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The classification of plants by laser-induced breakdown spectroscopy based on two chemometric methods
摘要： The applications of laser-induced breakdown spectroscopy (LIBS) on classifying complex natural organics are relatively limited and their accuracies still needs to be improved. To study the methods on classification of complex organics, three kinds of fresh leaves were measured by LIBS in this work. 100 spectra from 100 samples of each kind of leaves were measured and then they were divided into training set and test set in a ratio of 7:3. Two algorithms of chemometric methods including the partial least squares discriminant analysis (PLS-DA) and principal component analysis Mahalanobis distance (PCA-MD) were used to identify these leaves. By using 23 lines from 16 elements or molecules as input data, these two methods can both classify these three kinds of leaves successfully. The classification accuracies of training set are both up to 100% by PCA-MD and PLS-DA, respectively. The classification accuracies of test set are 93.3% by PCA-MD and 97.8% by PLS-DA, respectively. It means that PLS-DA is better than PCA-MD in classifying plant leaves. Because the components in PLS-DA process are more suitable for classification than those in PCA-MD process. We think that this work can provide a reference for plant traceability using LIBS.
关键词： classification of complex organics,partial least squares discriminant analysis,principal component analysis Mahalanobis distance,laser-induced breakdown spectroscopy
更新于2025-09-23 15:21:01
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Effect of fruit moving speed on online prediction of soluble solids content of apple using Vis/NIR diffuse transmission
摘要： The effect of fruit moving speed on online prediction of soluble solids content (SSC) of “Fuji” apples based on visible and near-infrared (Vis/NIR) spectroscopy was studied. Diffuse transmission spectra between 615 and 1,045 nm were collected with a commercial online system at speeds of 0.3 m/s (S1), 0.5 m/s (S2), and 0.7 m/s (S3). Compensation models for SSC of each speed alone (local models) and all speeds (global model) were established using partial least squares (PLS). For global model, spectra of each sample were divided into three parts (P1, P2, and P3), three kinds of spectra partition combinations (P12, P13, and P23) were established. Results showed that S3 performed better and the influence of speed on spectra greatly affected SSC evaluation accuracy between local models. Comparatively, global model was insensitive to fruit moving speed variation and effective wavelengths (EWs) selected by competitive adaptive reweighted sampling (CARS) after Savitzky–Golay smoothing (SGS) achieved better results than local models. Importantly, 36 EWs selected by CARS after SGS of global-P13 model achieved the best results with rp and RMSEP of 0.8419, 0.8895, 0.8948 and 0.6281, 0.5318, 0.5196(cid:1)Brix, respectively. Generally, global-P13 model with EWs is promisingly applied to online SSC prediction of apple by Vis/NIR diffuse transmission.
关键词： soluble solids content,online prediction,effective wavelengths,competitive adaptive reweighted sampling,partial least squares,fruit moving speed,apple,diffuse transmission,Vis/NIR spectroscopy
更新于2025-09-23 15:21:01
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Construction of global and robust near-infrared calibration models based on hybrid calibration sets using Partial Least Squares (PLS) regression
摘要： Near-infrared spectroscopy (NIR) models built on a particular instrument are often invalid on other instruments due to spectral inconsistencies between the instruments. In the present work, global and robust NIR calibration models were constructed by partial least square (PLS) regression based on hybrid calibration sets, which are composed of both primary and secondary spectra. Three datasets were used as case studies. The first consisted of 72 radix scutellaria samples measured on two NIR spectrometers with known baicalin content. The second was composed of 80 corn samples measured on two instruments with known moisture, oil, and protein concentrations. The third dataset included 279 primary samples of tobacco with known nicotine content and 78 secondary samples of tobacco with known nicotine concentrations. The effect of the number of secondary spectra in the hybrid calibration sets and the methods for selecting secondary spectra on the PLS model performance were investigated by comparing the results obtained from different calibration sets. This study shows that the global and robust calibration models accurately predicted both primary and secondary samples as long as the ratios of the number of primary spectra to the number of secondary spectra were less than 22. The models performance was not influenced by the selection method of the secondary spectra. The hybrid calibration sets included the primary spectral information and also the secondary spectra; rendering the constructed global and robust models applicable to both primary and secondary instruments.
