Search Results (57)

Bruising in ‘Korla’ pears represents a prevalent phenomenon that leads to progressive fruit decay and substantial economic losses. The detection of early-stage bruising proves challenging due to the absence of visible external characteristics, and existing deep learning models have limitations in weak feature extraction under complex optical interference. To address the postharvest latent damage detection challenges in ‘Korla’ pears, this study proposes a collaborative detection framework integrating structured-illumination reflectance imaging (SIRI) with multi-order gated attention mechanisms. Initially, an SIRI optical system was constructed, employing 150 cycles·m⁻¹ spatial frequency modulation and a three-phase demodulation algorithm to extract subtle interference signal variations, thereby generating RT (Relative Transmission) images with significantly enhanced contrast in subsurface damage regions. To improve the detection accuracy of latent damage areas, the MOGA-UNet model was developed with three key innovations: 1. Integrate the lightweight VGG16 encoder structure into the feature extraction network to improve computational efficiency while retaining details. 2. Add a multi-order gated aggregation module at the end of the encoder to realize the fusion of features at different scales through a special convolution method. 3. Embed the channel attention mechanism in the decoding stage to dynamically enhance the weight of feature channels related to damage. Experimental results demonstrate that the proposed model achieves 94.38% mean Intersection over Union (mIoU) and 97.02% Dice coefficient on RT images, outperforming the baseline UNet model by 2.80% with superior segmentation accuracy and boundary localization capabilities compared with mainstream models. This approach provides an efficient and reliable technical solution for intelligent postharvest agricultural product sorting. Full article

Cyanide species pose an environmental concern as they inhibit important biological processes in humans and aquatic systems. There is more focus on free-CN and weak acid dissociables cyanide as hazardous species compared to strong acid dissociables due to their higher reactivity and toxicity. However, the strong acid dissociables cyanide also poses health concerns as it liberates free-CN under ultraviolet irradiation or when present in acidic solutions. Detection of strongly acid dissociables cyanide typically requires its digestion in acidic solutions and measurement of the gaseous HCN produced. A simple infrared spectroscopic method is described here to speciate and quantify three strong acid dissociables cyanide: [Fe(CN)₆]³⁻, [Co(CN)₆]³⁻, and [Au(CN)₂]⁻. The strategy involves precipitating the strongly acid dissociables cyanide using cetyltrimethylethylammonium bromide, capturing the precipitate on a polyethylene membrane, and quantifying the individual strongly acid dissociables cyanide from the IR spectrum recorded in transmission mode through the membrane. Controlling the particle diameter to be in the range of 0.2–2 µm is important. Particles less than 0.2 µm pass through the membrane, whereas particles larger than about 2 µm lead to nonlinearity in quantification. The average %recoveries for [Fe(CN)₆]³⁻, [Co(CN)₆]³⁻, and [Au(CN)₂]⁻ were 100% (%RSD = 7), 91% (%RSD = 7), and 101% (%RSD = 8), respectively. The detection limit for [Fe(CN)₆]³⁻ and [Co(CN)₆]³⁻ were both 20 ppb CN⁻, whereas [Au(CN)₂]⁻ was 100 ppb CN⁻. The detection range was 20–750 ppb CN⁻ for [Fe(CN)₆]³⁻ and [Co(CN)₆]³⁻ and 100–750 ppb CN⁻ for [Au(CN)₂]⁻ with a linear regression of R² = 0.999–1.000. Full article

Post-harvest processing (PHP) is a key determinant of coffee quality, flavor profile, and market classification, yet verifying PHP claims remains a significant challenge in the specialty coffee industry. This study introduces near-infrared spectroscopy (NIRS) coupled with chemometrics as a rapid, non-destructive approach to classify green coffee beans based on PHP. For the first time, seven distinct PHP categories—Alchemy, Anaerobic Processing (Deep Fermentation), Dry-Hulled, Honey, Natural, Washed, and Wet-Hulled—were discriminated using NIRS, encompassing 20 different processing protocols under varying environmental and fermentation conditions. The NIR spectra (350–2500 nm) of 524 green Arabica coffee samples were analyzed using PCA-LDA models (750–2450 nm), achieving classification accuracies up to 100% for underrepresented categories and strong performance (91–95%) for dominant PHP groups in an independent test set. These results demonstrate that NIRS can detect subtle chemical signatures associated with diverse PHP techniques, offering a scalable tool for quality assurance, fraud prevention, and traceability in global coffee supply chains. While limited sample sizes for some PHP categories may influence model generalization, this study lays the foundation for future work involving broader datasets and integration with digital traceability systems. The approach has direct implications for producers, traders, and certifying bodies seeking reliable, real-time PHP verification. Full article

Surface-enhanced Raman spectroscopy was employed to measure lettuce seeds at five different germination stages. The experimental results show that 85% of the spectra of normally germinating seeds exhibited consistency in both peak positions and quantities at the same germination stage, while spectra from seeds that failed to germinate normally demonstrated significant differences compared to the normal ones. These data indicate that the surface-enhanced Raman spectrum of seeds could serve as an effective method for detecting seed germination rates. Full article

