2025

Selle valdkonna püsiv URIhttp://hdl.handle.net/10492/10054

Sirvi

Nüüd näidatakse 1 - 20 104

Preliminary study of microplastics in bottled and tap water in Estonia
(Estonian University of Life Sciences, 2024) Meitern, Annika Joy; Neilant, Keith; Raamets, Jane
Microplastics (MPs) are a growing environmental concern due to their widespread occurrence and potential harmful impacts on ecosystems and public health. This preliminary study -assesses the prevalence of MPs in bottled and tap water in Estonia and reviews related research in the field. The study aimed to evaluate the occurrence of MPs and understand the potential influence of the water source and packaging material on water properties. The study encompassed 12 different bottled water products from 9 Estonian brands and tap water samples from Tallinn and Tartu. All the tested water samples contained MPs, predominantly fibers, with blue and transparent being the most common colors. The packaging material, bottle caps, or the water source did not influence the number of MPs found in bottled water. Interestingly, water packaged in glass bottles contained a higher count of MPs than in plastic bottles and tap water. The study underscores the need for further research to determine the sources of contamination.
Analysis of charging capacity for electric vehicles in soviet-era apartment districts from the perspective of substation power availability
(Estonian University of Life Sciences, 2025) Lumi, Janek; Tooming, Allan; Estonian University of Life Sciences. Institute on Forestry and Engineering. Chair of Energy Application Engineering
This article analyses the potential for electric vehicle (EV) home charging in a Sovietera apartment district powered by the Lammi substation in Tartu, Estonia. Using one year of hourly electricity consumption data from 360 apartments, the study evaluates three load management scenarios to determine how many EVs can be supported without overloading the existing transformer infrastructure. The analysis is based on a worst-case winter week, reflecting realistic household consumption patterns and typical EV charging behaviour, which does not require daily charging. Three load control strategies are compared: (1) dynamic load management limited by weekly peak load; (2) fixed nighttime charging within a capped substation load; and (3) full dynamic charging for all apartments. The results show that up to 96, 218, and 360 EVs could be supported under these respective scenarios. The findings highlight how the choice of charging strategy significantly affects infrastructure demands and demonstrate that coordinated load management can enable broader EV integration without immediate large-scale investment. The study contributes practical insight for energy planners and housing associations seeking to align smart charging systems with the technical limits of existing substations.
Comparison of in vitro regeneration and transformation efficiency among five vietnamese indica rice cultivars
(Estonian University of Life Sciences, 2025) Cao, L.Q.; Nguyen, P.D.; Pham, X.H.; La, V.H.; Nguyen, X.V.; Nguyen, T.D.
This study optimized the in vitro regeneration and transformation processes for five popular indica rice cultivars in Vietnam named as BC15, Bac Thom 7 (BT7), Khang Dan 18 (KD18), OM5451, and TBR225. The highest callus induction rates (83–93.67%) were achieved on a medium containing 2.5 mgL-l 2,4-D, supplemented with 500 mg L-l each of L-proline, L-glutamine, and casein. Higher or lower concentrations of 2,4-D resulted in reduced callus induction. Among tested cultivars, BT7 exhibited the highest callus induction rate of 93.67%. Shoot regeneration was optimized on a medium with a combination of 0.5 mg L-l kinetin, 2.0 mg L-l BAP, and 0.5 mg L-l NAA, resulting in regeneration rates ranging from 80.23% to 90.77% across cultivars, with BT7 exhibiting the highest regeneration rate (90.77%). Hygromycin at 20 mg L-l was optimal for selecting transgenic calli, with BT7 showing the highest transformation efficiency opdetermined to be optimal for selecting transgenic calli, with BT7 achieving the highest transformation efficiency (44% hygromycin-resistant callus and 29% GUS expression). PCR analysis confirmed a high proportion (87.5%) of transgenic plants in the BT7 cultivar. These findings indicate that the BT7 is the most suitable cultivar for genetic transformation and gene editing applications.
