EMU DSpace
Digitaalarhiiv EMU DSpace kogub, säilitab ja loob ligipääsu Eesti Maaülikooli liikmeskonna poolt loodud või Eesti Maaülikooli vastutusvaldkondadega seotud teadustöödele toetamaks maaülikooli konkurentsivõimet ja teadmistepõhist ühiskonna arengut. Digitaalarhiivi haldab Eesti Maaülikooli raamatukogu.
Valdkonnad DSpace's
Valige valdkond, et selle kogusid sirvida.
- Institute of Forestry and Engineering (MII)
- Institute of Agricultural and Environmental Sciences (PKI)
- Institute of Veterinary Medicine and Animal Sciences (VLI)
- Publications
- Units
Hiljutised sisestused
An Ecosystem Services Based Approach to Characterising Riparian Forests and Developing Management Solutions
(Estonian University of Life Sciences, 2026) Rebane, Sille; Vodde, Floortje; Jõgiste, Kalev
Riparian forests along river corridors play a important role in sustaining ecosystem services, including water quality regulation, bank stabilization, carbon storage, biodiversity support, and cultural values. Despite their importance, riparian forests are frequently managed using generalized forest typologies that insufficiently reflect their functional roles, spatial heterogeneity, and strong coupling with hydrological processes.
The proposed approach is based on the premise that characterising riparian forests solely by site type or stand structure is insufficient for informed decision-making. Instead, riparian forests are described in terms of their capacity to provide ecosystem services, their sensitivity to disturbance, and their relevance for management interventions. Characterisation is structured along key environmental gradients shaping ecosystem service provision, including hydrological connectivity (flood frequency, groundwater interaction), geomorphological position (river bank, floodplain, terrace), vegetation structure and composition, and land-use legacies. Together, these factors determine the ability of riparian forests to regulate nutrient and sediment fluxes, mitigate flood impacts, maintain habitat continuity, and contribute to climate regulation.
Building on this characterisation, a multi-dimensional framework is introduced that links biophysical attributes to ecosystem service bundles rather than single functions. This enables the identification of riparian forest types that are particularly important for regulating services (e.g. nutrient retention and erosion control), supporting services (e.g. habitat provision and ecological connectivity), or cultural services (e.g. recreation and landscape values). The framework is designed to inform management by highlighting how different riparian forest types require distinct management solutions, ranging from strict protection and passive restoration to adaptive silviculture that maintains structural complexity while sustaining ecosystem service delivery.
The approach is intended to be operational across spatial scales, from individual river reaches to catchment-level planning, and compatible with existing forest inventory, spatial, and hydrological data. By explicitly linking ecosystem service–based characterisation with management options, the framework supports transparent evaluation of trade-offs and synergies among management objectives and helps prioritise areas where riparian forest conservation or restoration delivers the greatest societal benefits.
Crop And Fertilization Rate Effect On Greenhouse Gas (N2O, CO2, CH4) Emissions
(Eesti Maaülikool, 2026) Tuhkanen, Tiiu; Escuer Gatius, Jordi (advisor); Mullateaduse õppetool
The increasing use of mineral nitrogen fertilisers in agriculture is a primary driver of
nitrous oxide (N₂O) emissions, a greenhouse gas with a 100-year global warming potential
273 times that of CO₂. This study investigated the effects of mineral N fertilisation rate,
crop species (C3 vs C4), and the legacy effect of solid farmyard manure on N₂O, CO₂, and
CH₄ fluxes from a Stagnic Luvisol mineral soil during the 2024 growing season at the
IOSDV long-term fertilisation experiment in Õssu village, Kambja parish, Estonia. Three
crop species were studied — spring barley, spring wheat, and sorghum-sudangrass hybrid
(Sorghum bicolor x Sorghum sudanense) — under five mineral N rates (0, 40, 80, 120,
and 160 kg N ha⁻¹). GHG fluxes were measured on eleven sampling dates using the static
chamber method and analysed by gas chromatography. A three-way ANOVA and Tukey
HSD post-hoc test were used for statistical analysis.
Mineral N rate was a highly significant driver of all three GHG fluxes (p < 0.01).