Protein aggregates are known to disrupt normal cellular functions and homeostasis, serving as key hallmarks of various neurodegenerative disorders, including Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis (ALS). Automated detection of cytoplasmic, disease-associated aggregates in fluorescence images is crucial for characterizing these aggregates and exploring potential strategies for their prevention. In this study, we demonstrate that removing background fluorescence and improving the brightness of aggregates using an automated aggregate detection algorithm significantly enhances the detection efficiency of cytoplasmic aggregates formed by the 25 kDa C-terminal fragment of ALS-associated TDP-43 (TDP25). A high signal-to-noise ratio can improve detection efficiency. Our findings contribute to the development of more effective detection methods for disease-associated aggregates of heterogeneous sizes and fluorescence intensities, which are typically challenging to identify automatically. Full article

Unsaturated fatty acids have cis and trans isomers. The naturally stable isomer is the cis isomer, which is changed to the trans isomer by a thermal reaction. The reaction order, reaction constant, and activation energy are required to confirm the reaction mechanism. Therefore, the concentrations of the cis and trans isomers must be determined simultaneously. In the present study, oleic acid (cis isomer) and elaidic acid (trans isomer) were measured using Raman spectroscopy and partial least squares regression. The thermal reaction of oleic acid was performed at several temperatures. The reaction was determined as a first-order reaction. The reaction rate constants at several temperatures were determined as 1.3 × 10⁻³ to 5.2 × 10⁻³/h at 100 °C to 160 °C by plotting the logarithm of the oleic acid concentration against reaction time. The activation energy obtained by the Arrhenius plot was 31 kJ/mol. Full article

Time-resolved fluorescence techniques, such as fluorescence lifetime imaging microscopy (FLIM), fluorescence correlation spectroscopy (FCS), and time-resolved fluorescence spectroscopy, are ideally suited for investigating molecular dynamics and interactions in biological and chemical systems. However, the analysis and interpretation of these datasets require advanced computational tools capable of handling diverse models and datasets. This paper presents a comprehensive software solution designed for model generation and analysis of time-resolved fluorescence data with a strong focus on fluorescence for quantitative structural analysis and biophysics. The software supports the integration of multiple fluorescence techniques and provides users with robust tools for performing complex model analysis across diverse experimental data. By enabling global analysis, model generation, data visualization, and sampling over model parameters, the software enhances the interpretability of intricate fluorescence phenomena. By providing flexible modeling capabilities, this solution offers a versatile platform for researchers to extract meaningful insights from time-resolved fluorescence data, aiding in the understanding of dynamic biomolecular processes. Full article

Fourier-transform infrared (FTIR) spectroscopy can detect biomolecular changes in bacterial cells in response to drugs or other stimuli. Fully developing this area requires an understanding of IR spectral changes associated with the growth of unperturbed cells. Such an understanding is still lacking, however. To address this issue, attenuated total reflectance (ATR) FTIR spectroscopy has been used to probe changes in the composition of Staphylococcus aureus ATCC 6538 cells during exponential growth, with a 30 min time resolution. We find prominent spectral changes in proteins, nucleic acids, and carbohydrates evolving from the early (30–120 min) to the late (240–360 min) log phase of growth. Principal component analysis (PCA) shows that spectra obtained for cells during the early and late log phases of growth can be discriminated against with 100% accuracy. Protein-related spectral features are most significant in spectra collected at 30- and 90-min post-inoculation and provide a robust basis for temporal differentiation. Spectral changes that occur during the first 30 min after inoculation are shown to reverse over the next 30–120 min, indicating dynamic adaptations during cellular growth. Overall, we demonstrate a band assignment strategy based on time resolution, underscoring the utility of FTIR spectroscopy in dynamic studies of bacterial cells. Full article

Accurate estimation of optical properties and hemodynamic parameters is critical for advancing frequency-domain diffuse optical spectroscopy (FD-DOS) techniques in clinical neuroscience. However, conventional FD-DOS models often assume planar air–tissue interfaces, introducing errors in anatomically curved regions such as the forehead or infant heads. This study evaluates the impact of incorporating tissue curvature into forward models for FD-DOS analysis. Using simulations and optical phantoms, we demonstrate that curved models reduce errors in absorption coefficient estimation from 20% to less than 10% in high-curvature scenarios. Within the curvatures tested, even minor curvature mismatches resulted in errors significantly lower than those observed from planar approximations (p < 0.001). In low-curvature regions, curved models yielded errors comparable to planar models (<5% in both cases). When applied to human data, our proposed curved model increased absorption and hemoglobin concentration estimates by 10–15% compared to standard semi-infinite models, closer to physiological expectations. Overall, these results quantitatively demonstrate that accounting for tissue curvature in FD-DOS forward models significantly improves the accuracy of optical property estimation. We propose a numerical framework that achieves this in a fast and reliable manner, advancing FD-DOS as a robust tool for clinical and research applications in anatomically complex regions. Full article

