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Search Results (1,446)

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Keywords = precision spectroscopy

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18 pages, 4008 KiB  
Article
Carboxymethyl Chitosan Cinnamaldehyde Coated SilverNanocomposites for Antifungal Seed Priming in Wheat: A Dual-Action Approach Toward Sustainable Crop Protection
by María Mondéjar-López, María Paz García-Simarro, Lourdes Gómez-Gómez, Oussama Ahrazem and Enrique Niza
Polymers 2025, 17(15), 2031; https://doi.org/10.3390/polym17152031 (registering DOI) - 25 Jul 2025
Abstract
Biogenic silver nanoparticles (AgNPs) were synthesized via a green chemistry strategy using wheat extract and subsequently functionalized with a carboxymethyl chitosan–cinnamaldehyde (CMC=CIN) conjugate through covalent imine bonding. The resulting nanohybrid (AgNP–CMC=CIN) was extensively characterized to confirm successful biofunctionalization: UV–Vis spectroscopy revealed characteristic cinnamaldehyde [...] Read more.
Biogenic silver nanoparticles (AgNPs) were synthesized via a green chemistry strategy using wheat extract and subsequently functionalized with a carboxymethyl chitosan–cinnamaldehyde (CMC=CIN) conjugate through covalent imine bonding. The resulting nanohybrid (AgNP–CMC=CIN) was extensively characterized to confirm successful biofunctionalization: UV–Vis spectroscopy revealed characteristic cinnamaldehyde absorption peaks; ATR-FTIR spectra confirmed polymer–terpene bonding; and TEM analysis evidenced uniform nanoparticle morphology. Dynamic light scattering (DLS) measurements indicated an increase in hydrodynamic size upon coating (from 59.46 ± 12.63 nm to 110.17 ± 4.74 nm), while maintaining low polydispersity (PDI: 0.29 to 0.27) and stable surface charge (zeta potential ~ −30 mV), suggesting colloidal stability and homogeneous polymer encapsulation. Antifungal activity was evaluated against Fusarium oxysporum, Penicillium citrinum, Aspergillus niger, and Aspergillus brasiliensis. The minimum inhibitory concentration (MIC) against F. oxysporum was significantly reduced to 83 μg/mL with AgNP–CMC=CIN, compared to 708 μg/mL for uncoated AgNPs, and was comparable to the reference fungicide tebuconazole (52 μg/mL). Seed priming with AgNP–CMC=CIN led to improved germination (85%) and markedly reduced fungal colonization, while maintaining a favorable phytotoxicity profile. These findings highlight the potential of polysaccharide-terpene-functionalized biogenic AgNPs as a sustainable alternative to conventional fungicides, supporting their application in precision agriculture and integrated crop protection strategies. Full article
(This article belongs to the Special Issue Polymer Materials for Environmental Applications)
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14 pages, 7820 KiB  
Article
Role of Dystrophic Calcification in Reparative Dentinogenesis After Rat Molar Pulpotomy
by Naoki Edanami, Kunihiko Yoshiba, Razi Saifullah Ibn Belal, Nagako Yoshiba, Shoji Takenaka, Naoto Ohkura, Shintaro Takahara, Takako Ida, Rosa Baldeon, Susan Kasimoto, Pemika Thongtade and Yuichiro Noiri
Int. J. Mol. Sci. 2025, 26(15), 7130; https://doi.org/10.3390/ijms26157130 - 24 Jul 2025
Abstract
Vital pulp therapy with calcium hydroxide or mineral trioxide aggregate (MTA) rapidly induces dystrophic calcification and promotes the accumulation of two members of small integrin-binding ligand N-linked glycoproteins: osteopontin (OPN) and dentin matrix protein-1 (DMP1). However, the precise relationship between these initial events [...] Read more.
