Search Results (4,385)

Accurate soil moisture estimation is critical for precision agriculture and water resource management, yet traditional sampling methods are time-consuming, destructive, and provide limited spatial coverage. Ground Penetrating Radar (GPR) offers a promising non-destructive alternative, but optimal machine learning approaches for GPR-based soil moisture prediction remain unclear. This study presents a comparative analysis of regression tree and boosted tree algorithms for predicting soil moisture content from Ground Penetrating Radar (GPR) histogram features across 21 sites in Eastern Thailand. Soil moisture content was measured at multiple depths (0.5, 1.0, 1.5, 2.0, 2.5, and 3.0 m) using samples collected during Standard Penetration Test procedures. Feature extraction was performed using 16-bin histograms from processed GPR radargrams. A single regression tree achieved a cross-validation RMSE of 5.082 and an R² of 0.761, demonstrating superior training accuracy and interpretability. In contrast, the boosted tree ensemble achieved significantly better generalization performance, with a cross-validation RMSE of 4.7915 and an R² of 0.708, representing a 5.7% improvement in predictive performance. Feature importance analysis revealed that specific histogram bins effectively captured moisture-related variations in GPR signal amplitude distributions. A comparative evaluation demonstrates that while single regression trees offer superior interpretability for research applications, boosted tree ensembles provide enhanced predictive performance that is essential for operational deployment in precision agriculture and hydrological monitoring systems. Full article

Water quality deterioration poses a critical threat to ecological security and sustainable development, particularly in rapidly urbanizing regions. To enable proactive environmental management, this study develops a novel hybrid deep learning model, the NGO-CNN-GRU, for high-precision time-series water quality prediction in the Xijiang River Basin, China. The model integrates a Convolutional Neural Network (CNN) for spatial feature extraction and a Gated Recurrent Unit (GRU) for temporal dependency modeling, with hyperparameters optimized via the Northern Goshawk Optimization (NGO) algorithm. Using historical water quality (pH, DO, CODMn, NH3-N, TP, TN) and meteorological data (precipitation, temperature, humidity) from 11 monitoring stations, the model achieved exceptional performance: test set R² > 0.986, MAE < 0.015, and RMSE < 0.018 for total nitrogen prediction (Xiaodong Station case study). Across all stations and indicators, it consistently outperformed baseline models (GRU, CNN-GRU), with average R² improvements of 12.3% and RMSE reductions up to 90% for NH3-N predictions. Spatiotemporal analysis further revealed significant pollution gradients correlated with anthropogenic activities in the Pearl River Delta. This work provides a robust tool for real-time water quality early warning systems and supports evidence-based river basin management. Full article

The global transition toward plant-based diets has intensified the search for sustainable protein alternatives, positioning hemp-based meat analogs (HBMAs) as a promising solution due to their exceptional nutritional profile and environmental benefits. This comprehensive review critically examines hemp protein research, focusing on extraction technologies, nutritional excellence, functional innovation, and sustainable processing approaches for meat analog development. Hemp seeds contain 25–30% protein, primarily consisting of highly digestible edestin and albumin proteins that provide a complete amino acid profile comparable to soy and animal proteins. The protein exhibits superior digestibility (>88%) and generates bioactive peptides with demonstrated antioxidant, antihypertensive, and anti-inflammatory properties, offering significant health benefits beyond basic nutrition. Comparative analysis reveals that while alkaline extraction-isoelectric precipitation remains the industrial standard due to cost-effectiveness ($2.50–3.20 kg⁻¹), enzymatic extraction and ultrasound-assisted methods deliver superior functional properties despite higher costs. Hemp protein demonstrates moderate solubility and good emulsifying properties, though its gelation capacity requires optimization through enzymatic hydrolysis, high-pressure processing, or strategic blending with complementary proteins. Processing innovations, particularly high-moisture extrusion combined with protein blending strategies, enable fibrous structures closely mimicking conventional meat texture. Hemp protein can replace up to 60% of soy protein in high-moisture meat analogs, with formulations incorporating wheat gluten or chickpea protein showing superior textural attributes. Despite advantages in nutritional density, sustainability, and functional versatility, HBMAs face challenges including sensory limitations, regulatory barriers, and production scaling requirements. Hemp cultivation demonstrates 40–50% lower carbon footprint and water usage compared with conventional protein sources. Future research directions emphasize techniques and action processes, developing novel protein modification techniques, and addressing consumer acceptance through improved sensory properties for successful market adoption. Full article

