Search Results (524)

Evapotranspiration and crop coefficients are key variables for designing efficient irrigation strategies in tree crops, yet standard tabulated coefficients derived for mature, fully covering orchards often fail to represent the water use of young, high-density hazelnut systems. In recent years, updated crop coefficients for temperate fruit trees, including hazelnut, and transpiration-based models have been proposed, while several studies have successfully linked Vegetation Indices and thermal metrics to single and basal crop coefficients in vineyards, orchards and field crops. However, no information is available on the use of UAV-derived spectral and thermal indices to estimate crop coefficients in high-density hazelnut orchards. This study compares crop coefficients obtained from traditional approaches (the FAO56 single crop coefficient, a transpiration-based coefficient, and ground cover reduction factors) with coefficients estimated from UAV-derived Normalized Difference Water Index (NDWI) and Crop Water Stress Index (CWSI) in a subsurface-drip-irrigated hazelnut orchard (cv. Tonda Francescana^®) with two planting densities (625 and 1250 trees ha⁻¹) in central Italy. Multispectral and thermal UAV surveys carried out between 2021 and 2024 were used to derive canopy geometrical traits, ground cover, NDWI, and CWSI, while a local weather station provided reference evapotranspiration. Empirical relationships were calibrated between crop coefficients and ground cover, NDWI, and CWSI, and mid-season coefficients were applied to estimate daily crop evapotranspiration, which was then compared with the irrigation volumes supplied during the 2024 season. The standard FAO56 crop coefficient (Kc = 0.9) overestimated evapotranspiration, especially at the lower planting density, whereas ground cover-based reduction factors recalibrated for hazelnut and the transpiration-based coefficient provided estimates more consistent with the applied irrigation. UAV-based NDWI- and CWSI-derived crop coefficients produced mid-season values close to those obtained with the transpiration-based method for both planting densities, confirming that spectral and thermal information can effectively capture the combined effects of canopy development and water status. These results indicate that combining traditional methods with UAV-derived indices offers a flexible framework to refine crop coefficients in high-density hazelnut orchards and support more accurate and spatially explicit irrigation scheduling. Full article

Plum pox virus (PPV) is one of the most destructive pathogens affecting stone fruit trees. It causes sharka disease and severe yield losses. The genetically modified plum cultivar ‘HoneySweet’ was developed to provide long-lasting resistance to PPV via RNA interference. Long-term field trials of ‘HoneySweet’ have been conducted in the Czech Republic since 2001, involving the artificial inoculation of the cultivar with PPV alone, and with apple chlorotic leaf spot virus (ACLSV) and prune dwarf virus (PDV) in combination. This study evaluates the impact of viral infection on tree growth after 24 years in the field. Growth parameters—trunk cross-sectional area (TCSA) and canopy volume—were measured and analysed using ANOVA and Tukey’s test. The results show that infected trees exhibit significantly reduced growth compared to non-infected controls, with the strongest inhibition observed in trees inoculated with PPV + PDV + ACLSV. The presence of ACLSV had the most pronounced negative effect on growth, while PDV did not significantly influence tree vigour. These findings emphasise the importance of using virus-free rootstocks and certified planting material to prevent growth suppression in HoneySweet orchards. Full article

High-fidelity acquisition of canopy phenotypic data is critical for the advancement of orchard Artificial Intelligence (AI). Yet, an improper Light Detection and Ranging (LiDAR) installation height (IH) frequently induces data occlusion and substantial measurement errors. To address this limitation, this study developed an information collection vehicle (ICV) integrated with a 16-channel three-dimensional (3D) LiDAR to determine the optimal LiDAR IH. Three representative LiDAR IHs (1.4 m, 2.0 m, and 2.6 m) were evaluated on spindle-shaped cherry trees under both forward and reverse driving strategies. Subsequently, a novel 12-zone refined evaluation framework was introduced to quantify localized errors that are conventionally obscured by traditional whole-canopy metrics. Results demonstrated a profound nonlinear relationship between IH and measurement accuracy. Specifically, the 2.0 m IH (approximating the canopy’s geometric center) emerged as the optimal setup, maintaining relative errors (REs) below 5% with minimal dispersion. Conversely, the 2.6 m IH caused lower-canopy volume REs to surge beyond 16% owing to restricted downward viewing angles. Additionally, reverse driving at higher IHs exacerbated mechanical vibrations via the “lever arm effect”, thereby significantly degrading point cloud registration accuracy. Ultimately, these findings underscore the critical necessity of aligning sensors with the canopy geometric center, supplying essential theoretical guidelines for the hardware design of future orchard robots. Full article

