Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia

ABSTRACT: This study examined the use of the Gompertz, Groot, monomolecular, Richards and two-compartment-logistic mathematical models to investigate the kinetics of in vitro gas production of diets composed of combinations of Gliricidia hay or silage. In addition, the effects of Gliricidia hay or s...
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Autor*in:	Antonio Leandro Chaves Gurgel [verfasserIn] Jucileia Aparecida da Silva Morais [verfasserIn] Juliana Caroline Santos Santana [verfasserIn] Gelson dos Santos Difante [verfasserIn] João Virgínio Emerenciano Neto [verfasserIn] Luís Carlos Vinhas Ítavo [verfasserIn] Camila Celeste Brandão Ferreira Ítavo [verfasserIn] Vinícius da Silva Oliveira [verfasserIn] Maria Juciara Silva Teles Rodrigues [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch ; Portugiesisch

Erschienen:	2021

Schlagwörter:	fermentation kinetics Groot model hay non-linear functions silage

Übergeordnetes Werk:	In: Ciência Rural - Universidade Federal de Santa Maria, 2004, 51(2021), 11
Übergeordnetes Werk:	volume:51 ; year:2021 ; number:11

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1590/0103-8478cr20200993

Katalog-ID:	DOAJ017602793

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520			\|a ABSTRACT: This study examined the use of the Gompertz, Groot, monomolecular, Richards and two-compartment-logistic mathematical models to investigate the kinetics of in vitro gas production of diets composed of combinations of Gliricidia hay or silage. In addition, the effects of Gliricidia hay or silage inclusion on the in vitro cumulative gas production of these diets were evaluated. Rumen fermentation kinetics were analyzed by the in vitro cumulative gas production methodology. The model parameters were estimated using the Gauss Newton method, with the exception of the Richards model, which was used by Marquardt’s algorithm. Model fit was assessed using the determination coefficient, F test for parameters identity, concordance correlation coefficient, root mean square error of prediction, and decomposition of mean square error of prediction into mean error, systematic bias and random error. The models were compared for accuracy (pairwise mean square error of prediction) and precision (delta Akaike’s information criterion). All model evaluation and comparison statistics were calculated using Model Evaluation System software version 3.2.2. The Groot and Richards models did not differ from each other (P<0.05) and were the most precise and accurate (P<0.05). Therefore, the Groot model was selected due to its better accuracy and precision and easier access to the parameters. The inclusion of Gliricidia silage in the diet resulted in an increase in the time to obtain the maximum rate of degradation and in the time after incubation when half of the asymptotic level was reached. The Groot model is recommended to estimate the average curve. Dietary inclusion of Gliricidia silage alters the gas production curve due to the longer time required for the diet to reach the maximum rate of degradation, this can increase the time the diet remains in rumen and promote a reduction in the consumption.
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allfields	10.1590/0103-8478cr20200993 doi (DE-627)DOAJ017602793 (DE-599)DOAJ3b55cd65be324f9b97831c1f07682f38 DE-627 ger DE-627 rakwb eng por S1-972 Antonio Leandro Chaves Gurgel verfasserin aut Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT: This study examined the use of the Gompertz, Groot, monomolecular, Richards and two-compartment-logistic mathematical models to investigate the kinetics of in vitro gas production of diets composed of combinations of Gliricidia hay or silage. In addition, the effects of Gliricidia hay or silage inclusion on the in vitro cumulative gas production of these diets were evaluated. Rumen fermentation kinetics were analyzed by the in vitro cumulative gas production methodology. The model parameters were estimated using the Gauss Newton method, with the exception of the Richards model, which was used by Marquardt’s algorithm. Model fit was assessed using the determination coefficient, F test for parameters identity, concordance correlation coefficient, root mean square error of prediction, and decomposition of mean square error of prediction into mean error, systematic bias and random error. The models were compared for accuracy (pairwise mean square error of prediction) and precision (delta Akaike’s information criterion). All model evaluation and comparison statistics were calculated using Model Evaluation System software version 3.2.2. The Groot and Richards models did not differ from each other (P<0.05) and were the most precise and accurate (P<0.05). Therefore, the Groot model was selected due to its better accuracy and precision