Dry seeds of peas (Pisum sativum L.) have long been used as a staple food and feed globally, and its nutritional, health and ecological benefits comply with growing demand for novel vegan foods intended for health and sustainability conscious individuals. The aim of this study was to review research findings and latest information on field pea usage as a functional ingredient in vegan foods. Monographic method was used to analyse field pea Pisum sativum L. usage as a diverse and multifunctional ingredient in vegan foods, covering latest available information on chemical composition of field pea and main food ingredients made from field pea, focusing on the varieties from which yellow split pea is produced; their impact on ready product’s nutrition, sensory properties and application in food industry. Major types of novel vegan foods containing field peas available on market were named. Pea protein, starch and fibre have demonstrated functional properties in different food systems, including – emulsification, oil-in-water system stabilisation, texture modification, binding, gelation, foaming, and solubility. It is functionally possible and nutritionally and ecologically desirable to develop novel vegan foods intended as animal product alternatives with acceptable sensory properties.

Smoked sprats (Sprattus sprattus balticus) from the Baltic Sea are one of the most popular processed fish products in Latvia. The amount of catching and demand is annually increasing. For producers, it is important to provide stable quality throughout the year, which sometimes is challenging due to many factors. Smoked fish quality depends not only on the seasonality, but also on the applied technologies. The aim of the current study was to review research findings about factors affecting the smoked fish quality. The databases of Science Direct, Web of Science, Wiley Online Journals and Google Scholar were searched. The first parameter that affects quality of fish till processing is raw material, its catching place and season, as well as whether it is fresh or frozen fish, that includes not only microbiological parameters, but also physical and chemical changes in fish depending on the storage conditions. The second parameter is the applied pre-treatment methods (using salt, acids) before processing, which can improve fish texture and make better result for smoked fish. The third parameter is the used technology for the fish processing, heat treatment methods use of wood chips or liquid smoke, or adjustment of smoking conditions. These all together make a lot of sensorial and textural changes in the final product. If any of these parameters is changed during processing, they can affect the smoked fish quality. Therefore, to ensure constant quality of smoked fish, in-depth knowledge of parameters is extremely important.

This study is based on the authors’ research started in 2017 that resulted in the development of theoretical strategic and tactical models for the construction of a prototype for automated assessment of tourism economic impact in specific regions, including regions of national parks (NP), as well as for other studies. The aim of the research was testing the performance of the prototype in a research e-environment using the travellers’ survey data obtained in a study in 2019 on the national parks’ target groups (visitor behaviour) during the Gauja National Park (GNP) Travellers’ Days. The prototype was based on the open-source platform Drupal, MySQL used as a database management system (DMS). Drupal united with the Jupyter Notebook platform. The methodological substantiation of the test study is based on aspects of consumer behaviour. A quantitative study with details of qualitative research has been performed. Simple data sampling was used in the data acquisition, but in the analysis – induction, deduction approach, synthesis, data sorting and segmentation, determination of mean values and their expression in proportion; a comparative analysis was performed and conclusions characterizing the sample were made. After completing the prototype performance testing, the authors’ main findings indicate that the prototype’s performance efficiency in terms of time consumption is 23.3 times higher than equivalent work in MS Excel. The prototype has yielded quantitative results from the calculations, and that allows the formulation of the GNP’s Travellers’ Days visitor profile, which is characterized by a sample of the surveys.

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.

The socio-economic changes brought about by globalisation, the internationalisation and digitalisation of higher education, as well as the current demographic situation in Europe and Latvia, raise the issue of the competitiveness of academic staff in the context of multicultural higher education. The aim of the study is to provide a theoretical basis for the competitiveness of academic staff in the view of educational sciences, respecting the different trends and based on the conceptual approaches in personal/specialist competitiveness research. The following research methods were used: study, analysis and evaluation of scientific literature (theoretical research method); reflection of personal experience (empirical research method). As a result of the theoretical research, two trends for the substantiation of the concept of competitiveness in the educational sciences were identified. The first trend: the competitiveness of a person is substantiated through transfers from economic and management science, with a particular emphasis on specialist marketability and employability as a significant manifestation of competitiveness. The second trend: according to the new paradigm of competitiveness in educational sciences, the competitiveness of a human as a person and as a specialist is based on the perspective of pedagogy and psychology. The research results led to the conclusion that there are three conceptual approaches in the methodology of competitiveness research: 1) qualitative approach: identifies and lists competitive personality traits and qualities; 2) functional approach: describes the competitive behaviour of a person or specialist; 3) structural approach: competitiveness is substantiated as a complex combination of personal/ specialist qualities, identifying several structural components. All of these approaches are also characteristic to the research of competitiveness of academic staff. The following taxonomy should be respected in the substantiation of academic staff competitiveness: 1) substantiation of personal competitiveness; 2) substantiation of specialist competitiveness in the context of different industries; 3) the substantiation of the competitiveness of specifically academic staff in the context of the specifics of higher education.

