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Application of Visible-near Infrared Spectral Imaging for Monitoring Biological Materials
摘要： N ear infrared (NIR) spectroscopy is a powerful tool for the non-destructive evaluation of biological materials due to its generally weak absorption bands. Biological materials such as wood and plant leaves have a complicated structure in which the distribution of chemical composition and surface structure is non-uniform. Therefore, an imaging technique which combines high spatial resolution with the ability to acquire signal from a wider sample area is required. Three-dimensional image data such as hyperspectral imagery or a movie file has plenty of both spectral and spatial information. However, the visible-near infrared (vis-NIR) spectrum and the time profile of a single pixel normally display strong multicollinearity, thus requiring multivariate analysis for effective extraction of valuable information from three-dimensional image data. This article introduces two examples of image analysis for the non-destructive monitoring of biological materials.
关键词： spectroscopy,multivariate analysis,NIR,imaging,biological materials,hyperspectral,non-destructive evaluation,infrared
更新于2025-09-23 15:23:52
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Vibrational characterization of granulosa cells from patients affected by unilateral ovarian endometriosis: New insights from infrared and Raman microspectroscopy
摘要： Endometriosis is a chronic gynaecological disease characterised by the presence of endometrial cells in extra-uterine regions. One of the main factors impacting on the fertility of women affected by endometriosis is the poor oocyte quality. Granulosa Cells (GCs) regulate oocyte development and maintain the appropriate microenvironment for the acquisition of its competence; hence, the dysregulation of these functions in GCs can lead to severe cellular damages also in oocytes. In this study, luteinized GCs samples were separately collected from both ovaries of women affected by Unilateral Ovarian Endometriosis and analyzed by infrared and Raman microspectroscopy. The spectral data were compared with those of GCs from women with diagnosis of tubal, idiopathic or male infertility (taken as control group). The coupling of these two spectroscopic techniques sheds new light on the alteration induced by this pathology on GCs metabolism and biochemical composition. In fact, the study revealed similar biochemical modifications in GCs from both ovaries of women affected by unilateral ovarian endometriosis, such as the alteration of the protein pattern, the induction of oxidative stress mechanisms, and the deregulation of lipid and carbohydrate metabolisms. These evidences suggest that unilateral endometriosis impairs the overall ovarian functions, causing alterations not only in the ovary with endometriotic lesions but also in the contralateral “healthy” one.
关键词： Unilateral Ovarian Endometriosis,Multivariate analysis,FTIR microspectroscopy,Raman microspectroscopy
更新于2025-09-23 15:23:52
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Quantitative in situ mapping of elements in deep-sea hydrothermal vents using laser-induced breakdown spectroscopy and multivariate analysis
摘要： This study describes a method to quantify the chemical composition of deep-sea hydrothermal deposits in situ using laser-induced breakdown spectroscopy (LIBS). Partial least squares (PLS) regression analysis is applied to spectra obtained using a long laser pulse with a duration of 150 ns. The number of measurements needed to address the spatial heterogeneity of samples is determined through high-resolution mapping of the elemental distribution in rock samples. PLS applied to laboratory measured seawater-submerged samples achieved an average relative error (RE) of 25% for Cu, Pb, and Zn compared to benchmark concentration values in cross-validation and validation studies, where both the benchmark concentration values and LIBS spectral data are made available with this publication. The PLS model was applied to LIBS signals obtained in situ from hydrothermal deposits at 1000 m depth in the ocean. The results show that target inhomogeneity limits the accuracy of the surface LIBS measurements compared to benchmark values from bulk analysis of samples. Making multiple measurements with small position offsets at each location improves the accuracy of estimates compared to an equivalent number of measurements at a single position. Maps of element distribution generated using quantified in situ data demonstrate how chemical survey outputs can be generated by combining LIBS with multivariate analysis. This enables real-time chemical feedback during deep-sea operations and chemical surveys in situations or with platforms where sample recovery is not possible.
