Search Results (3,541)

Microplastics (MPs) are widely recognized as emerging contaminants in freshwater environments. Their identification often relies on extensive sample preparation and chemical treatments, which increase analysis time, reagent use, and overall resource consumption. Consequently, there is a growing need for sustainable analytical approaches enabling reliable MP detection while minimizing sample handling. This study proposes an analytical workflow based on hyperspectral imaging (HSI) as a proof-of-concept approach for direct identification of MPs in freshwater samples. Water samples collected from three different rivers, containing heterogeneous natural materials, were spiked with MPs (250–1000 μm) of three common polymers, namely high-density polyethylene (HDPE), polystyrene (PS), and polypropylene (PP), to simulate realistic contamination scenarios. HSI acquisitions were performed in the short-wave infrared range (SWIR: 1000–2500 nm). Spectral preprocessing and principal component analysis (PCA) were applied for data exploration, while a hierarchical partial least squares-discriminant analysis (Hi-PLS-DA) model was developed to classify five target classes: natural materials, water, HDPE, PS, and PP. Despite sample complexity, the proposed workflow achieved satisfactory classification results, as demonstrated by the predicted class map and the corresponding statistical metrics (sensitivity, specificity, precision, and F1-score: 0.900–0.999). These results highlight the potential of the SWIR-HSI-based approach as a rapid and sustainable method for direct MP identification in freshwater samples and provide methodological insights for rapid MP screening strategies requiring minimal sample preparation. Full article

Rapid and non-destructive detection of nitrogen content in greenhouse cucumber leaves is essential for precision fertilization, yet traditional chemical methods are destructive and time-consuming, and existing spectral technologies suffer from high cost and poor field adaptability. This study aims to propose a high-precision detection scheme for cucumber leaf nitrogen content based on a lightweight model, suitable for complex scenarios. A total of 698 cucumber leaf images covering three growth stages were collected to build a segmentation dataset. Four categories and eight types of deep learning segmentation models were optimized and compared, and the optimal one was selected to extract leaf regions. Nine color features were extracted and combined with Kjeldahl-measured nitrogen content to construct and optimize three machine learning models, forming a deep learning segmentation–color feature extraction–machine learning prediction process. The results showed that YOLOv11n achieved the best segmentation accuracy, with an IoU of 0.9212 and AP of 0.9998 for high-resolution images. The optimized XGBoost had the highest prediction accuracy, with an MAE of 0.469, MSE of 0.461, and RMSE of 0.679, which are 10.15%, 8.71%, and 4.36% lower than Support Vector Regression with Radial Basis Function kernel (SVR_RBF) respectively, and its predicted nitrogen content aligned well with true values. The proposed scheme integrating YOLOv11n and XGBoost offers a lightweight technical solution for nitrogen nutrition diagnosis and precise fertilization of greenhouse cucumbers. Full article

As hen eggs are a primary source of high-quality dietary protein, egg freshness is fundamentally linked to biochemical alterations during storage, including moisture redistribution, protein degradation, and fluctuating chemical profiles. Accurate assessment of these internal changes is paramount for quality control; nonetheless, conventional analytical techniques remain predominantly destructive, rendering them impractical for high-throughput industrial monitoring. While existing literature has explored individual spectroscopic methods, the synergistic potential of multi-sensor integration and advanced artificial intelligence (AI) algorithms remains insufficiently synthesized. This review systematically evaluates recent breakthroughs in integrating AI with diverse spectroscopic modalities for non-destructive freshness quantification, including Visible-Near-Infrared (VIS-NIR), Raman, Fluorescence, and Hyperspectral Imaging (HSI). We elucidate the underlying mechanisms of spectral response to internal quality degradation and discuss the evolution of data-driven modeling from traditional chemometrics to sophisticated deep learning architectures. Furthermore, this work identifies critical bottlenecks in real-time industrial implementation and proposes future research trajectories toward intelligent multi-sensor fusion platforms. Full article

