Search Results (1,884)

Protected crops are intensive production systems characterized by high vegetation density, high temperatures, and high moisture, making them favorable environments for the development of pests and diseases. Consequently, these systems often require several interventions with agrochemicals to maintain profitable yields and high produce quality. However, the application of plant protection products (PPPs) in such systems is not efficient and poses environmental concerns. This study aims at analysing spray behaviour, particularly in terms of foliar deposition and losses to the ground according to spraying equipment and foliage height, focusing on a specifically designed and developed system for agrochemical application in protected crops, and comparing it with a commonly used spraying system, namely, the cannon sprayer. Such a system consists in a fixed net of tubing and anti-drip nozzles positioned at the top of the greenhouse’s apex, connected to a pneumatic sprayer ‘Special Serre 2000’ outside the greenhouse. Findings revealed a significant effect of the spraying system (Kruskal–Wallis χ² = 12.239, df = 1, and p-value = 0.0004681) on normalized foliar deposition, with higher values obtained using the fixed spraying system. In addition, a simulation of the spatial distribution based on the principle of inverse distance weighting (IDW) was performed for qualitative spray assessment, confirming the heterogeneity of foliar deposition over the greenhouse with both of the used equipment. In addition, losses to the ground were affected by both spraying equipment and captor position. Full article

Built indoor IoT-based urban farms successfully combine the cultivation of fresh vegetables with attractive architectural designs. Moreover, implementing IoT-driven urban agriculture requires installing multiple IoT devices containing sensors, controllers, transceivers, and antennas for real-time data transmission. In this context, several factors, including the height of the IoT device above the soil level and the water content in the soil, can affect antenna performance and, consequently, the propagation of radio waves. This paper presents the results from numerical and experimental studies that evaluate the impact of soil on the performance of a monopole antenna for three different antenna positions relative to the soil in a pot and two soil water contents, presented by twelve scenarios. The results show that the antenna has a stable performance in six of the twelve scenarios, with a minimal shift in the resonant frequency of 3% and a narrowing of the frequency bandwidth by 2% compared to the antenna in free space. In the worst-case scenario, the antennas demonstrate a reduction in radiation efficiency of 44%, with the frequency bandwidth narrowing by up to 14% for the antenna fabricated on a PLA substrate and up to 17% for the one built on a foam board substrate. Full article

Orchards are complex agricultural systems with various characteristics that influence crop evapotranspiration (ET_c), such as variety, tree height, planting density, irrigation methods, and inter-row management. The preservation of biodiversity and improvement of soil fertility have become important goals in modern orchard management. Consequently, the traditional approach to weed control between rows, which relies on herbicides and soil mobilization, has gradually been replaced by the use of permanent living mulch (LM). This study explored the potential of a remote sensing (RS)-assisted method to monitor water use and water productivity in apple orchards with permanent mulch. The experimental data were obtained in the Lis Valley Irrigation District, on the Central Coast of Portugal, where the “Maçã de Alcobaça” (Alcobaça apple) is produced. The methodology was applied over three growing seasons (2019–2021), combining ground observations with RS tools, including drone flights and satellite images. The estimation of ET_a followed a modified version of the Food and Agriculture Organization of the United Nations (FAO) single crop coefficient approach, in which the crop coefficient (K_c) was derived from the normalized difference vegetation index (NDVI) calculated from satellite images and incorporated into a daily soil water balance. The average seasonal ET_a (FAO-56) was 824 ± 14 mm, and the water productivity (WP) was 3.99 ± 0.7 kg m⁻³. Good correlations were found between the K_c’s proposed by FAO and the NDVI evolution in the experimental plot, with an R² of 0.75 for the entire growing season. The results from the derived RS-assisted method were compared to the ET_a values obtained from the Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) surface energy balance model, showing a root mean square (RMSE) of ±0.3 mm day⁻¹ and a low bias of 0.6 mm day⁻¹. This study provided insights into mulch management, including cutting intensity, and its role in maintaining the health of the main crop. RS data can be used in this management to adjust cutting schedules, determine K_c, and monitor canopy management practices such as pruning, health monitoring, and irrigation warnings. Full article

