Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods

Abstract This study investigated the optimization of accelerated solvent extraction (ASE) of fatty acids (FAs) from three Coix seeds (SCS small Coix seed; BCS big Coix seed; TCS translucent Coix seed) by chemometrics methods. Partial least-squares regression (PLSR) and backpropagation neural network...
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Autor*in:	Liu, Xing [verfasserIn] Fan, Kai [verfasserIn] Song, Wei-Guo [verfasserIn] Wang, Zheng-Wu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	seed Fatty acids PLSR BPNN

Übergeordnetes Werk:	Enthalten in: Sensing and instrumentation for food quality and safety - New York, NY : Springer, 2007, 13(2019), 3 vom: 14. März, Seite 1773-1780
Übergeordnetes Werk:	volume:13 ; year:2019 ; number:3 ; day:14 ; month:03 ; pages:1773-1780

Links:	Volltext

DOI / URN:	10.1007/s11694-019-00095-7

Katalog-ID:	SPR021777454

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520			\|a Abstract This study investigated the optimization of accelerated solvent extraction (ASE) of fatty acids (FAs) from three Coix seeds (SCS small Coix seed; BCS big Coix seed; TCS translucent Coix seed) by chemometrics methods. Partial least-squares regression (PLSR) and backpropagation neural network (BPNN) were applied to build models that reflect the relationship between content of FAs and extraction conditions (temperature, time, and extraction solvent). Genetic algorithms (GAs) and particle swarm optimization (PSO) were utilized to optimize the combination of extraction conditions. The composition of FAs was analysed by gas chromatography-mass spectrometry (GC-MS). The PLSR models could reflect the relationship of FA content in both BCS and SCS and extraction conditions well, while the BPNN model was more suitable for TCS. The optimal extraction conditions for BCS and SCS were obtained by GAs, whereas those of TCS were obtained by PSO. The FA compositions of the three Coix seeds exhibited differences. The results show that ASE combined with chemometrics methods can rapidly and effectively obtain the optimal conditions for the extraction of FAs from Coix seed and there are differences in the extraction conditions and compositions of FAs among different varieties of Coix seed, but all the extraction time is shorter than other extractions methods.
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allfields	10.1007/s11694-019-00095-7 doi (DE-627)SPR021777454 (SPR)s11694-019-00095-7-e DE-627 ger DE-627 rakwb eng 630 640 ASE Liu, Xing verfasserin aut Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study investigated the optimization of accelerated solvent extraction (ASE) of fatty acids (FAs) from three Coix seeds (SCS small Coix seed; BCS big Coix seed; TCS translucent Coix seed) by chemometrics methods. Partial least-squares regression (PLSR) and backpropagation neural network (BPNN) were applied to build models that reflect the relationship between content of FAs and extraction conditions (temperature, time, and extraction solvent). Genetic algorithms (GAs) and particle swarm optimization (PSO) were utilized to optimize the combination of extraction conditions. The composition of FAs was analysed by gas chromatography-mass spectrometry (GC-MS). The PLSR models could reflect the relationship of FA content in both BCS and SCS and extraction conditions well, while the BPNN model was more suitable for TCS. The optimal extraction conditions for BCS and SCS were obtained by GAs, whereas those of TCS were obtained by PSO. The FA compositions of the three Coix seeds exhibited differences. The results show that ASE combined with chemometrics methods can rapidly and effectively obtain the optimal conditions for the extraction of FAs from Coix seed and there are differences in the extraction conditions and compositions of FAs among different varieties of Coix seed, but all the extraction time is shorter than other extractions methods. seed (dpeaa)DE-He213 Fatty acids (dpeaa)DE-He213 PLSR (dpeaa)DE-He213 BPNN (dpeaa)DE-He213 Fan, Kai verfasserin aut Song, Wei-Guo verfasserin aut Wang, Zheng-Wu verfasserin aut Enthalten in Sensing and instrumentation for food quality and safety New York, NY : Springer, 2007 13(2019), 3 vom: 14. März, Seite 1773-1780 (DE-627)528359339 (DE-600)2279937-0 1932-9954 nnns volume:13 year:2019 number:3 day:14 month:03 pages:1773-1780 https://dx.doi.org/10.1007/s11694-019-00095-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_285 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2059 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2153 GBV_ILN_2190 AR 13 2019 3 14 03 1773-1780
