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.

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.

Enhanced forest growth may respond to demand of woody resources and contribute to the climate change mitigation. Forest soil treatment with fertilizers, as well as drainage and thinning enhance forest growth. The analysis of needles is an established method in forest science to identify the nutrient status in the forest stand and need for forest soil enrichment with fertilizers. The aim of this research is to estimate the efficiency of forest soil enrichment with wood ash and ammonium nitrate in order to eliminate nutrient deficiency in forest stands. Forest soil was enriched with wood ash fertilizer or ammonium nitrate in 2016–2017. The current year needles were collected from fertilized and control plots, from three trees in each plot. The samples were collected in the period 2018–2019. Total nitrogen (g kgE−1), calcium (g kgE−1), magnesium (g kgE−1), and potassium (g kgE−1) were analysed in the collected samples. The chemical properties of collected needles were compared at the individual object level to estimate the impact of fertilizer on forest stand. A statistically significant increase in the concentrations of potassium and phosphorus was detected in some plots treated with wood ash and ammonium nitrate. In addition, a correlation analysis conducted between the variables of chemical properties of needles and soil showed few significant correlations between nutrient content in needles and in soil samples.

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.