Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen

A new phenomenological model, based on a second order dissolution kinetics, was developed for the alkaline removal of non-collagenous protein (NCP) from the skin of Nile tilapia (SNT). This model allows estimating the liquid concentration of NCP in terms of temperature, skin size, NaOH concentration...
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Autor*in:	Diego Enrique Giraldo-Rios [verfasserIn] Luis Alberto Rios [verfasserIn] José Edgar Zapata-Montoya [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Chemical engineering Dynamical system Transport process Materials characterization Chemical reaction kinetics Chemical characterization of food

Übergeordnetes Werk:	In: Heliyon - Elsevier, 2016, 6(2020), 5, Seite e03854-
Übergeordnetes Werk:	volume:6 ; year:2020 ; number:5 ; pages:e03854-

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.heliyon.2020.e03854

Katalog-ID:	DOAJ067926320

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520			\|a A new phenomenological model, based on a second order dissolution kinetics, was developed for the alkaline removal of non-collagenous protein (NCP) from the skin of Nile tilapia (SNT). This model allows estimating the liquid concentration of NCP in terms of temperature, skin size, NaOH concentration and time. This model was fitted with 135 experiments averaging a R2 of 0.99. The root-mean-square deviation and the mean-absolute-percentage error of the model were 0.0041 and 3.15%, respectively. The Arrhenius-activation energy was 15–122 kJ mol−1. Multi-objective optimization led to the highest NCP extraction (NCPE) of 24.3% and to the lowest loss of collagen (LC) of 1.3%, with R2 coefficients of 0.98 and 0.92, respectively. Ultimately, SNT deproteinized under optimal conditions was subjected to acid extraction and purification. FTIR and SEM analyses indicated that the product was a Type I collagen that could be used in the pharmaceutical industry.
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publishDate	2020
allfields	10.1016/j.heliyon.2020.e03854 doi (DE-627)DOAJ067926320 (DE-599)DOAJ408a78ca2f974e388f23967a8dd71c72 DE-627 ger DE-627 rakwb eng Q1-390 H1-99 Diego Enrique Giraldo-Rios verfasserin aut Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A new phenomenological model, based on a second order dissolution kinetics, was developed for the alkaline removal of non-collagenous protein (NCP) from the skin of Nile tilapia (SNT). This model allows estimating the liquid concentration of NCP in terms of temperature, skin size, NaOH concentration and time. This model was fitted with 135 experiments averaging a R2 of 0.99. The root-mean-square deviation and the mean-absolute-percentage error of the model were 0.0041 and 3.15%, respectively. The Arrhenius-activation energy was 15–122 kJ mol−1. Multi-objective optimization led to the highest NCP extraction (NCPE) of 24.3% and to the lowest loss of collagen (LC) of 1.3%, with R2 coefficients of 0.98 and 0.92, respectively. Ultimately, SNT deproteinized under optimal conditions was subjected to acid extraction and purification. FTIR and SEM analyses indicated that the product was a Type I collagen that could be used in the pharmaceutical industry. Chemical engineering Dynamical system Transport process Materials characterization Chemical reaction kinetics Chemical characterization of food Science (General) Social sciences (General) Luis Alberto Rios verfasserin aut José Edgar Zapata-Montoya verfasserin aut In Heliyon Elsevier, 2016 6(2020), 5, Seite e03854- (DE-627)835893197 (DE-600)2835763-2 24058440 nnns volume:6 year:2020 number:5 pages:e03854- https://doi.org/10.1016/j.heliyon.2020.e03854 kostenfrei https://doaj.org/article/408a78ca2f974e388f23967a8dd71c72 kostenfrei http://www.sciencedirect.com/science/article/pii/S240584402030699X kostenfrei https://doaj.org/toc/2405-8440 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 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_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 6 2020 5 e03854-