We report the design, implementation and test of a Mid-Infrared spectrometer proof-of-concept that utilizes an uncooled micro-bolometer array, sensitive in the 3–14 µm spectral range, integrated in a conventional optical dispersive spectrometry setup. Such a spectrometer enables instantaneous measurements across this broad spectral range, comparable to that of a FTIR but with a more compact design and without moving parts. This makes it ideal for integration into portable, battery-powered devices such as handheld scanners. The Mid-IR range offers significant advantages over NIR-SWIR spectrometers, especially for organic compound analysis. A notable application for this instrument: plastic waste sorting—including black plastics—was tested with significant accuracy and effectiveness of plastic classification (on PP, PET and PE samples) with a very simple machine learning algorithm. Full article

The pharmaceutical industry has witnessed exponential growth in production volumes, driven by factors such as an aging global population and the COVID-19 pandemic. To meet the demand for high product quality alongside increased productivity, there is a growing emphasis on developing innovative Fermentation Analytical Technology (FAT) and Process Analytical Technology (PAT) tools for real-time performance monitoring, modeling, measurement, and control. Building on our earlier work involving in-line monitoring of Bordetella pertussis fermentations using fluorescence spectroscopy, this review explores and compares the applications of vibrational and fluorescence spectroscopy for real-time bioprocess monitoring. We examine recent technological advancements and ongoing challenges in the field. Various spectroscopic techniques are evaluated in terms of cost-effectiveness and practical applicability, with a particular focus on in-line spectroscopy as a promising, low-cost solution for effective bioprocess monitoring. Full article

This paper presents a systematic absorption and circular dichroism spectroscopy study of short single strands of DNA, from 2 to 20 bases. They are composed of a sequence-specific nucleobase composition, either adenine (A), thymine (T), or AT repeats. The absorption spectra hypochromism and the circular dichroism one show butterfly-shaped spectra. Data analysis conducted on the spectra of these oligomers provides evidence for the formation of excitons and their delocalization length along the strand of DNA in relation to how many bases are involved in the excitonic coupling. In particular, the extent of this coupling is limited to adjacent nucleobases in the case of pure adenine strands but spans multiple nucleobases in the case of pure thymine strands. Predictably, AT repeats show a mixed behavior between the two. Full article

Mössbauer spectroscopy can be advantageous for studying catalysts. In particular, its use in in situ studies can provide unique access to structural features. However, special attention must be paid to the interpretation of data, since in most studies, the samples are not perfectly homogeneous. Balance and compromise should be found between the refinement of evaluations by extracting and interpreting data from spectra, while also considering the presence of possible inhomogeneities in samples. In this review, examples of studies on two types of catalysts are presented, from which, despite possible inhomogeneities, clear statements can be derived. The first example pertains to selected iron-containing microporous zeolites (with ⁵⁷Fe Mössbauer spectroscopy), from which unique information is collected on the coordination of iron ions. The second example is related to studies on supported PtSn alloy particles (with ¹¹⁹Sn probe nuclei), from which reversible modifications of the tin component due to interactions with the reaction partners are revealed. Full article

In this review, we demonstrate that the carotenoids–retinoids–cytochromes c triangle is an important cancer factor controlling most aspects of the development, proliferation, and progression of cancer. Cancer is a multidimensional disease that needs a balance between the enzymes controlling the amount of carotenoids, the production of retinoids (particularly retinoic acid), and the concentration of cytochromes (particularly cytochrome c). The proper balance between these enzymes will help in overcoming the bottleneck in cancer therapeutics using drugs. First, we discuss the impact of carotenoids on cancer. In the next section, we show how carotenoid cleavage products, including retinal, retinol, and retinoic acid, induce positive and negative effects on cancer development. Then, we discuss the impact of cytochrome c on cancer. We have demonstrated that an alteration in the cellular redox status of cytochrome c is a crucial factor in cancer, influencing numerous aspects of malignant progression. The results obtained by Raman imaging showed significant differences between normal and cancerous human cells. First, a significant redox imbalance in the hem group of cytochrome c with the upregulation of the reduced form of hem is observed. Cancer tissue has a higher concentration of reduced cytochrome c than normal tissue. Secondly, both breast and brain tumors exhibit enhanced de novo lipogenesis in comparison to normal cells. Third, this research illustrates the essential function of the extracellular matrix in oxidative phosphorylation and apoptosis pathways. Full article

Fourier transform infrared (FTIR) spectroscopy, coupled with machine learning (ML) analysis can be used for disease monitoring with high speed and accuracy, including the classification of mosquito samples by species, age and malaria detection. However, current FTIR instruments use low-brightness thermal light sources to generate infrared light, which limits their ability to measure complex biological samples, especially where high spatial resolution is necessary, such as for specific mosquito tissues. Moreover, these systems lack portability, which is essential for field applications. To overcome these issues, spectrometers using quantum cascade lasers (QCLs) have become an attractive alternative for building fast, and portable systems due to their high electrical-to-optical efficiency, small size, and potential for low-cost. Here, we present a QCL-based spectrometer prototype designed for large scale, low-cost, environmental field-based disease surveillance. Full article