Assessment of consumer awareness regarding the implementation of innovative food packaging
(Estonian University of Life Sciences, 2025) Gaworski, M.; Sołtys, P.
Food packaging fulfills many practical functions. They protect against harmful external factors and facilitate transport, distribution on the market, and storage of products in households. They also provide information on food products' type and composition, preparation method, and shelf life. The important role played by packaging contributes to their continuous improvement. An example of this improvement is the implementation of innovative solutions, including active and intelligent packaging. The question remains whether consumers know about these innovative facilities and whether they use them. In search of an answer to this question, a survey was conducted on 210 respondents in the Mazovian region (Poland). The survey aimed to assess consumer knowledge and awareness of active and intelligent food packaging. The study was conducted using the CAWI (Computer-Assisted Web Interview) method. As many as 79% of respondents did not know the term active packaging. It was similar in the case of intelligent packaging - 79% of respondents did not know this type of packaging. Respondents also showed a low level of knowledge regarding the different types of inserts in active packaging and examples of benefits offered by intelligent packaging. The survey results suggest the need to disseminate knowledge and benefits related to active and intelligent packaging.
Deciphering the paradox: the role of organizational identification in workaholism versus burnout
(Estonian University of Life Sciences, 2025) Geidelina-Lugovska, M.; Cekuls, A.
This study explores the complex relationship between organizational identification, workaholism, and burnout. Organizational identification, denoting individuals' psychological connection to their workplace, significantly influences their work-related attitudes and behaviors. While it often correlates with workaholic tendencies characterized by excessive work engagement, it does not directly cause burnout - a state of emotional exhaustion due to chronic work-related stress. Utilizing a qualitative grounded theory approach, we conducted a comprehensive literature review using Scopus, analyzing 141 articles to identify the antecedents of workaholism, burnout, and organizational identification. Our findings reveal that organizationrelated factors, such as job demands, social support, job autonomy, and organizational culture, significantly impact both organizational identification and burnout. Conversely, workaholism is primarily driven by personal factors like perfectionism, low self-esteem, and family background. These insights suggest that fostering positive organizational factors can enhance organizational identification and mitigate burnout, while addressing personal factors is crucial in managing workaholism. This research contributes to the economic understanding by highlighting the role of organizational culture and job design in employee well-being, which can impact productivity and organizational performance. The study underscores the importance of developing interventions that balance organizational identification with healthy work habits to promote a resilient and productive workforce. Future research should focus on empirical tests to better understand the influence of organizational and personal factors on these constructs, paving the way for more effective strategies to foster employee well-being.
Evaluating the efficiency, environmental impact, and operator benefits of GPS guidance and autosteer technologies in agricultural field operations
(Estonian University of Life Sciences, 2025) Haapala, H.; Sarvela, K.; Kalmari, J.; Appelgrén, I.; Linna, P.
This study evaluated the benefits of GPS guidance and autosteer technologies in agricultural operations through a three-year field experiment conducted at the Smart Bioeconomy Testbed in Central Finland. Adjacent fields were sown either with or without the use of GPS guidance and autosteer, while all other variables were standardized to isolate the impact of the technologies. The movement of the tractor–seeder combination was precisely tracked using RTK GPS with centimetre-level accuracy, and operational parameters were recorded via ISOBUS, supplemented by external measurements of environmental and agronomic factors. Key findings demonstrated that GPS-guided autosteer operations reduced total work time by 9.7% (p < 0.01), primarily due to a 21% (p < 0.01) decrease in overlap and unnecessary movement. This operational efficiency translated into a 20% (p < 0.01) reduction in fuel consumption and a corresponding decrease in CO₂ emissions per hectare. Moreover, GPS-based automation produced more uniform traffic patterns, mitigating localized soil compaction. Operator well-being also improved, with a 10% (p < 0.01) reduction in average heart rate, suggesting reduced physical strain. These benefits were particularly significant in small, irregular fields typical of Finnish agriculture. In conclusion, GPS guidance and autosteer technologies significantly enhance operational efficiency by reducing fuel use, field time, and emissions. These benefits are particularly pronounced in smaller fields, such as those typical in Finland, where improved manoeuvrability yields greater returns. While the technologies contribute positively to operator well-being, individual responses may vary. Further research is needed to assess long-term impacts, explore integration with advanced technologies such as robotics and AI-driven decision support systems, and address the challenges associated with broader adoption.