Surface properties in complex urban environments can significantly impact local-level temperature gradients and distribution on several scales. Studying temperature anomalies and identifying heat pockets in urban settings is challenging. Limited high-resolution datasets are available that do not translate into an accurate assessment of near-surface temperature. This study developed a model to predict land surface temperature (LST) at a high spatial–temporal resolution in urban areas using Landsat data and meteorological inputs from NLDAS. This study developed an urban microclimate (UC) model to predict air temperature at high spatial–temporal resolution for inner urban areas through a land surface and build-up scheme. The innovative aspect of the model is the inclusion of micro-features in land use characteristics, which incorporate surface types, urban vegetation, building density and heights, short wave radiation, and relative humidity. Statistical models, including the Generalized Additive Model (GAM) and spatial autoregression (SAR), were developed to predict land surface temperature (LST) based on surface characteristics and weather parameters. The model was applied to urban microclimates in densely populated regions, focusing on Manhattan and New York City. The results indicated that the SAR model performed better (R² = 0.85, RMSE = 0.736) in predicting micro-scale LST variations compared to the GAM (R² = 0.39, RMSE = 1.203) and validated the accuracy of the LST prediction model with R² ranging from 0.79 to 0.95. Full article

The genus Trichoderma is widely used in agriculture as a biological agent and biofertilizer, enhancing crop yield and quality. However, its use in hydroponic systems is limited. This study evaluated the potential of Trichoderma asperellum as a growth promoter for lettuce (Lactuca sativa L.) cv. Starfighter RZ in a floating-root hydroponic system (FHS). T. asperellum strains (TaMFP1 and TaMFP2) were isolated from soil and identified morphologically and molecularly. The experiment used a completely randomized design with the following four treatments (n = 4): root spraying with TaMFP1, TaMFP2, T. harzianum (Trichospore^®), and uninoculated plants (control). After 30 days, morphological, biochemical, and quality parameters were analyzed. All Trichoderma treatments significantly increased plant height (19.0%), root length (25.7%), total fresh biomass (76.4%), total dry biomass (82.63%), and number of leaves (18.18%). The nitrate levels in leaves were unaffected by TaMFP1 and TaMFP2, while Trichospore^® reduced the nitrate content by 24.94%. The foliar nitrogen content increased with specific treatments, though the phosphorus and magnesium levels decreased. Visual quality traits, including appearance and firmness, remained unchanged. T. asperellum strains TaMFP1 and TaMFP2 enhanced vegetative growth without compromising quality, demonstrating their potential as sustainable tools for hydroponic lettuce production in controlled environments. Full article

Estimating aboveground biomass (AGB) is vital for sustainable forest management and helps to understand the contributions of forests to carbon storage and emission goals. In this study, the effectiveness of plot-level AGB estimation using height and crown diameter derived from UAV-LiDAR, calibration of GEDI-L4A AGB and GEDI-L2A rh98 heights, and spectral variables derived from UAV-multispectral and RGB data were assessed. These calibrated AGB and height values and UAV-derived spectral variables were used to fit AGB estimations using a random forest (RF) regression model in Fuling District, China. Using Pearson correlation analysis, we identified 10 of the most important predictor variables in the AGB prediction model, including calibrated GEDI AGB and height, Visible Atmospherically Resistant Index green (VARIg), Red Blue Ratio Index (RBRI), Difference Vegetation Index (DVI), canopy cover (CC), Atmospherically Resistant Vegetation Index (ARVI), Red-Edge Normalized Difference Vegetation Index (NDVIre), Color Index of Vegetation (CIVI), elevation, and slope. The results showed that, in general, the second model based on calibrated AGB and height, Sentinel-2 indices, slope and elevation, and spectral variables from UAV-multispectral and RGB datasets with evaluation metric (for training: R² = 0.941 Mg/ha, RMSE = 13.514 Mg/ha, MAE = 8.136 Mg/ha) performed better than the first model with AGB prediction. The result was between 23.45 Mg/ha and 301.81 Mg/ha, and the standard error was between 0.14 Mg/ha and 10.18 Mg/ha. This hybrid approach significantly improves AGB prediction accuracy and addresses uncertainties in AGB prediction modeling. The findings provide a robust framework for enhancing forest carbon stock assessment and contribute to global-scale AGB monitoring, advancing methodologies for sustainable forest management and ecological research. Full article

