Avaldamisel

Selle kollektsiooni püsiv URIhttp://hdl.handle.net/10492/3352

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Nüüd näidatakse 1 - 20 31

Evaluation of maize (Zea mays L.) inbred lines for tolerance to Aluminum toxicity using selection indices
(Estonian University of Life Sciences, 2025) Zishiri, R.M.; Mutengwa, C.S.; Tandzi, L.N.; Manyevere, A.
Selection of genotypes with better yield performance when exposed to stress (biotic or abiotic) is key objective for every plant breeding program. Aluminum toxicity is one of the significant constraints to maize production in acidic soils in many parts of the world. The aim of this study was to identify desirable genotypes with Al tolerance based on selection indices at seedling stage and identify the most effective selection indices under Al stress conditions. 75 Quality Protein Maize (QPM) genotypes were evaluated in CRD with three replicates in the laboratory using a nutrient solution screening method. Additionally, the same genotypes were also screened in the greenhouse arranged in RCBD with three replicates using soil bioassays. The genotypes were exposed to aluminum (Al) toxicity and non-toxic conditions. Data were collected and seven selection indices namely: Stress susceptibility index (SSI); stress tolerance index (STI); geometric mean productivity (GMP); Tolerance index (TOL); Stress Resistance Index (SRI); Percentage Reduction (PCRD); and Mean Productivity (MP) were calculated. Dry Matter (DM) yield under Al toxicity and non-toxic conditions had highly significant (p < 0.001) effects with GMP, STI, SRI and MP, suggesting that these indices have the potential to differentiate genotypes for Al tolerance. Significant and negative correlations were observed between DM and PCRD, TOL, and SSI. Indices that had highly significant and very strong correlations amongst themselves were PCRD with SSI (r = 1.00), and GMP with STI (r = 1.00). The most desirable selection indices that can be used to select tolerant QPM genotypes included GMP, STI, SRI, PCRD, and TOL as they had strong correlations with dry matter under Al toxicity. The tested genotypes were classified into four groups using the principal component (PCA) analysis known as QPM genotypes with high performance under both environments (Group 1), those with high performance under optimum conditions (Group 2), genotypes with high performance under Al stress conditions (Group 3) and those with low performance under both conditions (Group 4). The top five most tolerant maize inbred lines were CML 486, QSY 2, IBL 9, IBL 5 and IBL 4. These tolerant genotypes could be used as parent material for hybridization programs in developing Al tolerant cultivars.
Effect of seed inoculation with bacterial inoculum and in-row application of biohumus on germination parameters, physiological and biochemical components of spring barley seedlings under laboratory conditions
(Estonian University of Life Sciences, 2026) Makarchuk, B.; Gerasko, T.; Pokoptseva, L.; Nezhnova, N.; Alekseeva, Т.
A short-term vegetative experiment was conducted at the Kyiv Specialized Branch of the Ukrainian Institute of Plant Variety Examination (Ukraine) to determine the effect of small doses (100–300 kg ha-1) of biohumus applied during sowing in rows with seeds, as well as pre-sowing inoculation of seeds with the BioStim™Seed preparation on germination parameters and physiological indicators of spring barley seedlings. In row application of biohumus, BioStim™Seed, and their combination improved germination response parameters under laboratory conditions. Pre-sowing inoculation of spring barley seeds with preparation BioStim™Seed without adding biohumus increased germination percentage, but at the same time the mean germination time was increased. The combined use of pre-sowing seed inoculation with the BioStim™Seed preparation with row application of biohumus significantly increased morphological parameters of spring barley shoots, chlorophyll a content, the sum and ratio of chlorophylls a and b, carotenoids content, catalase and peroxidase activity, while significantly reducing the MDA content in the leaves of spring barley seedlings.
Development and pilot testing of the ‘Lesion-Detect’ system for automated identification and scoring of gross lung lesions in pigs during slaughter
(Estonian University of Life Sciences, 2026) Banhazi, T.M.; Dunn, M.; Banhazi, A.; Reixach, J.; Gol, S.; Ramon-Perez, A.; Llonch, P.; Vujacic, V.; Sudar, J.; Kajari, N.; Maselyne, J.; Van Noten, N.; Tuyttens, F.
