Nowadays, veganism is becoming increasingly popular, because health concerns are usually the primary reason why people turn to vegan diet. The aim of the study was to identify the supply of vegan products on the Latvian market by analysing the ingredients used in the production of the products, nutritional and energy value of vegan products. 192 vegan products made in 20 different countries and available in online stores that offer their goods on the Latvian market were analysed. The research was carried out from January to March 2020. Information on the country of origin, ingredients, nutritional and energy value of the products was taken from product labels. The majority of the vegan products in Latvian online stores come from Germany. The most important ingredient in the production in product groups such as meat substitutes and dairy alternatives is soya (Glycine max.), which provides high protein content. The vegan products could not be characterized as low in fat, as the average fat content in the various product groups ranged from 7.9±1.7 to 19.7±3.3 g 100 gE−1 of product, except beverages. The average energy values for all product groups varied between 210.7 kJ 100 mLE−1 for beverages and 1226.0 kJ 100 gE−1 for snacks. There would be a need for everyday vegan products in the Latvian market, as most of the products are snacks at the moment, and legumes should be used as ingredient in the production of new vegan products with increased nutritional value.

The increasing frequency and magnitude of adverse meteorological events together with the growing uncertainty in the upcoming future pose more and more challenges to agriculture. Therefore, the future sustainability of agriculture will increasingly depend on its resilience, i.e. the capacity to withstand various perturbations and to recover from them. The direct payment (DP) system of the EU Common agricultural policy (CAP) is the most financed EU support scheme for agriculture; however, research on its impact on the important phenomena of resilience is scarce and fragmented. In order to fill this gap, this paper offers an extensive overview of literature and a summarized list of factors that are mentioned most often as potentially influencing the agricultural resilience. Based on this, the possible impact of DP on agricultural resilience was analysed. In this paper, it is argued that this impact is transferred mostly through changing farms’ financial capabilities as well as farmers’ attitudes and behaviour, and is both positive and negative. Such phenomena as low crop insurance uptake and decrease in productivity may be due to the overcrowding effects of direct payments. These hypotheses are being tested in a survey, conducted in the meantime.

Given the growing worldwide tendencies of online shopping and increasing popularity of online grocery shopping, building customer-based brand equity for online grocery stores is gaining its popularity among business owners and marketers. Building good customer-based brand equity is considered to be one of the crucial goals for online businesses that lead to successful competition and good customer experience. The aim of this research is to determine customer-based brand equity dimensions for online grocery stores. To reach the aim, this paper adopts analysis and synthesis of scientific and practical literature in the field of customer-based brand equity and empirical research of three stages: field analysis, expert interviews and customer survey. 33 dimensions of customer-based brand equity for online grocery stores grouped in 8 dimension clusters were generated from the field analysis and expert interviews. Generated dimensions were provided for the evaluation during the customer survey. Empirical research proved 31 valid dimensions of customer-based brand equity for online grocery stores evaluated as very relevant, relevant and of average relevance. Main drivers of customer-based brand equity for online grocery stores that proved to be very relevant are: saving time, good price, fresh products, quality of service, and reputation of retail chain behind.

Experience saved in the construction industry shows that the timber portal frames with semi-rigid connections at knee joint exhibit permanently increase displacements at the knee and apex point. Normally, timber portal frame with semi-rigid knee joint connection is made with mechanical fasteners located in double circles and cannot be designed without relevant rotation at connection during structures’ exploitation time. The only way to increase connection rigidity is to rise distance from fasteners location at connection, but at the same time, the tension and shear stress become significant at the external section of members. The previous experience is obtained by a model testing showing that deformations at semi-rigid connections are non-linear. These were tests under short-term load and did not disclose creep effects, which can be significant. This study is aimed at the examination of increasing deformations with time under constant static load (creep effects) in semi-rigid dowelled connection. Experimental test models were made and set under long-term load in controlled environmental conditions (heated laboratory room). Results show a significant creep influence to decrease connection stiffness. Corresponding numerical test of orthotropic 3d model by Dlubal RFEM software tools was performed analysing the value of expected deformations. Results of the numerical test showed that friction between timber elements and extra nuts on bolts can increase connection stiffness. Research results in this stage show that the creep can affect connection stiffness more than expected. Also, experimental test results showed lower deformation values comparing with the ones obtained by the numerical test.

Wet soils play an important role in hydrological, biological and chemical processes, and knowledge on their spatial distribution is essential in forestry, agriculture and similar fields. Digital elevation models (DEM) and various hydrological indexes are used to perform water runoff and accumulation processes. The prerequisite for the calculation of the hydrological indexes is the most accurate representation of the Earth’s surface in the DEM, which must be corrected as necessary to remove surface artefacts that create a dam effect. In addition, different resolutions for DEM give different results, so it is necessary to evaluate what resolution data is needed for a particular study. The aim of this study is to evaluate the feasibility of using existing ditch vector data for DEM correction and the resulting implications for soil moisture prediction. Applied methodology uses a network of available ditch vectors and creates gaps in the overlapping parts of the DEM. The data were processed using open source GIS software QGIS, GRASS GIS and Whitebox GAT. Ditch vector data were obtained from JSC Latvian State Forests and the Latvian Geospatial Information Agency. The results show that by applying the bottomless ditch approach in forest lands on moraine deposits, depending on the accuracy of the ditch vector data, the values of the prediction of the soil wetness both increase and decrease. On the other hand, in forest lands on graciolimnic sediments it is visible that predicted soil wetness values increase in the close proximity of ditches. For forest lands on glaciofluvial and eolitic sediments there were no visible changes because of lack of ditches.

