Search Results (1,152)

Yield prediction in longline aquaculture is essential for evaluating environmental impacts, facilitating risk assessment, and promoting sustainable management in fisheries. However, since cultured organisms in longline aquaculture are submerged and cannot be directly observed, existing yield prediction approaches are mostly based on indirect environmental proxies, which often lead to unsatisfactory accuracy. The Shadow Geometry Inversion for Aquaculture (SGIA) method enables direct and accurate yield estimation in longline aquaculture by utilizing the submergence state of buoys to infer load, which is determined by the weight of the cultured organisms and estimated by shadow lengths combined with solar altitude angles and buoy physical parameters in high-resolution unmanned aerial vehicle (UAV) imagery. Experiments have been conducted in a water body located in Shanghai and Fuding to validate the effectiveness of the SGIA method. The best results were achieved under solar altitudes of 10–25° and calm water conditions. Under these conditions, the SGIA-predicted yields closely matched the measured loads in the Shanghai controlled experiment (R² = 0.985, MAPE = 9.19%). In the Fuding field application, the model effectively captured spatial variations in buoy loads across the farming area, demonstrating its practicality and scalability for large-scale yield mapping in real aquaculture environments. Full article

Brazil is recognized for its rich biodiversity, including aromatic species of economic importance, among which Baccharis dracunculifolia De Candole (1836) stands out. The essential oil distilled from this species exhibits biological and therapeutic activities. Despite its relevance, studies addressing the chemodiversity of this species on a broad scale remain scarce. This study aimed to map and characterize the chemical and physicochemical profiles of B. dracunculifolia essential oils from different regions of the state of Rio de Janeiro, considering the influence of geographic factors and plant sex. Fifty georeferenced accessions of B. dracunculifolia were collected in 2023 and 2025, and dried leaves were subjected to hydrodistillation. The essential oils were characterized through physicochemical analyses and chemically analyzed by GC-FID and GC-MS. Essential oil yields ranged from 0.34 to 2.17%, relative density from 0.89 to 0.96 g/cm³, refractive index from 1.485 to 1.497 n^D, and specific optical rotation from −12.56° to +6.80°. Sixty-two compounds were identified, predominantly oxygenated sesquiterpenes, with E-nerolidol (16.8–51.0%), spathulenol, bicyclogermacrene, and germacrene D as the main compounds. Multivariate analysis revealed five chemical profiles, all containing E-nerolidol as the major compound, indicating moderate to low chemical diversity. No significant differences were observed between the essential oils from female and male plants. However, variation in the chemical profile of the essential oil was observed as a function of year and altitude. Full article

Selenium (Se) is an essential trace element for human health, which is crucial for antioxidant defense, immune function, and disease prevention. Se deficiency affects around 40 countries worldwide, with China being one of the most severely impacted. While previous research has explored factors influencing soil Se content, such as the parent material, climate, and soil properties, the dominant controlling mechanisms across different spatial scales remain a subject of debate, especially in the Se-rich coastal regions of southeastern China. This study focuses on Fujian Province, using hotspot analysis and geographically weighted regression (GWR) to systematically examine the spatial distribution of soil Se and its key influencing factors. Hotspot analysis reveals multi-scale patterns in Se distribution: at the 1 km scale, Se hotspots are closely linked to metal minerals like sulfide and coal deposits; at the 2 km scale, Se-rich carbonate rocks and carbonaceous mudstones dominate; and, at the 10 km scale, Se accumulation is mainly controlled by organic matter and low-temperature conditions in high-altitude areas (≥1200 m). GWR analysis further clarifies the nonlinear relationships between soil Se and key environmental factors: organic matter strongly correlates with Se in coastal regions but weakly in land, indicating that this relationship is modulated by factors such as weathering intensity and clay content. The mobility of Se increases in alkaline soils (pH > 8.5), thus reducing its content; meanwhile, in acidic soils (pH < 4.5), its fixation is more complex. In acidic, low-aluminum settings, iron oxides adsorb Se effectively, whereas organic matter becomes the main carrier under alkaline conditions. Precipitation affects Se via atmospheric deposition and leaching, temperature promotes sulfide substitution through deposition but also accelerates the breakdown of organic matter, and altitude influences Se through hydrothermal variations. This study provides the first comprehensive analysis of the multi-factor mechanisms controlling soil Se in the Se-rich coastal areas of southeastern China at a regional scale, offering a scientific basis for the sustainable use of Se-enriched land resources. Full article