Vital pulp therapy with calcium hydroxide or mineral trioxide aggregate (MTA) rapidly induces dystrophic calcification and promotes the accumulation of two members of small integrin-binding ligand N-linked glycoproteins: osteopontin (OPN) and dentin matrix protein-1 (DMP1). However, the precise relationship between these initial events and their roles in reparative dentinogenesis remain unclear. This study aimed to clarify the relationship between dystrophic calcification, OPN and DMP1 accumulation, and reparative dentin formation. Pulpotomy was performed on rat molars using MTA or zirconium oxide (ZrO2). ZrO2 was used as a control to assess pulp healing in the absence of dystrophic calcification. Pulpal responses were evaluated from 3 h to 7 days postoperatively via elemental mapping, micro-Raman spectroscopy, and histological staining. In the MTA-treated group, a calcium-rich dystrophic calcification zone containing calcite and hydroxyapatite was observed at 3 h after treatment; OPN and DMP1 accumulated under the dystrophic calcification zone by day 3; reparative dentin formed below the region of OPN and DMP1 accumulation by day 7. In contrast, these reactions did not occur in the ZrO2-treated group. These results suggest that dystrophic calcification serves as a key trigger for OPN and DMP1 accumulation and plays a pivotal role in reparative dentinogenesis. Full article
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13 pages, 1704 KiB  
Article
Rapid High-Accuracy Quantitative Analysis of Water Hardness by Combination of One-Point Calibration Laser-Induced Breakdown Spectroscopy and Aerosolization
by Ting Luo, Weihua Huang, Riheng Chen, Furong Chen, Jinke Chen, Zhenlin Hu and Junfei Nie
Chemosensors 2025, 13(8), 271; https://doi.org/10.3390/chemosensors13080271 - 23 Jul 2025
Viewed by 85
Abstract
Water quality should be tested to ensure it is acceptable for the healthy growth of plants and animals, and water hardness is one of the important testing indexes. Herein, a novel approach was proposed to achieve high accuracy and rapid quantitative analyses of [...] Read more.
Water quality should be tested to ensure it is acceptable for the healthy growth of plants and animals, and water hardness is one of the important testing indexes. Herein, a novel approach was proposed to achieve high accuracy and rapid quantitative analyses of water hardness by combining one-point calibration laser-induced breakdown spectroscopy (OPC–LIBS) and aerosolization. First, the water samples are aerosolized via the aerosol generation device and the LIBS spectra of aerosols are obtained. Then, a modified OPC–LIBS model is used to determine the elemental contents of the aerosols via LIBS spectra, in which the plasma temperature is calculated using the Multi-Element Saha–Boltzmann (ME–SB) plot. One suitable standard liquid sample (the concentrations of Ca, Mg, and Sr were 50 mg/L, 50 mg/L, and 500 mg/L, respectively) was selected to evaluate the quantitative performance of the modified OPC–LIBS. Then, the Ca and Mg concentrations in the three real water samples (from the Yangtze River, reservoir, and underground) were detected and quantified by the proposed method, and the quantitative results of three LIBS calibration methods were compared with that of inductively coupled plasma optical emission spectroscopy (ICP–OES). The average relative error of Ca and Mg found in the OPC–LIBS results was lower by 22.23% than the internal standard method and 14.50% lower than the external standard method. The method combining modified OPC–LIBS and aerosolization can achieve high-precision rapid quantification of water hardness detection, which provides a new path for rapid detection of water hardness and is expected to make online detection a reality in the water quality testing field. Full article
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41 pages, 3816 KiB  
Review
Updates on the Advantages and Disadvantages of Microscopic and Spectroscopic Characterization of Magnetotactic Bacteria for Biosensor Applications
by Natalia Lorela Paul, Catalin Ovidiu Popa and Rodica Elena Ionescu
Biosensors 2025, 15(8), 472; https://doi.org/10.3390/bios15080472 - 22 Jul 2025
Viewed by 131
Abstract
Magnetotactic bacteria (MTB), a unique group of Gram-negative prokaryotes, have the remarkable ability to biomineralize magnetic nanoparticles (MNPs) intracellularly, making them promising candidates for various biomedical applications such as biosensors, drug delivery, imaging contrast agents, and cancer-targeted therapies. To fully exploit the potential [...] Read more.
