Search Results (123)

This study evaluated the use of visible and near-infrared (Vis-NIR) spectroscopy combined with machine learning (ML) algorithms to predict soil fertility-related properties in two contrasting agroecological regions of Peru: the Highlands and the Rainforest. A total of 297 soil samples were analyzed using portable spectroradiometers covering a spectral range of 350–2500 nm, applying transformations such as Savitzky–Golay smoothing, first derivative, and band depth. Predictive models were developed using PLSR, Random Forest, Support Vector Machines, and neural networks. Results show variable predictive performance across soil properties and ecosystems. Organic matter in Highland soils and calcium in Rainforest soils achieved the strongest test-set accuracy (R² > 0.70), while pH and texture fractions showed moderate performance (R² = 0.42–0.67), and mobile nutrients including phosphorus, potassium, and sodium showed limited predictive accuracy due to their weak spectral expression. Spectral predictions were further integrated into a structured nutrient balance framework to assess agronomic reliability. Nitrogen fertilizer recommendations showed the strongest agreement between observed and predicted values across both ecosystems, whereas K₂O and CaO recommendations in Highland soils were substantially underestimated, demonstrating that property-level statistical performance does not guarantee agronomic reliability. These findings confirm that Vis-NIR spectroscopy combined with ML represents a fast, cost-effective, and sustainable alternative to conventional soil analysis, especially in rural areas with limited laboratory infrastructure. Expanding regional calibration datasets and exploring mid-infrared FTIR spectroscopy as a complementary technology are identified as priority directions for improving predictions of agronomically critical nutrients. Full article

Reliable analytical methods are essential for the assessment, effective quality control, and guarantee of consistent and reproducible performance of chemical profiles of non-psychoactive low-THC Cannabis sativa L. samples and their products. An integrated analytical approach was applied for the first time to evaluate low-THC C. sativa products on the Serbian legal market using chemometrics combined with five complementary techniques: ultraviolet–visible spectroscopy (UV–Vis), high-performance thin-layer chromatography (HPTLC), portable Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR) and gas chromatography–mass spectrometry (GC–MS). HPTLC rapidly differentiated key cannabinoids with R_F at 0.39 and 0.61, while GC–MS enabled comprehensive identification of major cannabinoids (CBG and CBD). Spectroscopic fingerprints provided characteristic UV–Vis absorption maximum (215, 235, and 275 nm), Raman (1700, 1550, 1517, 1224, 1096 cm⁻¹) and FTIR marker bands (615, 1059, 1288, 1620, 2932 cm⁻¹), supporting robust monitoring. Principal component analysis (PCA) across all five techniques revealed two major distinct sample clusters and identified the most influential analytical signals. The combined separation, spectroscopic, and multivariate approach is proven to be effective for systematic cannabinoid content assessment, authentication, and chemical profiling within a process-oriented context, thus enabling effective quality control in the cultivation process by targeting compounds of interest. Full article

This study assesses indicative technical correspondences and divergences between Francisco de Zurbarán’s painting practices and those observed in the seventeenth-century Óbidos workshop (Baltazar Gomes Figueira and Josefa d’Óbidos). We focus on the composition and function of priming layers, the shadow-to-light painting sequence, and pigment/binder usage. A multi-analytical approach was employed: portable X-ray Fluorescence (XRF), Optical Microscopy on polished cross-sections (OM), Scanning Electron Microscopy in backscattered mode with Energy-Dispersive X-ray analysis (SEM-BSE/EDS), Micro-Confocal Raman Spectroscopy (µ-Raman), and Micro-Fourier Transform Infrared Spectroscopy (µ-FTIR). Rather than treating single pigments as diagnostic, we compare patterns of application and stratigraphic behaviour—notably a two-layer priming, in which a finer, Fe-rich upper layer is actively used to build shadows, and a consistent exploitation of the priming as a value layer in a shadow-to-light sequence. Materials largely overlap, while priming compositions differ, plausibly reflecting local resources. Given the small corpus (two works by Zurbarán, one by Baltazar, and one by Josefa), conclusions are presented as indicative and contextualized within Iberian workshop practice. Full article

