Título :	Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain
Autor :	Rodrigues, Sandra Iara Furtado Costa Stringhini, José Henrique Tanure, Candice Bergmann Peripolli, Vanessa Melo, Luiza de Souza Seixas Pimentel, Concepta Margaret McManus
Assunto::	Frango de corte Metabolismo Valor nutritivo
Fecha de publicación :	2018
Editorial :	Sociedade Brasileira de Zootecnia
Citación :	RODRIGUES, Sandra Iara Furtado Costa et al. Prediction of apparent metabolizable energy and metabolizable energy corrected for nitrogen of corn according to physical classification of the grain. Revista Brasileira de Zootecnia, Viçosa, v. 47, e20170153, 2018. DOI: http://dx.doi.org/10.1590/rbz4720170153. Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982018000100522&lng=en&nrm=iso. Acesso em: 24 maio 2019. Epub July 30, 2018.
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.
metadata.dc.description.unidade:	Faculdade de Agronomia e Medicina Veterinária (FAV)
Licença::	Copyright © 2018 Sociedade Brasileira de Zootecnia. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI:	https://dx.doi.org/10.1590/rbz4720170153
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