Search Results (4,273)

Cadmium (Cd) accumulation by benthic organisms poses a significant threat to aquatic environmental safety. Both vegetation and water velocity in rivers could influence this process, yet their coupled interaction mechanisms remain unclear. This study used laboratory flume experiments to simulate four scenarios: static water (C0), pure water velocity (C+H), vegetation-water velocity (V+H), and coexistence of vegetation-water velocity-Corbicula fluminea (C. fluminea) (C+V+H). The dynamics of Cd release from sediment to overlying water and its bioaccumulation within C. fluminea were investigated. A mathematical model coupling Cd release, diffusion, and C. fluminea bioaccumulation was developed based on the lattice Boltzmann method (LBM). The results showed that compared to the non-vegetation group (C+H), the presence of vegetation (V+H, C+V+H) initially reduced sediment resuspension and Cd release. However, the turbulence induced by vegetation significantly increased the Cd diffusion coefficient and equilibrium concentration in the water. Consequently, Cd accumulation in C. fluminea within the vegetation-water velocity group (C+V+H) was significantly higher than in the pure water velocity group (C+H). The established LBM model exhibited good simulation accuracy (for overlying water Cd concentration: R² = 0.8201–0.942; for C. fluminea Cd concentration: R² = 0.7604–0.8191) and successfully reproduced the processes of Cd release and bioaccumulation under varying vegetation-water velocity conditions. This study elucidates the mechanism by which vegetation promotes Cd accumulation in C. fluminea by altering water velocity structure and diffusion characteristics, providing crucial theoretical parameters for multi-media migration and transformation models of heavy metals in complex water velocity environments and for early warning systems concerning Cd accumulation risks in riverine organisms. Full article

Accurate estimation of winter wheat yield under saline stress is crucial for addressing food security challenges and optimizing agricultural management in regional soils. This study proposed a method integrating Sentinel-2 data and field-measured soil salt content (SC) using a random forest (RF) method to improve yield estimation of winter wheat in Kenli County, a typical saline area in China’s Yellow River Delta. First, feature importance analysis of a temporal vegetation index (VI) and salinity index (SI) across all growth periods were achieved to select main parameters. Second, yield models of winter wheat were developed in VI-, SI-, VI + SI-, and VI + SI + SC-based groups. Furthermore, error assessment and spatial yield mapping were analyzed in detail. The results demonstrated that feature importance varied by growth periods. SI dominated in pre-jointing periods, while VI was better in the post-jointing phase. The VI + SI + SC-based model achieved better accuracy (R² = 0.78, RMSE = 720.16 kg/ha) than VI-based (R² = 0.71), SI-based (R² = 0.69), and VI + SI-based (R² = 0.77) models. Error analysis results suggested that the residuals were reduced as the input parameters increased, and the VI + SI + SC-based model showed a good consistency with the field-measured yields. The spatial distribution of winter wheat yield using the VI + SI + SC-based model showed significant differences, and average yields in no, slight, moderate, and severe salinity areas were 7945, 7258, 5217, and 4707 kg/ha, respectively. This study can provide a reference for winter wheat yield estimation and crop production improvement in saline regions. Full article

Trichomes in cannabis (Cannabis sativa L.) are specialized structures responsible for cannabinoid and terpene biosynthesis, making their density a critical parameter for both research and industrial applications. However, consistent trichome density assessment remains challenging due to anatomical variability and the absence of standardized methodologies. This review critically examines the existing literature on trichome quantification across key floral structures—such as bracts, sugar leaves, calyxes, and the main cola—to identify the most reliable sites and practices for accurate evaluation. Evidence suggests that bracts represent the most consistent sampling unit, given their homogeneous trichome distribution and elevated cannabinoid concentration. Whilst sugar leaves and calyxes are also frequently analyzed, their morphological variability requires cautious interpretation. Furthermore, trichome shape, size, maturity, and vegetal surface expansion/shrinkage during stress must be considered when correlating density with secondary metabolite production. We also highlight the advantages of using more than only one floral structure and integrating microscopic imaging and software-assisted analysis to enhance reproducibility and accuracy. By synthesizing current methodologies and proposing pathways for standardization, this review aims to support more robust trichome assessment protocols, ultimately improving cannabinoid yield optimization, quality control, broader cannabis research frameworks, and an important aesthetic parameter for consumers. Future research efforts should focus on advancing imaging methodologies and optimizing sampling protocols to further improve the precision and reproducibility of trichome density and cannabinoid analyses. Full article