spelling	10.1007/s11694-019-00095-7 doi (DE-627)SPR021777454 (SPR)s11694-019-00095-7-e DE-627 ger DE-627 rakwb eng 630 640 ASE Liu, Xing verfasserin aut Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study investigated the optimization of accelerated solvent extraction (ASE) of fatty acids (FAs) from three Coix seeds (SCS small Coix seed; BCS big Coix seed; TCS translucent Coix seed) by chemometrics methods. Partial least-squares regression (PLSR) and backpropagation neural network (BPNN) were applied to build models that reflect the relationship between content of FAs and extraction conditions (temperature, time, and extraction solvent). Genetic algorithms (GAs) and particle swarm optimization (PSO) were utilized to optimize the combination of extraction conditions. The composition of FAs was analysed by gas chromatography-mass spectrometry (GC-MS). The PLSR models could reflect the relationship of FA content in both BCS and SCS and extraction conditions well, while the BPNN model was more suitable for TCS. The optimal extraction conditions for BCS and SCS were obtained by GAs, whereas those of TCS were obtained by PSO. The FA compositions of the three Coix seeds exhibited differences. The results show that ASE combined with chemometrics methods can rapidly and effectively obtain the optimal conditions for the extraction of FAs from Coix seed and there are differences in the extraction conditions and compositions of FAs among different varieties of Coix seed, but all the extraction time is shorter than other extractions methods. seed (dpeaa)DE-He213 Fatty acids (dpeaa)DE-He213 PLSR (dpeaa)DE-He213 BPNN (dpeaa)DE-He213 Fan, Kai verfasserin aut Song, Wei-Guo verfasserin aut Wang, Zheng-Wu verfasserin aut Enthalten in Sensing and instrumentation for food quality and safety New York, NY : Springer, 2007 13(2019), 3 vom: 14. März, Seite 1773-1780 (DE-627)528359339 (DE-600)2279937-0 1932-9954 nnns volume:13 year:2019 number:3 day:14 month:03 pages:1773-1780 https://dx.doi.org/10.1007/s11694-019-00095-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_285 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2059 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2153 GBV_ILN_2190 AR 13 2019 3 14 03 1773-1780
allfields_unstemmed	10.1007/s11694-019-00095-7 doi (DE-627)SPR021777454 (SPR)s11694-019-00095-7-e DE-627 ger DE-627 rakwb eng 630 640 ASE Liu, Xing verfasserin aut Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study investigated the optimization of accelerated solvent extraction (ASE) of fatty acids (FAs) from three Coix seeds (SCS small Coix seed; BCS big Coix seed; TCS translucent Coix seed) by chemometrics methods. Partial least-squares regression (PLSR) and backpropagation neural network (BPNN) were applied to build models that reflect the relationship between content of FAs and extraction conditions (temperature, time, and extraction solvent). Genetic algorithms (GAs) and particle swarm optimization (PSO) were utilized to optimize the combination of extraction conditions. The composition of FAs was analysed by gas chromatography-mass spectrometry (GC-MS). The PLSR models could reflect the relationship of FA content in both BCS and SCS and extraction conditions well, while the BPNN model was more suitable for TCS. The optimal extraction conditions for BCS and SCS were obtained by GAs, whereas those of TCS were obtained by PSO. The FA compositions of the three Coix seeds exhibited differences. The results show that ASE combined with chemometrics methods can rapidly and effectively obtain the optimal conditions for the extraction of FAs from Coix seed and there are differences in the extraction conditions and compositions of FAs among different varieties of Coix seed, but all the extraction time is shorter than other extractions methods. seed (dpeaa)DE-He213 Fatty acids (dpeaa)DE-He213 PLSR (dpeaa)DE-He213 BPNN (dpeaa)DE-He213 Fan, Kai verfasserin aut Song, Wei-Guo verfasserin aut Wang, Zheng-Wu verfasserin aut Enthalten in Sensing and instrumentation for food quality and safety New York, NY : Springer, 2007 13(2019), 3 vom: 14. März, Seite 1773-1780 (DE-627)528359339 (DE-600)2279937-0 1932-9954 nnns volume:13 year:2019 number:3 day:14 month:03 pages:1773-1780 https://dx.doi.org/10.1007/s11694-019-00095-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_285 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2059 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2153 GBV_ILN_2190 AR 13 2019 3 14 03 1773-1780
allfieldsGer	10.1007/s11694-019-00095-7 doi (DE-627)SPR021777454 (SPR)s11694-019-00095-7-e DE-627 ger DE-627 rakwb eng 630 640 ASE Liu, Xing verfasserin aut Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study investigated the optimization of accelerated solvent extraction (ASE) of fatty acids (FAs) from three Coix seeds (SCS small Coix seed; BCS big Coix seed; TCS translucent Coix seed) by chemometrics methods. Partial least-squares regression (PLSR) and backpropagation neural network (BPNN) were applied to build models that reflect the relationship between content of FAs and extraction conditions (temperature, time, and extraction solvent). Genetic algorithms (GAs) and particle swarm optimization (PSO) were utilized to optimize the combination of extraction conditions. The composition