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

Abstract

Here, 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. Amore » 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.« less

Authors:
ORCiD logo [1];  [1];  [1];  [2];  [3];  [1];  [1]
  1. Univ. of Copenhagen (Denmark)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. National Renewable Energy Lab. (NREL), Golden, CO (United States); Waters Corp., Milford, MA (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1345717
Report Number(s):
NREL/JA-2700-67917
Journal ID: ISSN 0003-2670
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Analytica Chimica Acta
Additional Journal Information:
Journal Volume: 962; Journal Issue: C; Journal ID: ISSN 0003-2670
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; 54 ENVIRONMENTAL SCIENCES; NIR; calibration; correlated response variables; straw; enzymatic sugar release

Citation Formats

Rinnan, Asmund, Bruun, Sander, Lindedam, Jane, Decker, Stephen R., Turner, Geoffrey B., Felby, Claus, and Engelsen, Soren Balling. Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions. United States: N. p., 2017. Web. doi:10.1016/j.aca.2017.02.001.
Rinnan, Asmund, Bruun, Sander, Lindedam, Jane, Decker, Stephen R., Turner, Geoffrey B., Felby, Claus, & Engelsen, Soren Balling. Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions. United States. doi:10.1016/j.aca.2017.02.001.
Rinnan, Asmund, Bruun, Sander, Lindedam, Jane, Decker, Stephen R., Turner, Geoffrey B., Felby, Claus, and Engelsen, Soren Balling. Tue . "Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions". United States. doi:10.1016/j.aca.2017.02.001. https://www.osti.gov/servlets/purl/1345717.
@article{osti_1345717,
title = {Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions},
author = {Rinnan, Asmund and Bruun, Sander and Lindedam, Jane and Decker, Stephen R. and Turner, Geoffrey B. and Felby, Claus and Engelsen, Soren Balling},
abstractNote = {Here, 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.},
doi = {10.1016/j.aca.2017.02.001},
journal = {Analytica Chimica Acta},
number = C,
volume = 962,
place = {United States},
year = {Tue Feb 07 00:00:00 EST 2017},
month = {Tue Feb 07 00:00:00 EST 2017}
}

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