Wavelength Calibration Transfer between Diode Array UV-Visible Spectrophotometers

1995 ◽  
Vol 49 (5) ◽  
pp. 593-597 ◽  
Author(s):  
Marcelo Blanco ◽  
Jordi Coello ◽  
Hortensia Iturriaga ◽  
Santiago Maspoch ◽  
Esther Rovira
Keyword(s):  
Partial Least Squares Regression ◽  
Multivariate Calibration ◽  
Potassium Dichromate ◽  
Diode Array ◽  
Least Squares Regression ◽  
Calibration Transfer ◽  
Manufacturing Line ◽  
Straightforward Method ◽  
Zero Values ◽  
Uv Visible

The need to obtain expeditious results in control analyses of complex mixtures has turned multivariate calibration procedures into major choices for routine analyses. The inherent complexity of the calibration process and the practical need for analyses to be carried out as near the manufacturing line as possible occasionally entail calibrating with a different instrument from that subsequently employed for the analytical measurements proper. This paper exposes the problems potentially arising in transferring calibrations between diode array UV-Vis spectrophotometers. Basically, such problems originate in wavelength differences between spectrophotometers, even if they meet the manufacturer's specifications and the pharmacopoeia recommendations. We developed a straightforward method for harmonizing instrumental responses on the basis of reference wavelengths corresponding to zero values in the first-derivative spectra for potassium dichromate and benzoic acid standards. The method was applied to the analysis of binary mixtures of theophylline and doxylamine by multiple linear and partial least-squares regression with the use of one spectrophotometer for calibration and four others for analyses.

scholarly journals Rapid tannin profiling of tree fodders using untargeted mid-infrared spectroscopy and partial least squares regression

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Jordi Ortuño ◽  
Sokratis Stergiadis ◽  
Anastasios Koidis ◽  
Jo Smith ◽  
Chris Humphrey ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Multivariate Calibration ◽  
Plant Ecology ◽  
Coefficient Of Determination ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy

Abstract Background The presence of condensed tannins (CT) in tree fodders entails a series of productive, health and ecological benefits for ruminant nutrition. Current wet analytical methods employed for full CT characterisation are time and resource-consuming, thus limiting its applicability for silvopastoral systems. The development of quick, safe and robust analytical techniques to monitor CT’s full profile is crucial to suitably understand CT variability and biological activity, which would help to develop efficient evidence-based decision-making to maximise CT-derived benefits. The present study investigates the suitability of Fourier-transformed mid-infrared spectroscopy (MIR: 4000–550 cm−1) combined with multivariate analysis to determine CT concentration and structure (mean degree of polymerization—mDP, procyanidins:prodelphidins ratio—PC:PD and cis:trans ratio) in oak, field maple and goat willow foliage, using HCl:Butanol:Acetone:Iron (HBAI) and thiolysis-HPLC as reference methods. Results The MIR spectra obtained were explored firstly using Principal Component Analysis, whereas multivariate calibration models were developed based on partial least-squares regression. MIR showed an excellent prediction capacity for the determination of PC:PD [coefficient of determination for prediction (R2P) = 0.96; ratio of prediction to deviation (RPD) = 5.26, range error ratio (RER) = 14.1] and cis:trans ratio (R2P = 0.95; RPD = 4.24; RER = 13.3); modest for CT quantification (HBAI: R2P = 0.92; RPD = 3.71; RER = 13.1; Thiolysis: R2P = 0.88; RPD = 2.80; RER = 11.5); and weak for mDP (R2P = 0.66; RPD = 1.86; RER = 7.16). Conclusions MIR combined with chemometrics allowed to characterize the full CT profile of tree foliage rapidly, which would help to assess better plant ecology variability and to improve the nutritional management of ruminant livestock.

