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Modelling broilers' abdominal fat in response to dietary treatments.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Salarpour, A. Rahmatnejad, E. Khotanlou, H.
Description	Country affiliation: Iran Author Affiliation: Salarpour A ( Young Researchers & Elite Club, Hamedan Branch, Islamic Azad University, Hamedan, Iran.)
Abstract	Neural networks are capable of modelling any complex function and can be used in poultry production. Dietary crude fibre (CF) and exogenous enzymes (exEn) extensively affected abdominal fat (AF) of broilers. Current methods to study AF and its correlation with dietary CF levels and exEn supplements are costly, laborious and time-consuming. The purpose of this study was to develop an artificial neural network-genetic algorithm (ANN-GA) to model data on the response of broiler chickens (AF) to CF and exEn from 0 to 42 days of age. A data set containing eight treatments was divided to the train, validation, and test data set of the ANN models. The information about feeding eight diets at two periods [starter (0-21 days of age) and grower (22-42 days of age)] were used to estimate AF of broilers by ANN-GA. A multilayer feed-forward neural network with different structures was developed using matlab software, and optimal values for the ANN weights were obtained using the genetic algorithm (GA). Crude fibre, and exEn were used as input variables and AF of broilers was output variable. The best model of ANN-GA was determined based on the train root mean square error (RMSE). The best selected ANN-GA showed desirable results, RMSE, 0.1286% and R(2) coefficient, 0.876 for test data.
File Format	HTM / HTML
ISSN	09312439
Issue Number	2
Volume Number	99
e-ISSN	14390396
Journal	Journal of Animal Physiology and Animal Nutrition
Language	English
Publisher	Wiley-Blackwell
Publisher Date	2015-04-01
Publisher Place	Germany
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Discipline Physiology Discipline Veterinary Medicine Discipline Nutritional Sciences Abdominal Fat Physiology Animal Feed Analysis Chickens Diet Veterinary Algorithms Animal Nutritional Physiological Phenomena Animals Dietary Supplements Male Models, Genetic Neural Networks (computer) Journal Article Randomized Controlled Trial
Content Type	Text
Resource Type	Article
Subject	Animal Science and Zoology Food Animals

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Modelling broilers' abdominal fat in response to dietary treatments.

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