Search Results (25,857)

Urbanization imposes complex environmental gradients that threaten plant diversity and urban ecosystem integrity. Understanding the multifactorial drivers that govern species distribution in urban contexts is essential for biodiversity conservation and sustainable landscape planning. This study addresses this challenge by examining the environmental determinants of urban flora in a rapidly developing city. We integrated data from 397 floristic sampling sites and 13 environmental monitoring locations across Düzce, Türkiye. A multidimensional suite of environmental predictors—including microclimatic variables (soil temperature, moisture, light), edaphic properties (pH, EC (Electrical Conductivity), texture, carbonate content), precipitation chemistry (pH and major ions), macroclimatic parameters (CHELSA bioclimatic variables), and spatial metrics (elevation, proximity to urban and natural features)—was analyzed using nonlinear regression models and machine learning algorithms (RF (Random Forest), XGBoost, and SVR (Support Vector Regression)). Shannon diversity exhibited strong variation across land cover types, with the highest values in broad-leaved forests and pastures (>3.0) and lowest in construction and mining zones (<2.3). Species richness and evenness followed similar spatial trends. Evenness peaked in semi-natural habitats such as agricultural and riparian areas (~0.85). Random Forest outperformed other models in predictive accuracy. Elevation was the most influential predictor of Shannon diversity, while proximity to riparian zones best explained richness and evenness. Chloride concentrations in rainfall were also linked to species composition. When the models were recalibrated using only native species, they exhibited consistent patterns and maintained high predictive performance (Shannon R² ≈ 0.937474; Richness R² ≈ 0.855305; Evenness R² ≈ 0.631796). Full article

Schinus molle L. is a tree commonly found in agricultural fields, deserts, and semi-arid areas of central Mexico. Its distinctive aroma makes it a source of essential oil, extracted mainly from the bark and fruits. The leaves contain phenolic compounds, and their extracts have demonstrated antimicrobial activity. Obtaining these extracts requires a prior drying process. This study aimed to evaluate the effect of convective drying on phenolic compounds in pirul leaves and determine the thermodynamic properties of the process, including the effective diffusivity of water vapor (D) and activation energy (Ea). Drying kinetics were conducted at different air-drying temperatures (30, 40, and 50 °C) at a constant rate of 1 ms⁻¹, and the results were fitted to the second Fick’s law and semi-empirical models. After drying, a decrease in total flavonoid content was observed as the drying temperature increased, with losses of 37%, 49%, and 62% at 30, 40, and 50 °C, respectively. The final values ranged from 37.96 to 21.02 mg QE/100 g of dry leaf. The D varied between 1.32 × 10⁻¹² and 6.71 × 10⁻¹² m² s⁻¹, with an Ea of 66.06 kJ mol⁻¹. The fitting criteria (R², RMSE, AIC/BIC) indicated that the Logarithmic model best described the kinetics at 30–40 °C, while Page was adequate at 50 °C. These findings suggest an inverse relationship between drying temperature and flavonoid content, while higher temperatures accelerate water vapor diffusivity, reducing the processing time, as observed in plant matrices. Full article

The aim of the study is to investigate the influence of the physicochemical characteristics of the molecular and supramolecular structure of polymers on electroadhesive interactions and their change under the action of a constant electric field. Currently, this effect is modeled in electroadhesion studies, but the range of variable parameters is limited and includes permittivity, moisture content, and surface roughness. It is important to consider other physicochemical parameters, such as material crystallinity and surface characteristics, changes in which can affect the magnitude of electroadhesive forces. In this study, the electric field strength was varied by altering the constant voltage in the range of 3–8 kV. Polyethylene, ethylene-vinyl acetate copolymers, and polyvinyl acetate were used as substrates for adhesive systems. The influence of the concentration of vinyl acetate groups, which determine the energy characteristics of the surface, and the degree of crystallinity on electroadhesive interactions under conditions of an external constant electric field and without it was traced. The degree of crystallinity was varied both by the cooling rate and the orientation during drawing. It was shown that by changing the polar component of the surface energy and the proportion of the crystalline phase in the substrate, electroadhesive interactions can be increased by 4 times to 120 Pa compared to polyethylene. The obtained laws are explained by the local dipoles induced by polar functional groups, which enhance the polymer’s surface interactions with other materials and external fields. At the same time, the fixation of macromolecules in crystalline regions complicates polarization under the influence of an electric field. Full article

