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Rapid Quantitative Analysis of Forest Biomass Using Fourier Transform Infrared Spectroscopy and Partial Least Squares Regression
摘要： Fourier transform infrared reflectance (FTIR) spectroscopy has been used to predict properties of forest logging residue, a very heterogeneous feedstock material. Properties studied included the chemical composition, thermal reactivity, and energy content. The ability to rapidly determine these properties is vital in the optimization of conversion technologies for the successful commercialization of biobased products. Partial least squares regression of first derivative treated FTIR spectra had good correlations with the conventionally measured properties. For the chemical composition, constructed models generally did a better job of predicting the extractives and lignin content than the carbohydrates. In predicting the thermochemical properties, models for volatile matter and fixed carbon performed very well (i.e., R2 > 0.80, RPD > 2.0). The effect of reducing the wavenumber range to the fingerprint region for PLS modeling and the relationship between the chemical composition and higher heating value of logging residue were also explored. This study is new and different in that it is the first to use FTIR spectroscopy to quantitatively analyze forest logging residue, an abundant resource that can be used as a feedstock in the emerging low carbon economy. Furthermore, it provides a complete and systematic characterization of this heterogeneous raw material.
关键词： FTIR spectroscopy,forest logging residue,energy content,partial least squares regression,thermal reactivity,chemical composition
更新于2025-09-23 15:22:29
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Use of A Portable Camera for Proximal Soil Sensing with Hyperspectral Image Data
摘要： In soil proximal sensing with visible and near-infrared spectroscopy, the currently available hyperspectral snapshot camera technique allows a rapid image data acquisition in a portable mode. This study describes how readings of a hyperspectral camera in the 450–950 nm region could be utilised for estimating soil parameters, which were soil organic carbon (OC), hot-water extractable-C, total nitrogen and clay content; readings were performed in the lab for raw samples without any crushing. As multivariate methods, we used PLSR with full spectra (FS) and also combined with two conceptually different methods of spectral variable selection (CARS, “competitive adaptive reweighted sampling” and IRIV, “iteratively retaining informative variables”). For the accuracy of obtained estimates, it was beneficial to use segmented images instead of image mean spectra, for which we applied a regular decomposing in sub-images all of the same size and k-means clustering. Based on FS-PLSR with image mean spectra, obtained estimates were not useful with RPD values less than 1.50 and R2 values being 0.51 in the best case. With segmented images, improvements were marked for all soil properties; RPD reached values ≥ 1.68 and R2 ≥ 0.66. For all image data and variables, IRIV-PLSR slightly outperformed CARS-PLSR.
关键词： spectral variable selection,hyperspectral snapshot camera,partial least squares regression,multivariate calibration,hyperspectral imaging,proximal soil sensing
更新于2025-09-23 15:22:29
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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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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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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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The Inspection of CFRP Laminate with Subsurface Defects by Laser Arrays Scanning Thermography (LAsST)
摘要： Laser array scanning thermography (LAsST) was used to detect the subsurface defects of carbon fiber reinforced composite (CFRP). A series of bottom flat hole (BFHs) of CFRP were prepared for LAsST. Truncation pseudo-static matrix reconstruction (TC-PSMR) method was used to reconstruct the thermal response signal. Fast Fourier transform (FFT), principal component analysis (PCA) and partial least squares regression (PLSR) were used to process the thermal response signals, forming FFT image, PCA image, and PLSR image. The signal noise ratios (SNRs) of defects is calculated, and it is used to evaluate the defect detection ability of different post-processing algorithms. The experimental results show that the image based on FFT phase has a higher signal-to-noise ratio with PLSR image, and the FFT amplitude image and PLSR image can accurately represent the defect size.
关键词： FFT,Laser arrays scan thermography,Partial least squares regression,CFRP
更新于2025-09-23 15:19:57
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Calibration of near infrared spectroscopy (NIRS) data of three Eucalyptus species with extractive contents determined by ASE extraction for rapid identification of species and high extractive contents
摘要： Plantations of naturally durable timber species could substitute unsustainably harvested wood from tropical forests or wood treated with toxic preservatives. The New Zealand Dryland Forests Initiative (NZDFI) has established a tree-breeding program to develop genetically improved planting stock for durable eucalyptus plantations. In this study the durable heartwood of Eucalyptus bosistoana, Eucalyptus globoidea and Eucalyptus argophloia was characterized by near infrared (NIR) spectroscopy and NIR data was calibrated with the extractives content (EC), determined by accelerated solvent extraction (ASE) extraction, by means of a partial least squares regression (PLSR) model. It was possible to predict the EC content in the range of 0.34–18.9% with a residual mean square error (RMSE) of 0.9%. Moreover, the three species could also be differentiated by NIR spectroscopy with 100% accuracy, i.e. NIR spectroscopy is able to segregate timbers from mixed species forest plantations.