The frequency, intensity, and duration of extreme climate events will probably increase in various areas in the 21st century. This trend is especially critical for the western Tianshan Mountains, which are highly sensitive to climate variability. Here, we used tree core samples of Picea schrenkiana Fisch. & C.A.Mey. (P. schrenkiana) from the Kashi River Basin to establish standardized earlywood and latewood density chronologies, analyze correlations between the density chronologies and extreme climate indices, and explore the response of tree-ring density to climate and altitudinal variation. Earlywood and latewood densities were significantly correlated with major climatic indices: positively with warm nights (TN90p; June–August), Max Tmin (TNx; June–August), and Min Tmin (TNn; July), and negatively correlated with cold nights (TN10p; June–September). The climate has undergone significant changes particularly in minimum temperatures, and the sensitivity of tree-ring density to major extreme climate indices (TN90p, TNx, TNn, and TN10p) strengthened significantly in sample sites below 1900 m and above 2200 m during 1980–2015 and 1974–2009, respectively, reflecting the vulnerability of mid–high-altitude forests to drought stress. Combined with teleconnection analysis, the positive phase of the AMO is synergistic with the negative phase of NAO/AO, which aggravates the response of tree growth to drought. These results indicate that changes in extreme climate indices primarily exacerbate drought stress in the region’s vulnerable mountain ecosystems, suggesting that future forest management plans should accordingly strengthen their focus on P. schrenkiana. Full article

Potentilla erecta (L.) Raeusch. is a widely used medicinal species valued for its astringent, anti-inflammatory, and antimicrobial effects. This study examined the variation in hydrolysable tannin and flavonoid content in rhizomes of wild-growing populations collected along an elevational gradient in the Ukrainian Carpathians (180–2020 m above sea level). Rhizomes from fifteen populations were analyzed using pharmacopoeial methods, including thin-layer chromatography for tannins and spectrophotometry for flavonoids. Tannin levels ranged from 15.57% to 31.82%, while flavonoid contents varied between 0.23% and 0.40%, expressed as a percentage of dry weight. Both metabolites showed a strong positive correlation with altitude (r = 0.88 for tannins; r = 0.84 for flavonoids), indicating a clear influence of elevation on their accumulation. The highest concentrations were consistently found in high-mountain populations. These results suggest that environmental factors associated with increasing elevation, such as reduced temperature and enhanced ultraviolet radiation, play a significant role in shaping the phytochemical profile of P. erecta. The study contributes to the understanding of altitudinal effects on secondary metabolite accumulation in mountain plants and provides a basis for further ecological and pharmacological-oriented research related to this species. Full article

To elucidate the adaptive strategies of leaf functional traits of Larix principis-rupprechtii in the context of climate change, this study chose 2 and 3 year-old seedlings of Larix principis-rupprechtii as the focal research objects. The experiment entailed transplanting seedlings obtained from different sources into high and low altitudes: 1600 m, 1900 m, 2100 m, and 2400 m, respectively. With changes in transplant elevation, seedlings showed variable responses in photosynthesis, water-use efficiency, and leaf morphology, depending on the altitude. High-altitude seedlings transplanted to low altitudes increased SLA and branch extension, enhancing photosynthesis and C-N metabolism. Conversely, low-altitude seedlings transplanted to high altitudes improved cold resistance primarily via leaf thickening, adjusting the chlorophyll a/b ratio, and enhancing the redistribution of soluble proteins. For high-altitude sources, water-use efficiency and transpiration rate were strongly linked to leaf nitrogen and the carbon-to-nitrogen ratio, respectively, indicating the optimisation of photosynthetic and water-use efficiency through modulation of chlorophyll-a content and branch extension. Low-altitude seedlings chiefly adjusted the chla/b ratio, leaf morphological traits, and soluble protein to cope with altitudinal change. In summary, variation in leaf functional traits among seedlings of Larix principis-rupprechtii across elevational gradients did not reflect isolated changes in individual traits but rather arose from integrated adjustments of photosynthetic capacity, resource allocation, and metabolic coupling, thereby optimising the balance between light capture, water usage, and stress tolerance. These results, therefore, offer insights into adaptive strategies under climate change. Full article

