Temperature Robust Multivariate Calibration: An Overview of Methods for Dealing with Temperature Influences on near Infrared Spectra

2005 ◽  
Vol 13 (2) ◽  
pp. 53-62 ◽  
Author(s):  
J.A. Hageman ◽  
J.A. Westerhuis ◽  
A.K. Smilde
Keyword(s):  
Chemical Composition ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Data Sets ◽  
Near Infrared Spectra ◽  
Sample Composition ◽  
Spectral Intensities

Multivariate calibration is a powerful tool for establishing a relationship between spectral variables and properties of interest. Usually, changes in spectral variables are ascribed to changes in the chemical composition of the sample. However, spectral intensities that are measured at varying temperatures do not only change because of changes in sample composition but also respond to the change in temperature. In these cases, multivariate calibration can be (severely) hindered, resulting in a loss of prediction capabilities. This paper provides an overview of the characteristics and possibilities of (most) methods for temperature robust multivariate calibration. The methods are discussed by using two data sets.

Pure Component Selectivity Analysis of Multivariate Calibration Models from Near-Infrared Spectra

2004 ◽  
Vol 76 (9) ◽  
pp. 2583-2590 ◽  
Author(s):  
Mark A. Arnold ◽  
Gary W. Small ◽  
Dong Xiang ◽  
Jiang Qui ◽  
David W. Murhammer
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Pure Component ◽  
Near Infrared Spectra ◽  
Calibration Models

Diurnal variation in the composition of duodenal digesta

1997 ◽  
Vol 1997 ◽  
pp. 207-207
Author(s):  
S.J. Lister ◽  
R. Sanderson ◽  
A. Sargeant
Keyword(s):  
Chemical Composition ◽  
Chemical Analysis ◽  
Infrared Spectra ◽  
Chemical Structure ◽  
Near Infrared ◽  
Diurnal Changes ◽  
Difference Spectra ◽  
Near Infrared Spectra ◽  
Source Of Information ◽  
Detailed Chemical

The size of biological samples is often, by necessity, small and precludes a full and detailed chemical analysis of the material. Near infrared spectra are comprehensive records of the chemical structure and content of a substrate and are thus a rich source of information. To investigate diurnal changes in the chemical composition of duodenal digesta, NIR spectra and difference spectra were used to examine samples collected over a 24h period.

Multivariate calibration of near infrared spectra by orthogonal WAVElet correction using a genetic algorithm

2006 ◽  
Vol 555 (1) ◽  
pp. 84-95 ◽  
Author(s):  
I. Esteban-Díez ◽  
J.M. González-Sáiz ◽  
D. Gómez-Cámara ◽  
C. Pizarro Millan
Keyword(s):  
Genetic Algorithm ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Orthogonal Wavelet ◽  
Near Infrared Spectra

Reagentless Near-Infrared Determination of Glucose in Whole Blood Using Multivariate Calibration

1992 ◽  
Vol 46 (10) ◽  
pp. 1575-1578 ◽  
Author(s):  
David M. Haaland ◽  
M. Ries Robinson ◽  
Gary W. Koepp ◽  
Edward V. Thomas ◽  
R. Philip Eaton
Keyword(s):  
Infrared Spectra ◽  
Glucose Concentration ◽  
Whole Blood ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Blood Chemistry ◽  
Standard Errors ◽  
Diabetic Patients ◽  
Blood Samples ◽  
Near Infrared Spectra

Noninvasive monitoring of glucose in diabetic patients is feasible with the use of near-infrared spectroscopic measurements. As a step toward the final goal of the development of a noninvasive monitor, the near-infrared spectra (4250 to 6600 cm−1) of glucose-doped whole blood samples were obtained along with reference glucose values. Glucose concentrations and spectra of blood samples obtained from four subjects were subjected to multivariate calibration with the use of partial least-squares (PLS) methods. The cross-validated PLS standard errors of prediction for glucose concentration based on data obtained from each individual subject's blood samples averaged 33 mg/dL over the range from 3 to 743 mg/dL. Cross-validated standard errors for glucose concentration from PLS calibrations based on data from all four subjects were 39 mg/dL. However, when PLS models based upon three subjects' data were used for prediction on the fourth, glucose prediction abilities were poor. It is suggested that blood chemistry differences were sufficiently different for the four subjects to require that a larger number of subjects be included in the calibration for adequate prediction abilities to be obtained from near-infrared spectra of blood from subjects not included in the calibration.

Multivariate Calibration of Sulfur in Sour Crude Oils via Near-Infrared Spectra

2021 ◽  
Author(s):  
Slobodan Šašić ◽  
Howard Yokelson ◽  
Todd Kotecki ◽  
Stacy Austin ◽  
Kevin Thacker ◽  
...  
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Crude Oils ◽  
Near Infrared Spectra ◽  
Sour Crude
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