spelling	10.1016/j.heliyon.2020.e03854 doi (DE-627)DOAJ067926320 (DE-599)DOAJ408a78ca2f974e388f23967a8dd71c72 DE-627 ger DE-627 rakwb eng Q1-390 H1-99 Diego Enrique Giraldo-Rios verfasserin aut Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A new phenomenological model, based on a second order dissolution kinetics, was developed for the alkaline removal of non-collagenous protein (NCP) from the skin of Nile tilapia (SNT). This model allows estimating the liquid concentration of NCP in terms of temperature, skin size, NaOH concentration and time. This model was fitted with 135 experiments averaging a R2 of 0.99. The root-mean-square deviation and the mean-absolute-percentage error of the model were 0.0041 and 3.15%, respectively. The Arrhenius-activation energy was 15–122 kJ mol−1. Multi-objective optimization led to the highest NCP extraction (NCPE) of 24.3% and to the lowest loss of collagen (LC) of 1.3%, with R2 coefficients of 0.98 and 0.92, respectively. Ultimately, SNT deproteinized under optimal conditions was subjected to acid extraction and purification. FTIR and SEM analyses indicated that the product was a Type I collagen that could be used in the pharmaceutical industry. Chemical engineering Dynamical system Transport process Materials characterization Chemical reaction kinetics Chemical characterization of food Science (General) Social sciences (General) Luis Alberto Rios verfasserin aut José Edgar Zapata-Montoya verfasserin aut In Heliyon Elsevier, 2016 6(2020), 5, Seite e03854- (DE-627)835893197 (DE-600)2835763-2 24058440 nnns volume:6 year:2020 number:5 pages:e03854- https://doi.org/10.1016/j.heliyon.2020.e03854 kostenfrei https://doaj.org/article/408a78ca2f974e388f23967a8dd71c72 kostenfrei http://www.sciencedirect.com/science/article/pii/S240584402030699X kostenfrei https://doaj.org/toc/2405-8440 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 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_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 6 2020 5 e03854-
allfields_unstemmed	10.1016/j.heliyon.2020.e03854 doi (DE-627)DOAJ067926320 (DE-599)DOAJ408a78ca2f974e388f23967a8dd71c72 DE-627 ger DE-627 rakwb eng Q1-390 H1-99 Diego Enrique Giraldo-Rios verfasserin aut Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A new phenomenological model, based on a second order dissolution kinetics, was developed for the alkaline removal of non-collagenous protein (NCP) from the skin of Nile tilapia (SNT). This model allows estimating the liquid concentration of NCP in terms of temperature, skin size, NaOH concentration and time. This model was fitted with 135 experiments averaging a R2 of 0.99. The root-mean-square deviation and the mean-absolute-percentage error of the model were 0.0041 and 3.15%, respectively. The Arrhenius-activation energy was 15–122 kJ mol−1. Multi-objective optimization led to the highest NCP extraction (NCPE) of 24.3% and to the lowest loss of collagen (LC) of 1.3%, with R2 coefficients of 0.98 and 0.92, respectively. Ultimately, SNT deproteinized under optimal conditions was subjected to acid extraction and purification. FTIR and SEM analyses indicated that the product was a Type I collagen that could be used in the pharmaceutical industry. Chemical engineering Dynamical system Transport process Materials characterization Chemical reaction kinetics Chemical characterization of food Science (General) Social sciences (General) Luis Alberto Rios verfasserin aut José Edgar Zapata-Montoya verfasserin aut In Heliyon Elsevier, 2016 6(2020), 5, Seite e03854- (DE-627)835893197 (DE-600)2835763-2 24058440 nnns volume:6 year:2020 number:5 pages:e03854- https://doi.org/10.1016/j.heliyon.2020.e03854 kostenfrei https://doaj.org/article/408a78ca2f974e388f23967a8dd71c72 kostenfrei http://www.sciencedirect.com/science/article/pii/S240584402030699X kostenfrei https://doaj.org/toc/2405-8440 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 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_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 6 2020 5 e03854-
allfieldsGer	10.1016/j.heliyon.2020.e03854 doi (DE-627)DOAJ067926320 (DE-599)DOAJ408a78ca2f974e388f23967a8dd71c72 DE-627 ger DE-627 rakwb eng Q1-390 H1-99 Diego Enrique Giraldo-Rios verfasserin aut Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A new phenomenological model, based on a second order dissolution kinetics, was developed for the alkaline removal of non-collagenous protein (NCP) from the skin of Nile tilapia (SNT). This model allows estimating the liquid concentration of NCP in terms of temperature, skin size, NaOH concentration and time. This model was fitted with 135 experiments averaging a R2 of 0.99. The root-mean-square deviation and the mean-absolute-percentage