Canephora coffee genotypes developed in other growing regions, with traits of interest such as drought tolerance and high coffee bean yield, need to be introduced and characterized in other locations to check adaptability. The aim of this study was to check the agronomic performance and determine the genetic parameters of the clonal canephora coffee cultivar Marilândia ES 8143, composed by twelve genotypes, developed by the Capixaba Institute of Research, Technical Assistance and Rural Extension (Instituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural—Incaper), in an irrigated system of the Central Cerrado region of Brazil. The study was conducted in the experimental areas of Embrapa Cerrados at 1050 m altitude in a center pivot irrigation system using a management system with water stress controlled for around 65 days. A randomized block experimental design was used with three replications, and each plot consisted of eight plants. The clones were planted in February 2019 and in 2021 and 2022. Phenotyping was carried out to evaluate the following traits: coffee bean yields, sieve retention percentages, plant height, canopy projection, number of pairs of plagiotropic branches, and frost damage using a scoring scale. Clone 5 stood out in mean value in the two years evaluated for bean yield. Clones 5, 6, 7, 8, and 9 had higher mean values for flat-type coffee beans in both years. Clones 1 and 5 exhibited mean values indicating good vegetative development. Clones 5 and 12 showed no visible symptoms for low air temperatures and frost effects. Highly significant differences were observed among the genotypes for all the morphoagronomic traits evaluated, and high values of heritability, genetic coefficients of variation, and selective accuracy showed conditions favorable to the selection of clones for the agronomic traits analyzed. Clones 1, 2 and 6 have values in lower groups for chlorogenic acids and caffeine, and in higher groups for protein and soluble solids, thus showing greater potential for obtaining quality beverages. Full article

Although rhizobacteria are known to improve plant adaptation to abiotic stressors, their possible contribution to the inherent resilience exhibited by crops such as Sorghum bicolor is still poorly quantified. Here, three sorghum pre-release lines and three check varieties were established and evaluated at two low-altitude sites of less than 600 masl. Treatments were laid out in a randomized complete block design, replicated two times. Twenty-four rhizospheric soil samples comprising six sorghum genotypes with two replications across two sites were collected, processed using Zymo Research DNA extraction protocols, and the 16S rRNA amplicon sequences were generated for bacterial diversity quantifications following the Divisive Amplicon Denoising Algorithm 2 (DADA2) workflow. Grain yield data were also recorded and expressed in tonnes per hectare. Rhizobacteria recruitment and GY performance significantly (p < 0.05) varied with sorghum genotypes. Bacterial abundance significantly (p < 0.05) associated with sorghum grain yield performance with Actinobacteriota and Firmicutes being identified to be of economic importance, explaining between 52.23 and 85.64% of the variation in grain yield performance. The modelled relationships between rhizobacteria and grain yield performance revealed R² predicted values of up to 75.25% and a 10-fold R² of 75.54%, implying no model overfitting. Sorghum genotypes did not consistently exhibit direct variation between genetic worth values and grain yield performance. Superior grain yield performers, namely ICSV111IN, CHITICHI, and SV4, consistently associated with high incidences of occurrence of the bacteria phyla Chloroflexi (class = Chloroflexia) and Firmicutes (class = Bacilli), whilst integrating the conventional selection method with microbial diversity data, changed the genotype performance ranking, in which all the three pre-release lines, namely, IESV91070DL, ASARECA12-3-1, and ICSV111IN, exhibited superiority over the check varieties. The results demonstrated that the inherent stress resilience exhibited by some sorghum genotypes under climate change-induced stresses such as CDHS may be influenced by specific bacterial taxa recruited in the rhizosphere environment of the plants. Hence, more effort should be made to further exploit these beneficial plant–microbe interactions for enhanced sorghum productivity under abiotic stress conditions. Full article