Sub-clinical respiratory infection identified on farms by monitoring weight changes of pigs with the Weight-Detect instrument
(Estonian University of Life Sciences, 2025) Banhazi, T.; Dunn, M.; Banhazi, A.; Reixach, J.; Ramon-Perez, A.; Llonch, P.; Maselyne, J.
The essential task of growth rate monitoring of pigs is usually undertaken on farms using electronic scales, but new technologies are now available to continuously monitor the weight of pigs. One of these systems (Weight-Detect, WD, PLF Agritech, Brisbane, Australia) has been introduced on a commercial pig farm in Spain as part of the EU funded aWISH project to (1) assess the applicability of the technology and (2) use this information to assess the general welfare status of pigs. The WD unit was installed in early 2024 and manual weight recordings were undertaken periodically using an electronic scale to validate the WD system. In terms of absolute values, the manual measurements indicated that the WD system was able to predict the average pen weight of the pigs with 1.7% (2.0 kg) precision. More importantly, this case study demonstrated that the WD unit was able to detect weight reduction in pigs six days before the clinical signs of a respiratory disease infection were noticed. According to the WD measurements the study pigs achieved an average daily gain (ADG) of 882 g d-1 between the 20/03/24 and 16/04/2024. However, between the 17/4/2024 and 30/04/2024 their ADG dropped dramatically to 286 g d-1. The animals were diagnosed with respiratory disease on the 22/04/24, six days after the dramatic reduction in ADG was recorded by the WD system. This period of ADG stagnation has caused an approximate 14-day delay in reaching the desired slaughter weight, (approx. 130 kg), potentially creating significant financial losses for the producer. After the 1/05/24 pigs recovered and achieved an ADG of 645 g d-1 until their last recorded weighing day on the 20/5/24. These results highlight the WD system’s ability to alert livestock managers about impending health problems before clinical signs appear, so appropriate mitigation measures can be implemented to reduce the negative impacts on welfare and production performance.
Life cycle assessment (LCA) in construction materials – Review
(Estonian University of Life Sciences, 2025) Carvalho, J.G.R.O.; Cecchin, D.; de Azevedo, A.R.G.; do Carmo, D.F.; Paes, J.L.; Ferraz, P.F.P.; Hamacher, L.S.; Costa, K.A.; Rossi, G.; Bambi, G.
The construction industry is one of the most impactful sectors in terms of natural resource consumption and greenhouse gas emissions, demanding more sustainable and efficient solutions. This study systematically reviews the applicatication of Life Cycle Assessment (LCA) to evaluate sustainable materials and practices within the construction sector, emphasizing the replacement of tradicional materials with recycled, bioeconomic, and low-carbon alternatives. A systematic review was conducted using the Scopus database, covering studies published between 2020 and September 2024. The methodology included the use of VOS viewer software to generate keyword co-occurrence maps, aiding in the identification of emerging trends and patterns. Key findings indicate substantial environmental benefits from incorporating industrial wastes, agricultural by-products, and bioeconomic materials, demonstrating substantial reductions in CO₂ emissions, energy consumption, and natural resource usage. The analysis also highlights emerging technologies, such as 3D printing and nanotechnology, as innovative tools that further enhance sustainability in construction. However, challenges persist, including limited availability of reliable regional data, methodological complexities, and gaps in integrating socio-economic variables into LCA analyses. This paper contributes to advancing sustainable construction by identifying critical gaps and challenges, proposing strategies for improved data collection, recommending enhanced interdisciplinary collaboration, and suggesting increased governmental support and regulatory frameworks to promote broader adoption of LCA in industry practices.
