Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewes

Detalhes bibliográficos
Autor(a) principal: Gallo, Sarita Bonagurio
Data de Publicação: 2021
Outros Autores: Tedeschi, Luis Orlindo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: https://www.revistas.usp.br/sa/article/view/183240
Resumo: Intake is a multifactorial process that is influenced by animal type, environmental factors, and diet characteristics. Sheep, especially, have specific eating habits, with a greater selection of ingested feed compared to cattle. Thus, predictive equations for dry matter intake (DMI) must constantly be reviewed. The objective of this study was to combine different adjustment factors to develop one continuous adjustment factor for predicting the DMI of pregnant, dry, and lactating ewes. The equations evaluated for non-lactation ewes accounts for metabolic body weight and weight gain, and the equation for lactating ewes includes milk production and its fat content. The database used in this study was pooled from hair sheep ewes, two to four years old, with controlled feeding, during the pregnancy and lactating physiological phases. For the overall predictions (gestating and lactating ewes), the adjusted DMI prediction had greater accuracy but lower precision than the unadjusted DMI prediction. However, adjusting DMI increased the adequacy of the prediction as the mean square error of prediction difference (ΔMSEP) decreased (p = 0.0328). Similarly, for gestating ewes, the adjusted predicted DMI had a lower ΔMSEP than the unadjusted predicted DMI (p < 0.001). For lactating ewes, no difference was detected between the adjusted and unadjusted predicted DMI based on the ΔMSEP statistics (p = 0.3672), but the assumption that peak milk was 28 days (default) worsened the predictability of the adjusted predicted DMI as it had lower precision and accuracy. Adjustments for predicted DMI of dry and lactating ewes are necessary to increase adequacy and precision.
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spelling Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewesmathematical modelnutrition modelpredictionrequirementsheepIntake is a multifactorial process that is influenced by animal type, environmental factors, and diet characteristics. Sheep, especially, have specific eating habits, with a greater selection of ingested feed compared to cattle. Thus, predictive equations for dry matter intake (DMI) must constantly be reviewed. The objective of this study was to combine different adjustment factors to develop one continuous adjustment factor for predicting the DMI of pregnant, dry, and lactating ewes. The equations evaluated for non-lactation ewes accounts for metabolic body weight and weight gain, and the equation for lactating ewes includes milk production and its fat content. The database used in this study was pooled from hair sheep ewes, two to four years old, with controlled feeding, during the pregnancy and lactating physiological phases. For the overall predictions (gestating and lactating ewes), the adjusted DMI prediction had greater accuracy but lower precision than the unadjusted DMI prediction. However, adjusting DMI increased the adequacy of the prediction as the mean square error of prediction difference (ΔMSEP) decreased (p = 0.0328). Similarly, for gestating ewes, the adjusted predicted DMI had a lower ΔMSEP than the unadjusted predicted DMI (p < 0.001). For lactating ewes, no difference was detected between the adjusted and unadjusted predicted DMI based on the ΔMSEP statistics (p = 0.3672), but the assumption that peak milk was 28 days (default) worsened the predictability of the adjusted predicted DMI as it had lower precision and accuracy. Adjustments for predicted DMI of dry and lactating ewes are necessary to increase adequacy and precision.Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2021-01-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/18324010.1590/1678-992X-2019-0082Scientia Agricola; v. 78 n. 2 (2021); e20190082Scientia Agricola; Vol. 78 Núm. 2 (2021); e20190082Scientia Agricola; Vol. 78 No. 2 (2021); e201900821678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/183240/169922Copyright (c) 2021 Scientia Agricolahttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessGallo, Sarita Bonagurio Tedeschi, Luis Orlindo 2021-03-18T18:32:18Zoai:revistas.usp.br:article/183240Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2021-03-18T18:32:18Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewes
title Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewes
spellingShingle Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewes
Gallo, Sarita Bonagurio
mathematical model
nutrition model
prediction
requirement
sheep
title_short Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewes
title_full Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewes
title_fullStr Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewes
title_full_unstemmed Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewes
title_sort Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewes
author Gallo, Sarita Bonagurio
author_facet Gallo, Sarita Bonagurio
Tedeschi, Luis Orlindo
author_role author
author2 Tedeschi, Luis Orlindo
author2_role author
dc.contributor.author.fl_str_mv Gallo, Sarita Bonagurio
Tedeschi, Luis Orlindo
dc.subject.por.fl_str_mv mathematical model
nutrition model
prediction
requirement
sheep
topic mathematical model
nutrition model
prediction
requirement
sheep
description Intake is a multifactorial process that is influenced by animal type, environmental factors, and diet characteristics. Sheep, especially, have specific eating habits, with a greater selection of ingested feed compared to cattle. Thus, predictive equations for dry matter intake (DMI) must constantly be reviewed. The objective of this study was to combine different adjustment factors to develop one continuous adjustment factor for predicting the DMI of pregnant, dry, and lactating ewes. The equations evaluated for non-lactation ewes accounts for metabolic body weight and weight gain, and the equation for lactating ewes includes milk production and its fat content. The database used in this study was pooled from hair sheep ewes, two to four years old, with controlled feeding, during the pregnancy and lactating physiological phases. For the overall predictions (gestating and lactating ewes), the adjusted DMI prediction had greater accuracy but lower precision than the unadjusted DMI prediction. However, adjusting DMI increased the adequacy of the prediction as the mean square error of prediction difference (ΔMSEP) decreased (p = 0.0328). Similarly, for gestating ewes, the adjusted predicted DMI had a lower ΔMSEP than the unadjusted predicted DMI (p < 0.001). For lactating ewes, no difference was detected between the adjusted and unadjusted predicted DMI based on the ΔMSEP statistics (p = 0.3672), but the assumption that peak milk was 28 days (default) worsened the predictability of the adjusted predicted DMI as it had lower precision and accuracy. Adjustments for predicted DMI of dry and lactating ewes are necessary to increase adequacy and precision.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-06
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/sa/article/view/183240
10.1590/1678-992X-2019-0082
url https://www.revistas.usp.br/sa/article/view/183240
identifier_str_mv 10.1590/1678-992X-2019-0082
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/sa/article/view/183240/169922
dc.rights.driver.fl_str_mv Copyright (c) 2021 Scientia Agricola
http://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Scientia Agricola
http://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
dc.source.none.fl_str_mv Scientia Agricola; v. 78 n. 2 (2021); e20190082
Scientia Agricola; Vol. 78 Núm. 2 (2021); e20190082
Scientia Agricola; Vol. 78 No. 2 (2021); e20190082
1678-992X
0103-9016
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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