Modern agriculture is seeking methods that reduce pesticide use while simultaneously providing high-quality raw materials. The aim of this innovative study was to determine how treating potato planting tubers with ultrasound in an aqueous medium (pre-sowing treatment) affects the subsequent quality of the raw material and the final product. A three-year field experiment was conducted using a split-plot design with three replicates, comparing traditional technology with a technology using ultrasonic treatment of seed potatoes. Eight edible potato varieties were studied. Sonication significantly improved the processing quality of the tubers. Tubers from treated seed potatoes had significantly lower reducing sugar content (0.02 to 0.1%, depending on the variety). As a result, chips produced from sonicated tubers exhibited a lighter color, improved overall aesthetics and flavor, and reduced discoloration and moisture staining. The results obtained suggest that ultrasonic treatment of seed potatoes is a highly effective, non-thermal method for increasing the value of raw materials used in food processing. This is a promising, innovative technology with significant application potential, supporting sustainable agriculture by improving the quality of tubers and the finished product (chips) at the source. In the future, it will be necessary to optimize sonication parameters and evaluate the economic potential of this technology. Full article

Heracleum persicum Desf. ex Fischer, a species of the Apiaceae family, is endemic to Iran and has been historically utilized as a spice, condiment, and medicinal plant. The plant produces seeds that represent a potential new source of vegetable oil. In this study, the oil from these seeds was extracted using a solvent, and its physical, chemical, and nutritional properties were investigated. The oil extraction yield was determined to be 12.62%. Oleic acid (61.11%) and linoleic acid (25.84%) were identified as the predominant fatty acids in the extracted oil. Among its phytosterols, beta-sitosterol (65.6%) and stigmasterol (14.0%) were the most abundant. Furthermore, this oil exclusively contained alpha-tocopherol at a relatively high concentration (1610.9 ppm). The chlorophyll and carotenoid contents of the extracted oil were 28.34 mg/kg and 4.95 mg/kg, respectively. Regarding its nutritional indices, the atherogenic index, thrombogenic index, and hypocholesterolemic to hypercholesterolemic ratio were 0.13, 0.24, and 9.77, respectively. In conclusion, considering its unique oil composition and qualitative characteristics, this oil holds promise as a novel source of vegetable oil and a valuable byproduct of Heracleum persicum. Full article

Protein supplements are popular nutritional supplements consumed primarily by physically active individuals with increased protein demands. Despite the increasing consumer demand for protein supplements in Greece, detailed and comparative data on the nutritional profile of such products is scarce. The purpose of this study was to determine the nutritional quality of protein powder supplements available in the Greek market and to compare animal- with plant-based products. Data was extracted from the websites of the major retailers (n = 28). In total, 216 products were identified and grouped as animal- and plant-based, depending on the protein origin. Animal-based products were predominantly (84.0%) produced from whey. Protein content was significantly higher (p < 0.05) in animal-based products, providing 43.5% of the reference intake (RI) for men and 53.2% for women per serving. The content of essential amino acids (EAAs), branched amino acids (BCAAs) and alanine (Ala) was significantly higher (p < 0.05) in animal-based products (median: 11.0, 5.3 and 1.2 g/serving) compared with plant-based alternatives (median: 8.4, 4.0 and 1.0 g/serving size). Plant-based protein supplements contained significantly higher (p < 0.05) content of fiber, fat and salt and were more energy-dense per 100 g. Mean serving size was larger for animal-based products (29.9 ± 0.4 g) compared with the plant-based ones (28.1 ± 0.5 g). Animal-based supplements were more expensive to purchase by 4.3 € per kg. Overall, animal-based protein powder supplements show a more desirable nutritional profile regarding protein content and quality. Results of this study can serve as a tool for consumers to make informed and healthy choices and for health professionals to provide effective and personalized guidance based on the nutritional content of products. Full article