Respiratory diseases are the most significant health and welfare challenges in pig production. Enzootic pneumonia (EP) is often subclinical at farm level, making early detection difficult, yet its economic and welfare impacts are substantial. Suboptimal housing conditions are well-established risk factors that predispose pigs to respiratory disease. These conditions negatively affect animal health and welfare and are associated with increased mortality, higher medication costs, reduced feed intake, sub-optimal average daily gain, and increased organ condemnations, representing a major constraint to sustainable pig production. At slaughter, gross lung lesions associated with respiratory disease can be assessed in all carcasses, offering a valuable opportunity for herd-level monitoring. However, current Pig Health Monitoring System (PHMS) lesion scoring methods are labour-intensive, subjective, and poorly scalable. To address these limitations, we developed and pilot-tested Lesion-Detect (LD), an automated image-analysis system for identifying and scoring gross lung lesions under commercial slaughterhouse conditions. LD prototypes were deployed in two European slaughterhouses (Spain: hanging lungs; Serbia: tray-based presentation) and benchmarked against manual PHMS scoring. The system showed strong agreement with trained human assessors, with false positive and false negative rates typically within 2–3% of lung area, comparable to inter-observer variability. By delivering objective and scalable lesion scoring, LD could enable consistent respiratory health surveillance. Beyond data collection, rapid herd-level feedback supports earlier and more targeted on-farm interventions, potentially reducing antimicrobial use and improving animal welfare. With further refinement, the system may be extended to additional carcass-level welfare indicators, strengthening its role within precision livestock farming and integrated animal welfare assessment frameworks.
The impact of predecessors on yield and sunflower hybrids’ seed in the steppe of Ukraine
(Estonian University of Life Sciences, 2026) Andriienko, A.; Andriienko, O.; Vasylkovska, K.; Semeniaka, I.
Predecessors have a significant impact on the growth and development of the following crop. Depending on the predecessor crop there is different amount of nutrients, moisture left in the arable soil layer as well as phytosanitary conditions of fields differ. The research programme included the study of peculiarities of growth, development and yield formation of the new sunflower hybrids (LG59580, LG50609SX, PR64LE25, Suzuka), which belong to various ripeness groups, depending on predecessors in the north Steppe of Ukraine in order to improve major zonal energy-efficiency technology of sunflower cultivation. In terms of phytosanitary, cultivation of sunflower after sunflower had negative effect. During the cultivation the number of affected plants was twice fewer after other better predecessors. The Suzuka hybrid showed higher resistance. All of the hybrids formed higher productivity in case of their cultivation after winter wheat as a predecessor with 3.45–3.72 t ha-1 and after corn as their predecessor with 3.34–3.61 t ha-1. Sunflower re-seeding caused yield reduction by almost 1 t ha-1. The thousandkernel weight in all hybrids under research was higher in case of their cultivation after winter wheat as a predecessor. After winter wheat and grain corn this parameter fluctuated within the range of 71.5–74.5 and 69.3–72.5 g respectively, depending on the hybrid, while the parameter was much lower after sunflower and only reached 60 g in LG50609SX hybrids. The highest oil content in all the hybrids was measured after winter wheat and grain corn as predecessors. The highest oil content indications of 50.8–51.0% were defined in LG59580 and Suzuka hybrids. Thus, the cultivation of the hybrids under research after winter wheat and grain corn as predecessors contributed to the formation of healthy and productive plants, while growing sunflower in re-seeding conditions led to impaired phytosanitary conditions, reduced yield and decreased quality of seeds.
Comparative effects of deep ploughing and disking on soil properties and yield of winter wheat (Triticum aestivum L.) in Yernjatap, Armenia
(Estonian University of Life Sciences, 2026) Hokhanyan, M.; Tovmasyan, G.; Markosyan, A.; Yeritsyan, L.; Yeritsyan, S.; Mamajanyan, S.