This study aims to develop eco-efficient ceramic tiles through the valorization of recycled glass (GW; soda–lime glass cullet) as a partial raw material substituent, enabling a reduction in sintering temperature and, consequently, a decrease in thermal energy demand, carbon-equivalent emissions, and the depletion of virgin mineral resources. Ceramic tiles were elaborated by partially substituting natural bentonite with 30–50 wt.% GW and fired at 900 °C and 950 °C. Use of GW promoted liquid-phase sintering, driving significant densification evidenced by a marked reduction in open porosity and water absorption. SEM images confirm a denser, more homogeneous structure with reduced porosity, leading to improved mechanical strength and chemical durability. Compositions containing 30–35 wt.% bentonite exhibit the most optimized microstructure, characterized by well-dispersed crystalline phases embedded within a dense vitreous matrix. These findings demonstrate that high-performance ceramic tiles meeting standard classification thresholds can be manufactured at sub-1000 °C firing temperatures through judicious incorporation of recycled glass waste. This approach offers a viable pathway toward reduced energy consumption, diminished reliance on primary mineral resources, and enhanced circularity within the construction ceramics industry. Full article

Introduction: Fish skin is the first line of defense against the aquatic environment, acting as a physical, chemical, and immunological barrier. In addition to preventing pathogen entry, the skin and its mucus contribute to osmoregulation, innate immunity, and redox balance. Skin lesions—caused by mechanical damage, parasites, environmental stress, or handling—disrupt this barrier, increasing susceptibility to infections, inflammation, and production losses. Thus, efficient skin regeneration is essential for fish welfare and performance. Nutrition plays a key role in this process by providing substrates for epithelial repair, immune function, and antioxidant defense. Among dietary factors, zinc (Zn) is particularly important due to its involvement in cell proliferation, enzymatic activity, and maintenance of skin integrity. Objective: Our objective is to assess the effectiveness of image-based analysis in quantifying the skin healing process in Atlantic salmon fed diets supplemented with zinc. Methodology: The trial comprised three dietary treatments: a control diet with 42 mg Zn per kg (D1), and two diets supplemented up to 120 mg/kg of zinc, derived from inorganic (D2) or organic (D3) forms. Pit-tagged fish with an initial body weight (78 ± 0.1 g) were fed the diets for 75 days. After 15 days of experimental feeding, a standardized wound lesion (2.5 mm diameter × 0.5 mm depth) was inflicted in deeply anesthetized fish, with a disposable biopsy punch, in the dorsal area. After wound infliction, the fish resumed their normal feeding regime for the rest of the trial days. The progression of skin wound healing was assessed using standardized digital image analysis. High-resolution photographs of individual wounds were collected 8, 16, 24 and 32 days post-wounding. All images were acquired under standardized conditions with the inclusion of ArUco identifiers to enable a subsequent computer-assisted comparison. Morphometric parameters (wound width, diameter, perimeter and area) were used to assess wound contraction and closure over time. In parallel, a semi-quantitative visual scoring system was applied to each wound image to capture qualitative aspects of healing that are not fully described by morphometric data alone. Results: Full data analysis is currently underway, but the first results show beneficial effects of dietary zinc supplementation on the skin regenerative process. Conclusions: The combined use of objective digital measurements and standardized visual scoring enabled a comprehensive evaluation of wound healing progress, bridging quantitative tissue remodeling with biologically relevant phenotypic outcomes. This image-based framework provides a sensitive and reproducible approach for assessing dietary interventions targeting skin regeneration and barrier restoration in Atlantic salmon. Full article