With the advancement of automation in modern agriculture, the demand for intelligence in the post-picking sorting of fruits and vegetables is increasing. As a significant global agricultural product, the defect detection and sorting of tomato is essential to ensure quality and improve economic value. However, the traditional detection method (manual screening) is inefficient and involves high labor intensity. Therefore, a defect detection model named YOLO-RGDD is proposed based on YOLOv12s to identify five types of tomato surface defects (scars, gaps, white spots, spoilage, and dents). Firstly, the original C3k2 module and A2C2f module of YOLOv12 were replaced with RFEM in the backbone network to enhance feature extraction for small targets without increasing computational complexity. Secondly, the Dysample–Slim-Neck of the YOLO-RGDD was developed to reduce the computational complexity and enhance the detection of minor defects. Finally, dynamic convolution was used to replace the conventional convolution in the detection head in order to reduce the model parameter count. The experimental results show that the average precision, recall, and F1-score of the proposed YOLO-RGDD model for tomato defect detection reach 88.5%, 85.7%, and 87.0%, respectively, surpassing advanced object recognition detection algorithms. Additionally, the computational complexity of the YOLO-RGDD is 16.1 GFLOPs, which is 24.8% lower than that of the original YOLOv12s model (21.4 GFLOPs), facilitating the model’s deployment in automated agricultural production. Full article

Native and invasive plants of the riverain region undergo a range of environmental stresses that result in excess reactive oxygen species (ROS). Hydrogen peroxide (H₂O₂) is a relatively stable and quickly quantifiable way among different ROS. The herbaceous species including Artemisia princeps, Sicyos angulatus, and Solidago altissima were selected. The H₂O₂ and photosynthetic pigment of leaves were measured, soil samples were analyzed to quantify macronutrients such as total nitrogen (TN), total phosphorus (TP), and soil moisture, and photosynthetic photon flux density (PPFD) was also recorded at different observed sites of Arakawa Tarouemon, Japan. The H₂O₂ concentration of S. altissima significantly increased with high soil moisture content, whereas A. Princeps and S. angulatus significantly decreased with high soil moisture. In each species, H₂O₂ was negatively correlated with chlorophyll a (chl a) and chlorophyll b (chl a). When comparing different parameters involving TN, TP, PPFD, and soil moisture content with H₂O₂ utilizing the general additive model (GAM), only soil moisture content is significantly correlated with H₂O₂. Hence, this study suggests that H₂O₂ would be an effective biomarker for quantifying environmental stress within a short time, which can be applied for riparian native and invasive plant species vegetation regulation. Full article

Transpiration is the dominant process driving water loss in crops, significantly influencing their growth, development, and yield. Efficient monitoring of transpiration rate (Tr) is crucial for evaluating crop physiological status and optimizing water management strategies. The three-temperature (3T) model has potential for rapid estimation of transpiration rates, but its application to low-altitude remote sensing has not yet been further investigated. To evaluate the performance of 3T model based on land surface temperature (LST) and canopy temperature (T_C) in estimating transpiration rate, this study utilized an unmanned aerial vehicle (UAV) equipped with a thermal infrared (TIR) camera to capture TIR images of summer maize during the nodulation-irrigation stage under four different moisture treatments, from which LST was extracted. The Gaussian Hidden Markov Random Field (GHMRF) model was applied to segment the TIR images, facilitating the extraction of T_C. Finally, an improved 3T model incorporating fractional vegetation coverage (FVC) was proposed. The findings of the study demonstrate that: (1) The GHMRF model offers an effective approach for TIR image segmentation. The mechanism of thermal TIR segmentation implemented by the GHMRF model is explored. The results indicate that when the potential energy function parameter β value is 0.1, the optimal performance is provided. (2) The feasibility of utilizing UAV-based TIR remote sensing in conjunction with the 3T model for estimating Tr has been demonstrated, showing a significant correlation between the measured and the estimated transpiration rate (T_r-3T_C), derived from T_C data obtained through the segmentation and processing of TIR imagery. The correlation coefficients (r) were 0.946 in 2022 and 0.872 in 2023. (3) The improved 3T model has demonstrated its ability to enhance the estimation accuracy of crop Tr rapidly and effectively, exhibiting a robust correlation with T_r-3T_C. The correlation coefficients for the two observed years are 0.991 and 0.989, respectively, while the model maintains low RMSE of 0.756 mmol H₂O m⁻² s⁻¹ and 0.555 mmol H₂O m⁻² s⁻¹ for the respective years, indicating strong interannual stability. Full article