As a result of the energy crisis due, among other things, to climate change, most developed countries have taken steps with the main aim—among other things—of increasing the use of green energy sources that do not rely on fuels (including primarily liquid fuels) but use renewable energies. Plant biomass is a versatile substrate that can be used in many areas of the economy and production, but also for the production of various types of fuel. These range from rapeseed oil used as a component of biodiesel or maize starch for ethanol production to typically cellulosic plants such as energy willow, which can be used for direct combustion. The floodplain is home to this type of vegetation. It is characterized by great diversity in terms of geometric dimensions and mechanical and morphological properties. In addition, the location (easy access to water and sunlight) influences its potential energy value. Vegetation, thanks to favorable conditions, can achieve large weight gains in a relatively short period of time. Therefore, its properties should be carefully recognized in order to make more efficient use of energy and operating equipment used during harvesting. This paper presents an analysis of the changes in the elasticity of willow branches over a period of 16 days following harvesting. The changes were analyzed for branches taken from three different shrubs at three different plant height levels during the post-growth period. Based on the measurements carried out, the elastic modulus E of the shoots was estimated. The average modulus of elasticity ranged from about 4500 two days after cutting to about 5500 MPa 16 days after cutting and showed high variability, reaching even CV = 37%, both within a given shrub and depending on the measurement date. The results presented here indicate a high natural variability of mechanical parameters even within the same plant. Full article

Mulching is a widely adopted practice in vegetable cultivation globally. This technique employs various plastic materials, such as polyethylene (PE) film or polypropylene (PP) nonwoven fabric, with an increasing trend toward the use of biodegradable materials. Between 2014 and 2016, field experiments were conducted to evaluate the performance of the small-fruited tomato Intrigo F1 cultivated using synthetic mulches. The trials, designed as single-factor experiments employing a randomized block layout with three replicates, assessed plant morphological traits, yield, and the biological value of the tomato fruits. Weather conditions and the type of mulch applied had a pronounced influence on the quality of tomato plants and yield. Compared to the control, the use of black, red, and aluminum PE films and brown PP resulted in a 7.2% increase in plant height. All mulching treatments, except white film, increased the lateral spread of the plants by an average of 24.2%. Plants cultivated on red PE film exhibited a 26.4% increase in leaf count with respect to the control. Mulched treatments achieved an average increase of 19.6% in marketable yield. The highest marketable fruit yield was recorded with black nonwoven fabric mulch. Mulching had a significant effect on the chemical composition of tomato fruits. Fruits on biodegradable foil had the most potassium, lycopene, and polyphenols. Full article

Biomass is a vital index used to evaluate the vegetation rebuilding effect of mining slopes after restoration. It is essential to establish models for estimating the biomass and carbon storage of the vegetation community on mining slopes. Therefore, this paper establishes models for the biomass and carbon storage of such vegetation, taking an abandoned quarry after ecological restoration in Yixing City, Jiangsu Province, as the research object. Firstly, the variables of the biomass estimation models were determined based on the correlation analysis results; the vegetation biomass model was comprehensively selected, and the accuracy of the optimal models was verified. Meanwhile, the carbon storage calculation model was established in combination with the carbon content and the growth pattern of vegetation. The results showed that (1) the optimal models were the cubic and linear functions, respectively, for the shrubs and herbs, while the relevant variables of the shrub and the herb plants were the average height multiplied by the diameter of each shrub plant (DH) and the average height multiplied by the coverage rate (CH), respectively, with the verification results of R² > 0.814, R_S > 2.8%, and R_MA > 6%; and (2) in the restored mining slopes, the vegetation biomass was 120.264 t, including 10.586 t of herbs and 109.678 t of shrubs, and the vegetation carbon storage was 50.585 t, including 3.705 t of herbs and 46.880 t of shrubs. The proposed models have good prediction accuracy and reliability after quantitative evaluation and can be applied to the biomass estimation and carbon storage calculation of restored mining slopes, providing a reference for the environmental sustainability of post-mining areas and other ecologically restored slopes. Full article