Carbon and nitrogen accumulation by agricultural crop residue under three cropping systems
(Estonian University of Life Sciences, 2025) Rancāne, S.; Lazdiņš, A.; Petaja, G.; Purviņa, D.; Zute, S.; Jansone, I.; Damškalne, M.; Putniece, G.
Agricultural crops produce different biomass during their growth, including varying amounts of residue which accumulate a significant amount of carbon (C) and nitrogen (N). Assimilation capacity depends largely on species, variety and growing condition. Carbon accumulation in soil contributes to both - the agricultural production and maintenance of environmental quality reducing atmospheric C and greenhouse gas emissions. In this study, the amount of plant residue left on the field by above-ground and below-ground residue and the amount of C and N accumulated in them in three different cropping systems: organic (Bio); integrated with a low input of N fertiliser (Int-low-N) and; integrated with a high input of N fertiliser (Int-high-N) were evaluated. The most commonly grown cereal crops in Latvia were tested: winter wheat (WW); summer wheat (SW); winter rye (WR); winter triticale (WT); summer barley (SB); summer oat (SO); and buckwheat (BW) as pseudo-cereal crop. The highest biomass of dry matter of total harvest residue in all cropping systems was recorded in WR: 853.3 ± 40.76 g m-2; 1,482.0 ± 105.06 g m-2; 1,628.3 ± 115.49 g m-2 - in Bio; Int-low-N; Int-high-N cropping systems, respectively. The highest amount of carbon (g C m-2) using organic cropping system was accumulated by residue of: WR (268.6 ± 28.68), BW (239.4 ± 10.50) and WW (234.5 ± 27.41). The highest amount of carbon (g C m-2) using integrated cropping system was accumulated by residue of: WR - 473.8 ± 64.9; 496.6 ± 62.54 and WT - 458.2 ± 32.57; 521.1 ± 46.26 in Int-low-N and Int-high-N, respectively. Higher proportion of root biomass cereals formed using organic cropping system.
Advancing precision agriculture: a case study of open source autosteering with AgOpenGPS and RTKbase
(Estonian University of Life Sciences, 2025) Linna, P.; Haapala, H.
Precision agriculture increasingly relies on Real-Time Kinematic (RTK) services to perform highly accurate tasks in the field. Robotics are gradually entering farming, demanding precise and reliable correction signals. However, before widespread adoption of autonomous field robots becomes a reality, automated tractors will remain in use for a significant period, becoming progressively more advanced. The market is currently filled with various manufacturers offering aftermarket autosteering systems, which incrementally bring farmers closer to the functionality of fully autonomous field robots. This study explores open-source solutions for cost-effective autosteering systems and RTK base stations. The project involved retrofitting a single farmer’s tractor with an autosteering system and establishing an RTK base station. As the pilot progressed, word of the implementation spread, leading to the creation of a dedicated communication channel for interested farmers. This platform has facilitated knowledge sharing and further adoption. Information about the project also reached other regions, inspiring similar initiatives that have significantly increased the number of RTK base stations in just two years. The results of this project demonstrate a strong demand for alternative solutions. Many farmers lack the financial resources to invest in expensive, proprietary systems or are unwilling to commit to recurring subscription fees. The goal remains the same, regardless of the implementation method, agriculture is moving steadily toward smarter, more precise practices and the eventual adoption of field robotics.