The accurate estimation of tree canopy volume is fundamental in precision agriculture for quantifying vegetation structure, biomass, and productivity in perennial cropping systems. This study investigates a shadow geometry approach for estimating olive tree canopy volumes from a single, very high-resolution WorldView-3 multispectral image. The method integrates multispectral classification for canopy and shadow delineation with a geometric model that infers canopy height from shadow measurements, accounting for solar position and terrain morphology. Two classification strategies were evaluated: object-based image analysis (OBIA) and pixel-based (PB) classification, each applied to the original eight-band multispectral image and to a derived dataset enriched with vegetation indices (NDVI—Normalized Difference Vegetation Index; NDRE—Normalized Difference Red Edge Index) and principal component analysis (PCA) components. The canopy volume was estimated by integrating classified canopy and shadow areas with shadow-derived canopy height. The methodology was tested in a Mediterranean olive orchard and validated against UAV-derived point clouds for approximately 700 trees. The results indicate that the approach captures spatial variability in canopy structure. The Object-Based Image Analysis (OBIA) applied to filtered PCA-enhanced imagery achieved the highest accuracy in canopy volume estimation (RMSE = 2.04 m³; R² = 0.56), outperforming the alternative pixel-based (PB) classification applied to the original multispectral data. Overall, the study demonstrates the potential of single-image WorldView-3 data for rapid and scalable three-dimensional canopy characterization in precision agriculture. Full article

Climate change influences the agronomic behaviour of fruit trees. It is necessary to determine which cultivars adapt best to conditions in which water supplies are becoming increasingly scarce. This study analyses different phenological, morphological, physiological, agronomic and productive parameters to evaluate water stress tolerance in six late-blooming almond cultivars widely grown in Spain (‘Ferragnès’, ’Francolí’, ‘Masbovera’, ‘Glorieta’, ’Guara’ and ‘Lauranne’). Two different plots were analysed: one under regulated deficit irrigation, at Les Borges Blanques, Lleida, with a water deficit (146.2 mm/year) and the other under rainfed conditions, at Mas Bové, Constantí, Tarragona, with a water deficit (284.5 mm/year). Parameters, including an increase in canopy volume, leaf-to-air thermal gradient, and slope between leaf water potential and level of leaf saturation, have proven to be good indicators of resistance to water stress. Yield variation and leaf temperature variation between rainfed and irrigated conditions also perform quite well. An assessment of leaf chlorophyll content, measured using SPAD-502, suggested the presence of a collateral effect resulting from the opacity of the biomass, as well as to chlorophyll-related cuticular colouring. Finally, under the experimental conditions, ‘Guara’ and ‘Masbovera’ proved the most resistant cultivars; ‘Glorieta’ and ‘Francolí’ exhibited an intermediate level, and ‘Lauranne’ and ‘Ferragnès’ were the least resistant cultivars. Full article

To identify the most suitable rootstocks for bergamot production in Italy, vegetative growth, yield performance, and fruit quality were assed in “Femminello” bergamot trees grafted onto eight different rootstocks under the Mediterranean edaphoclimatic conditions of Reggio Calabria (Southern Italy). Rootstock selection significantly affected tree vigor, productivity, and fruit quality. Alemow induced the greatest vegetative growth, producing trees with canopy volumes up to 60% larger than those grafted onto Sour Orange, whereas Flying Dragon caused a strong dwarfing effect, reducing canopy volume by approximately 80%. Carrizo Citrange and Swingle Citrumelo exhibited the highest yield efficiency (9.7 and 9.5 kg m⁻³, respectively), about 30% higher than Sour Orange, while Alemow showed the lowest efficiency (1.8 kg m⁻³). Cumulative yield over seven cropping seasons was highest on Carrizo Citrange (196 kg tree⁻¹), with comparable values recorded for Sour Orange, Swingle Citrumelo, and Trifoliate Orange. In contrast, Alemow and Flying Dragon yielded 55% and 85% less, respectively. Rootstock selection significantly influenced fruit size, peel characteristics, and juice quality. Rootstock selection had a marked effect on fruit size, peel characteristics, and juice quality. Fruit weight ranged from under 170 g on Sour Orange, Volkameriana, and Alemow to approximately 196 g on Trifoliate Orange, while at full maturation, most rootstocks produced fruits weighing between 213 and 223 g, except for Alemow (<200 g). Trifoliate Orange and its hybrids promoted thinner peel and higher juice content, whereas Alemow and Volkameriana produced fruits with thicker peel and up to 15% lower juice content than Carrizo Citrange. Juice titratable acidity decreased during maturation, ranging from over 50 g L⁻¹ on Sour Orange and Alemow to around 39–41 g L⁻¹ on Trifoliate Orange, Carrizo Citrange, Troyer Citrange, and Flying Dragon at harvest. Overall, Trifoliate Orange, Carrizo Citrange, and Swingle Citrumelo emerged as promising alternatives to Sour Orange, combining high yield efficiency, satisfactory fruit quality, and improved yield precocity. Full article

