fuel and time but it can be minimized by applying accurate steering assistance and by adapting automatic section controls.

Key words:

, , , ,




97-107 T. Jokiniemi, H. Rossner and J.Ahokas
Simple and cost effective method for fuel consumption measurements of agricultural machinery
Abstract |
Full text PDF (135 KB)

Simple and cost effective method for fuel consumption measurements of agricultural machinery

T. Jokiniemi¹, H. Rossner² and J.Ahokas¹

¹Department of Agrotechnology, University of Helsinki, P.O. Box 28, 00014 Helsinki,
Finland; e-mail: tapani.jokiniemi@helsinki.fi; jukka.ahokas@helsinki.fi
²Institute of Agricultural and Environmental, Estonian University of Life Sciences,
Kreutzwaldi 1, Tartu EE51014, Estonia; e-mail: helis.rossner@emu.ee

Abstract:

Energy saving objectives in agriculture have created a demand for energy consumption figures of single field operations and for total fuel consumption in farm level. Although the fuel consumption of field operations is quite well known in general level, the conditions in different locations and years result in variation between these figures. In order to create an energy analysis for a single farm, a way to measure the fuel consumption on site is needed. The most useful unit for fuel consumption in most of the farming field operations is l ha-1, since it enables the comparison between different farms and years. Using this unit also reduces the effect of uncontrollable factors, for example weather and soil conditions. In this study, a simple and cost effective way to measure the fuel consumption of agriculture machinery in l ha-1 was tested. The fuel consumption was measured by the voltage signal of machine’s own fuel level sensor. The signal was recorded with a voltage data logger, and movements of the machine were recorded with a simple personal GPS-tracker. Manual bookkeeping was also made to provide support for data analysis. A calibration curve was created for each machine to calculate the corresponding fuel level for each voltage reading. Measuring system was inexpensive, easy to install and did not require any modifications to the fuel system. It can also be installed to almost any tractor or other self propelled farm machine. Results showed that this is a useful measuring method with certain restrictions. The measuring period has to be relatively long to obtain reliable results, and therefore the continuous working periods for each working phase has to be long enough. The conclusion was that this kind of measuring system can be used to provide average values for energy analysis and also to detect the critical points in the production system.

Key words:

, , , , , ,




361-366 E. Nugis, T. Võsa, K.Vennik, H. Meripõld, J. Kuht, M. Müüripeal
Results of observations of damages to field and landscape
Abstract |
Full text PDF (712 KB)

Results of observations of damages to field and landscape

E. Nugis¹, T. Võsa¹, K.Vennik², H. Meripõld¹, J. Kuht³, M. Müüripeal¹

¹Estonian Research Institute of Agriculture, Teaduse 13, Saku 75501, Estonia; e-mail:edvin.nugis@eria.ee, taavi.vosa@eria.ee.
²Tartu University, Faculty of Science and Technology, Vanemuise 46, Tartu 50090; e-mail: kersti.vennik@ksk.edu.ee
³Estonian University of Life Sciences, Kreutzwaldi 1, Tartu 51014; e-mail:jaan.kuht@emu.ee

Abstract:

It is a fact that crop growth conditions vary greatly within the same field. Provisionally actual growth conditions are made up of many components, i.e. variation of natural conditions (climate & soil), results of effects of machinery on soil (soil compaction) and unfavourable conditions for plant growing. In Estonia rather widely used ATV’s are causing remarkable damage to landscapes.All collected data were geo-referenced by means of a GPS-receiver and post-processed forposition correction. For All Terrain Vehicle (ATV) damage assessment the trajectory was recorded. Both the area and forms of damages were assessed for damaged sites, (e.g.) damage to potato by Colorado beetles. The collected data were compared to the digital soil map.Economic loss on the average, due to unfavourable conditions for plant growth, in thecase of winter rye "Portal" was 131 euros per ha, for medicago 18.5 euros per ha, for spring barley "Anni" 1000 euros per ha and for potato “Ando” 27.1 euros per ha.

Key words:

, , , , , , , ,