The accurate determination of the equilibrium moisture content (EMC) of gel-related powdery samples requires strictly controlled conditions and a long time period. In this study, the adsorption and desorption isotherms of two fructooligosaccharide (FOS) powders and three inulin powders were determined using a dynamic moisture sorption analyzer at 0.1–0.9 water activity (a_w) and 20–35 °C, respectively. The adsorption and desorption isotherms all exhibited type IIa sigmoidal curves; the desorptive isotherm was smooth, the FOS adsorption curves had three inflection points, and the inulin adsorption curves had five inflection points. Large hysteresis between the adsorption and desorption isotherms occurred at 0.1–0.7 a_w for FOS and 0.1–0.6 a_w for inulin. Seven equations, Boquet, Ferro–Fontan, Guggenheim–Anderson–de Boer (GAB), Generalized D’Arcy and Watt (GDW), modified GAB (MGAB), Peleg, and our developed Polynomial, were found to fit the isotherms of the FOS and inulin samples; for adsorption, the best equations were Ferro–Fontan and GDW, and for desorption, the best equations were Polynomial and MGAB. The GDW and MGAB equations could not distinguish the effect of temperature on the isotherms, while the Polynomial equation could. The mean adsorptive monolayer moisture content (M₀) values in FOS and inulin samples were predicted as 7.29% and 7.94% wet basis, respectively. The heat of moisture sorption of FOS and inulin approached that of pure water at about 32.5% and 22.5% wet basis (w.b.) moisture content (MC), respectively. Fourier Transform Infrared Spectroscopy (FTIR) showed that the peaks in inulin with absorbance values above 0.52 and in FOS with absorbance values above 0.35 were at 1020, 1084, and 337 cm⁻¹; these could represent the amorphous structure (primary alcohol C-OH), C-O group, and hydroxyl functional group, respectively. Microscopic structure analysis showed that inulin powder particles were more round-shaped and adhered together, resulting in hygroscopic and sticky characteristics, with a maximum equilibrium moisture content (EMC) of 34% w.b. In contrast, the FOS powders exhibited irregular amorphous particles and a maximum EMC of 60% w.b. As hydrogels, 3–10% FOS or inulin addition reduced the peak, trough, final, breakdown, and setback viscosities of rice starch pasting, but increased the peak time and pasting temperature. FOS addition gave stronger reduction in the setback viscosity and in amylose retrogradation of rice starch pasting than inulin addition. The differential scanning calorimeter (DSC) showed 3–10% FOS addition reduced the amylopectin aging of retrograded paste of rice starch, but 5–7% inulin addition tended to reduce. These results suggest that FOS and inulin have strong hygroscopic properties and can be used to maintain the freshness of starch-based foods. These data can be used for drying, storage, and functional food design of FOS and inulin products. Full article

Ship detection in synthetic aperture radar (SAR) remote sensing imagery is of great significance in military and civilian applications. However, two factors limit detection performance: (1) a high prevalence of small-scale ship targets with limited information content and (2) interference affecting ship detection from speckle noise and land–sea clutter. To address these challenges, we propose a novel end-to-end (E2E) transformer-based SAR ship detection framework, called Flow-Aligned Nested Transformer for SAR Small Ship Detection (FANT-Det). Specifically, in the feature extraction stage, we introduce a Nested Swin Transformer Block (NSTB). The NSTB employs a two-level local self-attention mechanism to enhance fine-grained target representation, thereby enriching features of small ships. For multi-scale feature fusion, we design a Flow-Aligned Depthwise Efficient Channel Attention Network (FADEN). FADEN achieves precise alignment of features across different resolutions via semantic flow and filters background clutter through lightweight channel attention, further enhancing small-target feature quality. Moreover, we propose an Adaptive Multi-scale Contrastive Denoising (AM-CDN) training paradigm. AM-CDN constructs adaptive perturbation thresholds jointly determined by a target scale factor and a clutter factor, generating contrastive denoising samples that better match the physical characteristics of SAR ships. Finally, extensive experiments on three widely used open SAR ship datasets demonstrate that the proposed method achieves superior detection performance, outperforming current state-of-the-art (SOTA) benchmarks. Full article

Quercetin, a key flavonoid in Anoectochilus roxburghii (Wall.) Lindl., plays an important role in determining the pharmacological value of this medicinal herb. However, traditional methods for quercetin quantification are destructive and time-consuming, limiting their application in real-time quality monitoring. This study investigates the hyperspectral response characteristics of quercetin using near-infrared hyperspectral imaging and establishes a feature-based model to explore its detectability in A. roxburghii leaves. We scanned standard quercetin solutions of known concentration under the same imaging conditions as the leaves to produce a dilution series. Feature-selection methods used included the successive projections algorithm (SPA), Pearson correlation, and competitive adaptive reweighted sampling (CARS). A 1D convolutional neural network (1D-CNN) trained on SPA-selected wavelengths yielded the best prediction performance. These key wavelengths—particularly the 923 nm band—showed strong theoretical and statistical relevance to quercetin’s molecular absorption. When applied to plant leaf spectra, the standard-trained model produced continuous predicted quercetin values that effectively distinguished cultivars with varying flavonoid contents. PCA visualization and ROC-based classification confirmed spectral transferability and potential for functional evaluation. This study demonstrates a non-destructive, spatially resolved, and biochemically interpretable strategy for identifying bioactive markers in plant tissues, offering a methodological basis for future hyperspectral inversion studies and intelligent quality assessment in herbal medicine. Full article