Soil tillage practices play a crucial role in maintaining soil fertility and ensuring sustainable agricultural production under rainfed conditions. This study evaluated the effects of conventional (deep ploughing, 20–22 cm) and shallow tillage (disking, 10–12 cm) on soil properties, nutrient availability, and the yield and grain quality of winter wheat (Triticum aestivum L.), cultivar ‘Tanya’, in Yernjatap settlement, Aragatsotn region, Armenia. The experiment was conducted during 2022–2024 using a randomized design with three replications. Shallow tillage improved soil structure and fertility, increasing humus content (up to 4.19%) and water-stable aggregates (up to 55.1%), while conventional tillage resulted in a decline in humus in the upper soil layer. Nutrient availability was also enhanced under disking, with available phosphorus increasing from 2.72 to 3.94 mg 100 g⁻¹ and potassium reaching 40.64 mg 100 g⁻¹ in the 0–20 cm layer. In contrast, both nutrients decreased under deep ploughing. Soil pH, electrical conductivity, and soluble salts were not significantly affected by tillage practices. Improved soil conditions under disking led to enhanced plant growth, higher biomass accumulation, and increased survival rates, exceeding deep ploughing by up to 13.9%. Grain yield was significantly higher under disking in 2024, reaching 1.71 t ha⁻¹ compared to 1.39 t ha⁻¹ under ploughing, representing a 23.0% increase (P = 0.003). Straw yield also increased by 21.4%. The results demonstrate that shallow tillage is a more effective and sustainable practice for improving soil fertility, enhancing winter wheat productivity, and supporting stable crop production under rainfed mountainous conditions.
Greenhouse gas emissions in natural and constructed wetland systems
(Estonian University of Life Sciences, 2026) Rochinha, I. da S. P.; do Carmo, D. de F.; da Silva, F. C.; Jabrasi, Y. D.; Cecchin, D.; Hamacher, L. da S. ; Santiago, A. da F. ; Nogueira, L. A.; Marotta, H.
Constructed wetlands (CWs) are nature-based technologies that emulate the biogeochemical processes of natural wetlands (NWs) to treat effluents enriched with organic matter and nutrients, such as those from fertilized soils and urban sewage. However, previous evidence from individual ecosystems indicated that constructed wetlands may exhibit substantially increased greenhouse gas (GHG) evasion to the atmosphere compared to natural ones, representing a significant source of greenhouse gas emissions that has not yet been accounted for. This study aimed to evaluate the first global dataset of GHG emissions, encompassing methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O), from natural and constructed freshwater wetlands. Based on an extensive literature search from 1980 to 2020, it was found that median CH4 and N2O emissions were significantly higher in constructed wetlands than in natural wetlands. These emissions reached global medians of ~6.46 ± 5.72 and 0.20 ± 1.30 mg m-2h-1, for CH4 and N2O, respectively, representing a difference of ~517% and 200% compared to natural wetlands. The median CO2 flux in constructed wetlands was ~171.20 ± 57.04 mg m-2h-1 and was not significantly different between the two groups. This indicates that effluent treatment conditions enhance the metabolic production of CH₄ and N₂O, due to intensified organic matter degradation. Furthermore, the dispersion in wetlands for CO2, CH4, and N2O emissions also reflects the substantial spatial variability in GHG emissions. Therefore, sewage treatment efficiency and GHG balance must be considered for planning the design of constructed wetlands.
Autonomous variable-rate UAV spot spraying using CDA nozzles and dual deposition sensing
(Estonian University of Life Sciences, 2026) Koppány, H.; Pinke, Gy.; Kovács, A.J.; Ambrus, B.
This study presents the laboratory evaluation of a PWM-controlled spraying system for an ABZ L10 Unmanned Aerial Vehicle (UAV) equipped with controlled droplet application (CDA) nozzles, as a step toward developing an autonomous precision spot-spraying system. The consumer-grade multicopter platform, originally designed for uniform spraying, was retrofitted with a modular spraying unit incorporating CDA nozzles. A custom control architecture was developed to interface with the flight controller and synchronize spray parameters with the drone’s flight path and forward velocity. System verification and performance evaluation were central to this study. Spray deposition and spatial accuracy were assessed using two complementary measurement approaches under controlled laboratory conditions. Water-sensitive indicator papers provided qualitative and semi-quantitative information on droplet coverage and spatial distribution. In parallel, a resistance-based sensor array, conceptually analogous to rainfall sensors and developed as part of this research, delivered continuous, real-time, quantitative measurements of local spray deposition by monitoring changes in surface conductivity as droplets accumulated on the sensor surface. The combined evaluation of these measurement methods provided an objective basis for assessing nozzle performance and PWM control. From an application perspective, the primary goal of the developed system is its future integration into precision farming workflows, specifically in herbicide applications where weed presence is the primary trigger. However, for insects or diseases, additional layers of decision-making, such as economic injury thresholds, would be required to justify application. By enabling accurate identification and targeted treatment of specific zones, the system is expected to reduce unnecessary chemical usage and off-target losses, thereby lowering environmental impact while improving the efficiency and sustainability of drone-based plant protection.
