Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization

Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtain...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Jiaqi Tan [verfasserIn] Pengshan Cui [verfasserIn] Shaoqin Ge [verfasserIn] Xu Cai [verfasserIn] Qian Li [verfasserIn] Hongkun Xue [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Cornus officinalis Ultrasound assisted aqueous two-phase extraction Polysaccharides Optimization Characterization

Übergeordnetes Werk:	In: Ultrasonics Sonochemistry - Elsevier, 2021, 84(2022), Seite 105966-
Übergeordnetes Werk:	volume:84 ; year:2022 ; pages:105966-

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.ultsonch.2022.105966

Katalog-ID:	DOAJ048128864

Internformat


LEADER	01000caa a22002652 4500
001	DOAJ048128864
003	DE-627
005	20230502090414.0
007	cr uuu---uuuuu
008	230227s2022 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.1016/j.ultsonch.2022.105966 \|2 doi
035			\|a (DE-627)DOAJ048128864
035			\|a (DE-599)DOAJdd904cc98696455d96c46a04263b5439
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
050		0	\|a QD1-999
050		0	\|a QC221-246
100	0		\|a Jiaqi Tan \|e verfasserin \|4 aut
245	1	0	\|a Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization
264		1	\|c 2022
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
520			\|a Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources
650		4	\|a Cornus officinalis
650		4	\|a Ultrasound assisted aqueous two-phase extraction
650		4	\|a Polysaccharides
650		4	\|a Optimization
650		4	\|a Characterization
653		0	\|a Chemistry
653		0	\|a Acoustics. Sound
700	0		\|a Pengshan Cui \|e verfasserin \|4 aut
700	0		\|a Shaoqin Ge \|e verfasserin \|4 aut
700	0		\|a Xu Cai \|e verfasserin \|4 aut
700	0		\|a Qian Li \|e verfasserin \|4 aut
700	0		\|a Hongkun Xue \|e verfasserin \|4 aut
773	0	8	\|i In \|t Ultrasonics Sonochemistry \|d Elsevier, 2021 \|g 84(2022), Seite 105966- \|w (DE-627)306713748 \|w (DE-600)1501094-6 \|x 18732828 \|7 nnns
773	1	8	\|g volume:84 \|g year:2022 \|g pages:105966-
856	4	0	\|u https://doi.org/10.1016/j.ultsonch.2022.105966 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/dd904cc98696455d96c46a04263b5439 \|z kostenfrei
856	4	0	\|u http://www.sciencedirect.com/science/article/pii/S1350417722000591 \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/1350-4177 \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a SSG-OLC-PHA
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_31
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_95
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_165
912			\|a GBV_ILN_170
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4700
951			\|a AR
952			\|d 84 \|j 2022 \|h 105966-

