The paper deals with the analysis of ground water quality when slurry is applied on crop rotation fields. The investigations were carried out in Juodkiskis study object of the Lithuanian Institute of Water Management in 1995-1998. According to the average concentrations, the quality of ground water samples taken from the borehole arranged in Juodkiskis test field was good compared with hygienic rates for drinking water. All samples taken for the estimation of ammonia and nitrate nitrogen amount were of good quality. However, nitrate-N concentration increased to 5.5-5.6 mg lE-1 in some periods. Having compared actual phosphate phosphorus concentrations with the allowable ones it may be confirmed that ground water is not polluted with phosphates as phosphate phosphorus concentrations did not reach P-load permissible for drinking water. Considering the correlation connection between ground water level and chemical compounds concentrations, it was determined that ammonia nitrogen and phosphorus compounds concentrations were influenced by ground water level fluctuations (correlation coefficient r = 0:54 and r = 0:62). (Given r values correspond to the reliability criterion tactual is greater than ttheor95%). Lower ground water levels in a borehole determine higher N - NH4**+, P - PO4**- and Ptotal concentrations. No relation between nitrate nitrogen (N - NO3**-), Ntotal and K**+ and ground water level fluctuations was determined.

At rural enterprises, besides the traditional resources - natural, financial, and human capital - there is some other kind of capital - it is social capital. Foreign scientists have done a lot of researches on it. The nature of social capital and its role in economics is not much studied in Latvia. The present scientific article reflects consumptions on social capital by different foreign scientists. The World Bank as an institution has also approached to the research of social capital. It studies social capital at institutions. The World Bank describes the social capital of two kinds. The scientific article characterizes Pieriga region. Rural enterprises and businessmen of agricultural, industrial and service branches in Pieriga region have been enquired. By the results of the enquiry, the presence of social capital in rural enterprises and its impact on their development have been analysed.

The process of creation of the informative systems based on the account of such animals as horses, sheep and goats is analyzed in the work. Three structural models are created and their comparative analysis is conducted. As a result of analysis the general elements of structures, characteristic to each model were found. The Meta modelling approach to facilitate the system was used. The system has a more abstract structure and allows dynamically to adding not only the animal specimens but also new types of attributes in fly during runtime. Recompilation of the system is not required there is no necessity of the analytical restructuring of the model, the absence of type explosions is guaranteed in a database because not a new table-type, but a new record in one or two tables is added.

GIS targeting, combining a range of different datasets including climate, topography, population, protected areas, road networks, agricultural production, and markets, is becoming an important tool in planning agricultural research for development. The impact of agricultural investments can be maximized by targeting them to areas where biophysical conditions are optimal for selected crops, and where population densities and market access maximize the economic possibilities. Targeting can be tailored to specific institutional requirements, for example, to emphasize improved nutrition or export-orientated cash crops.Tanzania is the fifth most populous country in Africa, with a very high percentage of its population dependent on agriculture. The incidence of poverty and child malnutrition is high, but large areas of potentially productive agricultural land are only partly developed. There is great scope for increased agricultural production through the introduction of improved crop varieties and novel farming systems, but these must be concentrated in the areas where they will have the greatest impact. Areas of cultivable land were identified by combining topographic data (slopes and altitude) with climate data (eliminating arid areas) and maps of protected areas (no farming in national parks). These were then further processed to remove those areas where predictions of climate change indicate a significant reduction in rainfall by 2025. Relative ease of access to markets (settlements with populations in excess of 20 000) was calculated using maps of land cover, road networks, and slope maps. A combination of cultivable land with ease of access to markets and medium-to-high population densities defines prime targets for agricultural development. For each target area, crop suitabilities were assessed, based on biophysical parameters.