Magnetotactic bacteria (MTB), a unique group of Gram-negative prokaryotes, have the remarkable ability to biomineralize magnetic nanoparticles (MNPs) intracellularly, making them promising candidates for various biomedical applications such as biosensors, drug delivery, imaging contrast agents, and cancer-targeted therapies. To fully exploit the potential of MTB, a precise understanding of the structural, surface, and functional properties of these biologically produced nanoparticles is required. Given these concerns, this review provides a focused synthesis of the most widely used microscopic and spectroscopic methods applied in the characterization of MTB and their associated MNPs, covering the latest research from January 2022 to May 2025. Specifically, various optical microscopy techniques (e.g., transmission electron microscopy (TEM), scanning electron microscopy (SEM), and atomic force microscopy (AFM)) and spectroscopic approaches (e.g., localized surface plasmon resonance (LSPR), surface-enhanced Raman scattering (SERS), and X-ray photoelectron spectroscopy (XPS)) relevant to ultrasensitive MTB biosensor development are herein discussed and compared in term of their advantages and disadvantages. Overall, the novelty of this work lies in its clarity and structure, aiming to consolidate and simplify access to the most current and effective characterization techniques. Furthermore, several gaps in the characterization methods of MTB were identified, and new directions of methods that can be integrated into the study, analysis, and characterization of these bacteria are suggested in exhaustive manner. Finally, to the authors’ knowledge, this is the first comprehensive overview of characterization techniques that could serve as a practical resource for both younger and more experienced researchers seeking to optimize the use of MTB in the development of advanced biosensing systems and other biomedical tools. Full article
(This article belongs to the Special Issue Material-Based Biosensors and Biosensing Strategies)
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17 pages, 2940 KiB  
Article
Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug Substance
by Bo Chen, Zhilong Tang, Zhenxing Zhu, Yang Xiao, Guangyao Mei and Xingchu Gong
Chemosensors 2025, 13(7), 265; https://doi.org/10.3390/chemosensors13070265 - 21 Jul 2025
Viewed by 106
Abstract
Stability assessments of drug substances and the detection of crystalline forms are critical for ensuring drug quality and medication safety. Atorvastatin calcium drug substance samples were characterized using powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC). DSC results demonstrated a precise discrimination [...] Read more.
Stability assessments of drug substances and the detection of crystalline forms are critical for ensuring drug quality and medication safety. Atorvastatin calcium drug substance samples were characterized using powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC). DSC results demonstrated a precise discrimination of the stability of samples. An analysis of PXRD characteristic peaks and DSC melting data suggested that instability likely stems from the presence of the amorphous phase. To validate this hypothesis, blended samples containing controlled ratios of amorphous phase and crystalline Form I were prepared. Quantitative models based on PXRD, DSC, and near-infrared spectroscopy (NIRS) data were developed to predict amorphous content, and classification accuracy was evaluated. Experimental results confirmed that all three models achieved classification accuracy values exceeding 70% in the stability prediction of the two groups of samples, which included “stable” and “unstable” samples, substantiating the hypothesis. Among them, the modeling method based on NIRS data was not only non-destructive and rapid but also demonstrates a superior discrimination accuracy value reaching 100% (n = 11), showing potential for promotion and application in industrial sample detection. The quantitative correlation between amorphous content and stability was successfully established in this study, offering a novel method for a quality stability assessment of atorvastatin calcium drug substances. Full article
(This article belongs to the Special Issue Spectroscopic Techniques for Chemical Analysis)
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15 pages, 2325 KiB  
Article
Research on Quantitative Analysis Method of Infrared Spectroscopy for Coal Mine Gases
by Feng Zhang, Yuchen Zhu, Lin Li, Suping Zhao, Xiaoyan Zhang and Chaobo Chen
Molecules 2025, 30(14), 3040; https://doi.org/10.3390/molecules30143040 - 20 Jul 2025
Viewed by 161
Abstract
Accurate and reliable detection of coal mine gases is the key to ensuring the safe service of coal mine production. Fourier Transform Infrared (FTIR) spectroscopy, due to its high sensitivity, non-destructive nature, and potential for online monitoring, has emerged as a key technique [...] Read more.