of FAs was analysed by gas chromatography-mass spectrometry (GC-MS). The PLSR models could reflect the relationship of FA content in both BCS and SCS and extraction conditions well, while the BPNN model was more suitable for TCS. The optimal extraction conditions for BCS and SCS were obtained by GAs, whereas those of TCS were obtained by PSO. The FA compositions of the three Coix seeds exhibited differences. The results show that ASE combined with chemometrics methods can rapidly and effectively obtain the optimal conditions for the extraction of FAs from Coix seed and there are differences in the extraction conditions and compositions of FAs among different varieties of Coix seed, but all the extraction time is shorter than other extractions methods. seed (dpeaa)DE-He213 Fatty acids (dpeaa)DE-He213 PLSR (dpeaa)DE-He213 BPNN (dpeaa)DE-He213 Fan, Kai verfasserin aut Song, Wei-Guo verfasserin aut Wang, Zheng-Wu verfasserin aut Enthalten in Sensing and instrumentation for food quality and safety New York, NY : Springer, 2007 13(2019), 3 vom: 14. März, Seite 1773-1780 (DE-627)528359339 (DE-600)2279937-0 1932-9954 nnns volume:13 year:2019 number:3 day:14 month:03 pages:1773-1780 https://dx.doi.org/10.1007/s11694-019-00095-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_285 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2059 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2153 GBV_ILN_2190 AR 13 2019 3 14 03 1773-1780
allfieldsSound	10.1007/s11694-019-00095-7 doi (DE-627)SPR021777454 (SPR)s11694-019-00095-7-e DE-627 ger DE-627 rakwb eng 630 640 ASE Liu, Xing verfasserin aut Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study investigated the optimization of accelerated solvent extraction (ASE) of fatty acids (FAs) from three Coix seeds (SCS small Coix seed; BCS big Coix seed; TCS translucent Coix seed) by chemometrics methods. Partial least-squares regression (PLSR) and backpropagation neural network (BPNN) were applied to build models that reflect the relationship between content of FAs and extraction conditions (temperature, time, and extraction solvent). Genetic algorithms (GAs) and particle swarm optimization (PSO) were utilized to optimize the combination of extraction conditions. The composition of FAs was analysed by gas chromatography-mass spectrometry (GC-MS). The PLSR models could reflect the relationship of FA content in both BCS and SCS and extraction conditions well, while the BPNN model was more suitable for TCS. The optimal extraction conditions for BCS and SCS were obtained by GAs, whereas those of TCS were obtained by PSO. The FA compositions of the three Coix seeds exhibited differences. The results show that ASE combined with chemometrics methods can rapidly and effectively obtain the optimal conditions for the extraction of FAs from Coix seed and there are differences in the extraction conditions and compositions of FAs among different varieties of Coix seed, but all the extraction time is shorter than other extractions methods. seed (dpeaa)DE-He213 Fatty acids (dpeaa)DE-He213 PLSR (dpeaa)DE-He213 BPNN (dpeaa)DE-He213 Fan, Kai verfasserin aut Song, Wei-Guo verfasserin aut Wang, Zheng-Wu verfasserin aut Enthalten in Sensing and instrumentation for food quality and safety New York, NY : Springer, 2007 13(2019), 3 vom: 14. März, Seite 1773-1780 (DE-627)528359339 (DE-600)2279937-0 1932-9954 nnns volume:13 year:2019 number:3 day:14 month:03 pages:1773-1780 https://dx.doi.org/10.1007/s11694-019-00095-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_285 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2059 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2153 GBV_ILN_2190 AR 13 2019 3 14 03 1773-1780
language	English
source	Enthalten in Sensing and instrumentation for food quality and safety 13(2019), 3 vom: 14. März, Seite 1773-1780 volume:13 year:2019 number:3 day:14 month:03 pages:1773-1780
sourceStr	Enthalten in Sensing and instrumentation for food quality and safety 13(2019), 3 vom: 14. März, Seite 1773-1780 volume:13 year:2019 number:3 day:14 month:03 pages:1773-1780
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	seed Fatty acids PLSR BPNN
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container_title	Sensing and instrumentation for food quality and safety
authorswithroles_txt_mv	Liu, Xing @@aut@@ Fan, Kai @@aut@@ Song, Wei-Guo @@aut@@ Wang, Zheng-Wu @@aut@@
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author	Liu, Xing
spellingShingle	Liu, Xing ddc 630 misc seed misc Fatty acids misc PLSR misc BPNN Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods
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topic_title	630 640 ASE Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods seed (dpeaa)DE-He213 Fatty acids (dpeaa)DE-He213 PLSR (dpeaa)DE-He213 BPNN (dpeaa)DE-He213
topic	ddc 630 misc seed misc Fatty acids misc PLSR misc BPNN
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title	Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods
