Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain
Autor(a) principal: | |
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Data de Publicação: | 2018 |
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=S1516-35982018000100522 |
Resumo: | ABSTRACT The objective of this study was to develop an equation to determine the apparent metabolizable energy (AME) and metabolizable energy corrected for nitrogen balance (AMEn) using a physical-based classification of corn. A total of 5,055 samples were taken from bulk cargo trucks, over a five-year period. The parameters studied were the variables related to the physical characteristics of grains. The density of maize was evaluated, and AME and AMEn were calculated. The average value for AME was 3,375 kcal/kg, and two groups were formed of high quality and low quality for all samples. Stepwise regression analysis was then carried out using grain quality to estimate AME and AMEn, and the validation of the equations was carried out with 6,490 independent samples. The average value for density was 767.7 kg/m3. The multiple regressions used to estimate AME and AMEn as a function of humidity, density, and physical composition of corn kernels showed that moisture was included for AME, but not for AMEn. The equations presented high coefficients of determination (R2) for AME (0.994) and AMEn (0.987). The discriminant analyses correctly classified 98% of the high-quality samples and 96.69% of low-quality samples, so the error was smaller than the expected. The calculated equations were shown to be good at discriminating between samples of high and low quality of corn according to its physical composition, and the most important variables for separation between groups were damaged grain fraction, impurities, burnt, and soft. The correlation between calculated (independent samples) and estimated metabolizable energy and AMEn were, respectively, 0.9942 and 0.9859. The corn energy values can be estimated based on physical evaluation of the grain. |
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Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grainbroilersmetabolizabilitynutritional valueABSTRACT The objective of this study was to develop an equation to determine the apparent metabolizable energy (AME) and metabolizable energy corrected for nitrogen balance (AMEn) using a physical-based classification of corn. A total of 5,055 samples were taken from bulk cargo trucks, over a five-year period. The parameters studied were the variables related to the physical characteristics of grains. The density of maize was evaluated, and AME and AMEn were calculated. The average value for AME was 3,375 kcal/kg, and two groups were formed of high quality and low quality for all samples. Stepwise regression analysis was then carried out using grain quality to estimate AME and AMEn, and the validation of the equations was carried out with 6,490 independent samples. The average value for density was 767.7 kg/m3. The multiple regressions used to estimate AME and AMEn as a function of humidity, density, and physical composition of corn kernels showed that moisture was included for AME, but not for AMEn. The equations presented high coefficients of determination (R2) for AME (0.994) and AMEn (0.987). The discriminant analyses correctly classified 98% of the high-quality samples and 96.69% of low-quality samples, so the error was smaller than the expected. The calculated equations were shown to be good at discriminating between samples of high and low quality of corn according to its physical composition, and the most important variables for separation between groups were damaged grain fraction, impurities, burnt, and soft. The correlation between calculated (independent samples) and estimated metabolizable energy and AMEn were, respectively, 0.9942 and 0.9859. The corn energy values can be estimated based on physical evaluation of the grain.Sociedade Brasileira de Zootecnia2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982018000100522Revista Brasileira de Zootecnia v.47 2018reponame:Revista Brasileira de Zootecnia (Online)instname:Sociedade Brasileira de Zootecnia (SBZ)instacron:SBZ10.1590/rbz4720170153info:eu-repo/semantics/openAccessRodrigues,Sandra Iara Furtado CostaStringhini,José HenriqueTanure,Candice BergmannPeripolli,VanessaSeixas,LuizaMcManus,Conceptaeng2018-07-26T00:00:00Zoai:scielo:S1516-35982018000100522Revistahttps://www.rbz.org.br/pt-br/https://old.scielo.br/oai/scielo-oai.php||bz@sbz.org.br|| secretariarbz@sbz.org.br1806-92901516-3598opendoar:2018-07-26T00:00Revista Brasileira de Zootecnia (Online) - Sociedade Brasileira de Zootecnia (SBZ)false |
dc.title.none.fl_str_mv |
Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain |
title |
Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain |
spellingShingle |
Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain Rodrigues,Sandra Iara Furtado Costa broilers metabolizability nutritional value |
title_short |
Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain |
title_full |
Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain |
title_fullStr |
Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain |
title_full_unstemmed |
Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain |
title_sort |
Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain |
author |
Rodrigues,Sandra Iara Furtado Costa |
author_facet |
Rodrigues,Sandra Iara Furtado Costa Stringhini,José Henrique Tanure,Candice Bergmann Peripolli,Vanessa Seixas,Luiza McManus,Concepta |
author_role |
author |
author2 |
Stringhini,José Henrique Tanure,Candice Bergmann Peripolli,Vanessa Seixas,Luiza McManus,Concepta |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Rodrigues,Sandra Iara Furtado Costa Stringhini,José Henrique Tanure,Candice Bergmann Peripolli,Vanessa Seixas,Luiza McManus,Concepta |
dc.subject.por.fl_str_mv |
broilers metabolizability nutritional value |
topic |
broilers metabolizability nutritional value |
description |
ABSTRACT The objective of this study was to develop an equation to determine the apparent metabolizable energy (AME) and metabolizable energy corrected for nitrogen balance (AMEn) using a physical-based classification of corn. A total of 5,055 samples were taken from bulk cargo trucks, over a five-year period. The parameters studied were the variables related to the physical characteristics of grains. The density of maize was evaluated, and AME and AMEn were calculated. The average value for AME was 3,375 kcal/kg, and two groups were formed of high quality and low quality for all samples. Stepwise regression analysis was then carried out using grain quality to estimate AME and AMEn, and the validation of the equations was carried out with 6,490 independent samples. The average value for density was 767.7 kg/m3. The multiple regressions used to estimate AME and AMEn as a function of humidity, density, and physical composition of corn kernels showed that moisture was included for AME, but not for AMEn. The equations presented high coefficients of determination (R2) for AME (0.994) and AMEn (0.987). The discriminant analyses correctly classified 98% of the high-quality samples and 96.69% of low-quality samples, so the error was smaller than the expected. The calculated equations were shown to be good at discriminating between samples of high and low quality of corn according to its physical composition, and the most important variables for separation between groups were damaged grain fraction, impurities, burnt, and soft. The correlation between calculated (independent samples) and estimated metabolizable energy and AMEn were, respectively, 0.9942 and 0.9859. The corn energy values can be estimated based on physical evaluation of the grain. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-01-01 |
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=S1516-35982018000100522 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982018000100522 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/rbz4720170153 |
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.47 2018 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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1750318152796864512 |