Atmospheric nitrogen input has been a severe challenge worldwide. The influences of N deposition on carbon cycling, loss, and storage have been recognized as a critical issue. This study aimed to assess the immediate responses of soil respiration to different N deposition treatments in radiata pine (Pinus radiata D. Don) and chestnut-leaved oak (Quercus castaneifolia C. A. Mey) plantations within 12 months. N treatments were performed monthly at levels of 0, 50, 100, and 150 kg N ha⁻¹ year⁻¹ from October 2017 to September 2018. Litterfall was collected and analyzed seasonally for its mass and C content. Within the 0–10 cm depth of mineral soil in both plantations, parameters such as total nitrogen, pH, microbial biomass carbon (MBC), organic carbon (OC), and fine root biomass were measured seasonally. Soil respiration (Rs) was determined through monthly measurements of CO₂ concentration in the field using a portable, closed chamber technique. The control plots exhibited the highest Rs during spring (2.96, 2.85 μmol CO₂ m⁻² s⁻¹) and summer (2.92, 3.1 μmol CO₂ m⁻² s⁻¹) seasons in oak and pine plantations, respectively. However, the introduction of nitrogen significantly diminished Rs in both plantations. Moreover, N treatments caused a notable reduction of soil MBC and fine root biomass. Soil microbial entropy and the C/N ratio were also significantly decreased by nitrogen treatments in both plantations, with the most prominent effects observed in summer. The observed decline in Rs in N-treated plots can be attributed to the decrease in MBC and fine root biomass, potentially with distinct contributions of these components in the pine and oak plantations. Our findings suggested that N-induced alteration in soil carbon dynamics was more pronounced in the oak plantation, which resulted in more SOC accumulation with increasing N inputs, while the pine plantation showed no significant changes in SOC. Full article

The present study aimed to evaluate the antifouling efficacy of Piper betle leaf extracts as a bioactive additive for eco-friendly antifouling coatings. The composition of P. betle extract was determined and analyzed. Phytochemical analysis revealed that the ethanol extract of P. betle contained phenolics, tannins, proteins, carbohydrates, and flavonoids, with total phenolic content reaching 260.3 mg GAE/g dry weight and flavonoid content reaching 52.56 mg QE/g dry weight. The antibacterial test results showed that the ethanol extract of P. betle exhibited maximum antibacterial efficacy against E. coli, B. subtilis, S. aureus, and marine bacteria, with inhibition zone diameters of 28.7 ± 0.5, 27.0 ± 1.6, 22.1 ± 0.6, and 35.1 ± 0.5 mm, respectively. Based on the laboratory test results, the ethanol extract of P. betle was chosen to be added to coatings as an antifouling additive. The content of the extract was 0.5, 1.0, and 1.5 wt.%. A field test conducted in tropical seawater (at Nha Trang Bay) demonstrated that incorporating 1 wt.% of P. betle extract into an acrylic copolymer-based coating significantly enhanced its antifouling performance. After nine months of immersion in seawater, this sample maintained an antifouling efficiency of 74%. These findings highlight the potential of P. betle extract as a sustainable alternative to conventional antifouling agents in marine coatings. Full article

Non-nutritive artificial sweeteners (NASs) are xenobiotics widely used in the food industry as sugar substitutes, since they provide few to no calories compared to sucrose. While NASs are considered safe at the acceptable daily intake (ADI) established by regulatory agencies, there is increasing controversy regarding their potential ability to promote metabolic derangements, especially to disrupt the gut microbiome balance. In this study, we analyzed a large cohort of the most commonly consumed beverages in Spain, categorizing them by the type of soda to determine the composition and content of the most frequently used NASs in the food industry. All commercial NAS formulations analyzed contained mixtures of different NASs. The NAS contents were always within regulated limits, although some samples yielded values close to these thresholds. Most soda samples analyzed contained NASs, even though the majority were not labeled as “zero sugars”, “no sugar added”, or “reduced calories”, which may mislead consumers. A preliminary statistical evaluation of the obtained results (cluster analysis) suggests that beverages can be grouped into three distinct clusters based on the total amount of NAS present in the samples. Differences in the total NAS content were significant among the three groups, with one cluster showing two- and four-fold higher levels than the others. Full article