error of the model were 0.0041 and 3.15%, respectively. The Arrhenius-activation energy was 15–122 kJ mol−1. Multi-objective optimization led to the highest NCP extraction (NCPE) of 24.3% and to the lowest loss of collagen (LC) of 1.3%, with R2 coefficients of 0.98 and 0.92, respectively. Ultimately, SNT deproteinized under optimal conditions was subjected to acid extraction and purification. FTIR and SEM analyses indicated that the product was a Type I collagen that could be used in the pharmaceutical industry. Chemical engineering Dynamical system Transport process Materials characterization Chemical reaction kinetics Chemical characterization of food Science (General) Social sciences (General) Luis Alberto Rios verfasserin aut José Edgar Zapata-Montoya verfasserin aut In Heliyon Elsevier, 2016 6(2020), 5, Seite e03854- (DE-627)835893197 (DE-600)2835763-2 24058440 nnns volume:6 year:2020 number:5 pages:e03854- https://doi.org/10.1016/j.heliyon.2020.e03854 kostenfrei https://doaj.org/article/408a78ca2f974e388f23967a8dd71c72 kostenfrei http://www.sciencedirect.com/science/article/pii/S240584402030699X kostenfrei https://doaj.org/toc/2405-8440 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 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_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 6 2020 5 e03854-
allfieldsSound	10.1016/j.heliyon.2020.e03854 doi (DE-627)DOAJ067926320 (DE-599)DOAJ408a78ca2f974e388f23967a8dd71c72 DE-627 ger DE-627 rakwb eng Q1-390 H1-99 Diego Enrique Giraldo-Rios verfasserin aut Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A new phenomenological model, based on a second order dissolution kinetics, was developed for the alkaline removal of non-collagenous protein (NCP) from the skin of Nile tilapia (SNT). This model allows estimating the liquid concentration of NCP in terms of temperature, skin size, NaOH concentration and time. This model was fitted with 135 experiments averaging a R2 of 0.99. The root-mean-square deviation and the mean-absolute-percentage error of the model were 0.0041 and 3.15%, respectively. The Arrhenius-activation energy was 15–122 kJ mol−1. Multi-objective optimization led to the highest NCP extraction (NCPE) of 24.3% and to the lowest loss of collagen (LC) of 1.3%, with R2 coefficients of 0.98 and 0.92, respectively. Ultimately, SNT deproteinized under optimal conditions was subjected to acid extraction and purification. FTIR and SEM analyses indicated that the product was a Type I collagen that could be used in the pharmaceutical industry. Chemical engineering Dynamical system Transport process Materials characterization Chemical reaction kinetics Chemical characterization of food Science (General) Social sciences (General) Luis Alberto Rios verfasserin aut José Edgar Zapata-Montoya verfasserin aut In Heliyon Elsevier, 2016 6(2020), 5, Seite e03854- (DE-627)835893197 (DE-600)2835763-2 24058440 nnns volume:6 year:2020 number:5 pages:e03854- https://doi.org/10.1016/j.heliyon.2020.e03854 kostenfrei https://doaj.org/article/408a78ca2f974e388f23967a8dd71c72 kostenfrei http://www.sciencedirect.com/science/article/pii/S240584402030699X kostenfrei https://doaj.org/toc/2405-8440 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 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_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 6 2020 5 e03854-
language	English
source	In Heliyon 6(2020), 5, Seite e03854- volume:6 year:2020 number:5 pages:e03854-
sourceStr	In Heliyon 6(2020), 5, Seite e03854- volume:6 year:2020 number:5 pages:e03854-
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Chemical engineering Dynamical system Transport process Materials characterization Chemical reaction kinetics Chemical characterization of food Science (General) Social sciences (General)
isfreeaccess_bool	true
container_title	Heliyon
authorswithroles_txt_mv	Diego Enrique Giraldo-Rios @@aut@@ Luis Alberto Rios @@aut@@ José Edgar Zapata-Montoya @@aut@@
publishDateDaySort_date	2020-01-01T00:00:00Z
hierarchy_top_id	835893197
id	DOAJ067926320
language_de	englisch
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callnumber-first	Q - Science
author	Diego Enrique Giraldo-Rios
spellingShingle	Diego Enrique Giraldo-Rios misc Q1-390 misc H1-99 misc Chemical engineering misc Dynamical system misc Transport process misc Materials characterization misc Chemical reaction kinetics misc Chemical characterization of food misc Science (General) misc Social sciences (General) Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen
