Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions

Research output: Contribution to journalJournal articlepeer-review

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Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics : The challenge of inherently intercorrelated response functions. / Rinnan, Åsmund; Bruun, Sander; Lindedam, Jane; Decker, Stephen R.; Turner, Geoffrey B.; Felby, Claus; Engelsen, Søren Balling.

In: Analytica Chimica Acta, Vol. 962, 2017, p. 15-23.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Rinnan, Å, Bruun, S, Lindedam, J, Decker, SR, Turner, GB, Felby, C & Engelsen, SB 2017, 'Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions', Analytica Chimica Acta, vol. 962, pp. 15-23. https://doi.org/10.1016/j.aca.2017.02.001

APA

Rinnan, Å., Bruun, S., Lindedam, J., Decker, S. R., Turner, G. B., Felby, C., & Engelsen, S. B. (2017). Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions. Analytica Chimica Acta, 962, 15-23. https://doi.org/10.1016/j.aca.2017.02.001

Vancouver

Rinnan Å, Bruun S, Lindedam J, Decker SR, Turner GB, Felby C et al. Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions. Analytica Chimica Acta. 2017;962:15-23. https://doi.org/10.1016/j.aca.2017.02.001

Author

Rinnan, Åsmund ; Bruun, Sander ; Lindedam, Jane ; Decker, Stephen R. ; Turner, Geoffrey B. ; Felby, Claus ; Engelsen, Søren Balling. / Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics : The challenge of inherently intercorrelated response functions. In: Analytica Chimica Acta. 2017 ; Vol. 962. pp. 15-23.

Bibtex

@article{bd7a0ef1904e4effbeca85b643e73c71,
title = "Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions",
abstract = "The combination of NIR spectroscopy and chemometrics is a powerful correlation method for predicting the chemical constituents in biological matrices, such as the glucose and xylose content of straw. However, difficulties arise when it comes to predicting enzymatic glucose and xylose release potential, which is matrix dependent. Further complications are caused by xylose and glucose release potential being highly intercorrelated. This study emphasizes the importance of understanding the causal relationship between the model and the constituent of interest. It investigates the possibility of using near-infrared spectroscopy to evaluate the ethanol potential of wheat straw by analyzing more than 1000 samples from different wheat varieties and growth conditions. During the calibration model development, the prime emphasis was to investigate the correlation structure between the two major quality traits for saccharification of wheat straw: glucose and xylose release. The large sample set enabled a versatile and robust calibration model to be developed, showing that the prediction model for xylose release is based on a causal relationship with the NIR spectral data. In contrast, the prediction of glucose release was found to be highly dependent on the intercorrelation with xylose release. If this correlation is broken, the model performance breaks down. A simple method was devised for avoiding this breakdown and can be applied to any large dataset for investigating the causality or lack of causality of a prediction model.",
keywords = "Calibration, Correlated response variables, Enzymatic sugar release, NIR, Straw",
author = "{\AA}smund Rinnan and Sander Bruun and Jane Lindedam and Decker, {Stephen R.} and Turner, {Geoffrey B.} and Claus Felby and Engelsen, {S{\o}ren Balling}",
year = "2017",
doi = "10.1016/j.aca.2017.02.001",
language = "English",
volume = "962",
pages = "15--23",
journal = "Analytica Chimica Acta",
issn = "0003-2670",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics

T2 - The challenge of inherently intercorrelated response functions

AU - Rinnan, Åsmund

AU - Bruun, Sander

AU - Lindedam, Jane

AU - Decker, Stephen R.

AU - Turner, Geoffrey B.

AU - Felby, Claus

AU - Engelsen, Søren Balling

PY - 2017

Y1 - 2017

N2 - The combination of NIR spectroscopy and chemometrics is a powerful correlation method for predicting the chemical constituents in biological matrices, such as the glucose and xylose content of straw. However, difficulties arise when it comes to predicting enzymatic glucose and xylose release potential, which is matrix dependent. Further complications are caused by xylose and glucose release potential being highly intercorrelated. This study emphasizes the importance of understanding the causal relationship between the model and the constituent of interest. It investigates the possibility of using near-infrared spectroscopy to evaluate the ethanol potential of wheat straw by analyzing more than 1000 samples from different wheat varieties and growth conditions. During the calibration model development, the prime emphasis was to investigate the correlation structure between the two major quality traits for saccharification of wheat straw: glucose and xylose release. The large sample set enabled a versatile and robust calibration model to be developed, showing that the prediction model for xylose release is based on a causal relationship with the NIR spectral data. In contrast, the prediction of glucose release was found to be highly dependent on the intercorrelation with xylose release. If this correlation is broken, the model performance breaks down. A simple method was devised for avoiding this breakdown and can be applied to any large dataset for investigating the causality or lack of causality of a prediction model.

AB - The combination of NIR spectroscopy and chemometrics is a powerful correlation method for predicting the chemical constituents in biological matrices, such as the glucose and xylose content of straw. However, difficulties arise when it comes to predicting enzymatic glucose and xylose release potential, which is matrix dependent. Further complications are caused by xylose and glucose release potential being highly intercorrelated. This study emphasizes the importance of understanding the causal relationship between the model and the constituent of interest. It investigates the possibility of using near-infrared spectroscopy to evaluate the ethanol potential of wheat straw by analyzing more than 1000 samples from different wheat varieties and growth conditions. During the calibration model development, the prime emphasis was to investigate the correlation structure between the two major quality traits for saccharification of wheat straw: glucose and xylose release. The large sample set enabled a versatile and robust calibration model to be developed, showing that the prediction model for xylose release is based on a causal relationship with the NIR spectral data. In contrast, the prediction of glucose release was found to be highly dependent on the intercorrelation with xylose release. If this correlation is broken, the model performance breaks down. A simple method was devised for avoiding this breakdown and can be applied to any large dataset for investigating the causality or lack of causality of a prediction model.

KW - Calibration

KW - Correlated response variables

KW - Enzymatic sugar release

KW - NIR

KW - Straw

U2 - 10.1016/j.aca.2017.02.001

DO - 10.1016/j.aca.2017.02.001

M3 - Journal article

C2 - 28231876

AN - SCOPUS:85012883293

VL - 962

SP - 15

EP - 23

JO - Analytica Chimica Acta

JF - Analytica Chimica Acta

SN - 0003-2670

ER -

ID: 176653403