To address the issue of normal displacement deviation induced by the geometric nonlinearity of cross-spring flexural pivots in pendulum-type interferometers, which leads to modulation attenuation, this study proposes a co-simulation method combining Finite Element Analysis (FEA) and Physical Optics. First, an optomechanical model was established based on the retroreflective property of cube-corner prisms and a double-pendulum differential scanning architecture (where the optical path difference is four times the mechanical displacement). Using the ANSYS Workbench 2022 R1 transient dynamics module with the “Large Deflection” algorithm enabled, the nonlinear motion trajectories of single-pivot and dual-pivot flexural hinges were quantitatively compared. Subsequently, a multi-physics data mapping interface was established to map mechanical motion errors into a physical optics simulation model, where the interference modulation was accurately calculated via electromagnetic field tracing. Results demonstrate that under ambient temperature (25 °C) and a spectral resolution of 1 cm⁻¹, the normal displacement deviation of the single-pivot hinge is only 0.00165 mm, representing a 95.6% reduction compared to the dual-pivot structure (0.03765 mm). Furthermore, the modulation of the single-pivot structure remains above 0.98 throughout the scanning range, significantly outperforming the nonlinear decay characteristic of the dual-pivot structure. These findings provide a theoretical basis for the structural optimization and selection of high-precision portable FTIR spectrometers. Full article

A highly selective and sensitive compact immunosensing strategy was developed for the determination of DJ-1, a potential biomarker of Parkinson’s disease, one of the leading neurodegenerative disorders, using a portable potentiostat. Initially, screen-printed carbon electrodes (SPCEs) were modified with gold nanoparticles (AuNPs), followed by functionalization with 4-mercapto-1-butanol (MOH). Subsequently, the AuNPs-doped and hydroxyl-functionalized electrodes were treated with 3-glycidoxypropyltrimethoxysilane (GPTMS) to facilitate immobilization of anti-DJ-1 antibodies. Immobilization steps were monitored using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) performed on a bench potentiostat, while the entire analytical performance of the developed biosensor system and its response in artificial cerebrospinal fluid (aCSF) were evaluated by monitoring cathodic current changes with a portable electrochemical reader. The resulting biorecognition element enabled the detection of DJ-1 within the concentration range of 0.001 to 0.3 ng/mL, based on cathodic current changes, achieving a limit of detection as low as 0.00059 ng/mL. Surface morphology and elemental composition alterations were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and energy-dispersive X-ray spectroscopy (EDX). A notable advantage of this GPTMS@AuNPs-based biosensor system is its prolonged storage stability and its capability to accurately quantify DJ-1 in artificial cerebrospinal fluid samples, with recovery rates ranging from 98.66% to 123.3%. Full article

Black crusts are multilayered alteration products that develop on historic masonry exposed to urban pollution. This study investigates the west enclosure wall of the XVII^th-century Golia Monastery in Iași, Romania—located along a busy traffic corridor—and presents multi-analytical results on two lime-based mortar fragments exhibiting well-developed blackened surface layers. Both the exposed (blackened) finishes and protected verso areas were analyzed using portable X-ray fluorescence (pXRF), scanning electron microscopy with energy-dispersive X-ray analysis (SEM–EDX), micro-FTIR spectroscopy, X-ray diffraction (XRD), CIE Lab colorimetry and optical microscopy (OM). The data reveal gypsum-rich surface layers enriched in traffic-derived particles, including metal oxides and soot, with marked contrasts relative to the minimally altered verso. Handheld XRF and SEM–EDX indicate elevated sulfur and associated traffic-related elements within porous gypsum matrices, while FTIR and XRD consistently identify calcium sulfate as the dominant secondary phase. Colorimetric measurements additionally document pronounced lightness loss and visible darkening on exposed surfaces. These results demonstrate the onset of directional sulfation and black crust formation on mortars under urban pollution pressure and establish an integrated analytical protocol for diagnosing black crusts on historic lime mortars in urban heritage settings. Full article

The composition of sunflower oil, rich in fatty acids, largely depends on the seed variety. Commercial sunflower oils are classified as low (SFO), medium (MOSFO), and high (HOSFO) oleic, distinguished by their oleic and linoleic acid content. Higher oleic acid levels enhance health benefits and oxidative stability. Due to their differing market values, ensuring the correct quality and authenticity of these oils is essential. Unsupervised chemometric methods have been applied to visualise the natural behaviour of sunflower oils, while supervised models have been used for authentication based on Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR-FTIR) fingerprints obtained from a benchtop spectrometer. Authentication of MOSFO is particularly challenging because of its wider oleic acid range (43.1–74.9%) and production via genetic modification or blending SFO/HOSFO. To address this, two multivariable PLS-R regression models were developed using ATR FT-IR and Fibre Optic Reflectance Spectroscopy (FORS) fingerprints, the latter obtained with a portable, cost-effective device. The results indicate that FORS could be used as a rapid quality control tool for on-site quantification. In contrast, ATR FT-IR is a more accurate tool for confirmation and quantification, achieving excellent results (Residual Predictive Deviation, RPD = 7.09 and Range Error Ratio, RER = 17.82). Full article