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topic_title	Q1-390 H1-99 Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen Chemical engineering Dynamical system Transport process Materials characterization Chemical reaction kinetics Chemical characterization of food
topic	misc Q1-390 misc H1-99 misc Chemical engineering misc Dynamical system misc Transport process misc Materials characterization misc Chemical reaction kinetics misc Chemical characterization of food misc Science (General) misc Social sciences (General)
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title	Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen
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title_full	Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen
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title_sort	kinetic modeling of the alkaline deproteinization of nile-tilapia skin for the production of collagen
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title_auth	Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen
abstract	A new phenomenological model, based on a second order dissolution kinetics, was developed for the alkaline removal of non-collagenous protein (NCP) from the skin of Nile tilapia (SNT). This model allows estimating the liquid concentration of NCP in terms of temperature, skin size, NaOH concentration and time. This model was fitted with 135 experiments averaging a R2 of 0.99. The root-mean-square deviation and the mean-absolute-percentage error of the model were 0.0041 and 3.15%, respectively. The Arrhenius-activation energy was 15–122 kJ mol−1. Multi-objective optimization led to the highest NCP extraction (NCPE) of 24.3% and to the lowest loss of collagen (LC) of 1.3%, with R2 coefficients of 0.98 and 0.92, respectively. Ultimately, SNT deproteinized under optimal conditions was subjected to acid extraction and purification. FTIR and SEM analyses indicated that the product was a Type I collagen that could be used in the pharmaceutical industry.
abstractGer	A new phenomenological model, based on a second order dissolution kinetics, was developed for the alkaline removal of non-collagenous protein (NCP) from the skin of Nile tilapia (SNT). This model allows estimating the liquid concentration of NCP in terms of temperature, skin size, NaOH concentration and time. This model was fitted with 135 experiments averaging a R2 of 0.99. The root-mean-square deviation and the mean-absolute-percentage error of the model were 0.0041 and 3.15%, respectively. The Arrhenius-activation energy was 15–122 kJ mol−1. Multi-objective optimization led to the highest NCP extraction (NCPE) of 24.3% and to the lowest loss of collagen (LC) of 1.3%, with R2 coefficients of 0.98 and 0.92, respectively. Ultimately, SNT deproteinized under optimal conditions was subjected to acid extraction and purification. FTIR and SEM analyses indicated that the product was a Type I collagen that could be used in the pharmaceutical industry.
abstract_unstemmed	A new phenomenological model, based on a second order dissolution kinetics, was developed for the alkaline removal of non-collagenous protein (NCP) from the skin of Nile tilapia (SNT). This model allows estimating the liquid concentration of NCP in terms of temperature, skin size, NaOH concentration and time. This model was fitted with 135 experiments averaging a R2 of 0.99. The root-mean-square deviation and the mean-absolute-percentage error of the model were 0.0041 and 3.15%, respectively. The Arrhenius-activation energy was 15–122 kJ mol−1. Multi-objective optimization led to the highest NCP extraction (NCPE) of 24.3% and to the lowest loss of collagen (LC) of 1.3%, with R2 coefficients of 0.98 and 0.92, respectively. Ultimately, SNT deproteinized under optimal conditions was subjected to acid extraction and purification. FTIR and SEM analyses indicated that the product was a Type I collagen that could be used in the pharmaceutical industry.
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title_short	Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen
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Kinetic modeling of the alkaline deproteinization of Nile-tilapia skin for the production of collagen

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