Re-evaluating temperature thresholds for growth and nutrient uptake in winter cereals in Estonia: a review of air-soil temperature dynamics
(Estonian University of Life Sciences, 2026) Saue, Triin; Kärp, Merko; Tamm, Kalvi
This study re-evaluates the agronomic validity of temperature thresholds for cereal growth and nutrient uptake in cool-temperate agroclimates. By integrating a physiological review with a spatiotemporal analysis of Estonian air temperature records (1965–2024), we assess the potential for phenological mismatch between atmospheric warming and soil thermal readiness. Our analysis reveals a significant advancement in the onset of the thermal growing season, particularly in South-Eastern Estonia, where spring now begins approximately 10 days earlier compared to the 1965–1990 baseline. Synthesizing these trends with established principles of soil thermal inertia, we identify a potential increase in the risk of ‘false springs’, where atmospheric signals trigger vegetative growth while soil conditions remain restrictive. Published evidence indicates that nutrient uptake is kinetically constrained in cool soils: nitrogen uptake becomes effective only at soil temperatures of +8–10 °C, and phosphorus uptake is critically limited by low diffusion rates and suppressed mycorrhizal activity, whereas potassium uptake is comparatively less sensitive. We suggest that under increasingly variable climatic conditions, relying solely on the standard +5 °C air temperature threshold may lead to premature fertilisation and nutrient losses. Therefore, agronomic decision-making in Northern Europe may need to increasingly account for the hysteresis between rapid atmospheric warming and slower soil thermal activation.
Assessment of common bean responses to light spectral composition and microbial inoculation using non-destructive methods
(Estonian University of Life Sciences, 2026) Alsina, I.; Dubova, L.; Duma, M.
Non-destructive methods are increasingly used to evaluate plant physiological status. This study assessed the applicability of spectrometry and chlorophyll fluorescence for monitoring common bean (Phaseolus vulgaris) responses to light quality and microbial seed inoculation. A two-factor growth chamber experiment was conducted using LED lighting of equal intensity but different red-to-blue ratios (1:1, red-dominated, blue-dominated) and seeds that were either uninoculated or inoculated with Rhizobium phaseoli strains or Proseed-Met. Non-destructive measurements were performed on the same leaves using a spectroradiometer RS-3500 and a FluorPen FP110 fluorometer. Vegetation indices were calculated to evaluate stress, pigment content, senescence, and water status, while fluorescence parameters described photosynthetic performance. Spectrometric indices more clearly reflected light treatment effects, showing higher pigment content under red light, greater senescence under balanced light, and increased stress under red-dominated spectra. Fluorescence parameters were mainly affected by microbial inoculation and were higher in inoculated plants. Limited correlations between the two methods indicated that they capture different aspects of plant physiology. Blue-dominated light increased pod number, whereas red light reduced pod and seed mass. Microbial inoculation alone did not significantly affect yield, but the highest seed yield was observed in Rhizobium-inoculated plants under blue light. The results highlight the importance of light spectral composition for bean productivity and support the combined use of spectrometric and fluorescence methods for comprehensive physiological assessment.
The improvement of the occupational health and safety system in the production company in Latvia
(Estonian University of Life Sciences, 2026) Cepure, I.; Roja, Ž.; Kaļķis, H.; Lāma, G.