Visible-Near-Infrared (Vis-NIR) spectroscopy, spanning approximately 400 to 2500 nm, is an innovative technology with growing relevance for diagnostics performed at the point of care (POC). This review explores the potential of Vis-NIR in veterinary medicine, highlighting its advantages over complex techniques like Raman and Fourier transform infrared spectroscopy (FTIR) by being rapid, non-invasive, reagent-free, and compatible with miniaturized, portable devices. The methodology involves directing a broadband light source, often using LEDs, toward the sample (e.g., blood, urine, faeces), collecting spectral information related to molecular vibrations, which is then analyzed using chemometric methods. Successful veterinary applications include hemogram analysis in dogs, cats, and Atlantic salmon, and quantifying blood in ovine faeces for parasite detection. Key limitations include spectral interference from strong absorbers like water and hemoglobin, and the limited penetration depth of light. However, combining Vis-NIR with Self-Learning Artificial Intelligence (SLAI) is shown to isolate and mitigate these multi-scale interferences. Vis-NIR spectroscopy serves as an important complement to centralized laboratory testing, holding significant potential to accelerate clinical decisions, minimize stress on animals during assessment, and improve diagnostic capabilities for both human and animal health, aligning with the One Health concept. Full article

This study investigates water-based gel and gel-like cleaning treatments on Superficie 553, an oil painting on canvas by Giuseppe Capogrossi, using portable NMR to assess their impact. The objective was to evaluate the effects of four cleaning systems composed of a buffer solution released in free form and combined with xanthan gum, a cross-linked silicone polymer gel, and an agar gel matrix. Two distinct NMR experiments were conducted. The first involved the acquisition of ¹H depth profiles to detect the distribution of the cleaning solution within the painted layer and the thickness variations resulting from cleaning procedures. The second employed the acquisition of relaxation times, facilitating the investigation of molecular mobility within the organic components of the paint layer. NMR results indicated that the agar gel system caused negligible structural changes, whereas the silicone gel induced rigidification, and the other systems permanently increased molecular mobility. These measurements provided insights into alterations in the dynamic behavior of the polymerized oil. A key strength of this investigation lies in the direct application of diagnostic methods on Superficie 553, made possible by the non-invasive nature and portability of the NMR-MOUSE system. Additionally, portable FTIR was used to detect residues and obtain chemical information, confirming that the silicone gel left detectable residues and identifying the agar gel as the most conservative cleaning method. This enabled in situ analysis of the original artwork without sampling or relocation—a crucial advantage given the difficulty of replicating the complex physicochemical conditions of historical paint surfaces under laboratory constraints. Such real-time, on-site monitoring ensured an authentic evaluation of the treatment effects, preserving the integrity of the artwork throughout the conservation process. Full article

Workers’ exposure to silica dust is a global occupational and public health concern and is particularly prevalent in Southern Africa, mainly because of inadequate dust control measures. It is worsened by the high prevalence of HIV/AIDS, which exacerbates tuberculosis and other occupational lung diseases. The prevalence of silicosis in the region ranges from 9 to 51%; however, silica dust exposure levels and controls, especially in the informal mining sector, particularly in artisanal small-scale mines (ASMs), leave much to be desired. This is important because silicosis is incurable and can only be eliminated by preventing worker exposure. Additionally, several studies have indicated inadequate occupational health and safety policies, weak inspection systems, inadequate monitoring and control technologies, and inadequate occupational health and hygiene skills. Furthermore, there is a near-absence of silica dust analysis laboratories in southern Africa, except in South Africa. This protocol aims to systematically evaluate the effectiveness of respirable dust and respirable crystalline silica dust exposure evaluation and control methodology for the mining industry. The study will entail testing the effectiveness of current dust control measures for controlling microscale particles using various exposure dose metrics, such as mass, number, and lung surface area concentrations. This will be achieved using a portable Fourier transform infrared spectroscope (FTIR) (Nanozen Industries Inc., Burnaby, BC, Canada), the Nanozen DustCount, which measures both the mass and particle size distribution. The surface area concentration will be analysed by inputting the particle size distribution (PSD) results into the Multiple-Path Particle Dosimetry Model (MPPD) to estimate the retained and cleared doses. The MPPD will help us understand the sub-micron dust deposition and the reduction rate using the controls. To the best of our knowledge, the proposed approach has never been used elsewhere or in our settings. The proposed approach will reduce dependence on highly skilled individuals, reduce the turnaround sampling and analysis time, and provide a reference for regional harmonised occupational exposure limit (OEL) guidelines as a guiding document on how to meet occupational health, safety and environment (OHSE) requirements in ASM settings. Therefore, the outcome of this study will influence policy reforms and protect hundreds of thousands of employees currently working without any form of exposure prevention or protection. Full article

