Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat

In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectrosco...
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Autor*in:	Kun Liang [verfasserIn] Jinpeng Song [verfasserIn] Rui Yuan [verfasserIn] Zhizhou Ren [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	spectroscopic techniques fusarium head blight fingerprint region data fusion

Übergeordnetes Werk:	In: Sensors - MDPI AG, 2003, 23(2023), 14, p 6600
Übergeordnetes Werk:	volume:23 ; year:2023 ; number:14, p 6600

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/s23146600

Katalog-ID:	DOAJ093828349

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520			\|a In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples.
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allfields	10.3390/s23146600 doi (DE-627)DOAJ093828349 (DE-599)DOAJ78f22942d35b4345805e66c67a5f0679 DE-627 ger DE-627 rakwb eng TP1-1185 Kun Liang verfasserin aut Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples. spectroscopic techniques fusarium head blight fingerprint region data fusion Chemical technology Jinpeng Song verfasserin aut Rui Yuan verfasserin aut Zhizhou Ren verfasserin aut In Sensors MDPI AG, 2003 23(2023), 14, p 6600 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:23 year:2023 number:14, p 6600 https://doi.org/10.3390/s23146600 kostenfrei https://doaj.org/article/78f22942d35b4345805e66c67a5f0679 kostenfrei https://www.mdpi.com/1424-8220/23/14/6600 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 14, p 6600
spelling	10.3390/s23146600 doi (DE-627)DOAJ093828349 (DE-599)DOAJ78f22942d35b4345805e66c67a5f0679 DE-627 ger DE-627 rakwb eng TP1-1185 Kun Liang verfasserin aut Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples. spectroscopic techniques fusarium head blight fingerprint region data fusion Chemical technology Jinpeng Song verfasserin aut Rui Yuan verfasserin aut Zhizhou Ren verfasserin aut In Sensors MDPI AG, 2003 23(2023), 14, p 6600 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:23 year:2023 number:14, p 6600 https://doi.org/10.3390/s23146600 kostenfrei https://doaj.org/article/78f22942d35b4345805e66c67a5f0679 kostenfrei https://www.mdpi.com/1424-8220/23/14/6600 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 14, p 6600
allfields_unstemmed	10.3390/s23146600 doi (DE-627)DOAJ093828349 (DE-599)DOAJ78f22942d35b4345805e66c67a5f0679 DE-627 ger DE-627 rakwb eng TP1-1185 Kun Liang verfasserin aut Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples. spectroscopic techniques fusarium head blight fingerprint region data fusion Chemical technology Jinpeng Song verfasserin aut Rui Yuan verfasserin aut Zhizhou Ren verfasserin aut In Sensors MDPI AG, 2003 23(2023), 14, p 6600 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:23 year:2023 number:14, p 6600 https://doi.org/10.3390/s23146600 kostenfrei https://doaj.org/article/78f22942d35b4345805e66c67a5f0679 kostenfrei https://www.mdpi.com/1424-8220/23/14/6600 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 14, p 6600
allfieldsGer	10.3390/s23146600 doi (DE-627)DOAJ093828349 (DE-599)DOAJ78f22942d35b4345805e66c67a5f0679 DE-627 ger DE-627 rakwb eng TP1-1185 Kun Liang verfasserin aut Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples. spectroscopic techniques fusarium head blight fingerprint region data fusion Chemical technology Jinpeng Song verfasserin aut Rui Yuan verfasserin aut Zhizhou Ren verfasserin aut In Sensors MDPI AG, 2003 23(2023), 14, p 6600 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:23 year:2023 number:14, p 6600 https://doi.org/10.3390/s23146600 kostenfrei https://doaj.org/article/78f22942d35b4345805e66c67a5f0679 kostenfrei https://www.mdpi.com/1424-8220/23/14/6600 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 14, p 6600
allfieldsSound	10.3390/s23146600 doi (DE-627)DOAJ093828349 (DE-599)DOAJ78f22942d35b4345805e66c67a5f0679 DE-627 ger DE-627 rakwb eng TP1-1185 Kun Liang verfasserin aut Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples. spectroscopic techniques fusarium head blight fingerprint region data fusion Chemical technology Jinpeng Song verfasserin aut Rui Yuan verfasserin aut Zhizhou Ren verfasserin aut In Sensors MDPI AG, 2003 23(2023), 14, p 6600 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:23 year:2023 number:14, p 6600 https://doi.org/10.3390/s23146600 kostenfrei https://doaj.org/article/78f22942d35b4345805e66c67a5f0679 kostenfrei https://www.mdpi.com/1424-8220/23/14/6600 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 14, p 6600
language	English
source	In Sensors 23(2023), 14, p 6600 volume:23 year:2023 number:14, p 6600
sourceStr	In Sensors 23(2023), 14, p 6600 volume:23 year:2023 number:14, p 6600
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	spectroscopic techniques fusarium head blight fingerprint region data fusion Chemical technology
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container_title	Sensors
authorswithroles_txt_mv	Kun Liang @@aut@@ Jinpeng Song @@aut@@ Rui Yuan @@aut@@ Zhizhou Ren @@aut@@
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callnumber-first	T - Technology
author	Kun Liang
spellingShingle	Kun Liang misc TP1-1185 misc spectroscopic techniques misc fusarium head blight misc fingerprint region misc data fusion misc Chemical technology Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat
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topic_title	TP1-1185 Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat spectroscopic techniques fusarium head blight fingerprint region data fusion
topic	misc TP1-1185 misc spectroscopic techniques misc fusarium head blight misc fingerprint region misc data fusion misc Chemical technology
topic_unstemmed	misc TP1-1185 misc spectroscopic techniques misc fusarium head blight misc fingerprint region misc data fusion misc Chemical technology
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title	Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat
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title_full	Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat
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title_sort	mid-level data fusion combined with the fingerprint region for classification don levels defect of fusarium head blight wheat
callnumber	TP1-1185
title_auth	Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat
abstract	In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples.
abstractGer	In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples.
abstract_unstemmed	In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples.
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title_short	Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat
url	https://doi.org/10.3390/s23146600 https://doaj.org/article/78f22942d35b4345805e66c67a5f0679 https://www.mdpi.com/1424-8220/23/14/6600 https://doaj.org/toc/1424-8220
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up_date	2024-07-03T19:37:36.262Z
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Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat

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