Various studies indicate that occupational health and safety (OHS) systems are essential for preventing workplace accidents, maintaining employee’s well-being, and ensuring long-term work ability, particularly in production environments undergoing technological and organizational change. As production companies introduce new technologies, upgrade equipment and adjust workflows, emerging risks require continuous adaptation of OHS practices in order to promote productivity. The aim of this study was to investigate the effectiveness of the existing OHS system in one of Latvia’s largest manufacturing companies and develop improvement opportunities, focusing on employee awareness, behavioural patterns and systemic areas. A cross-sectional survey design was used to evaluate employee awareness, compliance, involvement and perceptions of work-rest organization and health promotion activities. Data was collected using a questionnaire developed by the authors and adjusted to the existing company’s OHS system. A total of 234 from 1,200 employees participated. The results show a generally positive awareness of the OHS system. Production company’s OHS system is largely effective in informing and educating employees about workplace safety and risks. However, improvements are needed in reinforcing safe behaviour, strengthening employee participation, ensuring transparent reporting channels and optimizing balance of work-rest time. Addressing these areas through behavioural safety interventions, ergonomic fatigue management strategies and clearer communication mechanisms may substantially enhance safety culture and reduce workplace accidents in the production environment.
Reed- and straw-bale buildings: past and present. Studies in Estonia - minireview
(Estonian University of Life Sciences, 2026) Ruus, Aime; Raamets, Jane; Ivask, Mari; Nei, Lembit
The application of renewable resources for developing building materials should lower the carbon footprint of the construction industry. Reed was used as a construction material already by ancient societies, namely by Marsh Arabs and ancient Egyptians. It is generally known that straw-bale building technology was originally applied in Nebraska in the end of 1800s. More likely this technology may have occurred independently in different regions around the globe. Ancient societies, as Maya, Inca, and Aztecs, built their homes using grass and straw. Nowadays, straw- and reed-bale buildings are constructed globally in accordance to their environmental and commercial features. In Estonia, a pioneering straw-bale house was completed only in 2002, indicating the start of an increasing trend toward the more intensive exploiting of natural building materials. 150 straw-bale houses have been completed in Estonia before 2025. The relevant research in this field has mainly been focused on the mechanical and physical properties of construction elements made from reed and straw, including compressive strength, thermal conductivity, and moisture resistance. Recent studies have been launched with the aim of examining indoor climate performance, which is closely linked to the microbiological conditions within these buildings. Proper design and maintenance are essential to prevent mold growth and ensure healthy indoor environments.
Application of extruded pea hulls in plant-based burger patties: effects on nutritional, textural, and sensory properties
(Estonian University of Life Sciences, 2026) Kirse-Ozolina, A.; Gramatina, I.
The use of extruded pea hulls (EPH) in vegan bean burger patty formulation could allow to utilise by-product during pea protein processing, increase dietary fibre content, product yield and locally sourced ingredient use. Samples were made from white beans, bread crumbs, chia seeds, spices and EPH. Application of EPH in patties was formulated in two replacement strategies: (i) 25%, 50% and 75% substitution of bread crumbs, and (ii) 5%, 10% and 15% substitution of total ingredient weight with different EPH-to-water ratios. Moisture content, water activity, dietary fibre content and texture profile were evaluated. Sensory ratio scale was used to define firmness, flavour balance, pea flavour and sticky mouthfeel by an expert panel (n = 5). The impact of EPH on textural and sensory attributes varied with the substitution level and inclusion type. Higher EPH levels positively influenced total dietary fibre content of patties (P < 0.05). The substitution with EPH significantly affected such force-related texture attributes as hardness and adhesiveness (P < 0.05). A clear association was not found between instrumental hardness values and sensory perceptible firmness. The results indicate that EPH can be effectively incorporated in plant-based burger patty formulation at low to moderate inclusion levels (up to 50% substitution of breadcrumbs and up to 10% substitution of total ingredient weight, EPH-to-water ratio up to 1:1.5) to obtain value-added plant-based burger patties without compromising textural and sensory quality.
Accumulation and yield formation in potato across controlled and field experiments: implications for nitrogen use efficiency research
(Estonian University of Life Sciences, 2026) Taškova, I.; Rābante-Hāne, L.; Alsiņa, I.; Skrabule, I.