This study evaluated the combined effect of the modified atmosphere packaging (MAP1: 60% CO₂, 10% O₂/30% N₂ & MAP2: 40% CO₂, 30% O₂/30% N₂), and active packaging of oregano essential oil (1% v/w) used as a natural preservative, on the quality and shelf-life extension of fresh sea bream fillets. The samples were stored at four different temperatures (0, 4, 8, and 12 °C), and a microbiological analysis, pH measurements, and sensory evaluations were performed. In parallel, spectral data were obtained using three different spectroscopic sensors (two MultiSpectral Imaging devices and an FT-IR one), and nine different machine-learning regression models were applied to predict the microbiological counts. Oregano essential oil positively affected preservation, reducing microbial growth by 0.5 to 2 log CFU/g, and extending the fillets’ shelf life by up to 48 h based on sensory evaluation. Regarding the sensors’ data, the examined nine models exhibited encouraging results for the rapid microbiological assessment, with the FT-IR data showing the best performance for evaluating the microbiological population. Among the tested algorithms, the least Angle Regression (lars) achieved the best performance for both the flesh and skin datasets, with RMSE values of 0.6075 and 0.5953, MAE of 0.3008 and 0.4567, R² of 0.8858 and 0.7532, and accuracy of 87% and 91%, respectively. The Benchtop-MSI showed the best predictive performance for flesh (RMSE = 0.5926, MAE = 0.4876, R² = 0.7338, and Accuracy = 92%), while the artificial neural network (nnet) performed best for skin (RMSE = 0.6761, MAE = 0.5247, R² = 0.6560, and Accuracy = 84%). Regarding the Portable-MSI, the artificial neural network model gave the highest accuracy for flesh (RMSE = 0.5908, MAE = 0.4663, R² = 0.5903, and Accuracy = 87%), whereas principal component regression was the most effective for skin (RMSE = 0.6600, MAE = 0.5413, R² = 0.5534, and Accuracy = 83%). Full article

Livestock farming represents one of the primary sources of ammonia (NH₃) and greenhouse gas (GHG) emissions, including methane (CH₄), nitrous oxide (N₂O), and carbon dioxide (CO₂), having a significant environmental impact. Reducing emissions and recovering gas systems from these livestock buildings necessitate measuring gas concentrations to mitigate environmental impacts using an accurate, high-cost portable device. This study aims to evaluate the concentration of NH₃ and GHGs in a semi-open dairy farm located in southern Sicily, a region with a hot climate. The measurement campaign was carried out during the spring of 2025. The concentrations of NH₃, CH₄, CO_2, and N₂O were measured in different barn areas (i.e., manger, feeding alley, and service alley) using a portable gas detector (GASMET GT5000) based on Fourier Transform Infrared (FTIR) technology. Statistical analysis revealed that NH₃ concentrations were highest in the feeding alley, while CH₄ concentrations peaked at the manger. N₂O levels stayed low because there was no straw. Future research should investigate gas concentrations across different seasons (e.g., winter, summer) to analyze gas patterns under different climatic conditions. Additionally, the use of an accurate portable device enables further investigations into other barn typologies within the Mediterranean area to assess how farm construction and management practices influence gas production. Full article