Defatting methods are key to modulating the nutritional, functional, and bioactive characteristics of edible insect powders. This study evaluated the effects of mechanical pressing and ethanol-based solvent extraction on Hermetia illucens larvae powder. Solvent-defatted samples (DPSs) showed the highest protein content (54.96 g/100 g), with a 61% increase compared to full-fat powder (FP), and the lowest residual lipid content (3.18 g/100 g). In contrast, mechanical pressing (DPP) preserved higher antioxidant activity (68.30% DPPH inhibition), a 30% increase over FP. DPS also showed greater fiber content (13.90 g/100 g), improved water solubility, emulsification capacity, and reduced water activity (0.269), desirable traits for food formulations. DPP retained higher hygroscopicity and exhibited the highest antioxidant potential among the samples. These findings demonstrate that defatting method selection significantly impacts the techno-functional and nutritional quality of insect powders and should align with the desired end use, whether for protein enrichment, enhanced antioxidant activity, or development of sustainable food ingredients. This work supports the strategic use of Hermetia illucens as a functional, high-protein ingredient and reinforces its role in advancing circular and sustainable food systems. Full article

Bambara groundnut (Vigna subterranea), a vital yet underutilized African legume, significantly boosts food security due to its nutritional value and adaptability to harsh climates and soils. However, its processing yields substantial waste like husks, shells, and haulms, which are often carelessly discarded, causing environmental damage. This paper highlights the urgent need to valorize these waste streams to unlock sustainable growth and economic development. Given their lignocellulosic composition, Bambara groundnut residues are ideal for generating biogas and bioethanol. Beyond energy, these wastes can be transformed into various bio-based products, including adsorbents for heavy metal removal, activated carbon for water purification, and bioplastics. Their inherent nutritional content also allows for the extraction of valuable components like dietary fiber, protein concentrates, and phenolic compounds for food products or animal feed. The nutrient-rich organic matter can also be composted into fertilizer, improving soil fertility. These valorization strategies offer multiple benefits, such as reduced waste, less environmental contamination, and lower greenhouse gas emissions, alongside new revenue streams for agricultural producers. This integrated approach aligns perfectly with circular economy principles, promoting resource efficiency and maximizing agricultural utility. Despite challenges like anti-nutritional factors and processing costs, strategic investments in technology, infrastructure, and supportive policies can unlock Bambara groundnut’s potential for sustainable innovation, job creation, and enhanced food system resilience across Africa and globally. Ultimately, valorizing Bambara groundnut waste presents a transformative opportunity for sustainable growth and improved food systems, particularly within African agriculture. Full article

Mango (Mangifera indica L.) is cultivated in tropical and subtropical regions, with all parts of the tree—including leaves—used traditionally to treat diabetes, infections, pain, and other conditions. Mango leaves contain proteins, minerals, vitamins, and phenolic compounds, including mangiferin, quercetin, and kaempferol, whose content varies by cultivar. This study evaluated the functional and bioactive properties of dried mango leaves from five cultivars (Julie, DLO, Nam Dok Mai, Irwin, and Keïtt) to determine their potential for food and nutraceutical applications. Analyses included water- and oil-related parameters, swelling and solubility indices, foaming and emulsifying properties, and antioxidant activity (DPPH, ABTS, and FRAP in hydroalcoholic and water extracts), complemented by FT-IR/ATR spectroscopy. Significant differences between the five analyzed cultivars were observed. Irwin exhibited the highest antioxidant activity (2.65 ± 0.55 mg TE/g DM in DPPH assay), while Nam Dok Mai demonstrated superior foaming capacity (82.69 ± 7.79 mL). Strong correlations (r > 0.9) between reducing sugars and antioxidant capacity suggest cultivar selection based on sugar content could predict antioxidant potential. FT-IR confirmed the presence of polar phenolic and protein compounds. The results demonstrate that mango leaves offer cultivar-dependent functional and antioxidant attributes relevant to food systems. Their targeted valorization may support sustainable industrial applications and circular bioeconomy strategies, particularly in tropical regions where mango cultivation is widespread. Full article

