After the regaining of independence in Republic of Latvia, a new period in the structural-politics of national economy, in choice of enterprise forms and business companies, in their foundation and development began. Beginning from the regain of independence, there has been no published research on these issues for about 16 year period. All studies on this topic were dedicated to separate periods, processes or regions. In the Paper format results of original research have been expounded on the development of entrepreneurship content forms in four separate urban, strategic territories: Daugavpils or Southern-Latgale, Rezekne or Eastern-Latgale, Liepaja - Ventspils or Western-Kurzeme and Riga intra-regions. In the research the whole period since regaining of Latvia independence has been analyzed, as well as the adaption of the law package on entrepreneurship and the beginning of the real entrepreneurship activity in years 1991-1992. Substantial differences between the territories (agglomerations) and also conformities of common development have been defined. There are essential differences in the activity efficiency of entrepreneurship subjects and in the results of the work contributed. The urban influence of big cities increases. The subjects and components of logistics systems develop faster.

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.

If among engineering phenomena exist nonlinear interconnections, they are expressed with help of corresponding nonlinear functions. Teaching the regression analysis for the engineering science students one of the important topic is method of Least Square Method (LSM) and their application in the nonlinear regression analysis. Based on experience at Latvia University of Agriculture, the illustrated approach of teaching of nonlinear regression topics for undergraduate students in engineering applications is presented. Teaching statistics on regression analysis, students usually have problems with interpretation of the transformed regression model parameters significance. The tasks of teaching using LSM in the nonlinear regression analysis are discussed. On the figure 1 regression dependence are shown between such sizes as age of pine-tree and his height. The main species in Latvia is pine-tree (47% from total Latvia forest area); growth of trees motion is stipulated by tips of growth circumstances (Statistical Yearbook of Latvia, 2005).

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.