Simultaneous Measurements of Glucose, Glutamine, Ammonia, Lactate, and Glutamate in Aqueous Solutions by Near-Infrared Spectroscopy

1996 ◽  
Vol 50 (2) ◽  
pp. 270-276 ◽  
Author(s):  
Hoeil Chung ◽  
Mark A. Arnold ◽  
Martin Rhiel ◽  
David W. Murhammer
Keyword(s):  
Aqueous Solutions ◽  
Partial Least Squares Regression ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Least Squares Regression ◽  
Fermentation Processes ◽  
Near Ir ◽  
Calibration Models ◽  
Concentration Levels ◽  
Absorbance Spectra

Calibration models are generated and evaluated for the measurement of five different components in synthetic mixtures prepared in aqueous solutions. Mixtures of glucose, glutamine, ammonia, lactate, and glutamate were prepared to simulate concentration levels expected during routine bioreactor fermentation processes. Near-IR spectra were collected from these solutions over the spectral range from 5000 to 4000 cm−1. This spectral information was used to build individual multivariate calibration models for each analyte. Models were constructed on the basis of partial least-squares regression of raw and Fourier filtered absorbance spectra. Each analyte could be detected selectively with mean percent errors of prediction ranging from 4 to 8%.

scholarly journals The development of green analytical methods to monitor adulteration in honey by UV-visible spectroscopy and chemometrics models

2020 ◽  
Vol 211 ◽  
pp. 02011
Author(s):  
Omar Elhamdaoui ◽  
Aimen El Orche ◽  
Houda Bouchafra ◽  
Miloud El Karbane ◽  
Amine Cheikh ◽  
...  
Keyword(s):  
Analytical Methods ◽  
Partial Least Squares Regression ◽  
Cross Validation ◽  
Essential Element ◽  
Support Vector ◽  
Least Squares Regression ◽  
Visible Spectroscopy ◽  
Uv Visible ◽  
Non Destructive

The development of green and environmentally friendly analytical methods for agri-food products is an essential element to be treated by green analytical chemistry. In this study, UV-Visible spectroscopy, combined with a mathematical and statistical or chemometrics algorithm, has been developed to monitor honey quality. Partial Least Squares Regression (PLS-R) and Support Vector Machine Learning Regression (SVM-R) showed an adequate quantification of the percentage of impurity. The use of these models demonstrates a high ability to predict the quality of honey. R-square’s high value shows this ability, and the low value of root mean square error of calibration and cross-validation (RMSECV, RMSEC). The results indicate that UV-Visible spectroscopy allied with the Chemometrics algorithms can provide a quick, non-destructive, green, and reliable method to control the quality and predict honey’s adulteration level.

Calibration approaches for the measurement of aerosol multielemental concentration using spark emission spectroscopy

2018 ◽  
Vol 33 (3) ◽  
pp. 404-412 ◽  
Author(s):  
Lina Zheng ◽  
Pramod Kulkarni ◽  
Dionysios D. Dionysiou
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Emission Spectroscopy ◽  
Partial Least Squares Regression ◽  
Elemental Concentration ◽  
Multivariate Calibration ◽  
Least Squares Regression ◽  
Calibration Approach

A multivariate calibration approach, using partial least squares regression, has been developed for the measurement of aerosol elemental concentration.

Simultaneous Determination of Rubber Additives by FT-IR Spectrophotometry with Multivariate Calibration

1995 ◽  
Vol 49 (6) ◽  
pp. 747-753 ◽  
Author(s):  
M. Blanco ◽  
J. Coello ◽  
H. Iturriaga ◽  
S. Maspoch ◽  
E. Bertran
Keyword(s):  
Fourier Transform ◽  
Simultaneous Determination ◽  
Partial Least Squares Regression ◽  
Multivariate Calibration ◽  
Least Squares Regression ◽  
First Derivative ◽  
Vulcanized Rubber ◽  
Ir Spectrophotometry ◽  
Ft Ir

A new method for the simultaneous determination of vulcanized rubber additives by Fourier transform infrared (FT-IR) spectrophotometry using partial least-squares regression (PLSR) for multivariate calibration was developed. The effect of various wavenumber ranges and the use of the absorbance and first-derivative spectral modes on performance were studied by applying the method to three different sample batches containing several additives in different proportions, all of which were resolved with satisfactory results.

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