Traditional unmanned aerial vehicle (UAV) path planning methods for image-based 3D reconstruction often rely solely on geometric information from initial models, resulting in redundant data acquisition in non-architectural areas. This paper proposes a UAV path planning method via semantic segmentation of 3D reality mesh models to enhance efficiency and accuracy in complex scenarios. The scene is segmented into buildings, vegetation, ground, and water bodies. Lightweight polygonal surfaces are extracted for buildings, while planar segments in non-building regions are fitted and projected into simplified polygonal patches. These photography targets are further decomposed into point, line, and surface primitives. A multi-resolution image acquisition strategy is adopted, featuring high-resolution coverage for buildings and rapid scanning for non-building areas. To ensure flight safety, a Digital Surface Model (DSM)-based shell model is utilized for obstacle avoidance, and sky-view-based Real-Time Kinematic (RTK) signal evaluation is applied to guide viewpoint optimization. Finally, a complete weighted graph is constructed, and ant colony optimization is employed to generate a low-energy-cost flight path. Experimental results demonstrate that, compared with traditional oblique photogrammetry, the proposed method achieves higher reconstruction quality. Compared with the commercial software Metashape, it reduces the number of images by 30.5% and energy consumption by 37.7%, while significantly improving reconstruction results in both architectural and non-architectural areas. Full article

Coal mining disturbance induces progressive damage and fracturing in overlying rock (OLR), forming a complex fracture network. This process triggers groundwater depletion, ecological degradation, and severely compromises mine safety. Based on field drilling sampling and mechanical experiments, this paper reveals the occurrence properties and characteristics of weakly cemented overlying rock (WCOLR). At the same time, similar simulation experiments, DIC speckle analysis system, and fractal theory are used to explain the development and evolution mechanism of mining-induced fractures under this special geological condition. The OLR fracture is determined based on the grid fractal dimension (D) distribution. A stress arch-bed separation (BS) co-evolution model is established based on dynamic cyclic BS development and stress arch characteristics, enabling identification of BS horizons. The results show that the overlying weak and extremely weak rock accounts for more than 90%. During the process of longwall face (LF) advancing, the D undergoes oscillatory evolution through five distinct stages: rapid initial growth, constrained slow growth under thick, soft strata (TSS), dimension reduction induced by fracturing and compaction of TSS, secondary growth from newly generated fractures, and stabilization upon reaching full extraction. Grid-based D analysis further categorizes fracture zones, indicating a water conducting fracture zone (WCFZ) height of 160~180 m. Mining-induced fractures predominantly concentrate at dip angles of 0–10°, 40–50°, and 170–180°. Horizontally BS fractures account for 70.2% of the total fracture population, vertically penetrating fractures constitute 13.1% and transitional fractures make up the remaining 16.7%. The stress arch height is 314.4 m, and the stable BS horizon is 260 m away from the coal seam. Finally, an elastic foundation theory-based model was used to predict BS development under top-coal caving operations. This research provides scientific foundations for damage-reduced mining in ecologically vulnerable Western China coalfields. Full article

In factory-controlled recirculating aquaculture systems, precise regulation of water velocity is crucial for optimizing shrimp feeding behavior and improving aquaculture efficiency. However, quantitative analysis of the impact of water velocity on shrimp behavior remains challenging. This study developed an innovative multi-objective behavioral analysis framework integrating detection, tracking, and behavioral interpretation. Specifically, the YOLOv8 model was employed for precise shrimp detection, ByteTrack with a dual-threshold matching strategy ensured continuous individual trajectory tracking in complex water environments, and Kalman filtering corrected coordinate offsets caused by water refraction. Under typical recirculating aquaculture system conditions, three water circulation rates (2.0, 5.0, and 10.0 cycles/day) were established to simulate varying flow velocities. High-frequency imaging (30 fps) was used to simultaneously record and analyze the movement trajectories of Litopenaeus vannamei during feeding and non-feeding periods, from which two-dimensional behavioral parameters—velocity and turning angle—were extracted. Key experimental results indicated that water circulation rates significantly affected shrimp movement velocity but had no significant effect on turning angle. Importantly, under only the moderate circulation rate (5.0 cycles/day), the average movement velocity during feeding was significantly lower than during non-feeding periods (p < 0.05). This finding reveals that moderate water velocity constitutes a critical hydrodynamic window for eliciting specific feeding behavior in shrimp. These results provide core parameters for an intelligent Litopenaeus vannamei feeding intensity assessment model based on spatiotemporal graph convolutional networks and offer theoretically valuable and practically applicable guidance for optimizing hydrodynamics and formulating precision feeding strategies in recirculating aquaculture systems. Full article