Analysis of the potential of livestock excreta for urea production through anaerobic digestion: challenges and opportunities in Latin America
(Estonian University of Life Sciences, 2025) Villegas, S.; Rocha-Meneses, Lisandra; Luna-del Risco, M.; Arrieta-González, C.; González-Palacio, M.; Estonian University of Life Sciences. Institute of Forestry and Engineering
Urea is one of the most demanded fertilizers worldwide and in Latin America. The high dependence on international markets to meet the region’s urea demand, the high consumption of fossil energy for its production, and greenhouse gas emissions increase agricultural production costs and create the need to seek alternative processes for urea production to reduce these adverse effects. In this sense, this work explores the possibility of producing urea in Latin America from the ammonia and CO₂ generated in the anaerobic digestion process of livestock excreta under conditions that favor the production of both gases. The results indicate that it is possible to meet the demand for urea for agricultural use by utilizing 15% of its theoretical potential obtained from livestock excreta. This new alternative for obtaining urea brings economic benefits, reduces greenhouse gas emissions, and fosters social development. However, it faces legal, infrastructure, and technological barriers that may hinder the adoption of this technology in rural areas of Latin America.
The role of ICT and animal welfare concerns in Estonian food purchasing channel preferences
(Estonian University of Life Sciences, 2025) Aleksandrova, Olha; Põder, Anne; Kukk, Martin; Viira, Ants-Hannes; Tamm, Hardi; Estonian University of Life Sciences. Institute of Agricultural and Environmental Sciences. Chair of Rural Economics
The modern consumer is now more attentive to animal welfare practices, and this is an important factor when making food purchasing decisions. Different levels of concern for animal welfare as well as the use of information and communication technology (ICT) affect consumer food consumption and purchasing decisions and information access. This study explored both consumer preferences for food purchasing channels by using principal component analysis and regression analysis as well as the interaction between ICT use and animal welfare concerns. To analyse consumer preferences for food purchasing channels, we utilised data from a survey on the use of various retail outlets, such as buying online, retail stores, local markets, directly from producers, and organic or specialised shops. We used the varimax rotation method in principal component analysis to find the main factors in consumer choices related to animal health and welfare. Results from five generalised linear models indicated that Estonian consumers are more willing to purchase products of animal origin directly from producers or in organic or specialised shops when they pay attention to animal health and welfare. Animal health and general welfare practices aimed at ensuring the safety of food in large-scale production and distribution are significant for retail shop users. More frequent ICT use does not translate to a preference for online food shopping over more traditional retail purchasing. Compared with other age-gender groups, younger women prefer to buy food directly from producers. Older individuals in particular favour purchasing food from traditional retail stores rather than online. Consumers who prefer to buy food online are more concerned about animal health and welfare.
Liming alone is not enough: The role of phosphorus and boron in supporting legume pasture growth
(Estonian University of Life Sciences, 2025) Aguiar, P.; Arrobas, M.; Aguiar, C.; Rodrigues, N.; Jongen, M.; Teixeira, R.F.M.; Domingos, T.; Rodrigues, M.Â.
Soil fertility management is a critical factor for ensuring the persistence of the legume component in improved pastures in Mediterranean regions. To promote legume growth, the most common practices include the application of lime to correct Soil acidity and phosphate fertilizers to address phosphorus (P) deficiencies. This study examined two acidic soils and evaluated the need for P and boron (B) supplementation following liming. A factorial pot experiment (Soil type × vegetation type × fertilizer treatment) was conducted using subterranean clover (Trifolium subterraneum L.), annual ryegrass (Lolium multiflorum Lam.), and their mixture. Results revealed significantly higher dry matter yield (DMY) for the legume (18.1 g pot⁻¹) compared to the grass (5.9 g pot⁻¹), due to the legume's ability to access atmospheric nitrogen (N). Soil 2, which had higher initial P availability than Soil 1, and P fertilization both enhanced N accumulation in legume tissues, the percentage of N derived from the atmosphere (%Ndfa), and DMY. These outcomes indicate that liming alone was insufficient to increase P availability and eliminate the need for P fertilization. For instance, DMY increased from 15.0 g pot⁻¹ with liming alone to 19.4 g pot⁻¹ when P was supplemented. Additionally, B application increased N uptake and %Ndfa in the legume, with the latter rising from 48.9% in the liming-only control to 77.5% with B supplementation. These results suggest that liming, by increasing Soil pH, may reduce B bioavailability, highlighting the need for B supplementation following lime application.
