Comparison of sample preparation methods on the infected corn seed detection by NIR spectroscopy

The purpose of this study was to compare the sample preparation for detection of the corn seed infected with Aspergillus flavus by NIR (near infrared) spectroscopy. There were two kinds of samples: whole grain corn, and ground corn seed. The spectra of non-infected (normal seed) and infected seeds a...

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Main Authors: Phetkaeo T., Klaithin R., Theanjumpol P., Kunasakdakul K., Thanapornpoonpong S., Vearasilp S.
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Published: Chiang Mai University 2015
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http://cmuir.cmu.ac.th/handle/6653943832/38038
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spelling th-cmuir.6653943832-380382015-06-16T04:14:35Z Comparison of sample preparation methods on the infected corn seed detection by NIR spectroscopy Phetkaeo T. Phetkaeo T. Phetkaeo T. Klaithin R. Klaithin R. Theanjumpol P. Theanjumpol P. Kunasakdakul K. Kunasakdakul K. Kunasakdakul K. Thanapornpoonpong S. Thanapornpoonpong S. Thanapornpoonpong S. Vearasilp S. Vearasilp S. Vearasilp S. Multidisciplinary The purpose of this study was to compare the sample preparation for detection of the corn seed infected with Aspergillus flavus by NIR (near infrared) spectroscopy. There were two kinds of samples: whole grain corn, and ground corn seed. The spectra of non-infected (normal seed) and infected seeds at the ratio of 5, 10, 15 and 20% w/w were scanned by using NIRSystem 6500 in the wavelength range 1100-2500 nm. The ground sample was prepared by laboratory mill, then its spectrum was scanned using the same process as the whole infected grain. The mathematical techniques such as second derivative, multiplicative scatter correction and second derivative were used to transform the NIR spectra. The calibration equations to predict the infected quantity of infected seeds of whole grain and ground samples were developed by partial least squares regression (PLSR). It was found that the calibration equation for the infected seed prediction of ground sample provided the higher value of the correlation coefficient (R) and ratio of standard deviation of reference data in validation set to SEP (RPD) than whole grain samples which were 0.98, 5.36 and 0.80, 1.74 respectively. Meanwhile, the standard errors of calibration (SEC), the standard errors of prediction (SEP) and the averages of difference between actual and NIR values (Bias) of ground sample were lower than those from whole grain sample. There were 4.18, 4.08, 0.54% and 1.17, 1.32, 0.38% respectively. Therefore, ground sample is suggested before subject to NIR spectroscopy to detect the infected maize seed. 2015-06-16T04:14:35Z 2015-06-16T04:14:35Z 2012-12-01 Article 16851994 2-s2.0-84872230891 http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84872230891&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/38038 Chiang Mai University
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Multidisciplinary
spellingShingle Multidisciplinary
Phetkaeo T.
Phetkaeo T.
Phetkaeo T.
Klaithin R.
Klaithin R.
Theanjumpol P.
Theanjumpol P.
Kunasakdakul K.
Kunasakdakul K.
Kunasakdakul K.
Thanapornpoonpong S.
Thanapornpoonpong S.
Thanapornpoonpong S.
Vearasilp S.
Vearasilp S.
Vearasilp S.
Comparison of sample preparation methods on the infected corn seed detection by NIR spectroscopy
description The purpose of this study was to compare the sample preparation for detection of the corn seed infected with Aspergillus flavus by NIR (near infrared) spectroscopy. There were two kinds of samples: whole grain corn, and ground corn seed. The spectra of non-infected (normal seed) and infected seeds at the ratio of 5, 10, 15 and 20% w/w were scanned by using NIRSystem 6500 in the wavelength range 1100-2500 nm. The ground sample was prepared by laboratory mill, then its spectrum was scanned using the same process as the whole infected grain. The mathematical techniques such as second derivative, multiplicative scatter correction and second derivative were used to transform the NIR spectra. The calibration equations to predict the infected quantity of infected seeds of whole grain and ground samples were developed by partial least squares regression (PLSR). It was found that the calibration equation for the infected seed prediction of ground sample provided the higher value of the correlation coefficient (R) and ratio of standard deviation of reference data in validation set to SEP (RPD) than whole grain samples which were 0.98, 5.36 and 0.80, 1.74 respectively. Meanwhile, the standard errors of calibration (SEC), the standard errors of prediction (SEP) and the averages of difference between actual and NIR values (Bias) of ground sample were lower than those from whole grain sample. There were 4.18, 4.08, 0.54% and 1.17, 1.32, 0.38% respectively. Therefore, ground sample is suggested before subject to NIR spectroscopy to detect the infected maize seed.
format Article
author Phetkaeo T.
Phetkaeo T.
Phetkaeo T.
Klaithin R.
Klaithin R.
Theanjumpol P.
Theanjumpol P.
Kunasakdakul K.
Kunasakdakul K.
Kunasakdakul K.
Thanapornpoonpong S.
Thanapornpoonpong S.
Thanapornpoonpong S.
Vearasilp S.
Vearasilp S.
Vearasilp S.
author_facet Phetkaeo T.
Phetkaeo T.
Phetkaeo T.
Klaithin R.
Klaithin R.
Theanjumpol P.
Theanjumpol P.
Kunasakdakul K.
Kunasakdakul K.
Kunasakdakul K.
Thanapornpoonpong S.
Thanapornpoonpong S.
Thanapornpoonpong S.
Vearasilp S.
Vearasilp S.
Vearasilp S.
author_sort Phetkaeo T.
title Comparison of sample preparation methods on the infected corn seed detection by NIR spectroscopy
title_short Comparison of sample preparation methods on the infected corn seed detection by NIR spectroscopy
title_full Comparison of sample preparation methods on the infected corn seed detection by NIR spectroscopy
title_fullStr Comparison of sample preparation methods on the infected corn seed detection by NIR spectroscopy
title_full_unstemmed Comparison of sample preparation methods on the infected corn seed detection by NIR spectroscopy
title_sort comparison of sample preparation methods on the infected corn seed detection by nir spectroscopy
publisher Chiang Mai University
publishDate 2015
url http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84872230891&origin=inward
http://cmuir.cmu.ac.th/handle/6653943832/38038
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