The application of fourier-transformed near-infrared spectra to quantitative analysis by comparison of similarity indices (CARNAC)

Davies, A.M.C.; Britcher, Heather V.; Franklin, Jeremy; Ring, Susan M.; Grant, Alex; McClure, W. F.

doi:10.1007/bf01205839

Cited by 46 publications

(41 citation statements)

References 1 publication

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“…In fact, the technique adopted by Sinnaeve et al, 4 required two minutes per sample (with a 486 personal computer). The CARNAC procedure proposed by Davies et al 5 had a method of sample selection similar to the one adopted in LOCAL and resulted in faster prediction than the procedure used by Sinnaeve et al 4 Using a personal computer based 230 Investigation of a LOCAL Calibration Procedure for NIR Instruments on Intel ® Pentium 90 MHz, the prediction of the 400 corn samples with reduced spectra, using 200 selected samples per calibration with 26 PLS factors, was completed in about ten minutes. Prediction of the 679 haylage samples required 17 minutes.…”

Section: Speed Improvementmentioning

confidence: 99%

Investigation of a LOCAL Calibration Procedure for near Infrared Instruments

Shenk

Westerhaus

Berzaghi

1997

Journal of Near Infrared Spectroscopy

171

162

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A new procedure (LOCAL) for local calibrations is presented. LOCAL selects spectra from a library of samples and computes a PLS calibration equation for each constituent of the sample. This study evaluated the performances of LOCAL on the prediction of ground corn grain and haylage using several different combinations of data transformations, wavelength segment reduction, number of PLS factors and samples used in calibration. LOCAL resulted in lower SEP values for all the constituents of corn and dry matter of haylage with improvements ranging between 6 to 13%. Global calibrations had only a small advantage over LOCAL (1-2%) in the prediction of acid de-tergent fibre and crude protein in haylage. The two most important variables controlling the accuracy of predictions were number of samples in the calibration and number of PLS factors in the solution. Best results were obtained using 150 to 225 samples and more than 20 PLS factors per calibration equation. The speed of the LOCAL procedure is 0.5-2 s per sample on a 90 MHz computer. With this speed and accuracy, LOCAL is now available for real-time routine operation on a Windows platform.

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Section: Speed Improvementmentioning

confidence: 99%

Investigation of a LOCAL Calibration Procedure for near Infrared Instruments

Shenk

Westerhaus

Berzaghi

1997

Journal of Near Infrared Spectroscopy

171

162

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“…distance on PCA scores), users have the possibility of implementing local chemometrics methods to select only the most appropriate samples. Locally weighted regression [12,13] (LWR), LOCAL [14], and CARNAC [15,16] are the most common sample selection methods. These techniques have the advantage of being much less sensitive to nonlinearity and outliers than other full scale multivariate methods.…”

Section: Introductionmentioning

confidence: 99%

Local chemometrics for samples and variables: optimizing calibration and standardization processes

Igne

Hurburgh

2010

Journal of Chemometrics

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The ability of five sample selection methods for local chemometrics and three variable selection algorithms were compared for the development and the transfer of whole soybeans protein and oil near infrared prediction models. Two new methods based on a similarity index considering Euclidian distance among Fourier coefficients were introduced and tested against more common approaches (locally weighted regression, LOCAL). Genetic algorithms were also challenged with the development of models based on particle swarm optimization (PSO). A modification to the original PSO model was introduced. Sample and variable selection methods, as well as their combinations, were tested in the transfer of models in intra-and inter-brand situations using two Foss Infratecs and two Bruins OmegAnalyzerGs. For each brand, a master was designated and its models transferred onto the second unit of its network and the two units of the second brand. Calibration models were proven transferable from brand to brand with similar or better precisions than when all instruments were calibrated on their own calibration sets (relative predictive determinant (RPD) improving from 10.42 to 12.76 and 12.39 in intra-brand standardization for Infratec network with local and variable selection methods respectively). These methods provided contrasted results depending on the instrument, the parameter, and the variability of interest.

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“…Of the existing local regression methods, comparison analyses using restructured near‐infrared and constituent data, locally weighted regression (LWR), and the LOCAL algorithm patented by Shenk et al are the most widely used when dealing with NIRS applications. Such methods try to deal with nonlinear or clustering problems occurring during global model building.…”

Section: Introductionmentioning

confidence: 99%

“…Such methods try to deal with nonlinear or clustering problems occurring during global model building. Comparison analyses using restructured near‐infrared and constituent, proposed by Davies et al, is a simple and rapid method, which predicts the value of an unknown sample by calculating a weighted average of the analytical reference values of the similar samples, selected based on r 2 between the reduced and modified unknown spectrum and each spectrum in the database, compressed by a Fourier transformation . LWR was introduced by Cleveland and Devlin as a curve‐fitting method .…”

Section: Introductionmentioning

confidence: 99%

Local partial least squares based on global PLS scores

Shen

Lesnoff

Baeten

et al. 2019

Journal of Chemometrics

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A local‐based method for near‐infrared spectroscopy predictions, the local partial least squares regression on global PLS scores (LPLS‐S), is proposed in this work and compared with the usual local PLS (LPLS) regression approach. LPLS‐S is based on the idea of replacing the original spectra with a global PLS score matrix before using the usual LPLS. This is done with the aim of increasing the speed of the calculations, which can be an important parameter for online applications in particular, especially when implemented on large databases. In this study, the performance of the two local approaches was compared in terms of efficiency and speed. It could be concluded that the root‐mean‐square error of prediction of LPLS and LPLS‐S were 1.1962 and 1.1602, respectively, but the calculation speed for LPLS‐S was more than 20 times faster than for the LPLS algorithm.

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The application of fourier-transformed near-infrared spectra to quantitative analysis by comparison of similarity indices (CARNAC)

Cited by 46 publications

References 1 publication

Investigation of a LOCAL Calibration Procedure for near Infrared Instruments

Investigation of a LOCAL Calibration Procedure for near Infrared Instruments

Local chemometrics for samples and variables: optimizing calibration and standardization processes

Local partial least squares based on global PLS scores

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