Accurate and reliable detection of coal mine gases is the key to ensuring the safe service of coal mine production. Fourier Transform Infrared (FTIR) spectroscopy, due to its high sensitivity, non-destructive nature, and potential for online monitoring, has emerged as a key technique in gas detection. However, the complex underground environment often causes baseline drift in IR spectra. Furthermore, the variety of gas species and uneven distribution of concentrations make it difficult to achieve precise and reliable online analysis using existing quantitative methods. This paper aims to perform a quantitative analysis of coal mine gases by FTIR. It utilized the adaptive smoothness parameter penalized least squares method to correct the drifted spectra. Subsequently, based on the infrared spectral distribution characteristics of coal mine gases, they could be classified into gases with mutually distinct absorption peaks and gases with overlapping absorption peaks. For gases with distinct absorption peaks, three spectral lines, including the absorption peak and its adjacent troughs, were selected for quantitative analysis. Spline fitting, polynomial fitting, and other curve fitting methods are used to establish a functional relationship between characteristic parameters and gas concentration. For gases with overlapping absorption peaks, a wavelength selection method bassed on the impact values of variables and population analysis was applied to select variables from the spectral data. The selected variables were then used as input features for building a model with a backpropagation (BP) neural network. Finally, the proposed method was validated using standard gases. Experimental results show detection limits of 0.5 ppm for CH4, 1 ppm for C2H6, 0.5 ppm for C3H8, 0.5 ppm for n-C4H10, 0.5 ppm for i-C4H10, 0.5 ppm for C2H4, 0.2 ppm for C2H2, 0.5 ppm for C3H6, 1 ppm for CO, 0.5 ppm for CO2, and 0.1 ppm for SF6, with quantification limits below 10 ppm for all gases. Experimental results show that the absolute error is less than 0.3% of the full scale (F.S.) and the relative error is within 10%. These results demonstrate that the proposed infrared spectral quantitative analysis method can effectively analyze mine gases and achieve good predictive performance. Full article
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16 pages, 4720 KiB  
Article
Optical Response Tailoring via Morphosynthesis of Ag@Au Nanoparticles
by David Oswaldo Romero-Quitl, Siva Kumar Krishnan, Martha Alicia Palomino-Ovando, Orlando Hernández-Cristobal, José Concepción Torres-Guzmán, Jesús Eduardo Lugo and Miller Toledo-Solano
Nanomaterials 2025, 15(14), 1125; https://doi.org/10.3390/nano15141125 - 19 Jul 2025
Viewed by 211
Abstract
We present a simple method for customizing the optical characteristics of gold-core, silver-shell (Au@Ag) nanoparticles through controlled morphosynthesis via a seed-mediated chemical reduction approach. By systematically adjusting the concentration of cetyltrimethylammonium chloride (CTAC), we obtained precise control over both the thickness of the [...] Read more.
We present a simple method for customizing the optical characteristics of gold-core, silver-shell (Au@Ag) nanoparticles through controlled morphosynthesis via a seed-mediated chemical reduction approach. By systematically adjusting the concentration of cetyltrimethylammonium chloride (CTAC), we obtained precise control over both the thickness of the Ag shell and the particle shape, transitioning from spherical nanoparticles to distinctly defined nanocubes. Bright field and high-angle annular dark-field scanning transmission electron microscopy (BF-STEM and HAADF-STEM), and energy-dispersive X-ray spectroscopy (EDS) were employed to validate the structural and compositional changes. To link morphology with optical behavior, we utilized the Mie and Maxwell–Garnett theoretical models to simulate the dielectric response of the core–shell nanostructures, showing trends that align with experimental UV-visible absorption spectra. This research presents an easy and adjustable method for modifying the plasmonic properties of Ag@Au nanoparticles by varying their shape and shell, offering opportunities for advanced applications in sensing, photonics, and nanophotonics. Full article
(This article belongs to the Section Nanophotonics Materials and Devices)
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26 pages, 2816 KiB  
Review
Non-Destructive Detection of Soluble Solids Content in Fruits: A Review
by Ziao Gong, Zhenhua Zhi, Chenglin Zhang and Dawei Cao
Chemistry 2025, 7(4), 115; https://doi.org/10.3390/chemistry7040115 - 18 Jul 2025
Viewed by 244
Abstract
Soluble solids content (SSC) in fruits, as one of the key indicators of fruit quality, plays a critical role in postharvest quality assessment and grading. While traditional destructive methods can provide precise measurements of sugar content, they have limitations such as damaging the [...] Read more.
