Neural networks (NN) are a relatively new option to model growth in animal production systems. One self-organizing submodel of artificial NN is the group method of data handling (GMDH)-type NN. The use of such self-organizing networks has led to successful application of the GMDH algorithm over a broad range of areas in engineering, science, and economics. The present study aimed to apply the GMDH-type NN to predict caloric efficiency (CE, g of gain/kcal of caloric intake) and feed efficiency (FE, kg of gain/kg of feed intake) in tom and hen turkeys fed diets containing different energy and amino acid levels. Involved effective input parameters in prediction of CE and FE were age, dietary ME, CP, Met, and Lys. Quantitative examination of the goodness of fit for the predictive models was made using R2 and error measurement indices commonly used to evaluate forecasting models. Statistical performance of the developed GMDH-type NN models revealed close agreement between observed and predicted values of CE and FE. In conclusion, using such powerful models can enhance our ability to predict economic traits, make precise prediction of nutrition requirements, and achieve optimal performance in poultry production.

SUM M ARYThe success of poultry meat production has been strongly related to improvements in growth and carcass yield, mainly by increasing breast proportion and reducing carcass fat. Conventional laboratory techniques for determining carcass composition are expensive, cumbersome and time consuming. These disadvantages have prompted a search for alternative methods. In this respect, the potential benefits from modelling growth are considerable. Neural networks (NNs) are a relatively new option for modelling growth in animal production systems. One self-organizing sub-model of artificial NN is the group method of data handling-type NN (GMDH-type NN). The present study aimed at applying the GMDH-type NNs to data from two studies with broilers in order to predict carcass energy (C En , MJ/g) content and relative growth (g/g of body weight) of carcass components (carcass protein, breast muscle, leg and thigh muscles, carcass fat, abdominal fat, skin fat and visceral fat). The effective input variables involved in the prediction of C En and carcass fat content using data from the first study were dietary metabolizable energy (ME, kJ/kg), crude protein (CP, g/kg of diet), fat (g/kg of diet) and crude fibre (CF, g/kg of diet). For data from the second study, the effective input variables involved in the prediction of carcass components were dietary ME (MJ/kg), CP (g/kg of diet), methionine (g/kg of diet), lysine (g/kg of diet) and body weight (kg). Quantitative examination of the goodness of fit, using R 2 and error measurement indices, for the predictive models proposed by the GMDH-type NN revealed close agreement between observed and predicted values of C En and carcass components.

2021) Effects of dietary fat source and green tea (Camelliasinensis) extract on genes associated with lipid metabolism and inflammatory responses in female broiler chickens,

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Aim of study: The aim of the present study was to introduce a sinusoidal equation into poultry science by applying it to temporal growth data from quail.Material and methods: To examine the performance of the sinusoidal equation in describing the growth patterns of quail, four conventional growth functions (Gompertz, logistic, López and Richards) were used as reference in this study. Comparison of models was carried out by analysing model behaviour when fitting the curves using nonlinear regression and assessing statistical performance. Maximum log-likelihood estimation, mean squared error, Akaike and Bayesian information criteria were used to evaluate the general goodness-of-fit of each model to the different data profiles.Main results: The selected sinusoidal equation precisely describes the growth dynamics of quail. Comparison of the growth functions in terms of the goodness-of-fit criteria revealed that the sinusoidal equation was one of the most appropriate functions to describe the age-related changes of bodyweight in quail.Research highlights: To the best of our knowledge there are no studies available on the use of sinusoidal equations to describe the evolution of growth in quail. The sinusoidal equation used in this study represents a suitable alternative to conventional growth functions to describe the growth curves for a range of strains/lines of male and female Japanese quail.