In the context of global climate change and rapid urbanization, integrating urban blue-green infrastructure into the built environment is essential for mitigating the urban heat island effect and enhancing climate resilience. Focusing on urban riparian corridors as vital natural cooling systems, this study aims to: (1) quantify their cooling performance in terms of intensity and distance; (2) identify the key landscape drivers and their relative importance; (3) uncover nonlinear relationships and determine ecological thresholds for optimal thermal regulation; and (4) translate these findings into science-based guidelines for climate-adaptive design and sustainable management. Taking 27 representative riparian green spaces in Zhengzhou, China (average area: 17,539 m², range: 10,027–42,690 m²) as a case study, nine key factors characterizing vegetation structure and composition, corridor morphology, and blue-green spatial pattern were used as predictors in a Boosted Regression Tree (BRT) model to analyze their contributions and marginal-effect thresholds. Results show that these corridors provide substantial cooling, with an average intensity of 5.43 °C extending over 215.56 m. Canopy Density, 3D Green Volume per Unit Area, and Green Cover Ratio emerged as the three core drivers, jointly explaining >86% of the cooling performance. The key innovation lies in identifying explicit, design-oriented ecological thresholds—for example, cooling efficacy stabilizes when Green Cover Ratio reaches ~77%, Canopy Density attains 0.7, and the Blue-Green Space Width Ratio approaches 1:1. These thresholds can be directly translated into performance benchmarks for sustainable urban planning and landscape engineering, providing evidence-based parameters for optimizing vegetation structure and spatial configuration. This study demonstrates that applying quantified ecological thresholds can transform riparian corridors into efficient climate-resilient infrastructure, thereby synergistically improving thermal comfort, enhancing ecosystem services, and promoting sustainable land use in urban environments. Full article

A newly commercialized single-row multi-fan autonomous unmanned ground vehicle (UGV) sprayer, for use in trellised tree fruit crops, was tested to better understand air and spray patterns prior to wide-scale adoption in the modern apple orchard systems typical to Washington State. This sprayer was equipped with five brown and yellow Albuz ATR80 nozzles per fan (QM-420, Croplands Quantum). The fans were installed in a Q8 configuration, with eight fans (four on each side) staggered near the front and back as a stack to increase vertical span. Air velocity and spray delivery patterns of the commercialized sprayer unit were assessed in laboratory using a customized smart spray analytical system. Previous field trails of this sprayer unit revealed a hardware issue with electric proportional valve controls in fan-nozzle assembly, resulting in uneven spray deposition across V-trellised canopy. Post issue resolution, the sprayer characterization data showed an average Symmetry of 91%, and 84% for air velocity and spray volume delivery on either side. An average Uniformity of 57% and 48%, respectively was recorded for pertinent sprayer attributes across the spray height. Overall, after optimization, the UGV sprayer is suitable for efficient agrochemical application in modern orchard systems. Further evaluation of labor savings, biological efficacy gains from autonomous operation, and a full economic analysis would better inform grower adoption. Commercial viability of this UGV sprayer could also be improved by added features such as variable-rate application enabled by real-time crop sensing or task-map integration. Full article

Old-growth forests provide a key biodiversity reservoir due to their high amount of deadwood and abundance of tree-related microhabitats (TreMs). This research investigates the abundance and diversity of deadwood and TreMs in old-growth Caledonian pine forests located in the Cairngorms National Park, Scotland. The study area is a Scots pine (Pinus sylvestris L.)-dominated forest. A field survey campaign was conducted in 15 sample plots to collect data on stand and deadwood characteristics, and TreMs by category. Within circular plots of 531 m², the diameter at breast height, height, and insertion height of the canopy of all the living trees were measured, and the three deadwood components (snags, fallen deadwood, and stumps) and TreMs were recorded. The results showed a total deadwood volume of 37.53 ± 32.39 m³ ha⁻¹, mostly in the form of snags (68.9% of total volume) and in the lowest degree of decay (first decay class equals 36.8%). The average number of deadwood elements is 217 ha⁻¹, distributed to 127 snags ha⁻¹, 64 fallen deadwood ha⁻¹, and 26 stumps ha⁻¹. The results showed an average of 89.1 TreMs ha⁻¹ on snags and 26.4 ha⁻¹ on living trees. The abundance and diversity of TreMs are significantly related to the volume of snags (R² = 0.712), the deadwood diversity (R² = 0.664), and the degree of decomposition (R² = 0.416). Full article