Cumulative N₂O increased from below 25 mg N m⁻² at N0 to approximately 81 mg N m⁻²
at N160. Crop species significantly affected all gases (p < 0.05); sorghum-sudangrass
hybrid exhibited the lowest N₂O and CO₂ emissions across all treatments, with N₂O
approximately fourfold lower than wheat under N80, a pattern consistent with – though
not proof of –biological nitrification inhibition (BNI) by sorgoleone, given that crop-level
comparisons cannot fully separate BNI from differences in plant N uptake capacity. The
manure legacy effect significantly increased CO₂ emissions (p < 0.001), but its main effect
on N₂O was non-significant; however, the N rate × manure interaction was significant for
N₂O (p = 0.043), indicating that the manure legacy effect manifested only at high mineral
N inputs. N₂O correlated positively with soil temperature but not with soil moisture, likely
reflecting measurement spatial resolution limitations. The results support sorghumsudangrass
hybrid as a low-emission crop candidate for boreal mineral soils and suggest
that a mineral N rate of approximately 80 kg N ha⁻¹ represents a favourable balance
between biomass yield and GHG emissions.
Spectral behavior of Macaúba palms (Acrocomia aculeata) under different lighting conditions and phenological stages
(Estonian University of Life Sciences, 2026) Santana, L.S.; Surmani, C.L.S.; Santos, L.G. Maciel dos; Lopes, M.D.S.; da Silva, J.M.; Evaristo, A.B.; Rossi, G.; Bambi, G.
Climate change events highlighted concerns about renewable energy consumption. The Macaúba palm (Acrocomia aculeata) stands out as a palm with high potential for energy production. However, it is still in the domestication phase as an agricultural crop. Thus, integrating technologies such as remote sensing to monitor plant characteristics can contribute to understanding this crop's development. In this context, the study aimed to evaluate the spectral behavior of Macaúba (Acrocomia aculeata) under various lighting conditions and at different phenological stages. Multispectral images were obtained using a Multispectral Remotely Piloted Aircraft (RPA), with flights conducted at 8:00 AM, 12:00 PM, and 4:00 PM, and during two seasonal periods (February and June 2025). The aim was to analyze the effects of solar variation and plant development on reflectance and spectral indices. The results showed a strong influence of illumination on the spectral response, with an 80% reduction in reflectance under shade, with the red band being the most sensitive. Multitemporal analysis revealed marked decreases in the TCARI (-83.7%), OSAVI2 (-80.8%), and TCARI/OSAVI (-15.9%) indices, accompanied by a decrease in photosynthetic pigments and the onset of leaf senescence during the dry season. Conversely, the NDRE (+10.1%) and CIgreen (+24.7%) indices increased, reflecting maintenance of photosynthetic activity and the emergence of new leaves. NDVI remained stable, indicating the conservation of canopy structure. Multispectral RPAs' potential for phenological and physiological monitoring of tropical palms, emphasizing the importance of temporal and geometric standardization of acquisitions to ensure radiometric consistency. Integrating spectral data with solar parameters is an effective strategy to enhance the sustainable management of Macaúba palms.
Spatial modeling of coffee tree height and diameter using LiDAR SLAM, RGB imagery, and field measurements
(Estonian University of Life Sciences, 2026) Rubio, S.V.; Ferraz, G.A.S.; Cardozo, E.J.S.; Zavala, E.H.; de Oliveira, F.M.; Bambi, G.; Sarri, D.; Reis, G.M.; Ferraz, P.F.P.
Remote sensing has become established as a promising tool for crop management. In coffee farming, estimating canopy height and diameter is essential to characterize plant vigor, development, and uniformity. This study compared three approaches to obtain these variables: field measurements, RGB (Red, Green, Blue) imagery acquired by a Remotely Piloted Aircraft (RPA), and a handheld Light Detection and Ranging sensor (LiDAR), using geostatistics to assess spatial accuracy and agreement among methods. From three-dimensional data, surface and terrain models were derived, enabling estimation of canopy height and diameter, while geostatistics was used to characterize the spatial structure, select variogram models via cross-validation, and generate continuous maps through ordinary kriging. In pointwise comparison with field data, LiDAR showed better performance for height (R² = 0.80) than the RGB orthomosaic (R² = 0.63). For canopy diameter, LiDAR was also superior (R² = 0.79) relative to RGB imagery (R² = 0.71). At the spatial level, the comparison between kriged maps indicated greater agreement between LiDAR and field data, especially for plant height (r = 0.99), whereas RGB and field data showed lower spatial correspondence (r = 0.44). For canopy diameter, the maps derived from LiDAR and RGB showed good agreement with field data, with r = 0.88 and r = 0.83, respectively. Thus, the combination of pointwise assessment and geostatistical analysis proved suitable for comparing the studied methods and for interpreting, in an integrated manner, the estimation and spatial distribution of coffee tree height and canopy diameter.
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.