Corrections to prediction of backfat thickness and relationships among model parameters in INRAPORC®

Detalhes bibliográficos
Autor(a) principal: Magagnin,Sebastião Ferreira
Data de Publicação: 2020
Outros Autores: Hauptli,Lucélia, Warpechowski,Marson Bruck
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.
id SBZ-1_f6b3c9dc7f7e93eb447b60ddfbd1adb7
oai_identifier_str oai:scielo:S1516-35982020000100620
network_acronym_str SBZ-1
network_name_str Revista Brasileira de Zootecnia (Online)
repository_id_str
spelling 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
_version_ 1750318153729048576