Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC®
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Zootecnia (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982020000100620 |
Resumo: | ABSTRACT We evaluated whether the procedure for correcting backfat thickness (BT) equation coefficients and lipid mass (LM) initial values in animal profiles, as well as actual model parameter (MP) data and their interrelationships, could reduce errors in predicting body weight (BW) and BT in pigs reared in Southern Brazil. Because different combinations of actual and estimated MP values in advanced system calibration mode (ACM) give rise to distinct calibration procedures, their BT and BW prediction errors were compared with those obtained by INRAPORC® default mode calibration based on different parameter combinations. Correlations among MP were also verified. The BT prediction correction (BTcor) procedure reduced the BT standard deviation of the estimate (σ) from 3.25 to 2.42 mm, but the correction had no effect on BW. Actual BT and feed intake data at 50 kg BW (FI50), reported in ACM, reduced prediction errors of BW and BT, in which their σ values were reduced from 5.29 to <4.08 kg and 2.42 to <2.12 mm, respectively. Mean protein deposition (MeanPD), FI50, and feed intake at 100 kg BW (FI100) were strongly and positively correlated (r>0.98). In addition, initial BW (BWi) was strongly negatively correlated with these parameters (r<–0.87) but positively correlated with the maintenance adjustment factor (MAINT) (r = 0.75). The inclusion of actual or default MP values in the ACM strongly influenced the estimation of other values, as well the predicted outcomes for BW and BT. The BTcor procedure and the input of actual or default MP values into the ACM of INRAPORC® is justified to reduce prediction errors, as it yields considerably greater accuracy in a pig nutritional adjustment system. |
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Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC®backfat thicknesscalibration procedureslipid correctionnutritional modelingswineABSTRACT We evaluated whether the procedure for correcting backfat thickness (BT) equation coefficients and lipid mass (LM) initial values in animal profiles, as well as actual model parameter (MP) data and their interrelationships, could reduce errors in predicting body weight (BW) and BT in pigs reared in Southern Brazil. Because different combinations of actual and estimated MP values in advanced system calibration mode (ACM) give rise to distinct calibration procedures, their BT and BW prediction errors were compared with those obtained by INRAPORC® default mode calibration based on different parameter combinations. Correlations among MP were also verified. The BT prediction correction (BTcor) procedure reduced the BT standard deviation of the estimate (σ) from 3.25 to 2.42 mm, but the correction had no effect on BW. Actual BT and feed intake data at 50 kg BW (FI50), reported in ACM, reduced prediction errors of BW and BT, in which their σ values were reduced from 5.29 to <4.08 kg and 2.42 to <2.12 mm, respectively. Mean protein deposition (MeanPD), FI50, and feed intake at 100 kg BW (FI100) were strongly and positively correlated (r>0.98). In addition, initial BW (BWi) was strongly negatively correlated with these parameters (r<–0.87) but positively correlated with the maintenance adjustment factor (MAINT) (r = 0.75). The inclusion of actual or default MP values in the ACM strongly influenced the estimation of other values, as well the predicted outcomes for BW and BT. The BTcor procedure and the input of actual or default MP values into the ACM of INRAPORC® is justified to reduce prediction errors, as it yields considerably greater accuracy in a pig nutritional adjustment system.Sociedade Brasileira de Zootecnia2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982020000100620Revista Brasileira de Zootecnia v.49 2020reponame:Revista Brasileira de Zootecnia (Online)instname:Sociedade Brasileira de Zootecnia (SBZ)instacron:SBZ10.37496/rbz4920190177info:eu-repo/semantics/openAccessMagagnin,Sebastião FerreiraHauptli,LucéliaWarpechowski,Marson Bruckeng2020-11-17T00:00:00Zoai:scielo:S1516-35982020000100620Revistahttps://www.rbz.org.br/pt-br/https://old.scielo.br/oai/scielo-oai.php||bz@sbz.org.br|| secretariarbz@sbz.org.br1806-92901516-3598opendoar:2020-11-17T00:00Revista Brasileira de Zootecnia (Online) - Sociedade Brasileira de Zootecnia (SBZ)false |
dc.title.none.fl_str_mv |
Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC® |
title |
Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC® |
spellingShingle |
Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC® Magagnin,Sebastião Ferreira backfat thickness calibration procedures lipid correction nutritional modeling swine |
title_short |
Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC® |
title_full |
Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC® |
title_fullStr |
Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC® |
title_full_unstemmed |
Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC® |
title_sort |
Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC® |
author |
Magagnin,Sebastião Ferreira |
author_facet |
Magagnin,Sebastião Ferreira Hauptli,Lucélia Warpechowski,Marson Bruck |
author_role |
author |
author2 |
Hauptli,Lucélia Warpechowski,Marson Bruck |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Magagnin,Sebastião Ferreira Hauptli,Lucélia Warpechowski,Marson Bruck |
dc.subject.por.fl_str_mv |
backfat thickness calibration procedures lipid correction nutritional modeling swine |
topic |
backfat thickness calibration procedures lipid correction nutritional modeling swine |
description |
ABSTRACT We evaluated whether the procedure for correcting backfat thickness (BT) equation coefficients and lipid mass (LM) initial values in animal profiles, as well as actual model parameter (MP) data and their interrelationships, could reduce errors in predicting body weight (BW) and BT in pigs reared in Southern Brazil. Because different combinations of actual and estimated MP values in advanced system calibration mode (ACM) give rise to distinct calibration procedures, their BT and BW prediction errors were compared with those obtained by INRAPORC® default mode calibration based on different parameter combinations. Correlations among MP were also verified. The BT prediction correction (BTcor) procedure reduced the BT standard deviation of the estimate (σ) from 3.25 to 2.42 mm, but the correction had no effect on BW. Actual BT and feed intake data at 50 kg BW (FI50), reported in ACM, reduced prediction errors of BW and BT, in which their σ values were reduced from 5.29 to <4.08 kg and 2.42 to <2.12 mm, respectively. Mean protein deposition (MeanPD), FI50, and feed intake at 100 kg BW (FI100) were strongly and positively correlated (r>0.98). In addition, initial BW (BWi) was strongly negatively correlated with these parameters (r<–0.87) but positively correlated with the maintenance adjustment factor (MAINT) (r = 0.75). The inclusion of actual or default MP values in the ACM strongly influenced the estimation of other values, as well the predicted outcomes for BW and BT. The BTcor procedure and the input of actual or default MP values into the ACM of INRAPORC® is justified to reduce prediction errors, as it yields considerably greater accuracy in a pig nutritional adjustment system. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982020000100620 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982020000100620 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.37496/rbz4920190177 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Zootecnia |
publisher.none.fl_str_mv |
Sociedade Brasileira de Zootecnia |
dc.source.none.fl_str_mv |
Revista Brasileira de Zootecnia v.49 2020 reponame:Revista Brasileira de Zootecnia (Online) instname:Sociedade Brasileira de Zootecnia (SBZ) instacron:SBZ |
instname_str |
Sociedade Brasileira de Zootecnia (SBZ) |
instacron_str |
SBZ |
institution |
SBZ |
reponame_str |
Revista Brasileira de Zootecnia (Online) |
collection |
Revista Brasileira de Zootecnia (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Zootecnia (Online) - Sociedade Brasileira de Zootecnia (SBZ) |
repository.mail.fl_str_mv |
||bz@sbz.org.br|| secretariarbz@sbz.org.br |
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1750318153729048576 |