This article describes the results of the analysis of correlation between the soil electrical conductivity and BPEJ (valued soil-ecological units). The measurements were made in 2006 at the School Agribusiness Land Farm in Lány established by the Czech University of Life Sciences in Prague. The soil electrical conductivity (EC) was measured by the contact method using a sensor with six electrodes. The soil EC data measured were compared with the data obtained from BPEJ maps. The aim was to verify if any relationship exists between the soil EC and BPEJ. The results achieved show that the same dependency exists between the values of the main soil unit of the BPEJ code and the soil EC. The results achieved can be used in the precise agriculture system to improve the decision process. 131and distribute water and also the nutrients near the plants root system. The soil EC is also significantly influenced by the actual soil humidity but, as states Farahani (2007), "Soil water has a strong effect on the values of soil EC, but research shows that even though the values of soil EC may change as soil water changes, the patterns of a soil EC map stay unchanged. Thus, a single soil EC map for a field is probably sufficient for many years to characterize the soil variability patterns. " Doerge et al. (2007) states that the main factors influencing the values of soil EC are pore continuity, water content, salinity level, cation exchange kapacity, and soil depth. MATERIAL AND METHODSIn 2006, the soil EC measurements were made on the selected land "NS KONOPAS A 6001_3" of the School Agribusiness Land in Lány. The contact method was used for the soil EC measurement by means of a traktor-carried measuring frame with six electrodes (Figure 1). The measuring instrument was developed by the Department of Machinery Application, Faculty of Engineering of the Czech University of Life Sciences in Prague. This equipment provides the soil EC values into a measuring central, incl. the position data, in 5 seconds intervals. The position data were obtained by using the GPS unit. The data chains are stored into the .txt format. The BPEJ data were bought in the digital form by the Research Institute for Soil and Water Conservation, Prague-Zbraslav. The ArcView 9.1 software with Geostatistic and Spatial analyst add-in was used for the processing. RESULTS AND DISCUSSIONTwo data sets were used for the analysis, namely soil EC and BPEJ values. Several modifications were performed on the initial data set prior to statistical processing and evaluation. Before the proper elaboration, the voltage and electrical current data, measured by the measuring central, were re-calculated to the soil EC values. Non-complete records were deleted from the basic file, same as the records containing zeros and extreme values. The file modified in this way was then processed by the procedure described in (Thylén et al. 1997;Kumhála et al. 2001). As both authors identically mention, the most failures occur at the moment of driving the machine into a new row,...

Kavka M., Mimra M., Kumhála F. (2016): Sensitivity analysis of key operating parameters of combine harvesters. Res. Agr. Eng., 62: 113-121.The sensitivity analysis of key operating parameters on the average annual sub-profit in a group of three combine harvesters operating in companies providing agricultural services were analysed. Based on the results of the cost analysis, the following key operating parameters with the greatest influence on the costs were identified: the purchase price of the machine, the price of fuel, maintenance costs, personnel costs and annual performance. These parameters were used in the sensitivity analysis to investigate their effect on unit costs. Changing the above-mentioned parameters is calculated within ± 30% from their mean value. To perform a sensitivity analysis of the average annual sub-profit of combine harvesters, the unit price of mechanized work was additionally used. The results showed that greatest impact on both the average annual earnings of combines operation and on the changes in unit cost was those of the annual performance of the combine harvester, combine harvester purchase price and the cost of fuel. On the other hand, maintenance and personnel costs had a smaller influence concerning these changes of parameters.Keywords: annual performance; costs optimization; unit costs; cost analysis; average annual sub-profitThe aim of the sensitivity analysis is to evaluate the impact of changes in key operational parameters for the planned result. Appropriate choice of key parameters has a great impact on achieving successful results. Sensitivity analysis aims at assessing the average annual sub-profit of harvesters as a result of changes in the values of key operating parameters or as a result of others factors, e.g. fuel prices on world markets. It is advisable to perform a sensitivity analysis already in the design stage of the project. Its implementation will identify potential risks and identify key operational parameters influencing profitability.According to Rataj (2005), the implementation of sensitivity analysis is necessary to determine the most probable size of the deviations for both optimistic and pessimistic trends. The estimates are based on the development of these parameters in the past. It identifies the impact of parameter changes on the size of the output (or a project result). As reported by Fotr and Kislingerova (2009), the experience of business practice and empirical research findings show that optimistic distortions dominate strategic financial plans and the resulting values of cash flow.

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Th e "boundary line analysis method" calculates the minimal total annual operational costs used for the optimisation of number of tractors owned by agricultural companies. Th is calculation refl ects the actual need of tractors used in the selected time periods during a year. Th e above method is based on data gained during fi ve day periods (so-called pentads) in t he plant production Farm Estate Lány which belongs to the Czech University of Life Sciences Prague. Based on the annual use of tractors in the company, operational costs involve tractors owned and hired. Th e calculated curve changes in relation to the total annual costs for the owned tractors. Th e economically optimal number of the owned tractors would be reached at the minimum point where the total annual costs curve is low whilst all working operations in the company have been done. Due to the use of tractors during the pentads, it is recommended to own exactly the number of tractor-machine sets given by the calculated minimum. For all the other works, it is advisable to use hired tractors, operationally leased tractors or outsourced services.