The share of the renewable resources used continues to grow due to environmental, economic and political reasons. Consequently, intensification of forest management is on-going and expected to continue in the future. Logging residues, such as treetops, branches and stumps, are a significant renewable energy source. Since the logging residues are noticeably richer in nutrients than conventionally harvested stems, there is a concern related to the negative impact of intensified harvesting on the ecosystems, productivity of the sites and sustainability of forestry in general. To evaluate the impact, this study has compared different intensity harvesting effect on the next rotation young stand productivity in eight sites in Latvia. In a nutrient-rich site, the productivity of Norway spruce was higher in the whole-tree harvest (WTH) subplot comparing to stem-only harvesting (SOH) subplot three years after the planting. Productivity of Scots pine in oligotrophic conditions was observed to be higher in SOH subplot comparing to WTH subplot two and three years after planting. Furthermore, in a site on a mineral soil relatively richer in nutrients no significant differences were observed. Comparing WTH to whole tree harvest + stump biomass (SB) extraction subplots, the productivity of Norway spruce was higher in WTH four to five years after the planting; in a mixed stand of Norway spruce and black alder no productivity differences of spruce were detected, but productivity of black alder was higher in WTH+SB subplot five years after the planting; in black alder stands a significantly higher productivity was observed in WTH subplot four and five years after the planting.

Growing spruce and pine wood on land being out of active agricultural use is important for many European regions. The study of the qualitative characteristics of coniferous wood makes it possible to predict target indicators of the obtained raw materials. The influence of xylem structural elements on the density of spruce pine wood on the postagrogenic lands of the boreal zone of Russia was studied. The objects of the research were spruce-pine stands growing on old arable land in the Gatchina district of the Leningrad region. Depending on the share of the species, various anatomical indicators of the macro-structure of wood influence the formation of the spruce and pine wood density. For the spruce part of the forest stand, the width of the annual increase makes a greater contribution to the formation of indicators of wood density. For the pine part of the forest stand the density of the wood correlates with the proportion of late xylem. With a different proportion of the species, the influence of macro-structural elements on the density of wood changes. Conducted analysis of variance showed a significant effect of the forest stand composition on the anatomical macro-structure of spruce and pinewood.

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.

The purpose of the study was to compare forest and postagrogenic soils by parameters such as carbon content in organic matter and total nitrogen to predict the fertility state of lands that are at the stage of restoration of woody vegetation. Areas with similar soil formation conditions were selected on the postagrogenic and forested lands having mature forest stands related with such types of forest: Myrtillosum forest, Oxalidosum and Herbosa-Composita forest, and also areas under the soil complexes of postagrogenic fallow lands. A number of physico-chemical indicators for the soil were assessed according to the methods generally accepted in soil science: the particle size distribution, the bulk density and the thickness of the pedogenic horizons were determined. An analysis of the carbon stocks in organic matter (Corg) and nitrogen (Ntotal) in the genetic horizons of the soils of myrtillosum, Oxalidosum and Herbosa-Composita forest types shows an increase in the content of organic matter and total nitrogen from Myrtillosum to Herbosa-Composita forest type. A comparative analysis of the physical and agrochemical state of postagrogenic and forest soils showed that, despite the previous anthropogenic impact, the agroland horizon retains a high content of organic matter and total nitrogen. The properties of postagrogenic soils in the studied areas are not deteriorated, and the transformation towards the natural forest soils of the region is not observed, despite the long period of fallowing.