Vegetation volume is a useful indicator for assessing canopy structure and supporting vineyard management tasks such as foliar applications and canopy management. The photogrammetric processing of imagery acquired using unmanned aerial vehicles (UAVs) enables the generation of dense point clouds suitable for estimating canopy volume, although point cloud quality depends on spatial resolution, which is influenced by flight height. This study evaluates the effect of three flight heights (30 m, 60 m, and 100 m) on grapevine canopy volume estimation using convex hull, alpha shape, and voxel-based models. UAV-based RGB imagery and field measurements were collected during three periods at different phenological stages in an experimental vineyard. The strongest agreement with field-measured volume occurred at 30 m, where point density was highest. Envelope-based methods showed reduced performance at higher flight heights, while voxel-based grids remained more stable when voxel size was adapted to point density. Estimator behavior also varied with canopy architecture and development. The results indicate appropriate parameter choices for different flight heights and confirm that UAV-based RGB imagery can provide reliable grapevine canopy volume estimates. Full article

Rainfall is an essential component of boreal forest ecosystems. Aerotechnogenic pollution significantly affects the composition of rainfall. To predict the dynamics of biogeochemical cycles and develop strategies to enhance forest resilience in the Arctic zone, it is necessary to study the composition and characteristics of rainfall. The objective of this study is to evaluate the variation in the chemical composition of stemflow in the most typical pine and spruce forests of Fennoscandia under conditions of aerotechnogenic pollution based on long-term monitoring data from 1999 to 2022. The research was carried out in forests exposed to atmospheric industrial pollution from the largest copper–nickel smelter in northern Europe (Murmansk Region, Russia). The study of rainwater composition was conducted in four microsites: open areas (OA), between crowns (BWC), below crowns (BC) and stemflow (SF). A significant influence of the tree canopy on the rainfall composition was noted. Stemflow was found to have the highest concentration of pollutants, indicating a significant biochemical role of this type of precipitation. The results showed an increase in the concentrations of heavy metals and sulfates in rainwater as we moved closer to the pollution source. Below crowns and in the stemflow of spruce forests, element concentrations are higher compared to pine forests. The highest concentrations of major pollutants in stemflow (Ni, Cu and SO₄²⁻) are observed in June—at the beginning of the growing season. Long-term dynamics reveal a decrease in the concentrations of Cu, Cd and Cr in defoliated forests and technogenic sparse forests. Stemflow volume rises from background to technogenic sparse forests due to deteriorating tree-crown conditions. This is associated with the deteriorating condition of tree stands, as manifested by reductions in tree height, diameter and needle cover. It has been established that under pollution conditions, trees’ assimilating organs actively accumulate heavy metals, thereby altering the composition of precipitation passing through the canopy. Full article

Accurate quantification of forest aboveground biomass (AGB) is essential for monitoring terrestrial carbon stocks. While total AGB estimation is widely practiced, resolving component biomass such as canopy, branches, leaves, and trunks enhances the precision of carbon sink assessments and provides critical structural parameters for ecosystem modeling. Most studies rely on a single SAR sensor or a limited range of SAR features, which restricts their ability to represent vegetation structural complexity and reduces biomass estimation accuracy. Here, we propose a phased fusion strategy that integrates backscatter intensity, interferometric coherence, texture measures, and polarimetric decomposition parameters derived from dual-frequency ALOS-2, GF-3, and Sentinel-1A SAR data. These complementary multi-dimensional SAR features are incorporated into a Random Forest model optimized using an Adaptive Genetic Algorithm (RF-AGA) to estimate forest total and component estimation. The results show that the progressive incorporation of coherence and texture features markedly improved model performance, increasing the accuracy of total AGB to R² = 0.88 and canopy biomass to R² = 0.78 under leave-one-out cross-validation. Feature contribution analysis indicates strong complementarity among SAR parameters. Polarimetric decomposition yielded the largest overall contribution, while L-band volume scattering was the primary driver of trunk and canopy estimation. Coherence-enhanced trunk prediction increased R² by 13 percent, and texture improved canopy representation by capturing structural heterogeneity and reducing saturation effects. This study confirms that integrating coherence and texture information within the RF-AGA framework enhances AGB estimation, and that the differential contributions of multi-dimensional SAR parameters across total and component biomass estimation originate from their distinct structural characteristics. The proposed framework provides a robust foundation for regional carbon monitoring and highlights the value of integrating complementary SAR features with ensemble learning to achieve high-precision forest carbon assessment. Full article