Potato (Solanum tuberosum L.) productivity is strongly influenced by nitrogen (N), which regulates plant growth, biomass formation and tuber development. This study aimed to evaluate nitrogen accumulation and its relationship with biomass and yield, and to verify nitrogen use efficiency (NUE) assessment by comparing field trials with pot and in vitro experiments. Field experiments were conducted in Priekuļi, Latvia, under organic (OF) and integrated (IF) farming systems and in vitro experiments under controlled conditions. Pot trials were carried out in Jelgava. Three varieties (‘Monta’, ‘Prelma’, ‘Jogla’) were tested. Nitrogen was applied at 60 kg N ha⁻¹ in IF field plots; pots received 60 and 120 kg N ha⁻¹, while in vitro treatments included 7.5, 20 and 60 mmol L⁻¹ N. Nitrogen content in tubers was significantly affected by growing year and variety in both field systems (p < 0.05), with a significant year × variety interaction in OF. ‘Prelma’ consistently showed the highest nitrogen content, whereas ‘Jogla’ had the lowest across systems. Yield varied substantially among years and cultivation systems. In IF, ‘Jogla’ produced the highest yield, while in OF ‘Prelma’ performed best; ‘Monta’ had the lowest yields in both systems. In pot experiments, the highest yield was obtained at 120 kg N ha⁻¹, particularly for ‘Jogla’. Nitrogen use efficiency (NUE) decreased with increasing N rate. The relationship observed under field conditions that earlier-maturing varieties have lower NUE than later-maturing ones could not be confirmed in the in vitro and pot experiments. Overall, consistent varietal responses across systems indicate that controlled-environment methods can support NUE evaluation in potato research.
Platformised digital agriculture and technostress: implications for psychosocial occupational safety and health
(Estonian University of Life Sciences, 2026) Manzoni, D.; Černič Istenič, M.
Digitalisation in agriculture is increasingly structured through platformisation: daily work is mediated by interconnected sensors, dashboards, notification pipelines, and vendorgoverned service ecosystems. While automation and data-driven management can reduce physical workload and enable more flexible work organisation, platform-mediated arrangements may also increase psychosocial occupational safety and health (OSH) risks by reshaping temporality, interpretive responsibility, predictability, and practical agency. This article aims to explain how platform-mediated arrangements in digital agriculture generate technostress-related psychosocial OSH demands and to identify design and governance levers that may mitigate these risks in welfare- and time-critical settings. The study presents a theory-guided integrative review (narrative synthesis) using empirical ‘evidence anchors’; it is not a meta-analysis and does not provide pooled effect estimates, prevalence measures, or sector-wide quantitative inference. From a prior systematic review corpus, eleven scholarly sources (2004–2023) - primarily on automatic milking systems and related monitoring infrastructures - were selected and synthesised to identify recurring sociotechnical arrangements. The analysis yields a platform-architecture model linking work reorganisation to technostress appraisals clustered around four patterns: (1) availability pressures under always-on monitoring, (2) interpretive burden under opaque outputs and epistemic asymmetry, (3) constrained agency under proprietary service and update pathways, and (4) intensified self-evaluation under metricised dashboards. Framing technostress as an upstream outcome of platform-mediated work organisation clarifies why psychosocial OSH cannot be addressed through individual adaptation alone: risk depends on how platform design and governance allocate urgency, distribute uncertainty, and shape access to expertise, support, and repair. The article therefore proposes contestability - users’ capacity to inspect, adjust, and stabilise platform mechanisms - as a practical mitigation principle for OSH-sensitive digitalisation.
Comprehensive assessment of genotype–environment interaction and trait associations in sugar beet hybrids under short-rotation cropping systems of the Western Forest-Steppe of Ukraine
(Estonian University of Life Sciences, 2026) Kyselov, D.; Kalenska, S.; Chonka, M.; Solomukha, O.