To investigate the impact of underground multiple stress disturbances on the long-term stability of cemented tailings backfill (CTB), this study conducted experiments under different disturbance levels (20–80% of static strength) and frequencies (1–4 times). By comprehensively utilizing mechanical testing, wave velocity monitoring, digital image correlation (DIC), and scanning electron microscopy (SEM), the “heterogeneous” evolution mechanism of macro-micro damage was revealed. The results indicate that disturbance level and frequency exert distinctly different driving effects on the deterioration of CTB, rather than a simple linear superposition. Specifically, low-frequency disturbance produces a compaction strengthening effect, microscopically promoting the generation of Ca(OH)₂ and ettringite (increased Ca/Si ratio). In contrast, the combination of high disturbance and high frequency induces free water extrusion and inhibits hydration, leading to an advanced damage threshold based on energy evolution and the accelerated coalescence of microcracks, which favors the formation of C-S-H gel (decreased Ca/Si ratio). Within this heterogeneous mechanism, the disturbance level acts as the dominant controlling factor. This study clarifies the nonlinear mechanical and chemical evolution paths under composite disturbances, providing theoretical support for the dynamic stability control of backfill in deep multi-step mining. Full article

Soft polyurethane foams are commonly found in furniture, mattresses, shoes and soundproofing applications. These crosslinked foams are hard to recycle. This paper describes our approach of introducing chemical breakage points based on amino acid phosphoramidates (APtA) in the PUs’ backbones. The APtA monomers are combined with PEG, PPG and pTHF-chains to achieve different monomer structures. We demonstrate the hydrolysis of these APtA monomers at neutral pH 7 and the mass loss of the foams. It is shown that after 70 days, more than 50% of the p-THF-APtA monomer and 35% of the PPG-APtA monomer have degraded. However, a contrary trend was observed for the foams, with only 2.5% mass loss for the p-THF-APtA foam, but 26% mass loss for the PPG-APtA foam. The foams were also characterized using compression measurements, revealing a stiffer appearance of the p-THF-APtA foam compared to the foams based on PEG and PPG. SEM images were taken before and after the degradation of the foams to show the difference in morphology. Full article

This study reports the preparation of a nanocomposite using a black cumin surface as a carbon framework on which zinc oxide-doped manganese ferrite nanoparticles were deposited and grown. A simple precipitation method was used to prepare the nanocomposite. The resulting composite was characterized using various characterization analyses such as FTIR, XRD, EDX, SEM, TEM, and TGA. The composite surface was highly conformed with functional groups, and the nanocomposite was formed due to electrostatic and non-electrostatic interactions between the carbon framework and the nanoparticles. X-ray analysis revealed a crystalline structure with crystal sizes up to 45 nm. Microscopic images revealed the surface morphology, confirming the irregular distribution of particles within the composite. The resulting composite material was used for adsorption application. The composite material was tested for the removal of Congo red dye from water. It was found that under optimal conditions, a dose of 2 g per liter of absorbent removed nearly 100% of dye from a 10 mL volume of 10 mg per liter Congo red solution within 90 min and 7 pH. A monolayer adsorption was confirmed by the isotherm analysis. The monolayer adsorption capacity for the present study was ~13.0 mg per gram. The adsorption kinetics suggested the fitting of pseudo-second order. Based on the findings, it was concluded that the chemical mechanism was responsible for the present adsorption process. The regeneration study demonstrates the stability of current adsorbent up to two cycles only. This nanocomposite is the first of its kind which promotes the creation of nanocomposites in the future by using natural materials and reduces the dependency on activated carbon. Full article

Regenerative medicine integrates interdisciplinary approaches towards restoring the function of diseased organs. This study examined alterations that occurred in the liver under a high-fat diet (HFD) with the development of obesity and fatty liver, and changes in metabolic homeostasis and glucose levels, in mice. HFD nutrition causes hyperglycemia, leading to the formation and accumulation of advanced glycation end-products (AGEs) promoting protein post-translational modifications (PTMs) and introducing crosslinking in the extracellular matrix (ECM). Using histological and gene expression analyses, we detected an increase in adiposity, as well as in ECM protein deposition in the liver. Further, decellularization of the liver yielded the isolated ECM organ scaffold, allowing us to analyze the chemical modification in proteins by various imaging methods combined with spectroscopy. The measurements of intrinsic protein fluorescence are consistent with increased AGE-associated levels. SEM allows for the visualization of ECM fiber thickening as a result of protein crosslinking. Using cathodoluminescence, a label-free imaging method, we confirmed the protein modifications. The combination of innovative technologies highlights the ECM structural alterations associated with impaired glucose regulation and liver adiposity. These findings provide novel views on liver-scaffold ECM structure under metabolic diseases that will play a significant role in accelerating the understanding of effective regenerative therapies. Full article

