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This article uses a derived econometric model to estimate the impact of the physical properties of soil on its retention capacity and, subsequently, the impact of retention capacity on production potential. This is an important aspect considering climate change impacts, which are affecting food production across the world. An investigation of academic publications shows that very few studies address opportunities to price rainwater in relation to agricultural production. As such, the objective of the submitted article is to use soil physical property spatial data to create an econometric model. The econometric model itself determines the intensity and direction of action of the soil's physical properties on the ability of the soil to hold rainwater. The results demonstrate the positive effect of physical properties such as porosity and humus content. Important information for farming practice is the relatively pronounced influence of soil acidity (pH) on its retention capacity, which is mainly the result of its effect on soil biogeochemical processes. The most significant variable in terms of the extent of action is the depth of the soil profile, which is in line with general assumptions. The actual evaluation of soil retention capacity was undertaken using an option with the use of a sensitivity analysis. In order to include the non-production function of the soil (retention capacity), we conclude for individual enhanced quality soil ecological units an increased price of 1–12%. These conclusions are particularly valuable because some soils may have a low production potential while also being highly valuable for their particular location in terms of their non-production potential (typically desirable floodwater retention, etc.). Considering climate change, this is a particularly topical issue. The use of enhanced-quality soil ecological units is reflected in a wide range of fields through legislative processes—determining rural land protection class and, especially in the tax obligations of agricultural entities, farming agricultural land. [ABSTRACT FROM AUTHOR]

The aim of this article is to assess the effect of the applied land valuation system on the price of land, and as a consequence of the implied links to compare the valuation of soil units in Slovakia and the Czech Republic. In order to fulfil this objective, an econometric approach was chosen in the form of a hedonic price model, whereby the heteroscedastic corrected linear regression model was specifically applied. The estimated model shows a very high explanatory ability, together with a high parametric significance for most fictitious variables (land characteristics), and at the same time also fulfils the theoretical and logical consistency of general assumptions. From the results, it is evident that, in the case of Slovakia, ESEU [evaluated soil ecological unit] valuation is affected primarily by the climatic region and the main soil unit. When comparing the results of the effect of individual input factors on the price of land in the Czech Republic and Slovakia, it can be stated that the results are slightly different in the effect of certain factors. The characteristics of soils located in warm climatic regions with a valuable soil type of chernozem and low slope are significant and positively intensive factors. [ABSTRACT FROM AUTHOR]

This paper deals with the effects of biogas stations on CO2 emissions produced within agricultural sector. In last years, owing to a positive policy of renewable energy resources a number of biogas stations in the CR has rapidly increased – actually over 350 agricultural biogas stations with the total installed power 365 MW are in operation. Concerning CO2 emissions from the agricultural sector, there is a presumption of decrease in produced emissions owing to decrease of influence of animal wastes which are processed just in the biogas stations. From the results it is obvious that CO2 emissions produced by agriculture in the CR decrease by 93.7 thousand tonnes annually. A presumption P1 that building of biogas stations will further support this trend is documented with results of a simple dynamic linear regression model. Further, elasticities of particular variables influencing the total emission from agriculture are investigated in the paper. [ABSTRACT FROM AUTHOR]