This study aimed to evaluate genotype × environment (G×E) interaction, phenotypic stability, and multi-trait performance of sugar beet (Beta vulgaris L.) hybrids under short-rotation cropping systems of the Western Forest-Steppe of Ukraine. Eight commercial hybrids were tested across four environments (two locations over two years) using a randomized complete block design. Root yield (RY), sugar content (SC), sugar production (SP), impurity-related traits, and derived technological indices were analyzed using combined ANOVA, AMMI modeling, and BLUP-based stability metrics. Environmental effects were the dominant source of variation for RY, SC, and SP, while genotype and G×E interactions were smaller but statistically significant, confirming differential hybrid responses to contrasting environments. Stability was assessed using AMMI stability value (ASV), weighted average of absolute scores (WAASB), and the joint yield-stability index (WAASBY). BTS 9695, Strube Hubble, and KWS Ladislava consistently combined high mean productivity with low instability, indicating broad adaptation. Multi-trait evaluation using genotype by yield × trait (GYT) analysis revealed clear trade-offs between yield and technological quality. Hybrids BTS 9695 and Strube Hubble showed superior combinations for RY×SC and RY × low impurities, indicating high sugar productivity without major quality penalties. Overall, the integrated AMMI-WAASB/WAASBY–GYT framework proved effective for identifying sugar beet hybrids that combine high productivity, stability, and technological suitability under variable agroecological conditions, providing a robust basis for breeding and production recommendations.
Composting process parameters of different types of manure in a bioreactor
(Estonian University of Life Sciences, 2026) Bojarski, W.; Czekała, W.; Nowak, M.; Kupryaniuk, K.; Machaieie, L.
Composting has been practiced since ancient times, where it was used to enhance soil fertility and support crop production. It is therefore regarded as the oldest known method of biowaste treatment. Over time, the process has been systematically optimized through studies on the dynamics of aerobic biodegradation of various organic substrates, making it one of the most extensively investigated biological treatment technologies. Despite this long history, composting remains an important research topic, particularly in the context of circular economy strategies and sustainable development objectives. The aim of this study was to evaluate the composting dynamics of manure-based substrates differing in manure type, moisture content, and structural properties under controlled aerobic conditions. Experiments were conducted at the Ecotechnology Laboratory of the Poznań University of Life Sciences using four isothermal bioreactors (125 dm³ each) designed for controlled aerobic degradation. The tested materials included cattle manure (≈70% moisture), pig manure (> 80%), a mixture of cattle and pig manure (≈65%), and cattle manure (> 80%). During the process, O2 and CO2 concentrations, temperature, pH, bulk density, and mass loss were monitored, and dry matter, organic dry matter, organic carbon, and ash content were determined. The results showed clear differences in composting dynamics depending on manure type and moisture content. The cattle manure (70% moisture) exhibited rapid heating and a stable thermophilic phase, whereas highly moist pig manure showed slower temperature increase and lower intensity. The manure mixture demonstrated the highest microbiological activity, while excessive moisture in cattle manure (> 80%) reduced process efficiency. These findings confirm that manure type and moisture are key determinants of composting performance.
Analysis of the possibilities of using sawdust for bedding in poultry farms: A case study from eastern Poland
(Estonian University of Life Sciences, 2026) Gaworski, M.; Puszkarski, M.
The aim of the research study was to analyze the use of sawdust for poultry maintenance, from the perspective of a sawmill planning a possible expansion of its activities to include the preparation and distribution of sawdust bedding. The aim of the study became a prerequisite for proposing a test method that accounts for a diagnostic survey using a questionnaire addressed to owners of poultry farms within the potential distribution range of the sawdust producer. As a result of the study, the scale of poultry production on farms, the current mulching methods, and the actual consumption of bedding material were learned. An attempt was made to determine whether farmers are considering introducing sawdust into poultry houses, what concerns and limitations affect their decisions, and what conditions would need to be met to switch to sawdust as bedding in poultry houses. Expectations regarding the purchase and logistics service, including the preferred form of delivery, frequency of orders, and the way of handling used bedding, which affect the profitability of sawdust distribution by the sawmill to poultry farms, were examined.
Relationships between air relative humidity and soil temperature in open-field tomato production
(Estonian University of Life Sciences, 2026) Dallev, M.; Hristova, G.