关键词： global and robust models,hybrid calibration set,Near-infrared spectroscopy,partial least squares (PLS) regression
更新于2025-09-23 15:21:01
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Long-Term Agroecosystem Research in the Central Mississippi River Basin: Hyperspectral Remote Sensing of Reservoir Water Quality
摘要： In situ methods for estimating water quality parameters would facilitate efforts in spatial and temporal monitoring, and optical reflectance sensing has shown potential in this regard, particularly for chlorophyll, suspended sediment, and turbidity. The objective of this research was to develop and evaluate relationships between hyperspectral remote sensing and lake water quality parameters—chlorophyll, turbidity, and N and P species. Proximal hyperspectral water reflectance data were obtained on seven sampling dates for multiple arms of Mark Twain Lake, a large man-made reservoir in northeastern Missouri. Aerial hyperspectral data were also obtained on two dates. Water samples were collected and analyzed in the laboratory for chlorophyll, nutrients, and turbidity. Previously reported reflectance indices and full-spectrum (i.e., partial least squares regression) methods were used to develop relationships between spectral and water quality data. With the exception of dissolved NH3, all measured water quality parameters were strongly related (R2 ≥ 0.7) to proximal reflectance across all measurement dates. Aerial hyperspectral sensing was somewhat less accurate than proximal sensing for the two measurement dates where both were obtained. Although full-spectrum calibrations were more accurate for chlorophyll and turbidity than results from previously reported models, those previous models performed better for an independent test set. Because extrapolation of estimation models to dates other than those used to calibrate the model greatly increased estimation error for some parameters, collection of calibration samples at each sensing date would be required for the most accurate remote sensing estimates of water quality.
关键词： water quality,Mark Twain Lake,partial least squares regression,chlorophyll,hyperspectral remote sensing,nutrients,turbidity
更新于2025-09-23 15:21:01
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Variable selection for the determination of total polar materials in fried oils by near infrared spectroscopy
摘要： Total polar materials (TPM) content is considered as the best indicator and the most common parameter to check the quality of deep-frying oils. The development of simpler and quicker analytical techniques than the available methods to monitor oil quality in restaurants and fried food outlets is an important topic related to the human health. This paper reports a comparison of the variable selection of near infrared (NIR) spectra by multiple linear regression (MLR-NIR) with partial least squares (PLS-NIR) models for the quantification of TPM in fried vegetable oils. The use of PLS-NIR offers an alternative in laboratory bench equipment for the determination of TPM in oils employed for frying different kinds of foods with relative prediction errors of 6.5%, a coefficient of determination for prediction of 0.99 and a residual predictive deviation (RPD) of 9.2 when selected wavenumber intervals were employed. MLR-NIR allows the selection of a reduced number of wavenumber in order to develop low cost instruments to evaluate the frying oil quality. Based on the NIR signals at four wavenumbers, the relative prediction error was 12.1%, the coefficient of determination for prediction was 0.96 and the RPD was 5.0.
关键词： partial least squares,total polar materials,multiple linear regression,vegetable fried oils,Near infrared spectroscopy
更新于2025-09-23 15:21:01
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Retrieval of Chlorophyll-a and Total Suspended Solids Using Iterative Stepwise Elimination Partial Least Squares (ISE-PLS) Regression Based on Field Hyperspectral Measurements in Irrigation Ponds in Higashihiroshima, Japan
摘要： Concentrations of chlorophyll-a (Chl-a) and total suspended solids (TSS) are significant parameters used to assess water quality. The objective of this study is to establish a quantitative model for estimating the Chl-a and the TSS concentrations in irrigation ponds in Higashihiroshima, Japan, using field hyperspectral measurements and statistical analysis. Field experiments were conducted in six ponds and spectral readings for Chl-a and TSS were obtained from six field observations in 2014. For statistical approaches, we used two spectral indices, the ratio spectral index (RSI) and the normalized difference spectral index (NDSI), and a partial least squares (PLS) regression. The predictive abilities were compared using the coefficient of determination (R2), the root mean squared error of cross validation (RMSECV) and the residual predictive deviation (RPD). Overall, iterative stepwise elimination based on PLS (ISE–PLS), using the first derivative reflectance (FDR), showed the best predictive accuracy, for both Chl-a (R2 = 0.98, RMSECV = 6.15, RPD = 7.44) and TSS (R2 = 0.97, RMSECV = 1.91, RPD = 6.64). The important wavebands for estimating Chl-a (16.97% of all wavebands) and TSS (8.38% of all wavebands) were selected by ISE–PLS from all 501 wavebands over the 400–900 nm range. These findings suggest that ISE–PLS based on field hyperspectral measurements can be used to estimate water Chl-a and TSS concentrations in irrigation ponds.
关键词： total suspended solids,partial least squares regression,irrigation ponds,hyperspectral,chlorophyll-a
更新于2025-09-23 15:21:01
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Rapid qualitative evaluation of velvet antler using laser-induced breakdown spectroscopy (LIBS)
摘要： The aim of this work is to study a rapid analysis method to evaluate velvet antler products qualitatively, using laser-induced breakdown spectroscopy (LIBS). We used principal component analysis to select feature lines of LIBS spectra of velvet antler, and built two partial least squares-discriminant analysis (PLS-DA) classification models to distinguish between inferior and good quality velvet antler by using the intensities of all lines and feature lines as input variables, respectively. The correct classification rates (CCRs) of these two models were both 100%. In order to test the robustness of the models, we used these two models to discriminate the samples not included in the training set to build the model, and the CCRs were 87.5% and 100%, respectively. The results demonstrated that combining LIBS with PLS-DA could evaluate the quality of velvet antler, and the robustness could be improved by using the intensities of feature lines as inputs.