There has been a growing interest in polymer-based materials in recent years, and current research is focused on reducing fossil-derived epoxy compounds. This review examines the potential of epoxidised vegetable oils (EVOs) as sustainable alternatives to these systems. Epoxidation processes have been systematically analysed and their influence on chemical, thermal, and mechanical properties has been assessed. Results indicate that basic, low-toxicity epoxidation methods resulted in resins with comparable performance to those obtained through more complex common/commercial procedures. In total, 5–7% oxirane oxygen content (OOC) was found to be optimal to achieve a balanced crosslink density, thus enhancing tensile strength. Furthermore, mechanical properties have been insufficiently studied, as less than half of the studies were conducted at least tensile or flexural strength. Reinforcement strategies were also explored, with nano-reinforcing carbon nanotubes (CBNTs) showing the best mechanical and thermal results. Natural fibres reported better mechanical performance when mixed with EVOs than conventional systems. On the other hand, one of the main constraints observed is the lack of consistency in reporting key chemical and mechanical parameters across studies. Environmental properties and end-of-life use are significant challenges to be addressed in future studies, as there remains a significant gap in understanding the end-of-life of these materials. Future research should focus on the exploration of eco-friendly epoxidation reagents and standardise protocols to compare and measure oil properties before and after being epoxidised. Full article

This study investigated the influence of cane diameter on vegetative, productive, and physiological behaviors in Actinidia chinensis, cv. Gold 3. Conducted over two years (2021–2022), the experiment compared canes with larger (HD) and smaller (LD) proximal diameters. This research focused on parameters such as shoot morphology, leaf gas exchange, fruit quality, and hydraulic resistance. The results revealed that HD canes promoted more vigorous growth, with a higher proportion of long and medium shoots, whereas LD canes resulted in shorter shoots. Additionally, the HD canes demonstrated a higher leaf area and more extensive leaf coverage, contributing to enhanced photosynthetic activity, as evidenced by enhanced gas exchange, stomatal conductance, and transpiration rates. This higher photosynthetic efficiency in HD canes resulted in more rapid fruit growth, with a larger fruit size and weight, particularly in fruits from non-terminate shoots. By contrast, fruits on LD canes exhibited slower growth, particularly in terms of fresh weight and dry matter accumulation. Despite these differences, maturation indices, including soluble solids and acidity levels, were not significantly affected by cane type. The findings suggest that selecting HD canes during winter pruning could lead to earlier harvests, with improved fruit quality and productivity, making this practice beneficial for optimizing vineyard management in Actinidia chinensis. Full article

The analysis of soil nematode communities provides information on their impact on soil quality and the health of different agricultural cropping systems and soil management practices, which is necessary to evaluate their sustainability. Here, we evaluated the status of nematode communities and trophic groups’ abundance in fifteen fields hosting different cropping systems and managed according to organic or conventional practices. The nematode population densities differed significantly across cropping systems and management types covering various European climatic zones (spanning 121 to 799 individuals per sample). Population density was affected by the duration of the cropping system, with the lowest value in the vegetable cropping system (on average about 300 individuals) and the highest in the long-term fruiting system (on average more than 500 individuals). The occurrence and abundance of the different trophic groups was partly dependent on the cropping system or the management method, particularly for the bacteria, fungal and plant feeders. The taxonomical classification of a subset of samples allowed us to identify 22 genera and one family (Dorylaimidae) within the five trophic groups. Few taxa were observed in all fields and samples (i.e., Rhabditis and Cephalobus), while Aphelenchoides or Pratylenchus were present in the majority of samples. Phosphorus content was the only soil chemical parameter showing a positive correlation with total nematode population and bacterial feeders’ absolute abundance. Based on the nematological ecological indices, all three cropping systems were characterized by disturbed soil conditions, conductive and dominated by bacterivorous nematodes. This knowledge could lead to a choice of soil management practices that sustain a transition toward healthy soils. Full article

Land desertification represents a significant and sensitive global ecological issue. In the Inner Mongolia region of China, soil desertification and salinization are widespread, resulting from the combined effects of extreme drought conditions and human activities. Using Gaofen 5B AHSI imagery as our data source, we collected spectral data for seven distinct land cover types: lush vegetation, yellow sand, white sand, saline soil, saline shell, saline soil with saline vegetation, and sandy soil. We applied Particle Swarm Optimization (PSO) to fine-tune the Wavelet Packet (WP) decomposition levels, thresholds, and wavelet basis function, ensuring optimal spectral decomposition and reconstruction. Subsequently, PSO was deployed to optimize key hyperparameters of the Random Forest algorithm and compare its performance with the ResNet-Transformer model. Our results indicate that PSO effectively automates the search for optimal WP decomposition parameters, preserving essential spectral information while efficiently reducing high-frequency spectral noise. The Genetic Algorithm (GA) was also found to be effective in extracting feature bands relevant to land desertification, which enhances the classification accuracy of the model. Among all the models, integrating wavelet packet denoising, genetic algorithm feature selection, the first-order differential (FD), and the hybrid architecture of the ResNet-Transformer, the WP-GA-FD-ResNet-Transformer model achieved the highest accuracy in extracting soil sandification and salinization, with Kappa coefficients and validation set accuracies of 0.9746 and 97.82%, respectively. This study contributes to the field by advancing hyperspectral desertification monitoring techniques and suggests that the approach could be valuable for broader ecological conservation and land management efforts. Full article

