The article deals with the issue of rural development in Poland. The aim of the article is to determine the dynamics of change in the level of socio-economic development of rural communes in Poland (NUTS 5) in the years 2004 – 2014 through verification of the hypothesis of the existence of beta-convergence. The beta-convergence approach is verified by econometric modelling techniques. The statistical data came from the Local Data Bank (LDB) of the Central Statistical Office (CSO). Based on the analysis of changes in the development level of the rural areas in Poland it was stated that there is convergence. However, the strength of the convergence process is different depending on the dimensions of development. It reported a strong relationship between the average growth rate of aggregate indicators relating to the financial dimension. In other dimensions, such as labour market, living conditions, health and social care, education, demography and culture, it showed the occurrence of slow convergence processes.

Tree roots take up a high proportion of forest biomass, and nowadays we use different methods to estimate the root biomass. Methods vary greatly due to the different studies and different excavation methods used. In the summer 2010, a study of the below-ground biomass of young Scots pine Pinus sylvestris L. stands was carried out in central Latvia. In this paper, different below-ground biomass fractions data of 10 sample trees from the abandoned agricultural land plantations were approximated by allometric functions depending on tree stem diameter at breast height 1.3 m (DBH). The main objective was to determine the average below-ground biomass and approximated below-ground biomass fractions by allometric functions depending on tree DBH of young stands of Scots pine on abandoned agricultural land. Our regressions offer good overall approximations of the data. DBH – stump, coarse root and small root and total biomass regressions were highly significant (p is less than 0.001). The most substantial part of total below-ground biomass was from stumps (45%). The smallest shares of the biomass were coarse roots 38% and small roots 16%. The largest portion (52%) of the total fine-root biomass of 12- and 14-year-old Scots pine stands was located at a depth of 0–10 cm, decreasing in deeper mineral soil layers. Total dry (DM) below-ground biomass including fine-root biomass was 19.0 ±5.2 t DM ha-E1.

To forecast how different indices describing Latvian forest industry will develop in the future, the decision support program which is based on the research of supply chains and production processes as well as on systematic analysis of the whole industry should be developed. One of the most common types of analysis is modelling of processes. In this paper processes of forestry and wood processing in Latvia are modelled by using general approach for system modelling, and each process is described as an abstract system where only its input and output values were identified. Correlations of input and output value time series with a simple and multiple regression analysis method were analyzed. Regression analysis was created for 77 pairs of indices which theoretically could have significant correlations. Input and output factor linear regression analysis for set of processes Forestry and Wood processing shows that not always there is significant correlation between time series of chosen model factors. Some of correlations between time series of input and output data in the model of forest sector even showed controversial results. The amount of information about processes and their quantitative indicators in Latvian wood processing industry is not sufficient for development of precise simulation models. There is need to develop a list of criteria for missing information and carry out its collection process.

Timber structure is a very complex system with its own specific character that causes a lot of difficulties for designers to predict its precise behaviour under loading. Timber construction behaviour under load is affected by many factors that in most cases influence timber constructions in a negative manner. Part of these influencing factors are properties of material, the other are components of the environment where the timber construction is located. This paper presents the results of experimental research where seventeen softwood (Pinus sylvestris L.) timber beams of rectangular cross section were tested in four point bending under long-term load in uncontrolled microclimate conditions (unheated building, all year round weather in the region of Latvia). Values of mechanical properties (modulus of elasticity), physical properties (density, amount of latewood, number of annual rings in 1 cm of wood) were measured at the start of the test; while monitoring of moisture content of wood, relative humidity and air temperature were performed simultaneously for the whole period of test. It has been observed that the main factors that significantly influence timber beam behaviour during period under load in natural climatic conditions are modulus of elasticity (MoE), density of wood and number of annual rings per 1 cm of wood. Amount of latewood showed an insignificant impact on timber beam behaviour under load.

In this paper regression analysis was adopted to assess the wind-wave relationship between wind speeds and wave heights on the Lithuanian coast of the Baltic Sea. In the coastal observations register missing data of visual wave observations occur because of the fog, ice, evaporation or other meteorological phenomenon. There is also inconsistency in instrumental measurements of wave heights in the Lithuanian coast due to technical issues. First step to fill the gaps in the wave height data is to find a strong relationship between wind speeds and wave heights. In this study correlation coefficients for Nida and Klaipeda coastal hydrometeorological stations data both taking and not taking into consideration wind blowing directions were calculated. Every data set used in this study was treated separately and it was revealed that applying nonlinear regression the most common model for wind-wave relationship analysis on Lithuanian coast is DR-Hill model, while applying multivariable regression it is Full Cubic model. Relationship between wind speeds and wave heights always can be improved by removing swell waves from correlation.