关键词： Multivariate analysis,Laser-induced breakdown spectroscopy (LIBS),Deep-sea explorations,In situ chemical analysis,Seafloor mineral resources,Partial least squares regression analysis
更新于2025-09-23 15:19:57
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Determination of Drying Patterns of Radish Slabs under Different Drying Methods Using Hyperspectral Imaging Coupled with Multivariate Analysis
摘要： Drying kinetics and the moisture distribution map of radish slabs under different drying methods (hot-air drying (HAD), microwave drying (MD), and hot-air and microwave combination drying (HMCD)) were determined and visualized by hyperspectral image (HSI) processing coupled with a partial least square regression (PLSR)-variable importance in projection (VIP) model, respectively. Page model was the most suitable in describing the experimental moisture loss data of radish slabs regardless of the drying method. Dielectric properties (DP, ε) of radish slices decreased with the decrease in moisture content (MC) during MD, and the penetration depth of microwaves in radish was between 0.81 and 1.15 cm. The PLSR-VIP model developed with 38 optimal variables could result in the high prediction accuracies for both the calibration (R2 = 0.967 and RMSEC = 4.32%) and validation (R2 = 0.962 and RMSEC = 4.45%). In visualized drying patterns, the radish slabs dried by HAD had a higher moisture content at the center than at the edges; however, the samples dried by MD contained higher moisture content at the edges. The nearly uniform drying pattern of radish slabs under HMCD was observed in hyperspectral images. Drying uniformity of radish slabs could be improved by the combination drying method, which significantly reduces drying time.
关键词： multivariate analysis,moisture content,drying pattern,hyperspectral imaging,radish
更新于2025-09-23 15:19:57
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Artificial Intelligence Assisted Mid-Infrared Laser Spectroscopy In Situ Detection of Petroleum in Soils
摘要： A simple, remote-sensed method of detection of traces of petroleum in soil combining artificial intelligence (AI) with mid-infrared (MIR) laser spectroscopy is presented. A portable MIR quantum cascade laser (QCL) was used as an excitation source, making the technique amenable to field applications. The MIR spectral region is more informative and useful than the near IR region for the detection of pollutants in soil. Remote sensing, coupled with a support vector machine (SVM) algorithm, was used to accurately identify the presence/absence of traces of petroleum in soil mixtures. Chemometrics tools such as principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA), and SVM demonstrated the effectiveness of rapidly differentiating between different soil types and detecting the presence of petroleum traces in different soil matrices such as sea sand, red soil, and brown soil. Comparisons between results of PLS-DA and SVM were based on sensitivity, selectivity, and areas under receiver-operator curves (ROC). An innovative statistical analysis method of calculating limits of detection (LOD) and limits of decision (LD) from fits of the probability of detection was developed. Results for QCL/PLS-DA models achieved LOD and LD of 0.2% and 0.01% for petroleum/soil, respectively. The superior performance of QCL/SVM models improved these values to 0.04% and 0.003%, respectively, providing better identification probability of soils contaminated with petroleum.
关键词： chemometrics,soil,artificial intelligence (AI),multivariate analysis,mid-infrared (MIR) laser spectroscopy,petroleum,quantum cascade lasers (QCLs)
更新于2025-09-23 15:19:57
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Fast Classification of Geographical Origins of Honey Based on Laser-Induced Breakdown Spectroscopy and Multivariate Analysis
摘要： Traceability of honey is highly required by consumers and food administration with the consideration of food safety and quality. In this study, a technique named laser-induced breakdown spectroscopy (LIBS) was used to fast trace geographical origins of acacia honey and multi-floral honey. LIBS emissions from elements of Mg, Ca, Na, and K had significant differences among different geographical origins. The clusters of honey from different geographical origins were visualized with principal component analysis. In addition, support vector machine (SVM) and linear discrimination analysis (LDA) were used to quantitively classify the origins. The results indicated that SVM performed better than LDA, and the discriminant results of multi-floral honey were better than acacia honey. The accuracy and mean average precision for multi-floral honey were 99.7% and 99.7%, respectively. This study provided a fast approach for geographical origin classification, and might be helpful for food traceability.
关键词： geographical origin,classification,honey,laser-induced breakdown spectroscopy,multivariate analysis
更新于2025-09-23 15:19:57
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A new approach to non-linear multivariate calibration in laser-induced breakdown spectroscopy analysis of silicate rocks
摘要： In this paper a new approach to quantitative Laser-Induced Breakdown Spectroscopy (LIBS) analysis of silicate rocks is presented. The method is adapted from the Franzini and Leoni algorithm, a method widely used in X-Ray Fluorescence analysis for correcting the matrix effects in the determination of the composition of geological materials. To illustrate the features of the new method proposed, nine elements were quantified in 19 geological standards by building linear univariate calibration curves, linear multivariate calibration surfaces (PLS) and using Artificial Neural Networks. The results were then compared with the predictions derived from the application of the algorithm here proposed. It was found that the Franzini and Leoni approach gives results much more precise than linear uni- and multivariate approaches, and comparable with the ones derived from the application of Artificial Neural Networks. A definite advantage of the proposed approach is the possibility of building multivariate non-linear calibration surfaces using linear optimization algorithms, a feature which makes the application of the Franzini and Leoni method in LIBS analysis much simpler (and controllable) with respect to the algorithms based on Artificial Neural Networks.
