Prediction of the energy values of feedstuffs for broilers using meta-analysis and neural networks
F. C. M. Q. Mariano,C. A. Paixão,R. R. Lima,R. R. Alvarenga,P. B. Rodrigues and G. A. J. Nascimento (2013).
animal, Volume 7, Issue09, September 2013 pp 1440-1445
http://journals.cambridge.org/action/displayAbstract?aid=8962130
Several researchers have
developed prediction equations to estimate the metabolisable energy (ME)
of energetic and protein concentrate feedstuffs used in diets for
broilers. The ME is estimated by considering CP, ether extract, ash and
fibre contents. However, the results obtained using traditional
regression analysis methods have been inconsistent and new techniques
can be used to obtain better estimate of the feedstuffs’ energy value.
The objective of this paper was to implement a multilayer perceptron
network to estimate the nitrogen-corrected metabolisable energy (AMEn)
values of the energetic and protein concentrate feeds, generally used by
the poultry feed industry. The concentrate feeds were from plant
origin. The dataset contains 568 experimental results, all from Brazil.
This dataset was separated into two parts: one part with 454 data, which
was used to train, and the other one with 114 data, which was used to
evaluate the accuracy of each implemented network. The accuracy of the
models was evaluated on the basis of their values of mean squared error,
R
2, mean absolute deviation, mean absolute
percentage error and bias. The 7-5-3-1 model presented the highest
accuracy of prediction. It was developed an Excel® AMEn
calculator by using the best model, which provides a rapid and efficient
way to predict the AMEn values of concentrate feedstuffs for broilers.
animal, Volume 7, Issue09, September 2013 pp 1440-1445
http://journals.cambridge.org/action/displayAbstract?aid=8962130