关键词： qualitative evaluation,partial least squares-discriminant analysis (PLS-DA),velvet antler,principal component analysis (PCA),laser-induced breakdown spectroscopy (LIBS)
更新于2025-09-23 15:19:57
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EXPRESS: Comparison of Individual and Integrated Inline Raman, Near-Infrared, and Mid-Infrared Spectroscopic Models to Predict the Viscosity of Micellar Liquids
摘要： In many industries, viscosity is an important quality parameter which significantly affects consumer satisfaction and process efficiency. In the personal care industry, this applies to products like shampoo and shower gels whose complex structures are built up of micellar liquids. Measuring viscosity offline is well established using benchtop rheometers and viscometers. The difficulty lies in measuring this property directly in the process via on or inline technologies. Therefore, the aim of this work is to investigate whether proxy measurements using in-line vibrational spectroscopy, e.g., near infrared (NIR), mid-infrared (MIR), and Raman, can be used to predict the viscosity of micellar liquids. As optical techniques, they are non-destructive and easily implementable process analytical tools where each type of spectroscopy detects different molecular functionalities. Inline fiber optic coupled probes were employed; a transmission probe for NIR measurements, an attenuated total reflectance (ATR) probe for MIR and a backscattering probe for Raman. Models were developed using forward interval partial least squares (iPLS) variable selection and log viscosity was used. For each technique combinations of pre-processing techniques were trialed including detrending, Whittaker filters, standard normal variate (SNV) and multiple scatter correction (MSC). The results indicate that all three techniques could be applied individually to predict the viscosity of micellar liquids all showing comparable errors of prediction: NIR: 1.75 Pa s; MIR: 1.73 Pa s; and Raman: 1.57 Pa s. The Raman model showed the highest relative prediction deviation (RPD) value of 5.07, with the NIR and MIR models showing slightly lower values of 4.57 and 4.61, respectively. Data fusion was also explored to determine whether employing information from more than one dataset improved the model quality. Trials involved weighting datasets based on their signal to noise ratio and weighting based on transmission curves (IR datasets only). The signal to noise weighted NIR-MIR-Raman model showed the best performance compared with both combined and individual models with a RMSECV of 0.75 Pa s and an RPD of 10.62. This comparative study provides a good initial assessment of the three prospective process analytical technologies for the measurement of micellar liquid viscosity but also provides a good basis for general measurements of inline viscosity using commercially available process analytical technology. With these techniques typically being employed for compositional analysis, this work presents their capability in the measurement of viscosity–an important physical parameter, extending the applicability of these spectroscopic techniques.
关键词： MIR,viscosity,near-infrared,micellar liquids,spectroscopy,partial least squares,Raman,mid-infrared,NIR,PLS,Inline
更新于2025-09-23 15:19:57
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Determination of the isotopic composition of enriched materials using laser ablation molecular isotopic spectrometry: partial least squares and multivariate curve resolution for the determination of 15N content in enriched urea
摘要： A quantitative analytical method based on laser ablation molecular isotopic spectrometry (LAMIS) and multivariate analysis was developed and evaluated for the determination of the isotopic composition of enriched materials. The method consists preparing a concentrated solution of the enriched material, using small quantities of a sample (125 mg), and ensuring the economic efficiency of the analysis. Standard solutions of known isotopic contents are prepared by employing mixtures of urea highly enriched in 15N and urea of natural isotopic ratio and analyzed by mass spectrometry. A small volume (30 μL) of these solutions is delivered to a filter paper disc (3 cm diameter). After drying, the disc, offering a homogeneously distributed analyte, is presented to a LAMIS equipment to acquire the vibronic emission spectra containing information about the isotopologues of interest. To illustrate the proposed method, the content of 15N is determined in enriched samples of urea. In this case, each spectrum is normalized by the intensity of emission of the CN isotopologues for the electronic (Δν = 0) emission band at 387.1 nm, ensuring better accuracy. Selected regions and single wavelengths of the vibronic emission spectrum (Δν = + 1 or ? 1) related to CN species were employed to construct multivariate partial least squares (PLS) and univariate regression models to predict the isotopic content of new samples. Besides, the LAMIS data set was evaluated by multivariate curve resolution (MCR) algorithm. The best MCR and PLS models presented similar results regarding the accuracy to determine 15N content in enriched urea. MCR is capable of identifying spectral interferences and minimizing its effect. The results show that the proposed method based on LAMIS and PLS or MCR multivariate analysis can determine the 15N content in the range 5–50% with a root mean square error of prediction (RMSEP) respectively equal to 0.5 or 0.7% (m/m) in comparison with reference results obtained by mass spectrometry.
关键词： 15N determination in enriched urea,Laser ablation molecular isotopic spectrometry (LAMIS),Isotopic composition of enriched materials,Partial least squares,Multivariate regression,Multivariate curve resolution (MCR)
更新于2025-09-23 15:19:57
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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