Modern cell imaging is increasingly evolving toward high-content, label-free, and spectrally rich analytical approaches capable of resolving biochemical heterogeneity at cellular and subcellular levels. Raman microspectroscopy (µRS) and surface-enhanced Raman scattering (SERS) provide molecularly specific vibrational fingerprints with minimal photobleaching and high multiplexing capability, making them attractive tools for biomedical imaging and cellular analysis. However, broader implementation remains limited by weak intrinsic signals, insufficient targeting specificity, and limited control over nanoscale sensing environments in complex biological systems. Metal–organic framework (MOF) nanoparticles have recently emerged as promising platforms to address these challenges by offering porous, chemically tunable, and structurally well-defined scaffolds for Raman- and SERS-active nanostructures. Their high stability and favourable biocompatibility further support integration into biological applications. This review summarizes recent advances in MOF-assisted µRS and SERS across chemical sensing, bioanalytical detection, and biomedical diagnostics, with particular emphasis on cellular and subcellular imaging. Unlike previous reviews focused primarily on sensing performance, this work highlights the emerging role of MOF-SERS systems in high-content cellular imaging and evaluates their translation toward biologically relevant environments. Key design strategies and current challenges are critically discussed. Full article

In this work, we present the Chernozem Soil Aggregates Micromorphometrical Parameters Dataset for specific areas located in the Central Russian Upland that can be utilized for the development of a digital twin of Chernozem. The present dataset represents a collection of soil aggregates’ micromorphometrical parameters (aggregate total area, minimal and maximal Feret diameters, form factor, elongation, unevenness, orientation) obtained through segmentation of soil thin sections’ digital images. Also, the dataset represents the data on physical and chemical properties of the studied soils (organic carbon content, inorganic carbon content, clay, silt, and sand fractions content, mean weight diameter of aggregates). Soil excavation and sampling were conducted in two stages: 24–25 April 2023 and 4 June 2024. Soil sampling sites were selected to provide a comparison of virgin Chernozem soils with plowed, non-eroded, and severely eroded ones. Soil sections were excavated at 9 key points. Laboratory analysis yielded 60 sets of data on physical and chemical properties and over 51,000 micromorphometric values for soil aggregates. Full article

Foraminiferal shell crystals incorporate the chemical signals of their environment during growth. The recorded information is extracted from the crystals via proxies and can be used to reconstruct paleoenvironments, paleoclimates, and the change of the latter. However, the information that is obtained from the biocrystals is often biased, due to structural and chemical modification of the crystals resulting from dissolution, precipitation, recrystallization, and overall, the transformation of the biologically formed crystals into their inorganic analogs. Electron-backscatter diffraction (EBSD) measurements and analysis render a wide range of information regarding crystallographic-structural attributes of the crystals, such as crystal-microstructure, crystal-texture, the misorientation interrelation of adjacent crystals, crystal-twin-generation and many more. We demonstrate in this study that diagenetic overprint of foraminiferal shell Ca-carbonate crystals can be identified by structural-crystallographic characteristics obtained from EBSD measurements. We investigated modern/pristine and fossil Trilobatus sacculifer shells and observed an undisturbed shell surface for both. Despite the latter, we demonstrate here that with an increase in the degree of fossilization and diagenetic overprint, there is an increase in recrystallized calcite in the shells and a decrease in twinned calcite. Twinned calcite is the hallmark of pristine T. sacculifer shells. We show that, with increasing degrees of shell overprint, crystal-microstructure, and crystal-texture, the frequency of the 60°|<001> twin misorientation is modified and propose to use structural-crystallographic attributes determined with EBSD measurements for the identification of recrystallized/overprinted foraminiferal carbonate. We discuss that disclosing low degrees of overprint is of main importance, as minor structure changes of overprinted shells are easily overlooked with SEM imaging. Nonetheless, these are readily identified with EBSD-measurements. Full article

