Calibration transfer based on the weight matrix (CTWM) of PLS for near infrared (NIR) spectral analysis

2018 ◽  
Vol 10 (18) ◽  
pp. 2169-2179 ◽  
Author(s):  
Feiyu Zhang ◽  
Ruoqiu Zhang ◽  
Jiong Ge ◽  
Wanchao Chen ◽  
Wuye Yang ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Weight Matrix ◽  
Calibration Model ◽  
Calibration Transfer ◽  
Practical Applications

Calibration transfer is of great necessity for practical applications of near infrared (NIR) spectroscopy, since the original calibration model would become invalid when spectra are measured on different instruments or under different detection conditions.

Transfer of calibration model between near-infrared spectrometers for hematocrit measurement of grazing cattle

NIR news ◽  
2017 ◽  
Vol 28 (7) ◽  
pp. 16-21
Author(s):  
Xuan Luo ◽  
Akifumi Ikehata ◽  
Kunio Sashida ◽  
Shanji Piao ◽  
Tsutomu Okura ◽  
...  
Keyword(s):  
Near Infrared ◽  
Optimal Solution ◽  
Nir Spectroscopy ◽  
Final Diagnosis ◽  
Rapid Diagnosis ◽  
Calibration Model ◽  
Calibration Transfer ◽  
Current Time ◽  
Grazing Cattle ◽  
Robust Model

A major concern for the practical use of NIR spectroscopy is calibration transfer. In this study, different ways of calibration transfer were tried and compared to seek the optimal solution for our developed portable NIR spectrometers, which are designed for rapid diagnosis of bovine anemia due to parasites and are believed to be promising to replace the current time-consuming centrifugation way of measuring Hematocrit value (%) for final diagnosis. Our results show the importance of a robust model during the process of calibration transfer. It is risky to transfer a model which is not robust enough by using standardization algorithm.

scholarly journals Calibration Transfer Based on Affine Invariance for NIR without Transfer Standards

Molecules ◽  
2019 ◽  
Vol 24 (9) ◽  
pp. 1802 ◽  
Author(s):  
Yuhui Zhao ◽  
Ziheng Zhao ◽  
Peng Shan ◽  
Silong Peng ◽  
Jinlong Yu ◽  
...  
Keyword(s):  
Affine Transformation ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Regression Coefficients ◽  
Rank Test ◽  
Affine Invariance ◽  
Standard Samples ◽  
Calibration Transfer ◽  
Practical Applications ◽  
Predicted Values

Calibration transfer is an important field for near-infrared (NIR) spectroscopy in practical applications. However, most transfer methods are constructed with standard samples, which are expensive and difficult to obtain. Taking this problem into account, this paper proposes a calibration transfer method based on affine invariance without transfer standards (CTAI). Our method can be utilized to adjust the difference between two instruments by affine transformation. CTAI firstly establishes a partial least squares (PLS) model of the master instrument to obtain score matrices and predicted values of the two instruments, and then the regression coefficients between each of the score vectors and predicted values are computed for the master instrument and the slave instrument, respectively. Next, angles and biases are calculated between the regression coefficients of the master instrument and the corresponding regression coefficients of the slave instrument, respectively. Finally, by introducing affine transformation, new samples are predicted based on the obtained angles and biases. A comparative study between CTAI and the other five methods was conducted, and the performances of these algorithms were tested with two NIR spectral datasets. The obtained experimental results show clearly that, in general CTAI is more robust and can also achieve the best Root Mean Square Error of test sets (RMSEPs). In addition, the results of statistical difference with the Wilcoxon signed rank test show that CTAI is generally better than the others, and at least statistically the same.