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title_full	Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods
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author_browse	Liu, Xing Fan, Kai Song, Wei-Guo Wang, Zheng-Wu
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title_sort	optimization of accelerated solvent extraction of fatty acids from coix seeds using chemometrics methods
title_auth	Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods
abstract	Abstract This study investigated the optimization of accelerated solvent extraction (ASE) of fatty acids (FAs) from three Coix seeds (SCS small Coix seed; BCS big Coix seed; TCS translucent Coix seed) by chemometrics methods. Partial least-squares regression (PLSR) and backpropagation neural network (BPNN) were applied to build models that reflect the relationship between content of FAs and extraction conditions (temperature, time, and extraction solvent). Genetic algorithms (GAs) and particle swarm optimization (PSO) were utilized to optimize the combination of extraction conditions. The composition of FAs was analysed by gas chromatography-mass spectrometry (GC-MS). The PLSR models could reflect the relationship of FA content in both BCS and SCS and extraction conditions well, while the BPNN model was more suitable for TCS. The optimal extraction conditions for BCS and SCS were obtained by GAs, whereas those of TCS were obtained by PSO. The FA compositions of the three Coix seeds exhibited differences. The results show that ASE combined with chemometrics methods can rapidly and effectively obtain the optimal conditions for the extraction of FAs from Coix seed and there are differences in the extraction conditions and compositions of FAs among different varieties of Coix seed, but all the extraction time is shorter than other extractions methods.
abstractGer	Abstract This study investigated the optimization of accelerated solvent extraction (ASE) of fatty acids (FAs) from three Coix seeds (SCS small Coix seed; BCS big Coix seed; TCS translucent Coix seed) by chemometrics methods. Partial least-squares regression (PLSR) and backpropagation neural network (BPNN) were applied to build models that reflect the relationship between content of FAs and extraction conditions (temperature, time, and extraction solvent). Genetic algorithms (GAs) and particle swarm optimization (PSO) were utilized to optimize the combination of extraction conditions. The composition of FAs was analysed by gas chromatography-mass spectrometry (GC-MS). The PLSR models could reflect the relationship of FA content in both BCS and SCS and extraction conditions well, while the BPNN model was more suitable for TCS. The optimal extraction conditions for BCS and SCS were obtained by GAs, whereas those of TCS were obtained by PSO. The FA compositions of the three Coix seeds exhibited differences. The results show that ASE combined with chemometrics methods can rapidly and effectively obtain the optimal conditions for the extraction of FAs from Coix seed and there are differences in the extraction conditions and compositions of FAs among different varieties of Coix seed, but all the extraction time is shorter than other extractions methods.
abstract_unstemmed	Abstract This study investigated the optimization of accelerated solvent extraction (ASE) of fatty acids (FAs) from three Coix seeds (SCS small Coix seed; BCS big Coix seed; TCS translucent Coix seed) by chemometrics methods. Partial least-squares regression (PLSR) and backpropagation neural network (BPNN) were applied to build models that reflect the relationship between content of FAs and extraction conditions (temperature, time, and extraction solvent). Genetic algorithms (GAs) and particle swarm optimization (PSO) were utilized to optimize the combination of extraction conditions. The composition of FAs was analysed by gas chromatography-mass spectrometry (GC-MS). The PLSR models could reflect the relationship of FA content in both BCS and SCS and extraction conditions well, while the BPNN model was more suitable for TCS. The optimal extraction conditions for BCS and SCS were obtained by GAs, whereas those of TCS were obtained by PSO. The FA compositions of the three Coix seeds exhibited differences. The results show that ASE combined with chemometrics methods can rapidly and effectively obtain the optimal conditions for the extraction of FAs from Coix seed and there are differences in the extraction conditions and compositions of FAs among different varieties of Coix seed, but all the extraction time is shorter than other extractions methods.
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title_short	Optimization of accelerated solvent extraction of fatty acids from Coix seeds using chemometrics methods
url	https://dx.doi.org/10.1007/s11694-019-00095-7
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up_date	2024-07-04T00:20:01.944Z
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