Understanding microclimatic interactions between atmospheric and soil parameters is essential for precision agriculture and irrigation management. The present study evaluated the relationships between air temperature, relative humidity, soil temperature, and soil moisture under open-field tomato production using a portable ESP32-based monitoring system. Measurements were conducted at ten field points with three replicates per point (n = 30). Descriptive statistics indicated relatively stable environmental conditions during the observation period. Pearson correlation analysis revealed a statistically significant inverse relationship between air relative humidity and soil temperature (r = -0.376, p = 0.040), while no significant linear relationships were observed between the remaining variables (p > 0.05). Linear regression analysis confirmed that increasing air relative humidity was associated with decreasing soil temperature (R² = 0.142, p = 0.040), although the explanatory power of the model remained limited. Validation against a Meteobot® reference weather station demonstrated high accuracy of soil temperature measurements (relative error 0.74%) and acceptable performance for soil moisture (6.28%). The results indicate that low-cost IoT-based monitoring systems can reliably capture microclimatic interactions under field conditions and support their application in precision agriculture.
Three-dimensional reconstruction of the trunk volume of dairy cows using RGB-D images obtained by UAV for body mass prediction
(Estonian University of Life Sciences, 2026) Oliveira, F.M.; Ferraz, G.A.e.S.; Campos, L.L.; Reis, G.M.; Cecchin, D.; Becciolini, V.; Bambi, G.; Ferraz, P.F.P.
Accurate estimation of body mass (BM) in dairy cattle is essential for nutritional management, productivity monitoring, and animal welfare. In this context, three-dimensional (3D) morphometric descriptors derived from remote sensing technologies have emerged as promising alternatives to conventional weighing methods. This study proposes and evaluates a methodological framework for reconstructing the dorsal trunk volume of dairy cows using RGB-D data acquired by an unmanned aerial vehicle (UAV). Data were collected on a commercial dairy farm under a tie-stall system, with animals moving along a defined pathway after milking, enabling standardized overhead image acquisition. Top-view images were obtained using an Intel RealSense D435i depth camera mounted on a UAV platform (3DR Solo). Point clouds were generated and processed in CloudCompare, including dorsal surface segmentation, normal estimation, and volumetric mesh reconstruction using Poisson surface reconstruction. Only closed and geometrically consistent meshes were retained for analysis. The dataset comprised 25 dairy cows, resulting in 25 observations, with BM ranging from 500 to 750 kg, stratified into 50 kg intervals. Correlation analyses showed strong positive associations between reconstructed dorsal volume and BM, both globally (r = 0.979; ρ = 0.989) and across classes. A simple linear regression model, evaluated using a 70/30 train–test split and leave-one-out cross-validation, demonstrated high predictive performance (R² = 0.967 training; R² = 0.931 testing). These results confirm the technical feasibility and zootechnical relevance of UAV-based RGB-D acquisition combined with 3D reconstruction for non-invasive BM estimation in dairy cattle, highlighting its applicability in precision livestock farming systems.
Prediction of body mass in dairy cows using LiDAR technology
(Estonian University of Life Sciences, 2026) Mancini, S.; Ferraz, G.A.S.; de Oliveira, F.M.; Rubio, S.V.; Cecchin, D.; Reis, G.M.; Conti, L.; Becciolini, V.; Ferraz, P.F.P.
Precision livestock farming has driven the search for technological solutions that enable remote and non-invasive monitoring of animal health and zootechnical performance. This study aimed to investigate the use of computer vision for predicting body mass (BM) in a herd of Holstein Friesian dairy cows using three-dimensional images acquired via LiDAR (Light Detection and Ranging). From these images, the individual body volume (BV) of each animal was digitally estimated. Subsequently, the correlation between LiDAR-derived BV and body mass measured using the conventional weighing method was evaluated. Based on this relationship, statistical regression models were fitted to predict BM from BV. The results showed that BV measured using LiDAR achieved a coefficient of determination (R²) of 0.7861 and a mean absolute percentage error (MAPE) of 4.43%. These findings demonstrate the feasibility of LiDAR technology as an effective, non-invasive alternative tool for estimating bovine body mass. The use of LiDAR enabled detailed recording of morphological characteristics and measurements, allowing continuous monitoring of body development without the need for direct animal handling. In conclusion, the incorporation of computer vision systems into dairy cattle management can optimize operational efficiency, reduce labor requirements, and promote a more sustainable production system, while enhancing animal welfare through automated monitoring.

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