Validating the potential of multi-frequency synthetic aperture radar (SAR) data for multi-layer and profile soil moisture (SM) estimation modeling, we conducted an airborne multi-frequency SAR joint observation experiment (AMFSEX) over the Liao River Basin in China. The experiment simultaneously acquired airborne high spatial resolution quad-polarization (quad-pol) SAR data at five frequencies, including the Ka-, X-, C-, S-, and L-band. A preliminary “vegetation–soil” parameter estimation model based on the multi-frequency SAR data was established. Theoretical penetration depths of the multi-frequency SAR data were analyzed using the Dobson empirical model and the Hallikainen modified model. On this basis, a water cloud model (WCM) constrained by multi-polarization weighted and penetration depth weighted parameters was used to analyze the estimation accuracy of the multi-layer and profile SM (0–50 cm depth) under different vegetation types (grassland, farmland, and woodland). Overall, the estimation error (root mean square error, RMSE) of the surface SM (0–5 cm depth) ranged from 0.058 cm³/cm³ to 0.079 cm³/cm³, and increased with radar frequency. For multi-layer and profile SM (3 cm, 5 cm, 10 cm, 20 cm, 30 cm, 40 cm, 50 cm depth), the RMSE ranged from 0.040 cm³/cm³ to 0.069 cm³/cm³. Finally, a multi-input multi-output regression model (Gaussian process regression) was used to simultaneously estimate the multi-layer and profile SM. For surface SM, the overall RMSE was approximately 0.040 cm³/cm³. For multi-layer and profile SM, the overall RMSE ranged from 0.031 cm³/cm³ to 0.064 cm³/cm³. The estimation accuracy achieved by coupling the multi-source data (multi-frequency SAR data, multispectral data, and soil parameters) was superior to that obtained using the SAR data alone. The optimal SM penetration depth varied across different vegetation cover types, generally falling within the range of 10–30 cm, which holds true for both the scattering model and the regression model. This study provides methodological guidance for the development of multi-layer and profile SM estimation models based on the multi-frequency SAR data. Full article

This study investigated the effects of macronutrient type and concentration on the biomass yield and biochemical composition of hydroponically grown wheat sprouts (HWS), with the aim of identifying fertilization strategies that optimize both productivity and feed quality. HWS were cultivated using a nutrient film technique over a 7-day period under controlled environmental conditions, with treatments including calcium nitrate (CN1–CN3), potassium phosphate (CP1–CP3), potassium sulfate (CK1–CK2), and a balanced NPK 20–20–20 fertilizer (NPK1–NPK3), each applied at three increasing concentrations. The quantitative parameters assessed included biomass yield per unit of dry seed (DP, kg kg⁻¹) and dry matter content (DM, %), while qualitative traits included crude protein (CP), ether extract (EE), crude fiber (CF), and ash content. Results indicated that balanced NPK fertilization significantly enhanced performance, with NPK3 achieving the highest biomass yield (6.39 kg kg⁻¹), CP (24.26%), CF (5.63%), and ash (16.0%) content. In contrast, CN3 treatments reduced yield (4.84 kg kg⁻¹) despite increasing CP (19.65%), indicating trade-offs between nitrogen enrichment and vegetative expansion. Phosphorus-based treatments (CP2–CP3) improved nutrient density without suppressing yield. Regression analyses revealed strong correlations between DM and both CF (R² = 0.81) and ash (R² = 0.71), supporting their utility as indirect indicators of feed quality. EE content remained stable (2.07–2.67%) across all treatments, suggesting its limited responsiveness to macronutrient manipulation. These findings highlight the importance of nutrient synergy in hydroponic systems and provide a practical framework for tailoring fertilization regimes to meet specific agronomic and nutritional objectives in precision livestock feeding and provide practical guidance for optimizing hydroponic livestock feed production. Full article