Baltic States’ dairy sectors are important to their economies. All Baltic States have had substantial current account deficits that exceeded acceptable thresholds until the year 2009. The States are dairy product exporters. Export capability largely depends on international competitive position of dairy processing companies. Several factors, inter alia, company size determine the position. Largest companies have been formed by horizontal integration. At Baltic scale dairy processing is still fragmented. The aim of this paper is to evaluate economic effect aspects of integration related to exports in the Baltic States’ dairy sector secondary level. As the subject has not been explored earlier at company level, the author researched data of 188 annual reports of 53 Baltic dairy processing companies over the period 2003 to 2009. Descriptive statistics, time series analysis and regression analysis methods were primarily used. The author establishes that among dairy companies which generate significant exports turnover two-thirds are horizontally integrated and include all largest dairy processing firms in the Baltic States. A few smaller firms have succeeded in exporting due to suitable channel management. Among a large group of companies that generate less than 1% turnover from exports, 77% are non-integrated and all are small. Using regression analysis the author estimates that 1% increase in net turnover in the exporting dairy company group is expected to create 0.93 – 0.94% increase in net turnover from exports. Policies promoting mergers of some companies may thus lead to increased dairy exports, higher milk production and fuller realisation of economic potential of the sector.

The normal wood colour changes due to the biochemical reactions as well as under the fungal exposure. Some of these fungi during all the exposure time cause only a discoloration (staining fungi); others change not only colour, but also the structure of the wood in its further development (wood destructing fungi). The development of blue stain in sapwood of pine roundwood and its influencing factors were studied in the spring summer period of 2016 (April, May and June) in the districts of Nica, Jelgava and Daugavpils. 650 discs from pine log end planes were prepared in order to evaluate the influence of harvesting type, spreading type of fungi spores, placement in pile, storage duration, diameter, distance from the end plane, daily average temperatures, precipitation amount and relative humidity on blue stain of sapwood and rot development. The most important factors influencing the blue stain development on pine roundwood during the storage are the harvesting type of roundwood, spreading type of fungal spores, placement in pile, storage duration, diameter, and distance from the end plane, daily average temperature and amount of precipitation. By evaluating the daily average temperatures, it was concluded that blue stain of sapwood begins to develop when the average daily temperature reaches +5...+6 °С. But when the average daily temperatures reach +10 °С, depending on the harvesting type (chainsaw or harvester) and spreading type of the fungal spores (via air or bark beetle assistance) the first signs of blue stain may occur from 10 to 42 days of storage.

The traditional valuation of real estate in the field of civil engineering did not include the uncertainty of human behaviour, which cannot be explained by the traditional approach. There are different valuation methods for real estate appraisal, which are basically classified into three groups as a classic, statistical and advanced. In this article, we estimated the different housing price models using the sample of 37 residential apartments in Riga, Latvia, October 2018. In order to evaluate if there is a possible association between the variables involved in relation to the property price, the analytical data were analysed by correlation analysis, analysis of variance (ANOVA), regression analysis, covariance analysis (ANCOVA), principal component analysis (PCA) and cluster analysis. The models estimation results show that using ANCOVA models for the prices forecasting the model fitting to data is less than 58%. The preliminary results of this study suggest that the estimated properties can be distributed in 4 groups, depending on number of rooms, area and age. In addition, the decision tree was created based on algorithms (J48) and a preliminary definition of the best rules was made. The decision tree presents an accuracy of 84% with 31 accepted instances for a total of 37 currently classified instances.

The objective of this study is to elaborate the mathematical model describing the bark proportion (BP) in stems of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies [L.] Karst), silver birch (Betula pendula Roth.) and aspen (Populus tremula L.), as well as to analyze the vertical variation of the BP for the aforementioned species. The study material consists of data of 372 sample trees sampled in three regions of Latvia – Western (Kurzeme), Eastern (Latgale) and North-eastern (Vidzeme) during the years 2011 – 2014. The BP for each tree was calculated as a difference between the under-bark and over-bark stem volume. In this study, we compared the performance of three power regression models in predicting of BP using breast height diameter (DBH), tree height (H) and total volume (TV) as independent variables. The best fit to data was achieved by using tree height for the prediction of BP. Our results confirm that the highest proportion of the bark is at the upper part of the stem (relative height 95%) for all trees species. Pine stems have a lower BP of up to 30% relative height comparing to other species, while the spruce has the lowest bark percentage at the stem base relative to other tested species There were no significant differences found in BP among the stands from different regions for all studied species, indicating no need for derivation of separate equations for each region and ascertaining the possibility of use of the average BP values for the whole country.

Flax (Linum usitatissimum L.) fibre and seeds are widely used to produce healthy and environmentally friendly products. It is known that the main factors that influence flax fibre’ and seeds’ yield are genotype and growing conditions. The main task of the Latvian flax breeding program is to develop flax genotypes that are highly productive (both fibre and seeds) and well adaptable to changing environmental conditions. Goal of this study is to identify high yielding genotypes with good adaptation to local variable agro-ecological conditions. The agronomically important traits, such as yield of stem and seeds, total and technical plant height and fibre content were evaluated for 13 Latvian origin flax lines and standard variety ‘Vega 2’. The field trials have been carried out over the period from 2012 to 2015 at the Agricultural Scientific Centre of Latgale. The regression, correlation, coefficient of variation and cluster analysis between yield and yield provided components were used for identification of high yielding genotypes with good adaptation. On the basis of cluster analysis the genotypes were classified in two groups by lower and higher yield of stem, fibre content, total plant height and technical plant height. The line ‘I18-1’ was identifying as genotype with the highest average yield of stem (751.25 g mE-2) as well as highest yield against other genotypes in moisture and drought years. Most valuable by the average technical plant height was line ‘L26-1’ (73.05 cm).