Resource-based cities, characterized by a prolonged dependence on resource extraction and persistent urban expansion, frequently exhibit significant imbalances between the supply and demand of ecosystem services (ESs). Understanding how various types of resource-based cities respond to urbanization in terms of ESs supply–demand relationships is crucial for advancing sustainable urban development. This study examines three representative resource-based cities in Sichuan Province—Nanchong (growing), Luzhou (declining), and Panzhihua (mature)—to analyze changes in six key ESs from 2000 to 2020, including soil retention, carbon sequestration, water yield, habitat quality, food production, and recreational services. Ordinary least squares (OLS) regression and random forest (RF) models were employed to evaluate the effects of gross domestic product (GDP) density, construction land proportion (CLP), and population (POP) density on the ecosystem service supply–demand ratio (ESDR), and to explore variations in sensitivity among these cities. The results demonstrate that (1) ESs’ supply–demand patterns differ significantly among the three city types. Nanchong exhibited a declining supply and increasing demand for regulating services; Luzhou displayed improvements in its water yield and recreational services but persistent degradation of habitat quality; and Panzhihua achieved notable gains in carbon sequestration and habitat quality. (2) Urbanization generally reduced the ESDR across all three cities. However, the GDP density positively influenced the ESDR in Nanchong, while the CLP and the POP density exerted widespread negative effects. In Luzhou, the ESDR was primarily constrained by the CLP, whereas in Panzhihua, both the CLP and the POP density significantly reduced the ratio. (3) The sensitivity analysis revealed distinct response patterns: Nanchong was most sensitive to CLP, Luzhou responded most strongly to GDP density, and Panzhihua was highly sensitive to both GDP density and POP density. These findings underscore the necessity of formulating city-type-specific development strategies—such as land restoration, population control, and industrial upgrading—tailored to different types of resource-based cities, in order to reconcile urbanization with ecosystem service dynamics, promote green transformation, and contribute to the achievement of the Sustainable Development Goals (SDGs). Full article

Walnut septa, traditionally discarded as waste in walnut processing because they primarily serve a structural function in the walnut fruit, have recently gained attention for their potential abundance of phenolic compounds, suggesting their overlooked value. This study aimed to optimise extraction parameters to maximise the extraction yield of bioactive compounds and explore regional variations in antioxidant activity and chemical composition of Juglans regia L. septa. The experimental variables included extraction methods (maceration, dynamic maceration, ultrasound processing, and reflux extraction), temperature, solvent type (methanol, acetone, and ethanol), and the percentage of water in the solvent. The optimal conditions were determined based on the total phenolic content—reflux extraction using 60% ethanol as a solvent for a duration of 60 min. Samples from 12 different regions in Lithuania, Armenia, and Ukraine were analysed for their phenolic and proanthocyanidin content and antioxidant activity using the CUPRAC method. The total phenolic content ranged from 131.55 to 530.92 mg of gallic acid equivalents per g of dry weight of plant material (mg GAE/g dw), while the proanthocyanidin content varied from 1.14 to 7.65 mg of (–)-epicatechin equivalents per g dry weight of plant material (mg EE/g dw). Among all the regions studied, the Šiauliai sample demonstrated the highest concentrations of phenolic compounds, proanthocyanidins, and antioxidant activity, with statistically significant differences compared to the other samples (p < 0.05). These findings demonstrate that walnut septa are a valuable source of phenolic compounds and antioxidants, with significant potential for developing natural nutraceuticals and antioxidant products. Full article

The present study investigates the antimicrobial, antioxidant, and in vitro antidiabetic potential of cold infusions prepared from different parts of the Greek carob tree (Ceratonia siliqua L.), which is a xerophytic species. Carob samples, including green and ripe pods and leaves, were collected from an urban area of Attica, Greece, and extracted using food-grade solvents (water and a water–ethanol mixture, 90:10, v/v). The extracts were evaluated for antibacterial activity against Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 6538 using automated turbidometry. In addition, total phenolic content and antioxidant and antiradical activities were determined via spectrophotometry; the phenolic profile was analyzed using liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (LC-QToF-MS), and α-amylase inhibitory activity was assessed through an in vitro assay. All extracts exhibited statistically significant (p < 0.05) bacteriostatic effects, with green pods and leaves showing the highest activity. Ripe pods demonstrated the most potent α-amylase inhibition (up to 96.43%), especially when extracted with water–ethanol mixture (90:10, v/v). Liquid chromatography coupled with tandem quadrupole/time-of-flight mass spectrometry (LC-QToF-MS) analysis revealed a rich phenolic profile across all samples. While carob leaves showed no α-amylase inhibition, their phenolic profile suggests other potential health-related bioactivities. These findings support the development of carob-based functional food products and highlight the nutritional and pharmaceutical potential of this resilient Mediterranean crop. Full article