Air density and pressure above the Earth’s surface in the tropospheric region depend on altitude relative to sea level. When a given amount of pollutant gas enters the atmosphere at sea level, it produces a contaminated air mixture; if the same amount of pollutant gas enters the atmosphere at a location situated at higher altitude, atmospheric pollution certainly also occurs. However, the relative compositions are not the same in both cases due to the greater air density present at sea level compared to the air density at higher altitude. Current regulatory frameworks, including the National Ambient Air Quality Standards (NAAQS) of the United States Environmental Protection Agency and the Air Quality Guidelines (AQG) of the World Health Organization, establish constant numerical values for air quality standards uniformly applicable at all geographic locations, regardless of altitude, resulting in inadequate health protection for millions of people. To address this critical gap, a universal adjustment factor for atmospheric pollutant gas concentrations at different altitudes has been derived from first principles of atmospheric physics; this factor is $f=e^{-0.000115 h}$, where h is expressed in meters, assuming air at constant temperature given that small temperature variations do not substantially influence atmospheric density and pressure or pollutant concentrations at different altitudes. The factor was systematically applied to the NAAQS and WHO AQG, demonstrating that for altitudes of 3500 m, representative of cities such as Cusco, Peru, the adjusted standards are approximately 67% of the nominal values established at sea level, preserving the gaseous pollutant–air proportionality. Experimental measurements of atmospheric density in six Peruvian cities distributed along an altitudinal gradient of 0–3826 m validated the theoretical model with relative deviations less than 5%, confirming the physical consistency of the derived factor. The importance of this research lies in adequately regulating air quality standards related to public health and the environment, supporting the implementation of equitable environmental policies aligned with the United Nations (UN) 2030 Sustainable Development Goals, and establishing that the constant values defined at sea level must be adjusted according to the aforementioned factor when geographic altitude is considered. Full article

The pomegranate cultivar Barski slatki, the most widely cultivated on the Eastern Adriatic coast, was evaluated over one growing season across four growing areas to assess its pomological and chemical properties and antioxidant activity. Results showed that location significantly influenced fruit weight, volume, number of arils per fruit, and both total and individual aril weight, with the Kaštela (CRO) site producing the largest fruits and highest aril yields. Climatic factors, such as precipitation during bud differentiation, flowering, and early fruit development, were found to impact fruit set, aril number, and fruit size. Aril and juice yields, however, remained relatively stable across sites. Notable differences were observed in total soluble solids, titratable acidity, pH, total phenolic content, and anthocyanin profiles. Location with higher rainfall occurring during fruit growth favored enhanced phenolic accumulation. Although total anthocyanin content remained consistent among locations, significant variation occurred in aril coloration and composition of individual anthocyanins. In conclusion, microclimatic factors, particularly rainfall distribution, temperature, and altitude, play a decisive role in shaping the physical, chemical, and visual attributes of ‘Barski slatki’. Despite being cultivated under similar Mediterranean conditions, the observed differences across sites highlight the strong adaptability of this cultivar to diverse agroecological environments, while maintaining stable quality. Full article

This paper introduces a new approach to obtain robust tracking performance, disturbance resistance, and input variation resistance, and eliminate chattering phenomena in the control signal and output responses of an unmanned aerial vehicle (UAV) quadcopter with parametric uncertainty. This method involves a modified exponential reaching law (ERL) of the sliding mode control (SMC) based on a Gaussian kernel function with a continuous nonlinear Smoother Signum Function (SSF). The smooth continuous signum function is proposed as a substitute for the signum function to prevent the chattering effect caused by the switching sliding surface. The closed-loop system’s stability is ensured according to Lyapunov’s stability theory. Optimal trajectory tracking is attained based on particle swarm optimization (PSO) to select the controller parameters. A comparative analysis with a classical hierarchical SMC based on different ERLs (sign function, saturation function, and SSF) is presented to further substantiate the superior performance of the proposed controller. The outcomes of the simulation prove that the suggested controller has much better effectiveness, unknown disturbance resistance, input variation resistance, and parametric uncertainty than the other controllers, which produce chattering and make the control signal range fall within unrealistic values. Furthermore, the suggested controller outperforms the classical SMC by reducing the tracking integral mean squared errors by 96.154% for roll, 98.535% for pitch, 44.81% for yaw, and 22.8% for altitude under normal flight conditions. It also reduces the tracking mean squared errors by 99.05% for roll, 99.26% for pitch, 40.18% for yaw, and 99.998% for altitude under trajectory tracking flight conditions in the presence of external disturbances. Therefore, the proposed controller can efficiently follow paths in the presence of parameter uncertainties, input variation, and external disturbances. Full article