Non-thermal plasma technology (NTP) has found widespread applications across several fields, including agriculture. Researchers have explored the use of NTP to improve plant growth and increase agricultural product quality using plasma-activated water (PAW). This technology has shown potential benefits in boosting seed germination, promoting plant growth, as an effective defense against plant pathogens, and increasing systemic plant resistance. An experiment was set up over three different cultivation cycles to investigate the benefits of PAW administration on nursery production. Plasma-activated water was generated using two NTP intensities (PAW-HI = 600 mV; PAW-LI = 450 mV; CTR = tap water control) and manually applied to plants under greenhouse conditions. The species considered in the current study were tomato (Solanum lycopersicum L.), Swiss chard (Beta vulgaris L.), cabbage (Brassica oleracea L.), basil (Ocimum basilicum L.), and lettuce (Lactuca sativa L. var. Longifolia). The following morphological traits were measured at the end of each cycle and for each species: plant height (PH, cm), collar diameter (CD, mm), biomass (g), nutritional status (SPAD index), dry matter (DM, %), and chemical composition. The sturdiness index (SI) was determined by the PH-to-CD ratio. Results indicated a species-specific response to both PAW treatments compared to CTR. The plant height significantly increased in tomato (+11.9%) and cabbage (+5%) under PAW-HI treatment. In contrast, PAW-HI treatment negatively affected the PH in lettuce and basil (−18% and −9%, respectively). Swiss chard showed no significant response to either PAW-LI or PAW-HI treatments. Regarding DM, no significant differences were observed between the PAW treatments and CTR. However, an increase in total N content was detected in plant tissues across all species, except for basil, where no change was observed. The results suggest that PAW treatment has the potential to enhance vegetable nursery production, with species-specific responses observed in crops. Full article

Microalgae offer a promising alternative for heavy metal removal, and the search for highly efficient strains is ongoing. This study investigated the potential of two microalgae, Coelastrella sp. BGV (Chlorophyta) and Arthronema africanum Schwabe & Simonsen (Cyanoprokaryota), to bind zinc ions (Zn²⁺) and protect higher plants. Hydroponically grown pea (Pisum sativum L.) seedlings were subjected to ZnSO₄ treatment for 7 days in either a nutrient medium (Knop) or a microalgal suspension. The effects of increasing Zn²⁺ concentrations were evaluated through solution parameters, microalgal dry weight, pea growth (height, biomass), and physiological parameters, including leaf gas exchange, chlorophyll content, and normalized difference vegetation index (NDVI). Zinc accumulation in microalgal and plant biomass was also analyzed. The results revealed that microalgae increased pH and oxygen levels in the hydroponic medium while enhancing Zn accumulation in pea roots. At low ZnSO₄ concentrations (2–5 mM), microalgal suspensions stimulated pea growth and photosynthetic performance. However, higher ZnSO₄ levels (10–15 mM) caused Zn accumulation, leading to nutrient deficiencies and growth suppression in microalgae, which ultimately led to physiological disturbances in peas. Coelastrella sp. BGV exhibited greater tolerance to Zn stress and provided a stronger protective effect when co-cultivated with peas, highlighting its potential for phycoremediation applications. Full article

Background/Objectives: This study aimed to investigate the lifestyle and the behavioral factors that influence the nutritional status of adolescents from Transylvania, Romania. Methods: The Global School-Based Student Health Survey (GSHS) was used to collect data from 900 adolescents between 11 and 18 years old from the Transylvania region, Romania. This study assessed nutritional status by calculating BMI indicators adjusted to Z-Score, cut-off points according to the World Health Organization (WHO), using self-reported weight and height; perceived health status; food vulnerability; physical activity; addictive behaviors (cigarette, alcohol and drug consumption); number of hours spent in front of the computer/phone; hand and oral hygiene; sitting time/day; and sleep. Multivariate logistic regression was used to establish the lifestyle factors that influenced nutritional status. Results: The results showed that 8.7% (n = 78) of girls and 15.2% (n = 137) boys were overweight and obese. In total, 75% of the respondents were engaged in sedentary behaviors, and 65.8% (n = 592) had more than 2 h/day of screen exposure, considering that 98.7% of the study population had a mobile phone. The Romanian adolescents had poor dietary behaviors: over 80% of them did not meet the recommended amount of vegetable and fruit intake per day. Increased BMI was associated with higher-strength physical exercise and with being a boy. Conclusions: While some positive trends are evident, such as good oral and hand hygiene and low prevalence of smoking and drug use, significant challenges remain in areas like nutrition, physical activity, alcohol consumption and screen time. Full article