Soluble solids content (SSC) in fruits, as one of the key indicators of fruit quality, plays a critical role in postharvest quality assessment and grading. While traditional destructive methods can provide precise measurements of sugar content, they have limitations such as damaging the fruit’s integrity and the inability to perform rapid detection. In contrast, non-destructive detection technologies offer the advantage of preserving the fruit’s integrity while enabling fast and efficient sugar content measurements, making them highly promising for applications in fruit quality detection. This review summarizes recent advances in non-destructive detection technologies for fruit sugar content measurement. It focuses on elucidating the principles, advantages, and limitations of mainstream technologies, including near-infrared spectroscopy (NIR), X-ray technology, computer vision (CV), electronic nose (EN) technology and so on. Critically, our analysis identifies key challenges hindering the broader implementation of these technologies, namely: the integration and optimization of multi-technology approaches, the development of robust intelligent and automated detection systems, and issues related to high equipment costs and barriers to widespread adoption. Based on this assessment, we conclude by proposing targeted future research directions. These focus on overcoming the identified challenges to advance the development and practical application of non-destructive SSC detection technologies, ultimately contributing to the modernization and intelligentization of the fruit industry. Full article
(This article belongs to the Section Food Science)
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15 pages, 1642 KiB  
Article
Cryogenic System for FTIR Analysis of Hydrocarbon Fuels at Low Temperature and Atmospheric Pressure
by Gulzhan Turlybekova, Alisher Kenbay, Abdurakhman Aldiyarov, Yevgeniy Korshikov, Aidos Lesbayev, Assel Nurmukan and Darkhan Yerezhep
Appl. Sci. 2025, 15(14), 7944; https://doi.org/10.3390/app15147944 - 17 Jul 2025
Viewed by 229
Abstract
This study presents a novel approach to FTIR spectroscopy at low temperatures under atmospheric pressure. The work aimed to confirm the efficiency of a fundamentally new cryogenic setup that enables material research under the specified conditions. The new technique combines a nitrogen-based cryogenic [...] Read more.
This study presents a novel approach to FTIR spectroscopy at low temperatures under atmospheric pressure. The work aimed to confirm the efficiency of a fundamentally new cryogenic setup that enables material research under the specified conditions. The new technique combines a nitrogen-based cryogenic capillary cooling system with precise temperature monitoring via a PID controller, along with DRIFT spectroscopy for hydrocarbon materials. New fundamental data were obtained on the properties and behavior of hydrocarbon compounds such as methanol, kerosene, and ethanol. The IR spectra of these samples contain key characteristic vibrations of hydrocarbon functional groups, which demonstrate the effective operability of the cryogenic device. A detailed description of the setup and measurement technique is provided, along with a thorough comparison of the results with data from other authors. The application scope of the cryogenic device, the relevance of the research, and potential future developments are also discussed. Full article
(This article belongs to the Special Issue Advanced Spectroscopy Technologies)
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16 pages, 3149 KiB  
Article
Electrochemical Sensing of Dopamine Neurotransmitter by Deep Eutectic Solvent–Carbon Black–Crosslinked Chitosan Films: Charge Transfer Kinetic Studies and Biological Sample Analysis
by Alencastro Gabriel Ribeiro Lopes, Rafael Matias Silva, Orlando Fatibello-Filho and Tiago Almeida Silva
Chemosensors 2025, 13(7), 254; https://doi.org/10.3390/chemosensors13070254 - 12 Jul 2025
Viewed by 316
Abstract
Dopamine (DA) is a neurotransmitter responsible for important functions in mammals’ bodies, including mood, movement and motivation. High or low dopamine levels are associated mainly with mental illnesses such as schizophrenia and depression. Therefore, contributing to the development of electrochemical devices to precisely [...] Read more.