Bioactive compounds (BCs) are naturally occurring molecules found in plants, fungi, and microorganisms that can provide health benefits beyond nutrition. However, in order to administer them, they must be extracted from these organisms. This study reviews the extraction of anti-inflammatory bioactive compounds using deep eutectic systems (DESs). It was found that DES extraction media can be categorized as either choline chloride-based or natural product-based (e.g., proline, betaine, and lactic acid). Results indicate that extraction yields depended on many factors such as extraction method and DES composition, with values ranging from 0.02 to 200 mg/g. For example, curcumin extraction using ChCl–propylene glycol (1:2), for example, reached 23.1 mg/g, whereas rutin extraction using ChCl–levulinic acid (1:2) achieved 200 mg/g. Regarding this, most of the eutectic mixtures used are choline chloride (ChCl)-based combined with sugars, polyalcohols, organic acids, or even water. Nonpolar DESs combining betaine, L-proline, amino acids, sugars, and organic acids have also been used for the extraction of BCs with anti-inflammatory potential. Although the use of DES offers significant advantages for extraction processes, certain limitations still need to be overcome. This review highlights the comparative advantages of DESs in terms of extraction efficiency and environmental sustainability, offering practical insights for selecting optimal systems to extract anti-inflammatory bioactive compounds. Full article

The ATL03 data from the photon-counting LiDAR onboard the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) holds substantial potential for shallow-water bathymetry due to its high sensitivity and broad spatial coverage. However, distinguishing signal photons from noise in low-photon-density and complex terrain environments remains a significant challenge. This study proposes an adaptive photon extraction algorithm based on linear feature analysis, incorporating resolution adjustment, segmented Gaussian fitting, and linear feature-based signal identification. To address the reduction in signal photon density with increasing water depth, the method employs a depth-dependent adaptive neighborhood search radius, which dynamically expands into deeper regions to ensure reliable local feature computation. Experiments using eight ICESat-2 datasets demonstrated that the proposed method achieves average precision and recall values of 0.977 and 0.958, respectively, with an F1 score of 0.967 and an overall accuracy of 0.972. The extracted bathymetric depths demonstrated strong agreement with the reference Continuously Updated Digital Elevation Model (CUDEM), achieving a coefficient of determination of 0.988 and a root mean square error of 0.829 m. Compared to conventional methods, the proposed approach significantly improves signal photon extraction accuracy, adaptability, and parameter stability, particularly in sparse photon and complex terrain scenarios. In comparison with the DBSCAN algorithm, the proposed method achieves a 30.0% increase in precision, 17.3% improvement in recall, 24.3% increase in F1 score, and 22.2% improvement in overall accuracy. These findings confirm the effectiveness and robustness of the proposed algorithm for ICESat-2 shallow-water bathymetry applications. Full article

Enzymatic browning is the negative color effect of polyphenol oxidase activity in cut fresh fruit products, which reduces their quality, shelf life, and marketability. To preserve the color after cutting, apple cubes were treated with aqueous cabbage seed extracts (ACEs) at 5–10% w:v seed–water ratios, adjusted to pH 4.0 and 6.0 and 1% chitosan added to the ACE before preservation at 7 °C for 0–10 days. Chromatometric readings (L*, a*, and b*) and visual color score were used for shelf life calculation. The ACE total phenolics and glucosinolate levels showed differences among the 5–10% and control groups. Based on color score, uncoated or coated (chitosan or ACE combined with chitosan) apple cubes reached marketing limit levels (score > 3/5) on day one, but apple cubes treated with 5 or 10% ACE alone did so on day four, which was considered the effective shelf life. These findings were further supported by FT-IR analysis. ACE modification to pH 6.0 was more effective at keeping the natural cut apple color than pH 4.0. ACE treatment (at 5 or 10%) without coating is regarded as a very promising natural agent for extending the shelf life of fresh-cut apples, which is a key attribute in their marketing. Full article