and easier access to the parameters. The inclusion of Gliricidia silage in the diet resulted in an increase in the time to obtain the maximum rate of degradation and in the time after incubation when half of the asymptotic level was reached. The Groot model is recommended to estimate the average curve. Dietary inclusion of Gliricidia silage alters the gas production curve due to the longer time required for the diet to reach the maximum rate of degradation, this can increase the time the diet remains in rumen and promote a reduction in the consumption. fermentation kinetics Groot model hay non-linear functions silage Agriculture S Agriculture (General) Jucileia Aparecida da Silva Morais verfasserin aut Juliana Caroline Santos Santana verfasserin aut Gelson dos Santos Difante verfasserin aut João Virgínio Emerenciano Neto verfasserin aut Luís Carlos Vinhas Ítavo verfasserin aut Camila Celeste Brandão Ferreira Ítavo verfasserin aut Vinícius da Silva Oliveira verfasserin aut Maria Juciara Silva Teles Rodrigues verfasserin aut In Ciência Rural Universidade Federal de Santa Maria, 2004 51(2021), 11 (DE-627)320649970 (DE-600)2025834-3 16784596 nnns volume:51 year:2021 number:11 https://doi.org/10.1590/0103-8478cr20200993 kostenfrei https://doaj.org/article/3b55cd65be324f9b97831c1f07682f38 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021001100654&tlng=en kostenfrei https://doaj.org/toc/1678-4596 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 51 2021 11
spelling	10.1590/0103-8478cr20200993 doi (DE-627)DOAJ017602793 (DE-599)DOAJ3b55cd65be324f9b97831c1f07682f38 DE-627 ger DE-627 rakwb eng por S1-972 Antonio Leandro Chaves Gurgel verfasserin aut Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT: This study examined the use of the Gompertz, Groot, monomolecular, Richards and two-compartment-logistic mathematical models to investigate the kinetics of in vitro gas production of diets composed of combinations of Gliricidia hay or silage. In addition, the effects of Gliricidia hay or silage inclusion on the in vitro cumulative gas production of these diets were evaluated. Rumen fermentation kinetics were analyzed by the in vitro cumulative gas production methodology. The model parameters were estimated using the Gauss Newton method, with the exception of the Richards model, which was used by Marquardt’s algorithm. Model fit was assessed using the determination coefficient, F test for parameters identity, concordance correlation coefficient, root mean square error of prediction, and decomposition of mean square error of prediction into mean error, systematic bias and random error. The models were compared for accuracy (pairwise mean square error of prediction) and precision (delta Akaike’s information criterion). All model evaluation and comparison statistics were calculated using Model Evaluation System software version 3.2.2. The Groot and Richards models did not differ from each other (P<0.05) and were the most precise and accurate (P<0.05). Therefore, the Groot model was selected due to its better accuracy and precision and easier access to the parameters. The inclusion of Gliricidia silage in the diet resulted in an increase in the time to obtain the maximum rate of degradation and in the time after incubation when half of the asymptotic level was reached. The Groot model is recommended to estimate the average curve. Dietary inclusion of Gliricidia silage alters the gas production curve due to the longer time required for the diet to reach the maximum rate of degradation, this can increase the time the diet remains in rumen and promote a reduction in the consumption. fermentation kinetics Groot model hay non-linear functions silage Agriculture S Agriculture (General) Jucileia Aparecida da Silva Morais verfasserin aut Juliana Caroline Santos Santana verfasserin aut Gelson dos Santos Difante verfasserin aut João Virgínio Emerenciano Neto verfasserin aut Luís Carlos Vinhas Ítavo verfasserin aut Camila Celeste Brandão Ferreira Ítavo verfasserin aut Vinícius da Silva Oliveira verfasserin aut Maria Juciara Silva Teles Rodrigues verfasserin aut In Ciência Rural Universidade Federal de Santa Maria, 2004 51(2021), 11 (DE-627)320649970 (DE-600)2025834-3 16784596 nnns volume:51 year:2021 number:11 https://doi.org/10.1590/0103-8478cr20200993 kostenfrei https://doaj.org/article/3b55cd65be324f9b97831c1f07682f38 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021001100654&tlng=en kostenfrei https://doaj.org/toc/1678-4596 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 51 2021 11
