Search results for "partial least squares regression"
showing 10 items of 122 documents
A spectroscopic method for determining lignin content of softwood and hardwood kraft pulps
1998
Abstract A rapid method for determining the kappa number of unbleached and oxygen-delignified kraft pulps in the range 3–35 is presented. This novel method was based on the multivariate analysis of VIS spectral data on pulp samples. The calculated models and the test results indicated that partial least squares (PLS) and principal component regression (PCR) models yielded similar results, PLS being slightly more accurate. It was also found that for practical purposes a separate model for each wood feedstock and delignification process is needed.
FTIR Monitoring of Chemical Changes in Softwood During Heating
2000
Abstract A multivariate chemometric method for monitoring the mass loss of Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) by IR spectroscopic determination of chemical changes occurring during the heat treatment (160 - 260 °C, 2 - 8 h) of these wood materials was developed. The method was based on the handling of FTIR data on treated and untreated wood powder samples by the partial least squares (PLS) method. In addition, unknown samples (treated and untreated pine and spruce) were classified into separate groups by the principal component analysis (PCA) method. The chemical changes occurring in the wood samples during heating were also briefly discussed.
Optimization criteria in sample selection step of local regression for quantitative analysis of large soil NIRS database
2012
International audience; Large soil spectral libraries compiling thousands of NIR (Near Infrared) reflectance spectra have been created encompassing a wide diversity and heterogeneity of spectra. Among the many chemometric approaches to the calibration of chemical and physical properties from these large libraries, local calibrations have the advantage of being able to select the most similar spectra to the spectrum of a target sample. This is particularly relevant when dealing with highly heterogeneous media such as soils, where the mineral matrix has a strong influence on spectral features. A crucial step in the implementation of local calibration procedures is the construction of local ne…
Characterization of Odor-Active Compounds in Aromatic Caramel by GC-Olfactometry and GC-Mass Spectrometry
2014
The aim of this study was to characterize odor-active compounds and sensory properties of four aromatic caramels. The volatile fraction was isolated by solvent assisted flavor evaporation (SAFE) and analyzed by GC/MS and GC/O with the detection frequency method. Furthermore, descriptive sensory profiles were performed with a panel of 10 trained assessors. Of the 77 odorant areas detected (detection frequency≥33%), 40 were associated to identified molecules. GC/O data were correlated to sensory attributes by partial least squares regression (PLSR). Oxygenated heterocycles, cyclopentenone derivatives, and carboxylic acids appeared as the most important contributors in caramel aroma.
Determination of lidocaine in urine at low ppm levels using dispersive microextraction and attenuated total reflectance–Fourier transform infrared me…
2015
Abstract IR spectra provide valuable information about biological systems and can be obtained with compactable and affordable instruments, but the lack of sensitivity of this technique hampers its use in the determination of drugs in clinical fluids. Taking lidocaine as a target molecule, in this paper we introduced a methodology for determining drugs in urine samples using infrared spectroscopy. The lack of sensitivity of the IR was compensated with the combination of an effective and straightforward dispersive liquid–liquid microextraction and the measurement of the dry film of the organic extracts through attenuated total reflectance (ATR). The method developed improves the sensitivity b…
Rapid and Nondestructive Determination of Egg Freshness Category and Marked Date of Lay using Spectral Fingerprint
2020
The potential of nondestructive prediction of egg freshness based on near-infrared (NIR) spectra fingerprints would be beneficial to quality control officers and consumers alike. In this study, handheld NIR spectrometer in the range of 740 nm to 1070 nm and chemometrics were used to simultaneously determine egg freshness based on marked date of lay for eggs stored under cold and ambient conditions. The spectra acquired from the eggs were preprocessed using multiplicative scatter correction and principal component analysis (MSC-PCA). Linear discriminant analysis (LDA) was used to build identification model to predict the category of freshness, while partial least square regression (PLS-R) wa…
Non-destructive and clean prediction of aviation fuel characteristics through Fourier transform-Raman spectroscopy and multivariate calibration
2003
Abstract The combination of Fourier transform (FT)-Raman spectroscopy and partial least squares (PLS) regression is proposed to be used in off-line kerosene quality control. Here, six important physico-chemical properties have been studied: Abel flash point, initial boiling point (IBP), 10% of distilled sample, final boiling point (FBP), total percentage of aromatic compounds (% aromatics) and viscosity. The Raman spectra were obtained directly from standard 2 ml glass vials ( 12 mm ×32 mm), using a Bruker RFS 100 FT-Raman spectrometer, equipped with a 1064 nm Nd:YAG laser and a Ge detector, in back-scattering mode and accumulating 25 scans (150 s acquisition time) with a laser power of 30…
Green direct determination of mineral elements in artichokes by infrared spectroscopy and X-ray fluorescence.
2015
Near infrared (NIR) and X-ray fluorescence (XRF) spectroscopy were investigated to predict the concentration of calcium, potassium, iron, magnesium, manganese and zinc in artichoke samples. Sixty artichokes were purchased from different Spanish areas (Benicarlo, Valencia and Murcia). NIR and XRF spectra, combined with partial least squares (PLS) data treatment, were used to develop chemometric models for the prediction of mineral concentration. To obtain reference data, samples were mineralised and analysed by inductively coupled plasma optical emission spectrometry (ICP-OES). Coefficients of determination obtained for the regression between predicted values and reference ones for calcium, …
Determination of total phenolic compounds in compost by infrared spectroscopy
2016
Abstract Middle and near infrared (MIR and NIR) were applied to determine the total phenolic compounds (TPC) content in compost samples based on models built by using partial least squares (PLS) regression. The multiplicative scatter correction, standard normal variate and first derivative were employed as spectra pretreatment, and the number of latent variable were optimized by leave-one-out cross-validation. The performance of PLS-ATR-MIR and PLS-DR-NIR models was evaluated according to root mean square error of cross validation and prediction (RMSECV and RMSEP), the coefficient of determination for prediction ( R pred 2 ) and residual predictive deviation (RPD) being obtained for this la…
Chemometric determination of arsenic and lead in untreated powdered red paprika by diffuse reflectance near-infrared spectroscopy.
2008
It has been evaluated the potential of near-infrared (NIR) diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) as a way for non-destructive measurement of trace elements at microg kg(-1) level in foods, with neither physical nor chemical pre-treatment. Predictive models were developed using partial least-square (PLS) multivariate approaches based on first-order derivative spectra. A critical comparison of two spectral pre-treatments, multiplicative signal correction (MSC) and standard normal variate (SNV) was also made. The PLS models built after using SNV provided the best prediction results for the determination of arsenic and lead in powdered red paprika samples. Relativ…