Calibration Transfer and Measurement Stability of Near-Infrared Spectrometers

1992 ◽  
Vol 46 (5) ◽  
pp. 764-771 ◽  
Author(s):  
Yongdong Wang ◽  
Bruce R. Kowalski
Keyword(s):  
Near Infrared ◽  
Multivariate Calibration ◽  
Process Analysis ◽  
Starch Content ◽  
Industrial Process ◽  
Nir Spectroscopy ◽  
Calibration Model ◽  
Calibration Transfer ◽  
Small Set ◽  
Transfer Method

Near-infrared (NIR) spectroscopy has been widely accepted as a quantitative technique in which multivariate calibration plays an important role. The application of NIR to process analysis, however, has been largely limited by a problem identified as calibration transfer, the attempt to transfer a well-established calibration model from one instrument (e.g., located in the central laboratory) to another instrument of the same type (e.g., located on an industrial process). A calibration transfer method called piecewise direct standardization (PDS) is applied to a set of gasoline samples measured on two different NIR spectrometers. On the basis of the measurement of a small set of transfer samples on both instruments, a structured transformation matrix can be determined and applied to transform spectra between two instruments, enabling the transfer of calibration models. The effect of spectrum preprocessing on standardization is studied with the use of a set of gasoline samples. In a separate study, the day-to-day instrument variation as observed from the change in the polystyrene spectrum is related to the prediction of moisture, oil, protein, and starch content in corn samples, and then the possibility of using such generic standards to replace real samples in a transfer set is explored. In all cases, a standard error for prediction comparable to full set cross-validation is obtained through standardization.

Calibration Transfer between Miniature Photodiode Array-Based Spectrometers in the near Infrared Assessment of Mandarin Soluble Solids Content

2002 ◽  
Vol 10 (1) ◽  
pp. 27-35 ◽  
Author(s):  
C.V. Greensill ◽  
K.B. Walsh
Keyword(s):  
Near Infrared ◽  
Model Updating ◽  
Soluble Solids ◽  
Soluble Solid Content ◽  
Calibration Model ◽  
Calibration Transfer ◽  
Orthogonal Signal Correction ◽  
Significant Difference ◽  
Photodiode Array ◽  
Direct Standardisation

The transfer of predictive models among photodiode array based, short wave near infrared spectrometers using the same illumination/detection optical geometry has been attempted using various chemometric techniques, including slope and bias correction (SBC), direct standardisation (DS), piecewise direct standardisation (PDS), double window PDS (DWPDS), orthogonal signal correction (OSC), finite impulse transform (FIR) and wavelet transform (WT). Additionally, an interpolation and photometric response correction method, a wavelength selection method and a model updating method were assessed. Calibration transfer was attempted across two populations of mandarin fruit. Model performance was compared in terms of root mean squared error of prediction ( RMSEP), using Fearn's significance testing, for calibration transfer (standardisation) between pairs of spectrometers from a group of four spectrometers. For example, when a calibration model (Root Mean Square Error of Cross-Validation [ RMSECV = 0.26% soluble solid content (SSC)], developed on one spectrometer, was used with spectral data collected on another spectrometer, a poor prediction resulted ( RMSEP = 2.5% SSC). A modified WT method performed significantly better (e.g. RMSEP = 0.25% SSC) than all other standardisation methods (10 of 12 cases), and almost on a par with model updating (MU) (nine cases with no significant difference, one case and two cases significantly better for WT and MU, respectively).

Assessment of the Pulpwood Quality of Standing Trees Using near Infrared Spectroscopy

1998 ◽  
Vol 6 (A) ◽  
pp. A117-A123 ◽  
Author(s):  
L. R. Schimleck ◽  
A. J. Michell ◽  
C. A. Raymond ◽  
A. Muneri
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Tree Height ◽  
Tree Breeding ◽  
Pulp Yield ◽  
Calibration Model ◽  
Standing Trees ◽  
Sampling Height ◽  
Individual Trees ◽  
Whole Tree