allfields_unstemmed	10.1590/0103-8478cr20200993 doi (DE-627)DOAJ017602793 (DE-599)DOAJ3b55cd65be324f9b97831c1f07682f38 DE-627 ger DE-627 rakwb eng por S1-972 Antonio Leandro Chaves Gurgel verfasserin aut Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT: This study examined the use of the Gompertz, Groot, monomolecular, Richards and two-compartment-logistic mathematical models to investigate the kinetics of in vitro gas production of diets composed of combinations of Gliricidia hay or silage. In addition, the effects of Gliricidia hay or silage inclusion on the in vitro cumulative gas production of these diets were evaluated. Rumen fermentation kinetics were analyzed by the in vitro cumulative gas production methodology. The model parameters were estimated using the Gauss Newton method, with the exception of the Richards model, which was used by Marquardt’s algorithm. Model fit was assessed using the determination coefficient, F test for parameters identity, concordance correlation coefficient, root mean square error of prediction, and decomposition of mean square error of prediction into mean error, systematic bias and random error. The models were compared for accuracy (pairwise mean square error of prediction) and precision (delta Akaike’s information criterion). All model evaluation and comparison statistics were calculated using Model Evaluation System software version 3.2.2. The Groot and Richards models did not differ from each other (P<0.05) and were the most precise and accurate (P<0.05). Therefore, the Groot model was selected due to its better accuracy and precision and easier access to the parameters. The inclusion of Gliricidia silage in the diet resulted in an increase in the time to obtain the maximum rate of degradation and in the time after incubation when half of the asymptotic level was reached. The Groot model is recommended to estimate the average curve. Dietary inclusion of Gliricidia silage alters the gas production curve due to the longer time required for the diet to reach the maximum rate of degradation, this can increase the time the diet remains in rumen and promote a reduction in the consumption. fermentation kinetics Groot model hay non-linear functions silage Agriculture S Agriculture (General) Jucileia Aparecida da Silva Morais verfasserin aut Juliana Caroline Santos Santana verfasserin aut Gelson dos Santos Difante verfasserin aut João Virgínio Emerenciano Neto verfasserin aut Luís Carlos Vinhas Ítavo verfasserin aut Camila Celeste Brandão Ferreira Ítavo verfasserin aut Vinícius da Silva Oliveira verfasserin aut Maria Juciara Silva Teles Rodrigues verfasserin aut In Ciência Rural Universidade Federal de Santa Maria, 2004 51(2021), 11 (DE-627)320649970 (DE-600)2025834-3 16784596 nnns volume:51 year:2021 number:11 https://doi.org/10.1590/0103-8478cr20200993 kostenfrei https://doaj.org/article/3b55cd65be324f9b97831c1f07682f38 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021001100654&tlng=en kostenfrei https://doaj.org/toc/1678-4596 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 51 2021 11
allfieldsGer	10.1590/0103-8478cr20200993 doi (DE-627)DOAJ017602793 (DE-599)DOAJ3b55cd65be324f9b97831c1f07682f38 DE-627 ger DE-627 rakwb eng por S1-972 Antonio Leandro Chaves Gurgel verfasserin aut Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT: This study examined the use of the Gompertz, Groot, monomolecular, Richards and two-compartment-logistic mathematical models to investigate the kinetics of in vitro gas production of diets composed of combinations of Gliricidia hay or silage. In addition, the effects of Gliricidia hay or silage inclusion on the in vitro cumulative gas production of these diets were evaluated. Rumen fermentation kinetics were analyzed by the in vitro cumulative gas production methodology. The model parameters were estimated using the Gauss Newton method, with the exception of the Richards model, which was used by Marquardt’s algorithm. Model fit was assessed using the determination coefficient, F test for parameters identity, concordance correlation coefficient, root mean square error of prediction, and decomposition of mean square error of prediction into mean error, systematic bias and random error. The models were compared for accuracy (pairwise mean square error of prediction) and precision (delta Akaike’s information criterion). All model evaluation and comparison statistics were calculated using Model Evaluation System software version 3.2.2. The Groot and Richards models did not differ from each other (P<0.05) and were the most precise and accurate (P<0.05). Therefore, the Groot model was selected due to its better accuracy and precision and easier access to the parameters. The inclusion of Gliricidia silage in the diet resulted in an increase in the time to obtain the maximum rate of degradation and in the time after incubation when half of the asymptotic level was reached. The Groot model is recommended to estimate the average curve. Dietary inclusion of Gliricidia silage alters the gas production curve due to the longer time required for the diet to reach the maximum rate of degradation, this can increase the time the diet