Review: unmanned aerial vehicles and artificial intelligence in precision agriculture
(Estonian University of Life Sciences, 2025) Zvara, B.; Macák, M.; Galambošová, J.
To meet the needs of sustainable intensification in crop and animal production, farmers use a set of technologies which are referred to as Agriculture 4.0 to 5.0 or digital agriculture. Differences compared to traditional precision farming techniques are in extensive use of UAV, smart sensors implemented in machines, crops, animals and in the soil, cloud computing, IoT, together with extensive use of AI for data analyses. Unmanned Aerial Vehicles (UAV), also called drones, have become an essential tool in digital agriculture. UAVs have witnessed remarkable development in the past decades and so in the recent years, the topic of agricultural UAVs has gained the attention of many farmers. The submitted paper provides a review on recent scientific literature dedicated to the utilization of agricultural UAVs. The utilization areas are reviewed in monitoring (remote sensing), interventional applications of various inputs, and other areas of possible utilization. The novelty of this review highlights the importance of the integration of UAVs with artificial intelligence (AI) and the Internet of Things (IoT). Sophisticated artificial intelligence and machine-learning algorithms are developing to analyse UAV-collected data, enhancing the accuracy and efficiency. Machine learning models in combination with artificial intelligence are capable of yield prediction and crop management, effecting future decision-making processes. Several key opportunities can be identified for future research, including the development of more sophisticated decision-making processes and machine learning methods based on artificial intelligence, the automation of agricultural crop production, improved UAV autonomy, and the potential use of UAV swarms in different field operations.
Climate impact on electric vehicle energy consumption in the Baltic Region
(Estonian University of Life Sciences, 2025) Puusepp, Aimar; Jõgi , Jaak; Lumi, Janek; Estonian University of Life Sciences. Institute of Forestry and Engineering
Electric vehicles (EVs) have seen increased interest in recent years as a lower-emission alternative to internal combustion engine (ICE) vehicles, with much of their growth driven by government subsidies and incentives across Europe. However, as these incentives have slowed, the EV market faces new challenges, particularly in the Baltic countries where the climate significantly impacts EV performance. Low temperatures, common in Baltic weather, can notably affect EVs’ range and energy efficiency, influencing operational costs and user satisfaction. Understanding how Baltic weather conditions, primarily temperature, influence the energy consumption of EVs is essential to gaining a deeper understanding of their efficiency in low temperatures and harsh weather conditions. The main aim of this study is to assess the impact of varying weather conditions on EV energy consumption, providing valuable insights into their efficiency under cold and variable climatic conditions. The primary goal is to identify the factors most responsible for increased energy consumption in these conditions. In this study, a series of controlled real-world driving tests were conducted, during which an EV (Nissan Leaf) was driven multiple times along identical routes under different weather conditions. The temperatures during these tests ranged from 20 °C to -15 °C. The 2024/2025 winter season was unusually warm in the Baltic region; therefore, tests could not be conducted at lower temperatures. Variables such as distance, temperature, battery state, and the use of accessories were recorded and subsequently analysed. Additionally, energy losses during EV battery charging were measured and evaluated. The collected data was analysed statistically, and mathematical models were developed to provide accurate predictions of battery usage under varying ambient temperatures. The results indicate that low temperatures increase EV energy consumption due to the additional energy required for battery and cabin heating. A more detailed analysis reveals that the most significant increase in energy consumption occurs at an ambient temperature of -10 °C. Overall, this study demonstrates that Baltic weather conditions can lead to a substantial decrease in EV range and efficiency, with low temperatures being the most impactful factor. By providing real-world data, this study contributes to a deeper understanding of EV efficiency in the Baltic region, offering practical insights for EV users and researchers.
Using machine learning techniques to assess the technology adoption readiness levels of livestock producers
(Estonian University of Life Sciences, 2025) Mallinger, K.; Corpaci, L.; Goldenits, G.; Neubauer, T.; Tikász, I.E.; Banhazi, T.