Identifying the primary soil parameters, weather variables and crop management practices that influence spatial variations in crop water use is essential for strategically defining optimal agricultural management practices. In this study, soil physico-chemical, weather and crop management variables were used through random forest (RF)-based modeling to evaluate the determinants of actual evapotranspiration (ETa) in winter wheat across Slovakia. ETa was estimated using Landsat imagery and the Python implementation of the Surface Energy Balance Algorithm for Land (PySEBAL), along with information from the Land Use/Cover Area frame Survey (LUCAS) over four cropping seasons. Overall, good agreements were found between PySEBAL-derived ETa and measured values, with RMSE and R² values of 0.93 mm and 0.87, respectively. Seasonal ETa values ranged from 434.87 mm to 506.12 mm, with the highest and lowest average values found in the 2011/2012 and 2017/2018 cropping seasons, respectively. The RF model showed good performance in predicting seasonal ETa, with an RMSE of 21 mm/season for the training data and 32 mm/season for the validation data, and R² values of 0.90 and 0.72, respectively. Our analysis indicated that ETa was primarily influenced by relative humidity, wind speed, solar radiation, altitude, and pH. The study further indicated that wheat production was unsuitable above 600 m elevation, while optimal crop water use occurred below 200 m. Addressing issues such as soil erosion and acidification could improve wheat crop water use efficiency across Slovakia. This modeling approach can serve as a basis to develop a crop water use forecasting system for sustainable wheat production in the region. Full article

The safe operation of low-altitude UAVs is crucial for the effective utilization of low-altitude airspace, necessitating the development of appropriate risk assessment methods to evaluate the associated operational risks. However, current research primarily focuses on two-dimensional risk assessments, with limited focus on assessing risks across different heights, thus constraining the ability to guide UAV operations within three-dimensional airspace. In this study, we propose a three-dimensional airspace risk assessment method that integrates multisource data to estimate risks at various altitudes. First, we assess ground impact risks by considering factors such as population density, obstacle environment, and socioeconomic characteristics. Next, we develop a network signal evaluation model to estimate signal loss at various altitudes. Finally, we apply machine learning methods to classify multiple features to determine airspace risks at varying altitudes, resulting in a comprehensive three-dimensional risk map. The results indicate that the majority of the urban area falls within the low-risk category, accounting for approximately 84–87% of the city. High-risk regions are concentrated in central urban areas, with their proportion increasing from 5.9% at 30 m to 9.1% at 300 m. Although the overall trend remains broadly consistent across altitudes, the local variations highlight the necessity of three-dimensional risk evaluation. This three-dimensional risk map can effectively guide safe UAV operations across different altitude layers and provide valuable decision support for flight route planning. Full article

This paper addresses the issue of existing research that fails adequately capture the spatiotemporal nonstationarity caused by the building of occlusion and flight dynamics in air-to-ground channels from unmanned aerial vehicles (UAVs) in urban scenarios. This study focuses on the angular-altitude correlations of three key metrics: path loss (PL), shadow fading, and the Ricean K-factor. A dynamic path-loss model incorporating the look-down angle is proposed, an exponential decay model for the shadow-fading standard deviation is constructed, and a model for the angle-dependent variation of the Ricean K-factor is established based on line-of-sight probability. Simulations were conducted in two urban-geometry scenarios using WinProp to evaluate the combined effects of flight altitude and elevation angle. The results indicate that path loss decreases and subsequently stabilizes with increasing elevation angle, the shadow-fading standard deviation decreases significantly, and the Ricean K-factor increases with angle and saturates at high angles, in agreement with theoretical predictions. These models are more adaptable to UAV mobility scenarios than traditional fixed exponential models and provide a useful basis for UAV link planning and system optimization in urban environments. Full article

Acoustic fingerprints can be used for device-to-device authentication due to manufacturing-induced variations in microphones and speakers. However, previous works have focused mostly on recognizing single devices from a set of multiple devices, which may not be sufficiently realistic since in practice, a single device has to be recognized from a very large pool of devices that are not available for training machine learning classifiers. Therefore, in this work, we focus on one-class classification algorithms, namely one-class Support Vector Machine and the local outlier factor. As such, learning the fingerprint of a single device is sufficient to recognize the legitimate device and reject all other attempts to impersonate it. The proposed application can also rely on cloud-based deployment to free the smartphone from intensive computational tasks or data storage. For the experimental part, we rely both on smartphones and an automotive-grade Android headunit, exploring in-vehicle environments as the main area of application. We create a dataset consisting of more than 5000 measurements and achieve a recognition rate ranging from 50% to 100% for different devices under various environmental conditions such as distance, altitude, and component aging. These conditions also serve as our limitations, however, we propose different solutions for overcoming them, which are part of our threat model. Full article