In Australia, considerable effort has been directed at improving the pulp yield of plantation grown trees through tree breeding programs. However, an improvement in pulp yield relies on the assessment of large numbers of trees. Traditional methods of assessment are expensive, time consuming and destructive, inhibiting their use. Cores can be extracted non-destructively from standing trees using TRECOR, a handheld motor driven drill. The cores are milled, their near-infrared spectra obtained and pulp yield estimated using an appropriate calibration model. The height at which the core is taken is very important. It must represent the whole tree and sampling must be easy and practical. The longitudinal and radial (within-tree) variation of pulp yield for 15 Eucalyptus nitens trees was examined using near-infrared (NIR) spectroscopy. The trees were taken from three families (five trees per family) selected for giving high, medium and low pulp yields respectively. Three trees (one from each family) were examined in detail. Maps of within-tree variation of pulp yield were developed. Pulp yield was found to be highly variable within individual trees and between trees of the same family. The yield of samples from 10% of tree height (approximately 2.2 m) gave the best correlation with whole-tree yield. Samples from 5% of tree height (approximately 1.1 m) gave a slightly lower correlation but provided a more convenient sampling height. Ten Eucalyptus globulus and ten E. nitens trees growing on five sites in Australia were used to examine the longitudinal variation of pulp yield. Trees from sites in Tasmania, Western Australia and Victoria were sampled. The optimal sampling height for E. globulus was 1.1 m. No single sampling height could be recommended for E. nitens due to large site effects.

scholarly journals The application of NIR spectroscopy in moisture determining of vegetable seeds

2020 ◽  
Vol 38 (No. 2) ◽  
pp. 131-136
Author(s):  
Wojciech Poćwiardowski ◽  
Joanna Szulc ◽  
Grażyna Gozdecka
Keyword(s):  
Experimental Data ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Calibration Model ◽  
Least Squares Regression ◽  
Moisture Analysis ◽  
Non Destructive

The aim of the study was to elaborate a universal calibration for the near infrared (NIR) spectrophotometer to determine the moisture of various kinds of vegetable seeds. The research was conducted on the seeds of 5 types of vegetables – carrot, parsley, lettuce, radish and beetroot. For the spectra correlation with moisture values, the method of partial least squares regression (PLS) was used. The resulting qualitative indicators of a calibration model (R = 0.9968, Q = 0.8904) confirmed an excellent fit of the obtained calibration to the experimental data. As a result of the study, the possibilities of creating a calibration model for NIR spectrophotometer for non-destructive moisture analysis of various kinds of vegetable seeds was confirmed.<br /><br />

scholarly journals Predicting terpene content in dried conifer shoots using near infrared spectroscopy

2020 ◽  
Vol 28 (5-6) ◽  
pp. 308-314
Author(s):  
Emilie Champagne ◽  
Michaël Bonin ◽  
Alejandro A Royo ◽  
Jean-Pierre Tremblay ◽  
Patricia Raymond
Keyword(s):  
Gas Chromatography ◽  
Picea Glauca ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Calibration Method ◽  
Wide Distribution ◽  
Coefficient Of Determination ◽  
Calibration Model ◽  
Freeze Dried ◽  
Terpene Content

Terpenes are phytochemicals found in multiple plant genera, especially aromatic herbs and conifers. Terpene content quantification is costly and complex, requiring the extraction of oil content and gas chromatography analyses. Near infrared (NIR) spectroscopy could provide an alternative quantitative method, especially if calibration can be developed with the spectra of dried plant material, which are easier and faster to acquire than oil-based spectra. Here, multispecies NIR spectroscopy calibrations were developed for total terpene content (mono- and sesquiterpenes) and for specific terpenes (α-pinene, β-pinene and myrcene) with five conifers species ( Picea glauca, Picea rubens, Pinus resinosa, Pinus strobus and Thuja occidentalis). The terpene content of fresh shoot samples was quantified with gas chromatography. The NIR spectra were measured on freeze-dried samples (n = 137). Using a subset of the samples, modified partial least squares regressions of total terpene and the three individual terpenes content were generated as a functions of the NIR spectra. The standard errors of the internal cross-validations (values between 0.25 and 2.28) and the ratio of prediction to deviation ratios (RPD values between 2.20 and 2.38) indicate that all calibrations have similar accuracy. The independent validations, however, suggest that the calibrations for total terpene and α-pinene content are more accurate (respective coefficient of determination: r2 = 0.85 and 0.82). In contrast, calibrations for β-pinene and myrcene had a low accuracy (respectively: r2 = 0.62 and 0.08), potentially because of the low concentration of these terpenes in the species studied. The calibration model fits (i.e., r2) are comparable to previously published calibration using the spectra of dried shoot samples and demonstrate the potential of this method for terpenes in conifer samples. The calibration method used could be useful in several other domains (e.g. seedling breeding program, industrial), because of the wide distribution of terpenes and especially of pinenes.