Background: Bariatric surgeries, specifically laparoscopic sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB), are a common intervention for morbid obesity, significantly affecting food tolerance and quality of eating. Understanding these changes is crucial for improving postoperative care and long-term success. Methods: This observational study at University Hospital Mannheim involved 91 patients, aged between 18 and 65 year, who underwent SG or RYGB between 2009 and 2019. Food tolerance was assessed between 25 days and 117 months after surgery using the validated score by Suter et al. (Food Tolerance Score, FTS) and an additional score evaluating tolerance to specific food groups and quality of life. Data on body composition were collected through Bioelectrical Impedance Analysis (BIA) at follow-up visits. Statistical analyses included linear mixed models to analyze the association of food tolerance with body composition changes. Results: The FTS indicated moderate or poor food tolerance in 62.6% of patients, with no significant differences between SG and RYGB. Considering the results of the additional score, food groups such as red meat, wheat products, raw vegetables, carbon dioxide, fatty foods, convenience food, and sweets were the most poorly tolerated food groups. A total of 57 of the participants had a baseline and follow-up BIA measurement. Postoperatively, a significant reduction in body weight and BMI as well as in BIA parameters (fat mass, lean mass, body cell mass, and phase angle) was found. Quality of life improved after bariatric surgery and 76.9% rated their nutritional status as good or excellent, despite possible food intolerances. Conclusions: Bariatric surgery significantly reduces weight and alters food tolerance. Despite moderate or poor food tolerance, patients reported high satisfaction with their nutritional status and quality of life. Detailed food tolerance assessments and personalized dietary follow-ups are essential for the early detection and management of postoperative malnutrition, ensuring sustained weight loss and improved health outcomes. Full article

Tomato is the most widely cultivated fruit–vegetable worldwide, and the tomato leafminer (Tuta absoluta) is the primary pest of this crop. In this context, biological control using parasitoids belonging to the genus Trichogramma is crucial. This study aimed to evaluate the biological characteristics of T. pretiosum strains collected from different locations and exposed to eggs from various T. absoluta populations/generations, using parameters such as parasitism capacity, viability (percentage of emergence), sex ratio, and female longevity. The presence of endosymbionts in the T. absoluta populations was also assessed. The experiment followed a randomized design, with treatments consisting of eggs from T. absoluta populations collected in different years (2019, 2020, 2021, 2022, and 2023) and different strains of T. pretiosum. We used 20 replicates, with one female per replicate in each treatment, organized in a 5 × 4 factorial scheme (five populations of T. absoluta × four strains of T. pretiosum). The S2 strain of T. pretiosum was found to be the most efficient in terms of biological characteristics for parasitism of T. absoluta eggs, especially in T. absoluta populations collected in recent years (2022 and 2023). These results suggest that S2 is the preferred strain for future studies aimed at using this parasitoid as a control agent to combat T. absoluta. The endosymbionts Arsenophonus and Serratia were identified in T. absoluta populations collected in 2019–2020 and 2020–2021, respectively. These findings highlight the presence of these microorganisms in pest populations in different years. Full article

Increasing the shelf-life of fruits and vegetables using edible natural substances after harvest is economically important and can be useful for human health. Postharvest techniques help maintain the quality of edible tissues resulting in extended marketing periods and reduced food waste. The edible coating on perishable commodities is a common technique used by the food industry during the postharvest supply chain. The objective of this research was to study the effect of edible oil to minimize the loss of postharvest physio-chemical and nutritional attributes of bananas. The study selected two banana cultivars (Musa, ‘Cavendish’ and ‘Milk’) to conduct this experiment, and two edible oils (olive oil (Olea europaea) and moringa oil (Moringa peregrina)) were applied as an edible coating under two different storage conditions (15 and 25 °C). The fruit’s physio-chemical properties including weight loss, firmness, color, total soluble solids (TSS), pH, titratable acidity (TA), TSS: TA ratio, and mineral content were assessed. The experiment lasted for 12 days. The physicochemical properties of the banana coated with olive and moringa oils were more controlled than the non-coated (control) banana under both storage temperatures (15 °C and 25 °C). Coated bananas with olive and moringa oils stored at 15 °C resulted in further inhibition in the ripening process. There was a decrease in weight loss, retained color, and firmness, and the changes in chemical parameters were slower in banana fruits during storage in the olive and moringa oil-coated bananas. Minerals were highly retained in coated Cavendish bananas. Overall, the coated samples visually maintained acceptable quality until the final day of storage. Our results indicated that olive and moringa oils in this study have the potential to extend the shelf-life and improve the physico-chemical quality of banana fruits. Full article