Dopamine (DA) is a neurotransmitter responsible for important functions in mammals’ bodies, including mood, movement and motivation. High or low dopamine levels are associated mainly with mental illnesses such as schizophrenia and depression. Therefore, contributing to the development of electrochemical devices to precisely determine the DA levels in urine samples, a simple and low-cost sensor is proposed in this work. The proposed sensor design is based on crosslinked chitosan films combining carbon black (CB) and deep eutectic solvents (DESs), incorporated onto the surface of a glassy carbon electrode (GCE). Fourier Transform Infrared Spectroscopy (FT-IR) was applied to characterize the produced DESs and their precursors, while the films were characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The sensor modified with CB and DES–ethaline (DES (ETHA)-CB/GCE) showed a significantly enhanced analytical signal for DA using differential pulse voltammetry under the optimized working conditions. Moreover, a better heterogeneous electron transfer rate constant (k0) was obtained, about 45 times higher than that of the bare GCE. The proposed sensor achieved a linear response range of 0.498 to 26.8 µmol L−1 and limits of detection and quantification of 80.7 and 269 nmol L−1, respectively. Moreover, the sensor was successfully applied in the quantification of DA in the synthetic urine samples, with recovery results close to 100%. Furthermore, the sensor presented good precision, as shown from the repeatability tests. The presented method to electrochemically detect DA has proven to be efficient and simple compared to the conventional methods commonly reported. Full article
(This article belongs to the Special Issue Electrochemical Sensing in Medical Diagnosis)
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9 pages, 856 KiB  
Article
The Application of Quantitative 1H-NMR for the Determination of Melatonin and Vitamin B6 in Commercial Melatonin Products
by Xinyu Gao, Jiahao Niu, Zhengjian Xiao, Da Rong, Mingming Yu, Sherwin K. B. Sy, Cong Wang and Zhihua Lv
Molecules 2025, 30(14), 2942; https://doi.org/10.3390/molecules30142942 - 11 Jul 2025
Viewed by 254
Abstract
Melatonin supplements have been widely used to improve sleep quality and overcome sleep disorders, with melatonin and vitamin B6 serving as the primary active ingredients. This study developed a novel analytical method for the simultaneous quantification of melatonin and vitamin B6 using 1 [...] Read more.
Melatonin supplements have been widely used to improve sleep quality and overcome sleep disorders, with melatonin and vitamin B6 serving as the primary active ingredients. This study developed a novel analytical method for the simultaneous quantification of melatonin and vitamin B6 using 1H-NMR spectroscopy. The characteristic signals of melatonin and vitamin B6 hydrochloride at δ 7.09 ppm and δ 8.12 ppm were selected for quantitative analysis, with maleic acid used as the internal standard. The method was validated for specificity, precision, and stability. The results demonstrate that the method exhibits high precision and complies with the guidelines established by the China Food and Drug Administration (CFDA). Furthermore, this method has been successfully applied to commercially available formulations. Compared to conventional methods, the 1H-NMR technique offers a more efficient and simpler alternative, making it suitable for the simultaneous quantitative determination of melatonin and vitamin B6 hydrochloride. This approach ensures the quality, stability, and safety of commercial melatonin products. Full article
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31 pages, 6826 KiB  
Article
Machine Learning-Assisted NIR Spectroscopy for Dynamic Monitoring of Leaf Potassium in Korla Fragrant Pear
by Mingyang Yu, Weifan Fan, Junkai Zeng, Yang Li, Lanfei Wang, Hao Wang, Feng Han and Jianping Bao
Agronomy 2025, 15(7), 1672; https://doi.org/10.3390/agronomy15071672 - 10 Jul 2025
Viewed by 225
Abstract
Potassium (K), a critical macronutrient for the growth and development of Korla fragrant pear (Pyrus sinkiangensis Yu), plays a pivotal regulatory role in sugar-acid metabolism. Furthermore, K exhibits a highly specific response in near-infrared (NIR) spectroscopy compared to elements such as nitrogen (N) [...] Read more.
