Developing a continuous adjustment factor for dry matter intake of gestating and lactating ewes
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Outros Autores: | |
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. |
id |
USP-18_c1a7842956fb10dad912227d244703fd |
---|---|
oai_identifier_str |
oai:revistas.usp.br:article/183240 |
network_acronym_str |
USP-18 |
network_name_str |
Scientia Agrícola (Online) |
repository_id_str |
|
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 |
_version_ |
1800222794510761984 |