remains in rumen and promote a reduction in the consumption. fermentation kinetics Groot model hay non-linear functions silage Agriculture S Agriculture (General) Jucileia Aparecida da Silva Morais verfasserin aut Juliana Caroline Santos Santana verfasserin aut Gelson dos Santos Difante verfasserin aut João Virgínio Emerenciano Neto verfasserin aut Luís Carlos Vinhas Ítavo verfasserin aut Camila Celeste Brandão Ferreira Ítavo verfasserin aut Vinícius da Silva Oliveira verfasserin aut Maria Juciara Silva Teles Rodrigues verfasserin aut In Ciência Rural Universidade Federal de Santa Maria, 2004 51(2021), 11 (DE-627)320649970 (DE-600)2025834-3 16784596 nnns volume:51 year:2021 number:11 https://doi.org/10.1590/0103-8478cr20200993 kostenfrei https://doaj.org/article/3b55cd65be324f9b97831c1f07682f38 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021001100654&tlng=en kostenfrei https://doaj.org/toc/1678-4596 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 51 2021 11
allfieldsSound	10.1590/0103-8478cr20200993 doi (DE-627)DOAJ017602793 (DE-599)DOAJ3b55cd65be324f9b97831c1f07682f38 DE-627 ger DE-627 rakwb eng por S1-972 Antonio Leandro Chaves Gurgel verfasserin aut Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT: This study examined the use of the Gompertz, Groot, monomolecular, Richards and two-compartment-logistic mathematical models to investigate the kinetics of in vitro gas production of diets composed of combinations of Gliricidia hay or silage. In addition, the effects of Gliricidia hay or silage inclusion on the in vitro cumulative gas production of these diets were evaluated. Rumen fermentation kinetics were analyzed by the in vitro cumulative gas production methodology. The model parameters were estimated using the Gauss Newton method, with the exception of the Richards model, which was used by Marquardt’s algorithm. Model fit was assessed using the determination coefficient, F test for parameters identity, concordance correlation coefficient, root mean square error of prediction, and decomposition of mean square error of prediction into mean error, systematic bias and random error. The models were compared for accuracy (pairwise mean square error of prediction) and precision (delta Akaike’s information criterion). All model evaluation and comparison statistics were calculated using Model Evaluation System software version 3.2.2. The Groot and Richards models did not differ from each other (P<0.05) and were the most precise and accurate (P<0.05). Therefore, the Groot model was selected due to its better accuracy and precision and easier access to the parameters. The inclusion of Gliricidia silage in the diet resulted in an increase in the time to obtain the maximum rate of degradation and in the time after incubation when half of the asymptotic level was reached. The Groot model is recommended to estimate the average curve. Dietary inclusion of Gliricidia silage alters the gas production curve due to the longer time required for the diet to reach the maximum rate of degradation, this can increase the time the diet remains in rumen and promote a reduction in the consumption. fermentation kinetics Groot model hay non-linear functions silage Agriculture S Agriculture (General) Jucileia Aparecida da Silva Morais verfasserin aut Juliana Caroline Santos Santana verfasserin aut Gelson dos Santos Difante verfasserin aut João Virgínio Emerenciano Neto verfasserin aut Luís Carlos Vinhas Ítavo verfasserin aut Camila Celeste Brandão Ferreira Ítavo verfasserin aut Vinícius da Silva Oliveira verfasserin aut Maria Juciara Silva Teles Rodrigues verfasserin aut In Ciência Rural Universidade Federal de Santa Maria, 2004 51(2021), 11 (DE-627)320649970 (DE-600)2025834-3 16784596 nnns volume:51 year:2021 number:11 https://doi.org/10.1590/0103-8478cr20200993 kostenfrei https://doaj.org/article/3b55cd65be324f9b97831c1f07682f38 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021001100654&tlng=en kostenfrei https://doaj.org/toc/1678-4596 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 51 2021 11
language	English Portuguese
source	In Ciência Rural 51(2021), 11 volume:51 year:2021 number:11
sourceStr	In Ciência Rural 51(2021), 11 volume:51 year:2021 number:11
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	fermentation kinetics Groot model hay non-linear functions silage Agriculture S Agriculture (General)
isfreeaccess_bool	true
container_title	Ciência Rural
authorswithroles_txt_mv	Antonio Leandro Chaves Gurgel @@aut@@ Jucileia Aparecida da Silva Morais @@aut@@ Juliana Caroline Santos Santana @@aut@@ Gelson dos Santos Difante @@aut@@ João Virgínio Emerenciano Neto @@aut@@ Luís Carlos Vinhas Ítavo @@aut@@ Camila Celeste Brandão Ferreira Ítavo @@aut@@ Vinícius da Silva Oliveira @@aut@@ Maria Juciara Silva Teles Rodrigues @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	320649970