This paper presents a method for the automatic detection and assessment of trees and tree-covered areas in Katowice, the capital of the Upper Silesian Industrial Region in southern Poland. The proposed approach utilizes satellite imagery and height maps, employing image-processing techniques and integrating data from various sources. We developed a data pipeline for gathering and pre-processing information, including vegetation data and numerical land-cover models, which were used to derive a new method for tree detection. Our findings confirm that automatic tree detection can significantly enhance the efficiency of urban tree management processes, contributing to the creation of greener and more resident-friendly cities. Full article

Forest canopy height (FCH) is a critical parameter for forest management and ecosystem modeling, but there is a lack of accurate FCH distribution in large areas. To address this issue, this study selected Wuyishan National Park in China as a case study to explore the calibration method for mapping FCH in a complex subtropical mountainous region based on ZiYuan-3 (ZY3) stereo imagery and limited Unmanned Aerial Vehicle (UAV) LiDAR data. Pearson’s correlation analysis, Categorical Boosting (CatBoost) feature importance analysis, and causal effect analysis were used to examine major factors causing extraction errors of digital surface model (DSM) data from ZY3 stereo imagery. Different machine learning algorithms were compared and used to calibrate the DSM and FCH results. The results indicate that the DSM extraction accuracy based on ZY3 stereo imagery is primarily influenced by slope aspect, elevation, and vegetation characteristics. These influences were particularly notable in areas with a complex topography and dense vegetation coverage. A Bayesian-optimized CatBoost model with directly calibrating the original FCH (the difference between the DSM from ZY3 and high-precision digital elevation model (DEM) data) demonstrated the best prediction performance. This model produced the FCH map at a 4 m spatial resolution, the root mean square error (RMSE) was reduced from 6.47 m based on initial stereo imagery to 3.99 m after calibration, and the relative RMSE (rRMSE) was reduced from 36.52% to 22.53%. The study demonstrates the feasibility of using ZY3 imagery for regional forest canopy height mapping and confirms the superior performance of using the CatBoost algorithm in enhancing FCH calibration accuracy. These findings provide valuable insights into the multidimensional impacts of key environmental factors on FCH extraction, supporting precise forest monitoring and carbon stock assessment in complex terrains in subtropical regions. Full article

Urban expansion encroaches on green spaces and weakens ecosystem services, potentially leading to a trade-off between ecological conditions and socio-economic growth. Effectively coordinating the two elements is essential for achieving sustainable development goals at the urban scale. However, few studies have measured urban–ecological linkage in terms of trade-off. In this study, we propose a framework by linking the degraded ecological conditions and urban land use efficiency from a return on investment perspective. Taking a rapidly expanding city as a case study, we comprehensively quantified urban–ecological conditions in four aspects: urban heat island, flood regulating service, habitat quality, and carbon sequestration. These conditions were assessed on 1 km² grids, along with urban land use efficiency at the same spatial scale. We employed the slack-based measure model to evaluate trade-off efficiency and applied the geo-detector method to identify its driving factors. Our findings reveal that while urban–ecological conditions in Zhengzhou’s periphery degraded over the past two decades, the inner city showed improvement in urban heat island and carbon sequestration. Trade-off efficiency exhibited an overall upward trend during 2000–2020, despite initial declines in some inner city areas. Interaction detection demonstrates significant synergistic effects between pairs of drivers, such as the Normalized Difference Vegetation Index and building height, and the number of patches of green spaces and the patch cohesion index of built-up land, with q-values of 0.298 and 0.137, respectively. In light of the spatiotemporal trend of trade-off efficiency and its drivers, we propose adaptive management strategies. The framework could serve as guidance to assist decision-makers and urban planners in monitoring urban–ecological conditions in the context of urban expansion. Full article