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.

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.

Wheat (Triticum) is one of the three most important field crops used for food in the world, as well as in Latvia. The two-factorial trial was conducted at the Research and Study farm ‘Pēterlauki’, Latvia, with the aim to find out the effect of soil tillage and crop rotation on winter wheat grain yield formation. Two soil tillage systems (conventional and reduced), and three crop rotations with different winter wheat (Triticum aestivum) proportion in it (100, 67 and 25%) and different fore-crops (wheat, oilseed rape (Brassica napus ssp. oleifera), faba bean (Vicia faba)) were used. Long-term trial was started in 2009, however, the data from 2016/2017, 2017/2018 and 2018/2019 growing seasons was used for this report. The highest average wheat yield was harvested in 2017 (7.17 t haE−1), and it was significantly (p is less than 0.001) higher than yields in 2018 and 2019 (on average 6.18 t haE−1 and 5.68 t haE−1, respectively). Crop rotation with winter wheat proportion 25%, in which faba bean was wheat fore-crop, showed the highest average grain yield (7.35 t haE−1), but the lowest yield was obtained in rotation with 100% wheat proportion (on average 5.52 t haE−1). Crop rotation scheme had a significant influence on the yield (p is less than 0.001) and 1000 grain weight (p is less than 0.001). Forecrop influenced the yield (p is less than 0.001), number of spikes per 1 square m (p is less than 0.001), and number of grain per spike (p=0.008) significantly. Soil tillage did not affect the studied parameters importantly. Conditions of the trial year affected all parameters significantly.

Breeding work on Ribes species has been started at the National University of Life and Environmental Sciences of Ukraine in Kyiv since 1984 by Petro Sherenhovyj. The breeding programme has been focused on fruit quality, yield, resistance to diseases and pests, as well as on adaptive responses to environmental conditions. As a result of the long-term work, 18 new cultivars were included in the State Register of Plant Varieties of Ukraine in 1999– 2016. The aim of this paper is to describe these varieties: 10 blackcurrant (‘Dochka Vorskly’, ‘Hovtva’, ‘Pam`yati Leonida Mykhalevskoho’, ‘Universytetska’, ‘Aspirantska’, ‘Didorivska’, ‘Poltava 584’, ‘Petrivska’, ‘Yuvileina Sherenhovoho’, and ‘Leleka’), 5 redcurrant (‘Kyianochka’, ‘Poliana Holosiivska’, ‘Buzhanska’, ‘Malva’, and ‘Olha’), 1 whitecurrant (‘Lebidka’), and 2 gooseberry (‘Vasylko’, and ‘Tikych’). The varieties described give farmers and scientists the best knowledge about these cultivars with good level of commercial traits, suitable for dissemination in Ukraine.

Puccinia striiformis is a biotrophic pathogen able to cause broad scale epidemics in wheat growing regions. P. striiformis is genetically highly variable pathogen. New, aggressive genetic lineages, adapted to warm temperatures have been observed in the last decades worldwide. The study aimed to ascertain the structure of genetic lineages of P. striiformis in Latvia. Forty one wheat leaf samples with yellow rust symptoms were collected in 2017–2019. Fenotyping and genotyping methods were used for identification of genetic lineages in Global Rust Reference Center, Denmark. Assessments of leaf diseases on winter wheat differentials – ‘Ambition’, ‘Mariboss’, ‘Moro’, ‘Compair’, ‘Rendezvous’, ‘Spalding Prolific’ and local variety ’Fredis’ were made during the research. Five genetic lineages of P. striiformis – PstS4, PstS7, PstS10, PstS13 and PstS14 were found. 56% from the samples belonged to PstS14, 17.1% PstS10, 12.2% PstS4 and PstS7, 2.4% PstS13. Genetic lineages identified from Latvian wheat samples are found in the biggest cereal growing regions in Europe and are able to cause epidemics on wheat. Genetic lineages of P. striiformis from Latvian samples have not been identified before. All differential varieties were infected with P. striiformis in 2017, ‘Ambition’ and ‘Moro’ in 2018, no infection was observed on differentials in 2019 despite the presence of P. striiformis on winter wheat variety ‘Fredis’. The identification of genetic lineages of P. striiformis on wheat in Latvia is necessary to continue.