Indexfelder

author_variant	j t jt p c pc s g sg x c xc q l ql h x hx
matchkey_str	article:18732828:2022----::lrsudsitdqeutohsetatooplschrdsrmonsfiiaifutoeigpiia
hierarchy_sort_str	2022
callnumber-subject-code	QD
publishDate	2022
allfields	10.1016/j.ultsonch.2022.105966 doi (DE-627)DOAJ048128864 (DE-599)DOAJdd904cc98696455d96c46a04263b5439 DE-627 ger DE-627 rakwb eng QD1-999 QC221-246 Jiaqi Tan verfasserin aut Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources Cornus officinalis Ultrasound assisted aqueous two-phase extraction Polysaccharides Optimization Characterization Chemistry Acoustics. Sound Pengshan Cui verfasserin aut Shaoqin Ge verfasserin aut Xu Cai verfasserin aut Qian Li verfasserin aut Hongkun Xue verfasserin aut In Ultrasonics Sonochemistry Elsevier, 2021 84(2022), Seite 105966- (DE-627)306713748 (DE-600)1501094-6 18732828 nnns volume:84 year:2022 pages:105966- https://doi.org/10.1016/j.ultsonch.2022.105966 kostenfrei https://doaj.org/article/dd904cc98696455d96c46a04263b5439 kostenfrei http://www.sciencedirect.com/science/article/pii/S1350417722000591 kostenfrei https://doaj.org/toc/1350-4177 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 84 2022 105966-
spelling	10.1016/j.ultsonch.2022.105966 doi (DE-627)DOAJ048128864 (DE-599)DOAJdd904cc98696455d96c46a04263b5439 DE-627 ger DE-627 rakwb eng QD1-999 QC221-246 Jiaqi Tan verfasserin aut Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources Cornus officinalis Ultrasound assisted aqueous two-phase extraction Polysaccharides Optimization Characterization Chemistry Acoustics. Sound Pengshan Cui verfasserin aut Shaoqin Ge verfasserin aut Xu Cai verfasserin aut Qian Li verfasserin aut Hongkun Xue verfasserin aut In Ultrasonics Sonochemistry Elsevier, 2021 84(2022), Seite 105966- (DE-627)306713748 (DE-600)1501094-6 18732828 nnns volume:84 year:2022 pages:105966- https://doi.org/10.1016/j.ultsonch.2022.105966 kostenfrei https://doaj.org/article/dd904cc98696455d96c46a04263b5439 kostenfrei http://www.sciencedirect.com/science/article/pii/S1350417722000591 kostenfrei https://doaj.org/toc/1350-4177 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 84 2022 105966-
allfields_unstemmed	10.1016/j.ultsonch.2022.105966 doi (DE-627)DOAJ048128864 (DE-599)DOAJdd904cc98696455d96c46a04263b5439 DE-627 ger DE-627 rakwb eng QD1-999 QC221-246 Jiaqi Tan verfasserin aut Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources Cornus officinalis Ultrasound assisted aqueous two-phase extraction Polysaccharides Optimization Characterization Chemistry Acoustics. Sound Pengshan Cui verfasserin aut Shaoqin Ge verfasserin aut Xu Cai verfasserin aut Qian Li verfasserin aut Hongkun Xue verfasserin aut In Ultrasonics Sonochemistry Elsevier, 2021 84(2022), Seite 105966- (DE-627)306713748 (DE-600)1501094-6 18732828 nnns volume:84 year:2022 pages:105966- https://doi.org/10.1016/j.ultsonch.2022.105966 kostenfrei https://doaj.org/article/dd904cc98696455d96c46a04263b5439 kostenfrei http://www.sciencedirect.com/science/article/pii/S1350417722000591 kostenfrei https://doaj.org/toc/1350-4177 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 84 2022 105966-
allfieldsGer	10.1016/j.ultsonch.2022.105966 doi (DE-627)DOAJ048128864 (DE-599)DOAJdd904cc98696455d96c46a04263b5439 DE-627 ger DE-627 rakwb eng QD1-999 QC221-246 Jiaqi Tan verfasserin aut Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources Cornus officinalis Ultrasound assisted aqueous two-phase extraction Polysaccharides Optimization Characterization Chemistry Acoustics. Sound Pengshan Cui verfasserin aut Shaoqin Ge verfasserin aut Xu Cai verfasserin aut Qian Li verfasserin aut Hongkun Xue verfasserin aut In Ultrasonics Sonochemistry Elsevier, 2021 84(2022), Seite 105966- (DE-627)306713748 (DE-600)1501094-6 18732828 nnns volume:84 year:2022 pages:105966- https://doi.org/10.1016/j.ultsonch.2022.105966 kostenfrei https://doaj.org/article/dd904cc98696455d96c46a04263b5439 kostenfrei http://www.sciencedirect.com/science/article/pii/S1350417722000591 kostenfrei https://doaj.org/toc/1350-4177 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 84 2022 105966-
allfieldsSound	10.1016/j.ultsonch.2022.105966 doi (DE-627)DOAJ048128864 (DE-599)DOAJdd904cc98696455d96c46a04263b5439 DE-627 ger DE-627 rakwb eng QD1-999 QC221-246 Jiaqi Tan verfasserin aut Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources Cornus officinalis Ultrasound assisted aqueous two-phase extraction Polysaccharides Optimization Characterization Chemistry Acoustics. Sound Pengshan Cui verfasserin aut Shaoqin Ge verfasserin aut Xu Cai verfasserin aut Qian Li verfasserin aut Hongkun Xue verfasserin aut In Ultrasonics Sonochemistry Elsevier, 2021 84(2022), Seite 105966- (DE-627)306713748 (DE-600)1501094-6 18732828 nnns volume:84 year:2022 pages:105966- https://doi.org/10.1016/j.ultsonch.2022.105966 kostenfrei https://doaj.org/article/dd904cc98696455d96c46a04263b5439 kostenfrei http://www.sciencedirect.com/science/article/pii/S1350417722000591 kostenfrei https://doaj.org/toc/1350-4177 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 84 2022 105966-
language	English
source	In Ultrasonics Sonochemistry 84(2022), Seite 105966- volume:84 year:2022 pages:105966-