Technology adoption in agriculture, particularly in precision livestock farming (PLF), is often hindered by a range of barriers such as high investment costs, limited infrastructure, and uncertainty regarding the reliability and integration of new systems. Understanding these barriers is crucial for promoting the uptake of innovations that enhance sustainability and productivity. This study investigates technology adoption barriers in precision livestock farming to support sustainable agricultural development. A survey of 266 farms across several European countries and Israel was conducted to assess existing infrastructure and farmers' attitudes toward smart farming technologies. Using machine learning techniques, farmers were grouped into two clusters representing different levels of technological readiness. The study identified the most prominent factors influencing technology adoption, including the presence of smart technologies on-site, market accessibility, cost efficiency, and the ability to manage labor shortages. A Logistic Regression model further demonstrated high predictive accuracy for farmers' technological readiness based on these characteristics. These findings provide valuable insights into the main drivers and barriers of PLF adoption and highlight the relevance of data-driven approaches for requirement analysis and targeted policy interventions. By uncovering critical user traits and adoption barriers, this study offers structured guidance for policymakers, industry stakeholders, and researchers to foster the broader adoption of precision livestock technologies.
A literature review of plants with antiparasitic properties against horse endoparasites
(Estonian University of Life Sciences, 2025) Eberharde, P.A.; Bandere, D.; Teterovska, R.
In light of the expansion of anthelmintic resistance, this literature review focusses on plant use against common endoparasites in horses: strongyles, cyathostomins, and ascarids, all of which negatively impact the horse's quality of life. Evidence-based literature from databases such as ScienceDirect and PubMed and search engines such as GoogleScholar was selected, and publications that met the criteria were included in the review. The plants included in the review are native species in Europe or can be easily grown in the provided climate. The search provided a total of 5936 publications from which, after evaluation, only 12 were included in the review. The main aim of the research was to compare the efficacy of selected plants by evaluating the information of the study design, a plant component or preparation and its concentration used in the investigation, and the results obtained, while also describing the bioactive compounds that are responsible for the potential antiparasitic effect. The search covered commonly mentioned plants with anthelmintic potential for equines, and in the result, only eight of the plants had their effectiveness evaluated in the form of research, Artemisia absinthium, Hippophae rhamnoides, Onobrychis viciifolia, Allium sativum, Inula helenium, Zingiber officinale, Cichorium intybus and Pimpinella anisum. The results emphasize the necessity for further explorations to be made - the results tend to be inconsistent with each other, showing that there might be a possibility for the plants to become a part of routine anthelmintic therapy, but many of the findings have not been convincing enough so far.
Metabolic hormone profiles pre- and post-fattening in sheep breeds in Latvia with varying feed efficiency
(Estonian University of Life Sciences, 2025) Trapina, I.; Plavina, S.; Krasņevska, N.; Paramonovs, J.; Kairisa, D.; Paramonova, N.
In sheep production, livestock fattening constitutes a major source of income, with overall economic efficiency largely determined by feed efficiency (Fe). Feed efficiency, in turn, is influenced by the hormone-regulated physiological state of the animal. Monitoring hormone levels as biomarkers can significantly optimise the lamb fattening process, improving outcomes. The study aims to analyse levels of hormone IGF-1, insulin, total T4, ACTH, haematocrit (HCT), haemoglobin (Hb), and glucose in sheep breeds raised in Latvia at different ages or fattening periods and corresponding Fe indicators. Blood samples and phenotypic data were collected from 76 and 92 intensively fattened lambs at ~81 and ~150 days of age, respectively, with ~60% representing the Latvian Dark-Head breed. Post-fattening levels of IGF-1, insulin, haematocrit, and haemoglobin were statistically higher, while glucose was elevated pre-fattening. IGF-1 and insulin varied significantly across five and three breeds; HCT and Hb levels differed significantly in one breed each. Pre-fattening IGF-1 and glucose levels correlated with feed efficiency traits. Regression analysis showed that pre-fattening hormone levels explained 24.7% of FCR, 22.8% of RGR, and 31.6% of KR variance. Results demonstrate breed-specific hormonal differences in Latvian sheep and indicate the potential of hormone levels as biomarkers for assessing and optimising feed efficiency, emphasizing the need to study hormone levels across breeds and at different fattening stages.