The glycemic index (GI) of rice is a complex trait, affected by amylose content (AC), size, and packaging of starch granules (SGs). In this study, the electron microscopy results of starch morphology of nine rice genotypes showed varying AC (6.93–36.9%), and the predicted GI (pGI: 41.07–82.46) in relation to genetic factors revealed that smaller SG surface area (20.06 µm²) and irregular morphology (Hap 3-3 P-11, pGI = 41.07) were associated with a lower pGI, while larger SG surface area (47.68 µm²) and spherical structure were associated with a higher pGI (NON-HAI, pGI = 82.46). The expression of starch biosynthesis and packaging-related genes (OsSSIIb, OsSSIIc, OsSBEIIa, OsISA1, OsISA3, OsGBP, OsFLO6, and OsBT1) revealed downregulation of OsGBP and OsISA3 genes in low pGI lines IRRI-147 (pGI = 56.2) and Hap 3-1-p-18 (pGI = 41.79), respectively, while higher levels of expression of the OsBT1 gene in Makro (pGI = 59.06) and OsSSIIb in Swarna (pGI = 58.06) were observed. All these genotypes had similar AC (~30%), but the difference in expression pattern was correlated with starch granule morphology, suggesting its role in influencing pGI. Further, analysis of allelic variation in eight starch-related genes across 20 rice genotypes showed that allelic variants of only OsGBP were correlated with AC, where allele group 2 showed lower AC (9.62%), while all other allele groups showed consistently high AC (22–24%). These findings underscore the critical role of starch granule morphology and OsGBP allelic variation in determining AC and GI, providing actionable insights for developing low GI rice varieties using tools like CRISPR. Full article

Taro (Colocasia esculenta) is the fifth most cultivated root crop in the world. During the asexual reproduction of taro, the frequent mutation of somatic cells leads to high genetic diversity. With the continuous increase in the amount of taro germplasm resources collected, efficiently and accurately genotyping taro has become a major problem. The identification of taro resources using penta-primer amplification refractory mutation system single-nucleotide polymorphisms (SNP-PARMS) is a relatively efficient method. After resequencing 29 taro resources in this study, approximately 86.95 million SNPs were obtained. Then, 252 specific SNP loci were screened. Based on these 252 specific SNP loci, 36 pairs of PARMS-SNP markers were formed. Among them, 9 pairs of PARMS-SNP markers with a sample loss rate > 15% were eliminated, and finally 27 pairs of PARMS-SNP markers were determined. The average values of minimal allele frequency (MAF), polymorphic information content (PIC), gene diversity (GD), and heterozygosity of these markers are 0.63, 0.34, 0.49, and 0.45, respectively. We analyzed the population structure and the evolutionary group, and the results showed that the 72 taro resources could be divided into 6 groups. The clustering result of the 72 taro resources based on phenotypic traits showed a potential congruence with the result of grouping in the evolutionary tree, with only a few differences detected between the two classifications. Using these markers, DNA fingerprint maps of 72 taro resources were constructed, and all taro resources were differentiated. Some resources show potential similarities in DNA fingerprint maps, as well is in their phenotypic traits, confirming the validity of the fingerprint. The study’s findings serve as a reference for the analysis of the genetic diversity of taro resources. Full article

Canopy chlorophyll content (CCC) is an important index for monitoring the growth and estimating the productivity of citrus fruit trees. This study optimized the PROSAIL model by adjusting the average leaf angle (ALA) parameter. A hybrid inversion model was then developed by combining the simulated data with UAV multispectral measurements using machine learning to determine the optimal data fusion ratio for improved citrus CCC prediction. The results show that (1) the most pragmatic accommodation for the hybrid inversion model in this study is the 1:4 ratio of measured data to simulated data; (2) the adjusted ALA (ALA_adj) value of citrus fruit trees is 42°, and the spectral response region of the adjusted PROSAIL parameters is more conducive to leaf chlorophyll content (LCC) and the leaf area index (LAI) for CCC modeling; and (3) the ALA_adj hybrid inversion model showed significantly better performance than the ALA-unadjusted model under all four machine learning methods, with the peak prediction accuracy, measured by R², rising from 0.723 to 0.823—a 13.8% increase. The proposed method effectively improves the prediction accuracy of citrus CCCs, demonstrating the strong potential of the ALA_adj-based PROSAIL model for UAV-scale CCC monitoring. Full article