The objective of precision beekeeping is to minimize resource consumption and maximize productivity of bees. This is achieved by detecting and predicting beehive states by monitoring apiary and beehive related parameters like temperature, weight, humidity, noise, vibrations, air pollution, wind, precipitation, etc. These parameters are collected as a raw input data by use of multiple different sensory devices, and are often imperfect and require creation of correlation between time data series. Currently, most researches focus on monitoring and processing each parameter separately, whereas combination of multiple parameters produces information that is more sophisticated. Raw input data sets that complement one another could be pre-processed by applying data fusion methods to achieve understanding about global research subject. There are multiple data fusion methods and classification models, distinguished by raw input data type or device usage, whereas sensor related data fusion is called sensor fusion. This paper analyses existing data fusion methods and process in order to identify data fusion challenges and correlate them with precision beekeeping objectives. The research was conducted over a period of 5 months, starting from October, 2019 and was based on analysis and synthesis of scientific literature. The conclusion was made that requirement of data fusion appliance in precision beekeeping is determined by a global research objective, whereas input data introduces main challenges of data and sensor fusion, as its attributes correlate with potential result.

Deep learning algorithms are becoming default solution for application in business processes where recognition, identification and automated learning are involved. For human identification, analysis of various features can be applied. Face feature analysis is most popular method for identification of person in various stages of life, including children and infants. The aim of this research was to propose deep learning solution for long-term identification of children in educational institutions. Previously proposed conceptual model for long-term re-identification was enhanced. The enhancements include processing of unexpected persons’ scenarios, knowledge base improvements based on results of supervised and unsupervised learning, implementation of video surveillance zones within educational institutions and object tracking results’ data chaining between multiple logical processes. Object tracking results are the solution we found for long-term identification realization.

Latvia University of Life Sciences and Technologies, Latvia Precision of the forest inventory planning is still one of the most important problems in the forestry nowadays. The aim of this research was to estimate the sample tree height results of the combined forest inventory (LiDAR CFI) and LiDAR (Light Identification Detection and Ranging) height data by calculating an average value from sample tree neighbouring pixel values in the ripening Scotch pine forest stands, comparing the results with the measurements of the height in the area. For the update of LiDAR calculated data and LiDAR CFI height results, the increment algorithms of the Latvian State Forest Research Institute ‘Silava’ were used, comparing the results with the sample plot measurements. Both results showed a close correlation – in the case of LiDAR CFI with R2 =0.82, LiDAR data with R2 =0.93, demonstrating a standard deviation: 2.40 and 2.75, accordingly and standard error: 0.11 and 0.13, accordingly. The results indicate that both technologies can be used in the forest management, offering reliable information about the forest inventory. Positive values were reached by minimizing the human error factor, which is problematic for the field inventory.

The analysis of regeneration processes on post-agrogenic lands allows establishing patterns and features of succession processes in phytocenosis, to identify the most appropriate measures to promote natural regeneration and to establish the possibility and feasibility of the production of forestry crops on lands left out of agricultural use. A study of forest regeneration processes in areas of fallow land for agricultural purposes adjacent to the floodplain of the Oredezh River in Gatchina district of Leningrad region. On the prepared study plots (0.25 ha) in different elements of the slope relief, the natural regeneration of pine and spruce and living ground cover was also taken into account. The soils on the objects of the study are agricultural soils of different thickness, from 30 to 45 cm. In two areas the soil is turfy, well-cultivated, concealed podzolic, ferrous illuvial soil on sands. On plots No. 3–5, the soil is turfy, well-cultivated, concealed podzolic, ferrous illuvial, clayey, on a red loam. The purpose of the study was to identify the nature of forest regeneration processes in areas of fallow land for agricultural purposes. It has been established that the composition of the emerging undergrowth depends on a number of factors: the type of soil, the taxation characteristics of the adjacent forest, the forest vegetation subzone, and the living ground cover. In these soil conditions on the deposits, young mixed undergrowth with a predominance of spruce and pine after a meadow stage of ruderal vegetation is formed.

The aim of the study is to analyse the empirical data collected in 2017, explaining the distribution of mechanically damaged trees left after the commercial thinning, in order to characterize the potential impact of the change of soil scarification working direction on the intensity of damage to the trees left in the felling during the following pre-commercial thinning. The study found that extraction or leaving logging residues in the felling area did not significantly affect the productivity of the soil scarification, but in areas where logging residues were extracted, the depth of the furrows increased significantly, implying a better quality of soil preparation in these areas. The study did not identify the correlation between strip-road patterns (combined or uncoupled ends) with damage intensity, but the research hypothesis was confirmed that the number and proportion of damaged trees is significantly increasing at the ends of the technological corridors. A bigger increase of proportion of damaged trees at the end of strip-roads was found in pine stands. When modelling the effect of soil preparation and logging design on the proportion of damaged trees, species specific parameters should be used – the proportion of damaged trees at the corridor ends in pine stands is 68%, in spruce stands – 45% compared to the rest of the stand. The rest of the stand can be characterized by production statistics or by the results of the study – the average proportion of damaged trees in spruce stands is 4.9% and in pine stands – 0.8% of the remaining trees.