Research and justification of parameters for a flexible sectional screw working body
(Estonian University of Life Sciences, 2025) Bulgakov, V.; Olt, Jüri; Ihnatiev, Yevhen; Holovach, I.; Trokhanyak, O.; Estonian University of Life Sciences. Institute of Forestry and Engineering
The article presents a new design of the hinged-sectional working body of a flexible screw conveyor intended for transporting bulk agricultural materials. The influence of the hinge mechanism’s structural parameters on its operational efficiency is investigated, particularly in terms of ensuring the required angular displacement of axes, preventing jamming, and minimizing energy losses. Analytical dependencies are proposed to determine the arc displacement of the ball along friction surfaces, its velocity, and the efficiency coefficient of the hinge mechanism. It is established that the maximum efficiency coefficient ranges between 0.88 and 0.91 when the ratio of the ball radius to the rotation radius of ball centers is within 0.3–0.45. Calculations show that an increase in the conical socket inclination angle leads to a reduction in efficiency. To enhance the overall conveyor efficiency, it is recommended to reduce the hinge axis deviation angle, which results in a larger bending radius of the screw. Specifically, it is determined that the axis deviation angle should not exceed 20–25° while maintaining an efficiency coefficient of at least 0.9. To determine the optimal structural characteristics of the screw working body sections, computer modeling of force load influence on corresponding deformations was conducted. The results show that an increase in torque leads to a greater twisting angle of the section, with the most significant deformation occurring at a minimal number of axial rods. The proposed design improves the efficiency of loading and unloading operations while expanding technological capabilities in transporting grain and other bulk materials.
Assessing the yield potential of soybean maturity groups in different Ukrainian climatic zones
(Estonian University of Life Sciences, 2025) Yatsenko, V.; Yatsenko, N.; Komisarenko, N.; Kravchenko, V.; Vyshnevska, L.; Kovtunyuk, Z.; Lozinska, A.; Usyk, S.
In the context of global climate change, increasing demands for food security, and the need to expand sources of plant-based protein, soybean is gaining particular importance as a highly productive and valuable agricultural crop. Purpose. The study aimed to evaluate the yield potential of soybean cultivars from different maturity groups under various agro-climatic conditions of Ukraine by analysing their adaptability, productivity, and stability. The objective was to justify the selection of maturity groups best suited for specific regions to ensure sustainable soybean production. Methods. Field experiments were conducted in 2023–2024 across three agro-climatic zones: Odesa (Steppe), Cherkasy (Forest-Steppe), and Zhytomyr (Polissia). A total of 26 early- and mid-maturing soybean cultivars of Ukrainian and foreign origin were evaluated. Adaptive variability was assessed using standard statistical methods. Results. Among early-maturing cultivars, Taverna, Eri, and Calgary showed superior individual productivity, surpassing the standard by 9–13% in seed weight per plant and reaching yields up to 3.15 t ha⁻¹ in Polissia. These cultivars demonstrated high plasticity and stability across environments. Among mid-maturing cultivars, ES Visitor and ES Collector delivered consistently high yields across all zones, exceeding the standard by 0.09–0.26 t ha⁻¹. Alicia also showed high productivity in the Forest-Steppe and Polissia, making it suitable for regions with moderate moisture. The highest average yield for early-maturing cultivars was recorded in Polissia (2.50 t ha⁻¹), and for mid-maturing ones - in the Forest-Steppe (2.68 t ha⁻¹). Regardless of the zone, Taverna, Eri, Calgary, ES Visitor, and ES Collector demonstrated stable and high productivity. Conclusions. The findings provide a basis for optimising cultivar selection and soybean production technologies, tailored to regional climatic conditions and challenges posed by climate change.

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