Tomato (Solanum lycopersicum) is a globally important horticultural crop, with Asia contributing 60.45% of total production, followed by the Americas at 13.36%. Tomato productivity is increasingly constrained by southern blight, a destructive disease responsible for yield losses ranging from 30 to 90% and annual economic damage of $10–20 million. The causal pathogen, Sclerotium rolfsii, infects the stem base and induces reddish-brown cankers through secretion of oxalic acid (OA) and cell wall-degrading enzymes, which girdle tissues, impair water transport, and result in rapid plant wilting and death. Its persistence in soil via sclerotia, broad host range, and adaptability make the disease difficult to manage. Recent advances in genomics, transcriptomics, proteomics and other multi-omics approaches have substantially improved understanding of pathogen virulence factors, host defense responses and disease epidemiology. These studies have revealed key roles of OA, carbohydrate-active enzymes, effector proteins, and sclerotial melanization in pathogenesis, while highlighting the activation of salicylic acid (SA)-, jasmonic acid (JA)-, and ethylene (ET)-mediated defense pathways in tomato. Although cultural, biological, and chemical measures are available, these measures often provide inconsistent protection when used alone. Promising strategies include the use of biocontrol agents, hypovirulence-inducing mycoviruses, and chemical fungicides such as carboxamides and quinone outside inhibitors (QoIs), though fungicide resistance remains a risk factor. Integrated Disease Management (IDM) approaches, such as combining biocontrol agents with fungicides, demonstrate enhanced efficacy. This review also evaluates progress in resistance breeding, grafting, RNA interference (HIGS and SIGS), CRISPR-based genome editing, and exploitation of wild genotypes for durable resistance. Furthermore, emerging precision agriculture tools, including hyperspectral imaging, machine learning-assisted disease detection and climate-resilient management strategies, were discussed as new components of sustainable disease management. Full article

Research on the cataloging of microstructures and chemical compound localization in peanut hulls in relation to fungal tolerance remains limited. The hull (pericarp) is the first physical interface with the soil environment and may contribute to defense against fungal invasion. Here, hull microstructure and histochemical localization of alkaloid-like compounds, cellulose, lignin, starch, and total proteins were characterized across reproductive developmental stages R3–R6 in three commercially grown cultivars (Georgia-06G, Georgia-12Y, and Georgia-18RU). Stained sections were examined by light and fluorescence microscopy, and images were quantified in Fiji-ImageJ as stained area percentage. Among the compounds studied, the highest area percentages were observed at later stages (R5 and R6). Alkaloid-like compounds, cellulose, and starch were higher at the R5 stages of G-18 (9.61 ± 0.75), G-12Y (22.96 ± 5.84), and G-06 (6.31 ± 1.13) respectively, while lignin and total proteins were highest at the R6 stage of G-18 (respectively, 14.49 ± 1.43 and 13.90 ± 1.45). The lowest histochemical presence for most metabolites occurred in the early stages (R3–R4). This indicates that hull maturation is accompanied by increased physical (sclerenchyma and lignified cells) and biochemical (alkaloid-like compounds, proteins) features consistent with protective roles. As the analysis was based on representative sections and regions of interest (ROI)-level quantification, the results are intended to guide future studies on hull-mediated defense and breeding for Aspergillus tolerance. Full article

Nanofiber scaffolds play a crucial role in bioengineering by providing structural support for tissue and organoid growth. For composite nanofibers, optimizing their properties for specific applications often requires analyzing the spatial distribution of their chemical structure. This review focuses on the applications of Raman hyperspectral imaging to the mapping of the chemical composition of nanofibers. While the technique is diffraction-limited to the size of the scanning beam, it is possible to decipher the nanoscale features of these fibers by employing oversampling during scanning. Subsequently, these oversampled data can be analyzed by a singular-value decomposition (SVD) analysis and classical least-squares (CLS) decomposition. In many cases, this technique is essential for verifying the spatial distribution of different chemical components within multi-component nanofibers. Full article