scholarly journals Monitoring of CO2 Absorption Solvent in Natural Gas Process Using Fourier Transform Near-Infrared Spectrometry

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Mohd Yusop Nurida ◽  
Dolmat Norfadilah ◽  
Mohd Rozaiddin Siti Aishah ◽  
Chan Zhe Phak ◽  
Syafiqa M. Saleh
Keyword(s):  
Fourier Transform ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Infrared Spectrometry ◽  
Calibration Model ◽  
Co2 Absorption ◽  
Processing Unit

The analytical methods for the determination of the amine solvent properties do not provide input data for real-time process control and optimization and are labor-intensive, time-consuming, and impractical for studies of dynamic changes in a process. In this study, the potential of nondestructive determination of amine concentration, CO2 loading, and water content in CO2 absorption solvent in the gas processing unit was investigated through Fourier transform near-infrared (FT-NIR) spectroscopy that has the ability to readily carry out multicomponent analysis in association with multivariate analysis methods. The FT-NIR spectra for the solvent were captured and interpreted by using suitable spectra wavenumber regions through multivariate statistical techniques such as partial least square (PLS). The calibration model developed for amine determination had the highest coefficient of determination (R2) of 0.9955 and RMSECV of 0.75%. CO2 calibration model achieved R2 of 0.9902 with RMSECV of 0.25% whereas the water calibration model had R2 of 0.9915 with RMSECV of 1.02%. The statistical evaluation of the validation samples also confirmed that the difference between the actual value and the predicted value from the calibration model was not significantly different and acceptable. Therefore, the amine, CO2, and water models have given a satisfactory result for the concentration determination using the FT-NIR technique. The results of this study indicated that FT-NIR spectroscopy with chemometrics and multivariate technique can be used for the CO2 solvent monitoring to replace the time-consuming and labor-intensive conventional methods.

scholarly journals Near-Infrared Spectroscopy Combined with Multivariate Calibration to Predict the Yield of Sesame Oil Produced by Traditional Aqueous Extraction Process

2017 ◽  
Vol 2017 ◽  
pp. 1-5
Author(s):  
Yong-Dong Xu ◽  
Yan-Ping Zhou ◽  
Jing Chen
Keyword(s):  
Near Infrared ◽  
Multivariate Calibration ◽  
Nir Spectroscopy ◽  
Extraction Process ◽  
Sesame Oil ◽  
Aqueous Extraction ◽  
Oil Yield ◽  
Support Vector ◽  
Calibration Model ◽  
Aqueous Extraction Process

Sesame oil produced by the traditional aqueous extraction process (TAEP) has been recognized by its pleasant flavor and high nutrition value. This paper developed a rapid and nondestructive method to predict the sesame oil yield by TAEP using near-infrared (NIR) spectroscopy. A collection of 145 sesame seed samples was measured by NIR spectroscopy and the relationship between the TAEP oil yield and the spectra was modeled by least-squares support vector machine (LS-SVM). Smoothing, taking second derivatives (D2), and standard normal variate (SNV) transformation were performed to remove the unwanted variations in the raw spectra. The results indicated that D2-LS-SVM (4000–9000 cm−1) obtained the most accurate calibration model with root mean square error of prediction (RMSEP) of 1.15 (%, w/w). Moreover, the RMSEP was not significantly influenced by different initial values of LS-SVM parameters. The calibration model could be helpful to search for sesame seeds with higher TAEP oil yields.

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