id	DOAJ017602793
language_de	englisch portugiesisch
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In addition, the effects of Gliricidia hay or silage inclusion on the in vitro cumulative gas production of these diets were evaluated. Rumen fermentation kinetics were analyzed by the in vitro cumulative gas production methodology. The model parameters were estimated using the Gauss Newton method, with the exception of the Richards model, which was used by Marquardt’s algorithm. Model fit was assessed using the determination coefficient, F test for parameters identity, concordance correlation coefficient, root mean square error of prediction, and decomposition of mean square error of prediction into mean error, systematic bias and random error. The models were compared for accuracy (pairwise mean square error of prediction) and precision (delta Akaike’s information criterion). All model evaluation and comparison statistics were calculated using Model Evaluation System software version 3.2.2. 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callnumber-first	S - Agriculture
author	Antonio Leandro Chaves Gurgel
spellingShingle	Antonio Leandro Chaves Gurgel misc S1-972 misc fermentation kinetics misc Groot model misc hay misc non-linear functions misc silage misc Agriculture misc S misc Agriculture (General) Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia
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topic_title	S1-972 Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia fermentation kinetics Groot model hay non-linear functions silage
topic	misc S1-972 misc fermentation kinetics misc Groot model misc hay misc non-linear functions misc silage misc Agriculture misc S misc Agriculture (General)
topic_unstemmed	misc S1-972 misc fermentation kinetics misc Groot model misc hay misc non-linear functions misc silage misc Agriculture misc S misc Agriculture (General)
topic_browse	misc S1-972 misc fermentation kinetics misc Groot model misc hay misc non-linear functions misc silage misc Agriculture misc S misc Agriculture (General)
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title	Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia
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title_full	Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia
author_sort	Antonio Leandro Chaves Gurgel
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author_browse	Antonio Leandro Chaves Gurgel Jucileia Aparecida da Silva Morais Juliana Caroline Santos Santana Gelson dos Santos Difante João Virgínio Emerenciano Neto Luís Carlos Vinhas Ítavo Camila Celeste Brandão Ferreira Ítavo Vinícius da Silva Oliveira Maria Juciara Silva Teles Rodrigues
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title_sort	mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved gliricidia
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title_auth	Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia
abstract	ABSTRACT: This study examined the use of the Gompertz, Groot, monomolecular, Richards and two-compartment-logistic mathematical models to investigate the kinetics of in vitro gas production of diets composed of combinations of Gliricidia hay or silage. In addition, the effects of Gliricidia hay or silage inclusion on the in vitro cumulative gas production of these diets were evaluated. Rumen fermentation kinetics were analyzed by the in vitro cumulative gas production methodology. The model parameters were estimated using the Gauss Newton method, with the exception of the Richards model, which was used by Marquardt’s algorithm. Model fit was assessed using the determination coefficient, F test for parameters identity, concordance correlation coefficient, root mean square error of prediction, and decomposition of mean square error of prediction into mean error, systematic bias and random error. The models were compared for accuracy (pairwise mean square error of prediction) and precision (delta Akaike’s information criterion). All model evaluation and comparison statistics were calculated using Model Evaluation System software version 3.2.2. The Groot and Richards models did not differ from each other (P<0.05) and were the most precise and accurate (P<0.05). Therefore, the Groot model was selected due to its better accuracy and precision and easier access to the parameters. The inclusion of Gliricidia silage in the diet resulted in an increase in the time to obtain the maximum rate of degradation and in the time after incubation when half of the asymptotic level was reached. The Groot model is recommended to estimate the average curve. Dietary inclusion of Gliricidia silage alters the gas production curve due to the longer time required for the diet to reach the maximum rate of degradation, this can increase the time the diet remains in rumen and promote a reduction in the consumption.