Potassium (K), a critical macronutrient for the growth and development of Korla fragrant pear (Pyrus sinkiangensis Yu), plays a pivotal regulatory role in sugar-acid metabolism. Furthermore, K exhibits a highly specific response in near-infrared (NIR) spectroscopy compared to elements such as nitrogen (N) and phosphorus (P). Given its fundamental impact on fruit quality parameters, the development of rapid and non-destructive techniques for K determination is of significant importance for precision fertilization management. By measuring leaf potassium content at the fruit setting, expansion, and maturity stages (decreasing from 1.60% at fruit setting to 1.14% at maturity), this study reveals its dynamic change pattern and establishes a high-precision prediction model by combining near-infrared spectroscopy (NIRS) with machine learning algorithms. “Near-infrared spectroscopy coupled with machine learning can enable accurate, non-destructive monitoring of potassium dynamics in Korla pear leaves, with prediction accuracy (R2) exceeding 0.86 under field conditions.” We systematically collected a total of 9000 leaf samples from Korla fragrant pear orchards and acquired spectral data using a benchtop near-infrared spectrometer. After preprocessing and feature extraction, we determined the optimal modeling method for prediction accuracy through comparative analysis of multiple models. Multiplicative scatter correction (MSC) and first derivative (FD) are synergistically employed for preprocessing to eliminate scattering interference and enhance the resolution of characteristic peaks. Competitive adaptive reweighted sampling (CARS) is then utilized to screen five potassium-sensitive bands, specifically in the regions of 4003.5–4034.35 nm, 4458.62–4562.75 nm, and 5145.15–5249.29 nm, among others, which are associated with O-H stretching vibration and changes in water status. A comparison between random forest (RF) and BP neural network indicates that the MSC + FD–CARS–BP model exhibits the optimal performance, achieving coefficients of determination (R2) of 0.96% and 0.86% for the training and validation sets, respectively, root mean square errors (RMSE) of 0.098% and 0.103%, a residual predictive deviation (RPD) greater than 3, and a ratio of performance to interquartile range (RPIQ) of 4.22. Parameter optimization revealed that the BPNN model achieved optimal stability with 10 neurons in the hidden layer. The model facilitates rapid and non-destructive detection of leaf potassium content throughout the entire growth period of Korla fragrant pears, supporting precision fertilization in orchards. Moreover, it elucidates the physiological mechanism by which potassium influences spectral response through the regulation of water metabolism. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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16 pages, 533 KiB  
Review
Challenges in the Diagnosis of Biliary Stricture and Cholangiocarcinoma and Perspectives on the Future Applications of Advanced Technologies
by Kevin Gaston, Abdelkhalick Mohammad, Suresh Vasan Venkatachalapathy, Ioan Notingher, George S. D. Gordon, Arvind Arora, Frankie J. Rawson, Jane I. Grove, Abhik Mukherjee, Dhanny Gomez, Padma-Sheela Jayaraman and Guruprasad P. Aithal
Cancers 2025, 17(14), 2301; https://doi.org/10.3390/cancers17142301 - 10 Jul 2025
Viewed by 341
Abstract
In the management of cholangiocarcinoma, effective biliary drainage and accurate diagnosis are vital to allow further treatment. Confirmation of tissue diagnosis and molecular characterization is also required to guide future treatment options including surgery and chemotherapy as well as the possible use of [...] Read more.
In the management of cholangiocarcinoma, effective biliary drainage and accurate diagnosis are vital to allow further treatment. Confirmation of tissue diagnosis and molecular characterization is also required to guide future treatment options including surgery and chemotherapy as well as the possible use of personalized treatments that target specific mutations present within individual tumours. Initial CT or MRI scans may be followed by endoscopic ultrasound (EUS) or endoscopic retrograde cholangiopancreatography (ERCP) to obtain tissue samples. However, these methods often fall short due to difficulty in accessing entire bile duct strictures. SpyGlass cholangioscopy can improve diagnosis, yet may fail to provide sufficient tissue for molecular characterization. Here we present a perspective on the development of snake-like agile robots with integrated optical imaging and Raman spectroscopy. These robots could improve the mapping of the biliary tree and the precision of biopsy collection and allow tissue analysis in situ, as well as facilitating stenting to restore the flow of bile. A multidisciplinary approach that brings together clinicians, pathologists, and engineers is required to develop these new robotic technologies and improve patient outcomes. Full article
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14 pages, 2441 KiB  
Article
Reduced Graphene Oxide/β-Cyclodextrin Nanocomposite for the Electrochemical Detection of Nitrofurantoin
by Al Amin, Gajapaneni Venkata Prasad, Venkatachalam Vinothkumar, Seung Joo Jang, Da Eun Oh and Tae Hyun Kim
Chemosensors 2025, 13(7), 247; https://doi.org/10.3390/chemosensors13070247 - 10 Jul 2025
Viewed by 383
Abstract
In this work, a glassy carbon electrode (GCE) modified with reduced graphene oxide and β-cyclodextrin (rGO/β-CD) nanocomposite was developed for the electrochemical detection of nitrofurantoin (NFT). The structural and morphological characteristics of the synthesized nanocomposite were determined using scanning electron microscopy (SEM), Raman [...] Read more.