sourceStr	In Ultrasonics Sonochemistry 84(2022), Seite 105966- volume:84 year:2022 pages:105966-
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Cornus officinalis Ultrasound assisted aqueous two-phase extraction Polysaccharides Optimization Characterization Chemistry Acoustics. Sound
isfreeaccess_bool	true
container_title	Ultrasonics Sonochemistry
authorswithroles_txt_mv	Jiaqi Tan @@aut@@ Pengshan Cui @@aut@@ Shaoqin Ge @@aut@@ Xu Cai @@aut@@ Qian Li @@aut@@ Hongkun Xue @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	306713748
id	DOAJ048128864
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ048128864</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502090414.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2022 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.ultsonch.2022.105966</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ048128864</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJdd904cc98696455d96c46a04263b5439</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QD1-999</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QC221-246</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Jiaqi Tan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cornus officinalis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ultrasound assisted aqueous two-phase extraction</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Polysaccharides</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Characterization</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Chemistry</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Acoustics. Sound</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Pengshan Cui</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Shaoqin Ge</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Xu Cai</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Qian Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Hongkun Xue</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Ultrasonics Sonochemistry</subfield><subfield code="d">Elsevier, 2021</subfield><subfield code="g">84(2022), Seite 105966-</subfield><subfield code="w">(DE-627)306713748</subfield><subfield code="w">(DE-600)1501094-6</subfield><subfield code="x">18732828</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:84</subfield><subfield code="g">year:2022</subfield><subfield code="g">pages:105966-</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.ultsonch.2022.105966</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/dd904cc98696455d96c46a04263b5439</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.sciencedirect.com/science/article/pii/S1350417722000591</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1350-4177</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_150</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_165</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2106</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2232</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">84</subfield><subfield code="j">2022</subfield><subfield code="h">105966-</subfield></datafield></record></collection>
callnumber-first	Q - Science
author	Jiaqi Tan
spellingShingle	Jiaqi Tan misc QD1-999 misc QC221-246 misc Cornus officinalis misc Ultrasound assisted aqueous two-phase extraction misc Polysaccharides misc Optimization misc Characterization misc Chemistry misc Acoustics. Sound Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization
authorStr	Jiaqi Tan
ppnlink_with_tag_str_mv	@@773@@(DE-627)306713748
format	electronic Article
delete_txt_mv	keep
author_role	aut aut aut aut aut aut
collection	DOAJ
remote_str	true
callnumber-label	QD1-999
illustrated	Not Illustrated
issn	18732828
topic_title	QD1-999 QC221-246 Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization Cornus officinalis Ultrasound assisted aqueous two-phase extraction Polysaccharides Optimization Characterization
topic	misc QD1-999 misc QC221-246 misc Cornus officinalis misc Ultrasound assisted aqueous two-phase extraction misc Polysaccharides misc Optimization misc Characterization misc Chemistry misc Acoustics. Sound
topic_unstemmed	misc QD1-999 misc QC221-246 misc Cornus officinalis misc Ultrasound assisted aqueous two-phase extraction misc Polysaccharides misc Optimization misc Characterization misc Chemistry misc Acoustics. Sound
topic_browse	misc QD1-999 misc QC221-246 misc Cornus officinalis misc Ultrasound assisted aqueous two-phase extraction misc Polysaccharides misc Optimization misc Characterization misc Chemistry misc Acoustics. Sound
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	Ultrasonics Sonochemistry
hierarchy_parent_id	306713748
hierarchy_top_title	Ultrasonics Sonochemistry
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)306713748 (DE-600)1501094-6
title	Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization
ctrlnum	(DE-627)DOAJ048128864 (DE-599)DOAJdd904cc98696455d96c46a04263b5439
title_full	Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization
author_sort	Jiaqi Tan
journal	Ultrasonics Sonochemistry
journalStr	Ultrasonics Sonochemistry
callnumber-first-code	Q
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2022
contenttype_str_mv	txt