abstractGer	ABSTRACT: This study examined the use of the Gompertz, Groot, monomolecular, Richards and two-compartment-logistic mathematical models to investigate the kinetics of in vitro gas production of diets composed of combinations of Gliricidia hay or silage. In addition, the effects of Gliricidia hay or silage inclusion on the in vitro cumulative gas production of these diets were evaluated. Rumen fermentation kinetics were analyzed by the in vitro cumulative gas production methodology. The model parameters were estimated using the Gauss Newton method, with the exception of the Richards model, which was used by Marquardt’s algorithm. Model fit was assessed using the determination coefficient, F test for parameters identity, concordance correlation coefficient, root mean square error of prediction, and decomposition of mean square error of prediction into mean error, systematic bias and random error. The models were compared for accuracy (pairwise mean square error of prediction) and precision (delta Akaike’s information criterion). All model evaluation and comparison statistics were calculated using Model Evaluation System software version 3.2.2. The Groot and Richards models did not differ from each other (P<0.05) and were the most precise and accurate (P<0.05). Therefore, the Groot model was selected due to its better accuracy and precision and easier access to the parameters. The inclusion of Gliricidia silage in the diet resulted in an increase in the time to obtain the maximum rate of degradation and in the time after incubation when half of the asymptotic level was reached. The Groot model is recommended to estimate the average curve. Dietary inclusion of Gliricidia silage alters the gas production curve due to the longer time required for the diet to reach the maximum rate of degradation, this can increase the time the diet remains in rumen and promote a reduction in the consumption.
abstract_unstemmed	ABSTRACT: This study examined the use of the Gompertz, Groot, monomolecular, Richards and two-compartment-logistic mathematical models to investigate the kinetics of in vitro gas production of diets composed of combinations of Gliricidia hay or silage. In addition, the effects of Gliricidia hay or silage inclusion on the in vitro cumulative gas production of these diets were evaluated. Rumen fermentation kinetics were analyzed by the in vitro cumulative gas production methodology. The model parameters were estimated using the Gauss Newton method, with the exception of the Richards model, which was used by Marquardt’s algorithm. Model fit was assessed using the determination coefficient, F test for parameters identity, concordance correlation coefficient, root mean square error of prediction, and decomposition of mean square error of prediction into mean error, systematic bias and random error. The models were compared for accuracy (pairwise mean square error of prediction) and precision (delta Akaike’s information criterion). All model evaluation and comparison statistics were calculated using Model Evaluation System software version 3.2.2. The Groot and Richards models did not differ from each other (P<0.05) and were the most precise and accurate (P<0.05). Therefore, the Groot model was selected due to its better accuracy and precision and easier access to the parameters. The inclusion of Gliricidia silage in the diet resulted in an increase in the time to obtain the maximum rate of degradation and in the time after incubation when half of the asymptotic level was reached. The Groot model is recommended to estimate the average curve. Dietary inclusion of Gliricidia silage alters the gas production curve due to the longer time required for the diet to reach the maximum rate of degradation, this can increase the time the diet remains in rumen and promote a reduction in the consumption.
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title_short	Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia
url	https://doi.org/10.1590/0103-8478cr20200993 https://doaj.org/article/3b55cd65be324f9b97831c1f07682f38 http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021001100654&tlng=en https://doaj.org/toc/1678-4596
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The Groot and Richards models did not differ from each other (P<0.05) and were the most precise and accurate (P<0.05). Therefore, the Groot model was selected due to its better accuracy and precision and easier access to the parameters. The inclusion of Gliricidia silage in the diet resulted in an increase in the time to obtain the maximum rate of degradation and in the time after incubation when half of the asymptotic level was reached. The Groot model is recommended to estimate the average curve. 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Mathematical models to adjust the parameters of in vitro cumulative gas production of diets containing preserved Gliricidia

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