关键词： variable selection (sMC),Eucalyptus argophloia,E. bosistoana,partial least squares regression (PLSR),E. globoidea,PLS-discriminant analysis (PLS-DA)
更新于2025-09-19 17:15:36
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Hyperspectral Imaging for Evaluating Impact Damage to Mango According to Changes in Quality Attributes
摘要： Evaluation of impact damage to mango (Mangifera indica Linn) as a result of dropping from three different heights, namely, 0.5, 1.0 and 1.5 m, was conducted by hyperspectral imaging (HSI). Reflectance spectra in the 900–1700 nm region were used to develop prediction models for pulp firmness (PF), total soluble solids (TSS), titratable acidity (TA) and chroma (?b*) by a partial least squares (PLS) regression algorithm. The results showed that the changes in the mangoes’ quality attributes, which were also reflected in the spectra, had a strong relationship with dropping height. The best predictive performance measured by coefficient of determination (R2) and root mean square errors of prediction (RMSEP) values were: 0.84 and 31.6 g for PF, 0.9 and 0.49 oBrix for TSS, 0.65 and 0.1% for TA, 0.94 and 0.96 for chroma, respectively. Classification of the degree of impact damage to mango achieved an accuracy of more than 77.8% according to ripening index (RPI). The results show the potential of HSI to evaluate impact damage to mango by combining with changes in quality attributes.
关键词： partial least squares regression,quality attributes,impact damage,mango,hyperspectral imaging
更新于2025-09-19 17:15:36
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Improved measurement on quantitative analysis of coal properties using laser induced breakdown spectroscopy
摘要： It is of great significance to realize the rapid or online analysis of coal properties for combustion optimization of thermal power plants. In this work, a set of calibration schemes based on laser-induced breakdown spectroscopy (LIBS) was determined to improve the measurement on quantitative analysis of coal properties, including proximate analysis (calorific value, ash, volatile content) and ultimate analysis (carbon and hydrogen). Firstly, different normalization methods (channel normalization and normalization with the whole spectral area) combined with two regression algorithms (partial least-squares regression [PLSR] and support vector regression [SVR]) were compared to initially select the appropriate calibration method for each indicator. Then, the influence of de-noising by the wavelet threshold de-noising (WTD) on quantitative analysis was further studied, thereby the final analysis schemes for each indicator were determined. The results showed that WTD coupled SVR can be well estimated calorific value and ash, the root mean square error of prediction (RMSEP) were 0.80 MJ kg?1 and 0.60%. Coupling WTD and PLSR performed best for the measurement of volatile content, the RMSEP was 0.76%. For the quantitative analysis of carbon and hydrogen, normalization with the whole spectral area combined with SVR can get better measurement results, the RMSEP of the measurements were 1.08% and 0.21%, respectively. The corresponding average standard deviation (RSD) for calorific value, ash, volatile content, carbon and hydrogen of validation sets were 0.26 MJ kg?1, 0.57%, 0.79%, 0.47% and 0.08%, respectively. The results demonstrated that the selection of appropriate spectral pre-processing coupled with calibration strategies for each indicator can effectively improve the accuracy and precision of the measurement on coal properties.
关键词： partial least-squares regression (PLSR),quantitative analysis,normalization,Laser-induced breakdown spectroscopy (LIBS),coal properties,support vector regression (SVR),wavelet threshold de-noising (WTD)
更新于2025-09-19 17:13:59
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Simultaneous determination of proteins in microstructured optical fibers supported by chemometric tools
摘要： A new perspective on the relevant problem—creating simple, rapid, and efficient protein sensors based on microstructured optical fibers using a simple homogeneous analysis format—was proposed. Commercially available long-period grating hollow core microstructured optical fibers (LPG HCMOF) were used to determine bovine serum albumin (BSA) and albumin from chicken eggs (OVA) in binary mixtures as well as immunoglobulin G (IgG) in the presence of BSA and OVA. LPG HCMOF transmission spectra allowed the detection of both BSA and OVA up to 10 mg/mL with LOD as low as 0.1 and 0.8 μg/mL, respectively. Partial least squares regression (PLS) was utilized for modeling of LPG HCMOF spectral data and quantitative analysis of BSA, OVA, total protein, and IgG in binary and ternary mixtures. Rather high coefficients of determination (R2) and low root mean square error for the calibration (RMSEC) (15%) and prediction (RMSEP) (20%) were obtained for all PLS models. The proposed approach was tested in the analysis of BSA in spiked horse blood hemolyzed (HBH). The results demonstrated the functionality of the proposed approach and offered the opportunity for the creation of a wide range of sensors for protein determination in complex mixtures.
关键词： Chemometrics,Partial least squares regression,Protein determination,Long-period grating fiber,Microstructured optical fibers
更新于2025-09-16 10:30:52