container_start_page	105966
author_browse	Jiaqi Tan Pengshan Cui Shaoqin Ge Xu Cai Qian Li Hongkun Xue
container_volume	84
class	QD1-999 QC221-246
format_se	Elektronische Aufsätze
author-letter	Jiaqi Tan
doi_str_mv	10.1016/j.ultsonch.2022.105966
author2-role	verfasserin
title_sort	ultrasound assisted aqueous two-phase extraction of polysaccharides from cornus officinalis fruit: modeling, optimization, purification, and characterization
callnumber	QD1-999
title_auth	Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization
abstract	Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources
abstractGer	Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources
abstract_unstemmed	Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 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_4338 GBV_ILN_4367 GBV_ILN_4700
title_short	Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization
url	https://doi.org/10.1016/j.ultsonch.2022.105966 https://doaj.org/article/dd904cc98696455d96c46a04263b5439 http://www.sciencedirect.com/science/article/pii/S1350417722000591 https://doaj.org/toc/1350-4177
remote_bool	true
author2	Pengshan Cui Shaoqin Ge Xu Cai Qian Li Hongkun Xue
author2Str	Pengshan Cui Shaoqin Ge Xu Cai Qian Li Hongkun Xue
ppnlink	306713748
callnumber-subject	QD - Chemistry
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.1016/j.ultsonch.2022.105966
callnumber-a	QD1-999
up_date	2024-07-03T16:05:31.736Z
_version_	1803574555953856512
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ048128864</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502090414.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2022 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.ultsonch.2022.105966</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ048128864</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJdd904cc98696455d96c46a04263b5439</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QD1-999</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QC221-246</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Jiaqi Tan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Cornus officinalis polysaccharides (COPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest COPs yield (7.85 ± 0.09)% was obtained at the ultrasound power of 350 W, extraction temperature of 51 ℃, liquid-to-solid ratio of 17 mL/g, and extraction time of 38 min. Subsequently, the crude COPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (COPs-4-SG, 33.64 kDa) that contained galacturonic acid, arabinose, mannose, glucose, and galactose in a molar ratio of 34.82:14.19:6.75:13.48:12.26. The structure of COPs-4-SG was also characterized with UV–vis, fourier-transform infrared spectroscopy (FT–IR), atomic force microscopy (AFM), scanning electron microscopy (SEM), Congo-red test, and circular dichroism (CD). The findings provide a feasible way for the extraction, purification, and optimization of polysaccharides from plant resources</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cornus officinalis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ultrasound assisted aqueous two-phase extraction</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Polysaccharides</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Characterization</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Chemistry</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Acoustics. Sound</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Pengshan Cui</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Shaoqin Ge</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Xu Cai</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Qian Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Hongkun Xue</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Ultrasonics Sonochemistry</subfield><subfield code="d">Elsevier, 2021</subfield><subfield code="g">84(2022), Seite 105966-</subfield><subfield code="w">(DE-627)306713748</subfield><subfield code="w">(DE-600)1501094-6</subfield><subfield code="x">18732828</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:84</subfield><subfield code="g">year:2022</subfield><subfield code="g">pages:105966-</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.ultsonch.2022.105966</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/dd904cc98696455d96c46a04263b5439</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.sciencedirect.com/science/article/pii/S1350417722000591</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1350-4177</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_150</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_165</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2106</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2232</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">84</subfield><subfield code="j">2022</subfield><subfield code="h">105966-</subfield></datafield></record></collection>
score	7.40088

Nicht das Richtige dabei?

Schreiben Sie uns!

Ultrasound assisted aqueous two-phase extraction of polysaccharides from Cornus officinalis fruit: Modeling, optimization, purification, and characterization

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?