Accurate estimation of tree biomass and volume is essential for sustainable forest management, climate change mitigation, and ecosystem service assessment. Recent advances in unmanned aerial vehicle (UAV) technology enable the acquisition of ultra-high-resolution optical and three-dimensional data, providing a resource-efficient alternative to traditional field-based inventories. This review synthesizes 181 peer-reviewed studies on UAV-based estimation of tree biomass and volume across forestry, agricultural, and urban ecosystems, integrating bibliometric analysis with qualitative literature review. The results reveal a clear methodological shift from early structure-from-motion photogrammetry toward integrated frameworks combining three-dimensional canopy metrics, multispectral or LiDAR data, and machine learning or deep learning models. Across applications, tree height, crown geometry, and canopy volume consistently emerge as the most robust predictors of biomass and volume, enabling accurate individual-tree and plot-level estimates while substantially reducing field effort and ecological disturbance. UAV-based approaches demonstrate particularly strong performance in orchards, plantation forests, and urban environments, and increasing applicability in complex systems such as mangroves and mixed forests. Despite significant progress, key challenges remain, including limited methodological standardization, insufficient uncertainty quantification, scaling constraints beyond local extents, and the underrepresentation of biodiversity-rich and structurally complex ecosystems. Addressing these gaps is critical for the operational integration of UAV-derived biomass and volume estimates into sustainable land management, carbon accounting, and climate-resilient monitoring frameworks. Full article

Targeted coverage of crushed grass segments under the fruit tree canopy synergistically achieves the agronomic goals of soil moisture conservation, weed suppression, and soil fertility improvement. To address issues like incomplete grass cutting and high risk of damaging fruit trees in complex orchard environments with traditional mowing devices, a lateral grass discharge blade for orchard mowers was designed. Based on airflow field theory, the dynamic basis of the airflow field, critical conditions for carrying crushed grass segments, and their movement laws on the blade and in the air were analyzed to identify key factors affecting discharge. CFD simulations were conducted using the Flow Simulation module of SolidWorks 2021 to explore the effects of the blade airfoil’s long side, short side lengths, and horizontal included angle on the outlet velocity and outlet volumetric flow rate of crushed grass segments, determining the reasonable parameter range. With these three as test factors and the two indicators above, orthogonal tests and parameter optimization were performed via Design-Expert 13.0 software, yielding optimal parameters: long side 125 mm, short side 35 mm, horizontal included angle 60°, corresponding to 9.105 m/s outlet velocity and 0.045 m³/s volume flow rate. A prototype mowing device with these parameters was fabricated for orchard field tests. Results show an average stubble stability coefficient of 94.2%, average over-stubble loss rate of 0.39%, and crushed grass segment distribution variation coefficient of 23.8%, meeting orchard mower operation requirements and providing technical support for orchard weed mowing, coverage, and utilization. Full article

Accurately measuring the three-dimensional green quantity (3DGQ) of urban trees is crucial for quantifying carbon sequestration benefits (CSB) in high-density cities. In this study, 540 street trees across 18 species (30 per species) in Shanghai were analyzed to evaluate an Improved Simpson Model (ISM) for UAV-derived crown volume estimation against a traditional Approximate Geometry Model (AGM) and a LiDAR-based point cloud method (PCM). The ISM integrates UAV imagery, edge-based canopy profiling, and Simpson’s numerical integration to account for irregular crown shapes and internal leaf-stem gaps. Results show that ISM achieved consistently lower estimation errors than the benchmark methods. Overall, ISM’s 3DGQ estimates had a root mean square error (RMSE) of approximately 5.2 m³ and a mean absolute error (MAE) of about 4.1 m³, indicating a close match with PCM reference values. This represents a dramatic error reduction, on the order of 90%–95% improvement in RMSE, compared to the conventional AGM approach. Broadleaf species with dense, regular canopies (e.g., Cinnamomum camphora and Platanus × acerifolia) exhibited the highest accuracy, with ISM-predicted volumes deviating only ~1%–2% from field measurements. Even for species with more irregular or porous crowns, the ISM maintained robust performance, yielding smaller errors than AGM and nearly matching the LiDAR-based PCM “ground truth.” These findings demonstrate that the proposed ISM can provide highly accurate 3D crown volume and carbon sequestration estimates in complex urban environments, outperforming existing geometric models and offering a practical, efficient alternative to labor-intensive LiDAR surveys. Full article