Two folding screens by futurist artist Giacomo Balla (1871–1958) in the collection of the Kröller-Müller Museum (the Netherlands) were investigated: Paravento con linea di velocità (1916–1917) and Paravento (1916/1917–1958). The screens are painted on both sides, the first on four canvases, stretched onto two wooden strainers and framed with painted wooden strips, and the second on wooden panels set into four painted stiles. In the past, damages on Paravento con linea di velocità were restored by conservators, while Paravento was probably first reworked by the artist himself and later restored by conservators. Yellowed varnish and discolored retouches on both screens led to a wish for treatment. The aim of this research was to gain insight into the painting techniques, layer buildup, pigments, binders, and varnishes of the two artworks. This information supported the decision making for treatment, and it broadens the knowledge on the materials used by Balla. Up to now, only a few published studies deal with the technical examination of paintings by this artist. Both folding screens were subjected to technical photography (UV, IR photography, and X-ray) and were examined with portable point X-ray fluorescence (pXRF) and Raman spectroscopy. Moreover, samples were taken. Cross-sections were studied with optical microscopy, scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), attenuated total reflection Fourier-transform infrared (ATR-FTIR) imaging, and micro-Raman spectroscopy. Loose samples were examined with SEM-EDX, FTIR and micro-Raman spectroscopy, and pyrolysis gas chromatography mass spectrometry (Py-GC/MS). For Paravento con linea di velocità, all pigments and fillers of the painted canvases are compatible with the dating of the screen (1916–1917), but they differ from those on the frame. Here, rutile, in combination with various pigments, among which are blue copper phthalocyanine (PB15) and other synthetic organic pigments, was found. This indicates that the frame has been painted later, likely after the Second World War. The composition of the binders differs as well. Drying oil and pine resin have been used on the canvases, explaining the smooth and glossy appearance and solvent-sensitivity of the paint. On the frame, oil with some alkyd resin was identified. The provenance of the screen before 1972 is not clear, nor when the frame was made and painted and by whom. The results for Paravento indicate that the palettes of the two sides—painted in different styles—are comparable. Mainly inorganic pigments were found, except for the dark red areas, where toluidine red (PR3) is present. pXRF showed high amounts of zinc; cross-sections revealed that zinc white is present in the lower layers. These pigments are compatible with the dating of the screen (1916–1917). In many of the upper paint layers though, except for some green, dark red, and black areas, rutile has been identified. This indicates that these layers were applied later, likely after the Second World War. Since this folding screen was used by the artist and his family until his death in 1958, it seems likely that Balla himself reworked the screen. Full article

Prostate cancer remains one of the most prevalent malignancies among men worldwide, with late-stage diagnosis contributing significantly to mortality rates. In this study, we report the development of a graphene oxide (GO)-based QCM biosensor for the early and sensitive detection of Prostate Cancer Antigen 3 (PCA3), a biomarker with higher specificity than conventional PSA tests. The sensor interface was fabricated via a layer-by-layer approach of L-cysteine, GO, and a capture probe onto a gold electrode, resulting in enhanced surface area and biomolecular recognition capacity. Structural and morphological characterizations using XRD, FE-SEM, AFM, and FT-IR confirmed the successful and uniform integration of GO and functional layers. Optimization of fabrication parameters, including EDC-NHS activation time, capture probe concentration, and target incubation time, was performed to achieve maximum sensitivity and binding efficiency. The biosensor demonstrated a distinct, concentration-dependent frequency shift upon hybridization with PCA3 targets over a range of 1.00 fM to 1.00 μM, with a calculated limit of detection (LOD) of 0.268 nM and a rapid response time of 20 min. These results underscore the potential of GO-modified QCM platforms for highly sensitive, rapid, and portable diagnostics, not only for prostate cancer screening but also for broader clinical applications involving biomarkers. Full article

Foodborne illnesses remain a global challenge, requiring rapid and sensitive detection platforms. We developed a magnetosome-based electrochemical immunosensor for lipopolysaccharide (LPS) antigens from Escherichia coli and Salmonella typhimurium. Magnetosomes isolated from Magnetospirillum sp. RJS1 were characterized by HR-TEM and functionalized with antibodies (2 CFU mL⁻¹), with FTIR confirming successful conjugation. The antibody–magnetosome complexes were immobilized on a chitosan/glutaraldehyde-modified glassy carbon electrode. AFM revealed globular (200–700 nm) and island-like (1–3 µm) features after antigen binding. Electrochemical impedance spectroscopy showed stepwise increases in charge-transfer resistance upon electrode modification and antigen interaction. The sensor exhibited high sensitivity toward E. coli (3–7 CFU mL⁻¹) and Salmonella (3–8 CFU mL⁻¹), achieving an immune sensitivity of 36.24 Ω/CFU mL⁻¹ and a detection limit of 1 CFU mL⁻¹. These results demonstrate the potential of magnetosome-based immunosensors as portable, efficient platforms for the rapid detection of foodborne pathogens in real samples. Full article