Multivariate quality control solved by one-class partial least squares regression: identification of adulterated peanut oils by mid-infrared spectroscopy

2011 ◽  
Vol 25 (10) ◽  
pp. 568-574 ◽  
Author(s):  
Lu Xu ◽  
Chen-Bo Cai ◽  
De-Hua Deng
Keyword(s):  
Quality Control ◽  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy ◽  
Multivariate Quality Control

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.

scholarly journals Determination of carbohydrates present in Saccharomyces cerevisiae using mid-infrared spectroscopy and partial least squares regression

2013 ◽  
Vol 405 (25) ◽  
pp. 8241-8250 ◽  
Author(s):  
Maria R. Plata ◽  
Cosima Koch ◽  
Patrick Wechselberger ◽  
Christoph Herwig ◽  
Bernhard Lendl
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy

Fast determination of anthocyanins in red grape musts by Fourier transform mid-infrared spectroscopy and partial least squares regression

2015 ◽  
Vol 240 (5) ◽  
pp. 897-908 ◽  
Author(s):  
Z. Rasines-Perea ◽  
N. Prieto-Perea ◽  
M. Romera-Fernández ◽  
L. A. Berrueta ◽  
B. Gallo
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares Regression ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Fast Determination ◽  
Red Grape ◽  
Grape Musts

scholarly journals Thermal infrared spectroscopy and partial least squares regression to determine mineral modes of granitoid rocks

2012 ◽  
Vol 13 (3) ◽  
pp. n/a-n/a ◽  
Author(s):  
Christoph Hecker ◽  
John H. Dilles ◽  
Mark van der Meijde ◽  
Freek D. van der Meer
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Thermal Infrared ◽  
Least Squares Regression ◽  
Granitoid Rocks ◽  
Thermal Infrared Spectroscopy
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