In this work, a glassy carbon electrode (GCE) modified with reduced graphene oxide and β-cyclodextrin (rGO/β-CD) nanocomposite was developed for the electrochemical detection of nitrofurantoin (NFT). The structural and morphological characteristics of the synthesized nanocomposite were determined using scanning electron microscopy (SEM), Raman spectroscopy, X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). Moreover, the electrochemical behavior of the modified electrodes was thoroughly examined using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), with the rGO/β-CD-modified glassy carbon electrode (GCE) demonstrating superior electron transfer capability. Key experimental parameters, including scan rate, material loading, and solution pH, were systematically optimized. After optimizing the experimental conditions, the modified sensor showed excellent electrocatalytic performance and selectivity toward NFT, achieving a broad linear detection range from 0.5 to 120 μM, a low limit of detection (LOD) of 0.048 μM, and a high sensitivity of 12.1 µA µM–1 cm–2 using differential pulse voltammetry (DPV). Furthermore, the fabricated electrode exhibited good anti-interference ability, stability, precision, and real-time applicability for NFT detection in a wastewater sample. These results highlight the potential of the rGO/β-CD nanocomposite as a high-performance platform for electrochemical sensing applications. Full article
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31 pages, 3723 KiB  
Review
Chemical Profiling and Quality Assessment of Food Products Employing Magnetic Resonance Technologies
by Chandra Prakash and Rohit Mahar
Foods 2025, 14(14), 2417; https://doi.org/10.3390/foods14142417 - 9 Jul 2025
Viewed by 480
Abstract
Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) are powerful techniques that have been employed to analyze foodstuffs comprehensively. These techniques offer in-depth information about the chemical composition, structure, and spatial distribution of components in a variety of food products. Quantitative NMR [...] Read more.
Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) are powerful techniques that have been employed to analyze foodstuffs comprehensively. These techniques offer in-depth information about the chemical composition, structure, and spatial distribution of components in a variety of food products. Quantitative NMR is widely applied for precise quantification of metabolites, authentication of food products, and monitoring of food quality. Low-field 1H-NMR relaxometry is an important technique for investigating the most abundant components of intact foodstuffs based on relaxation times and amplitude of the NMR signals. In particular, information on water compartments, diffusion, and movement can be obtained by detecting proton signals because of H2O in foodstuffs. Saffron adulterations with calendula, safflower, turmeric, sandalwood, and tartrazine have been analyzed using benchtop NMR, an alternative to the high-field NMR approach. The fraudulent addition of Robusta to Arabica coffee was investigated by 1H-NMR Spectroscopy and the marker of Robusta coffee can be detected in the 1H-NMR spectrum. MRI images can be a reliable tool for appreciating morphological differences in vegetables and fruits. In kiwifruit, the effects of water loss and the states of water were investigated using MRI. It provides informative images regarding the spin density distribution of water molecules and the relationship between water and cellular tissues. 1H-NMR spectra of aqueous extract of kiwifruits affected by elephantiasis show a higher number of small oligosaccharides than healthy fruits do. One of the frauds that has been detected in the olive oil sector reflects the addition of hazelnut oils to olive oils. However, using the NMR methodology, it is possible to distinguish the two types of oils, since, in hazelnut oils, linolenic fatty chains and squalene are absent, which is also indicated by the 1H-NMR spectrum. NMR has been applied to detect milk adulterations, such as bovine milk being spiked with known levels of whey, urea, synthetic urine, and synthetic milk. In particular, T2 relaxation time has been found to be significantly affected by adulteration as it increases with adulterant percentage. The 1H spectrum of honey samples from two botanical species shows the presence of signals due to the specific markers of two botanical species. NMR generates large datasets due to the complexity of food matrices and, to deal with this, chemometrics (multivariate analysis) can be applied to monitor the changes in the constituents of foodstuffs, assess the self-life, and determine the effects of storage conditions. Multivariate analysis could help in managing and interpreting complex NMR data by reducing dimensionality and identifying patterns. NMR spectroscopy followed by multivariate analysis can be channelized for evaluating the nutritional profile of food products by quantifying vitamins, sugars, fatty acids, amino acids, and other nutrients. In this review, we summarize the importance of NMR spectroscopy in chemical profiling and quality assessment of food products employing magnetic resonance technologies and multivariate statistical analysis. Full article
(This article belongs to the Special Issue Quantitative NMR and MRI Methods Applied for Foodstuffs)
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