关键词： LIBS,Artificial Neural Networks,Multivariate Analysis,Geology,PLS
更新于2025-09-19 17:13:59
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Determination of the bruise degree for cherry using Vis-NIR reflection spectroscopy coupled with multivariate analysis
摘要： Determination and classification of the bruise degree for cherry can improve consumer satisfaction with cherry quality and enhance the industry’s competiveness and profitability. In this study, visible and near infrared (Vis-NIR) reflection spectroscopy was used for identifying bruise degree of cherry in 350–2500 nm. Sampling spectral data were extracted from normal, slight and severe bruise samples. Principal component analysis (PCA) was implemented to determine the first few principal components (PCs) for cluster analysis among samples. Optimal wavelengths were selected by loadings of PCs from PCA and successive projection algorithm (SPA) method, respectively. Afterwards, these optimal wavelengths were empolyed to establish the classification models as inputs of least square-support vector machine (LS-SVM). Better performance for qualitative discrimination of the bruise degree for cherry was emerged in LS-SVM model based on five optimal wavelengths (603, 633, 679, 1083, and 1803 nm) selected directly by SPA, which showed acceptable results with the classification accuracy of 93.3%. Confusion matrix illustrated misclassification generally occurred in normal and slight bruise samples. Furthermore, the latent relation between spectral property of cherries in varying bruise degree and its firmness and soluble solids content (SSC) was analyzed. The result showed both colour, firmness and SSC were consistent with the Vis-NIR reflectance of cherries. Overall, this study revealed that Vis-NIR reflection spectroscopy integrated with multivariate analysis can be used as a rapid, intact method to determine the bruise degree of cherry, laying a foundation for cherry sorting and postharvest quality control.
关键词： LS-SVM,Vis-NIR reflection spectroscopy,cherry,bruise degree,multivariate analysis
更新于2025-09-12 10:27:22
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Multivariate approach for studying the degradation of perovskite solar cells
摘要： Despite the progress in the performance of perovskite solar cells (PSCs), the absorber layer degradation during prolonged exposure to multiple environmental conditions is still a major issue. As the degradation depends upon many intrinsic and extrinsic factors, the need to adopt a multivariate testing protocol, which provides rapid assessment of device stability, is required. To do this, a Plackett Burman (PB) screening design has been used to analyze 9 different factors that affect the PSC stability; including four extrinsic factors (oxygen, moisture, UV exposure and temperature) and five intrinsic factors (selection of hole transport layer and electron transport layer, absorber layer thickness, halide type and perovskite deposition process). This approach allows us to rank the relative severity of these factors and can be used to narrow the scope of materials and device architectures to be modified, by identifying materials and configurations, which are the most stable. The least and most stable device configurations have been identified and the success of the screening approach has been demonstrated by testing the optimized configurations under ISOS-D1 and –L2 protocols. Importantly, only 12 experiments are needed to establish the most stable combination from the 9 factors thus providing a rapid assessment. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) measurements of perovskite absorber films have been performed in order to understand the degradation pathways and to support the conclusion of PB screening technique.
关键词： Perovskite solar cells,Degradation studies,Stability,Multivariate analysis
更新于2025-09-12 10:27:22
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Direct Detection of Bacteria Using Positively-charged Ag/Au Bimetallic Nanoparticles: A Label-Free SERS Study Coupled with Multivariate Analysis
摘要： Rapid detection and discrimination of pathogenic bacteria for food safety, environmental pollution, medical diagnoses, and chemical and biological threats remains a considerable challenge. In the present work, we demonstrate positively charged Ag/Au bimetallic nanoparticles (Ag/Au bmNPs) as a potential surface-enhanced Raman scattering (SERS) substrate for label-free detection and discrimination of three bacteria, viz., Escherichia coli, Salmonella typhimurium and Bacillus subtilis with excellent reproducibility. The approach relies on a priori synthesis of Ag/Au bmNPs and subsequent SERS studies on bacteria. The positive surface charge on Ag/Au bmNPs offers significant advantages of short acquisition time at very low power, high sensitivity, and simple operating procedure without the need of very specific procedures/protocols used to capture the bacteria. The reproducible and specific intrinsic fingerprint of the cell wall and intracellular components of three bacteria obtained by label-free SERS enables precise discrimination and classification of three bacteria using multivariate analysis such as principal component analysis and canonical discriminant analysis.
关键词： SERS,multivariate analysis,Optical,Magnetic,label-free study,and Hybrid Materials,bacteria detection,Ag/Au bimetallic nanoparticles,Plasmonics
更新于2025-09-11 14:15:04