Multivariate analysis of sources of polyunsaturated fatty acids, selenium, and chromium on the productive performance of second-cycle laying hens

An experiment was conducted to evaluate the effect of the intake of a mixture of fish and sacha inchi oils (iOM), organic selenium (iSe), and organic chromium (iCr) on egg production (EP) and feed conversion ratio (FCR) of Isa Brown second-cycle laying hens (SCLH) for 16 weeks (91-106 weeks old). Egg production and FCR were evaluated using multivariate models that included conventional equations and artificial neural networks (ANN) to study multiple nutritional interactions as alternatives to univariate dose-response models. Based on the best models, iOM, iSe, and iCr levels were optimized, and a global sensitivity analysis was implemented to quantify their influence on EP and FCR. The modified logistic model was selected as the best strategy to represent EP. In the case of FCR, an ANN model with a feed-forward architecture and softmax transfer function was selected as the best alternative. One of the scenarios to simultaneously optimize EP (89.1%) and FCR (1.94 kg feed/kg egg) at 16 weeks of production was established with 3.3 g/hen·day of iOM, 0.132 mg/ hen·day of iSe, and 0.176 mg/hen·day of iCr. However, optimization considering only FCR results in much lower optimal iCr levels (between 0.083 and 0.105 mg/hen·day) with a slight decrease in EP (87.9%). The global sensitivity analysis showed that iSe is an essential factor associated with the increase in EP, and iCr is the most influential factor for the decrease in FCR. When both criteria were taken into account simultaneously from a desirability function, iSe was the most critical factor.(AU)

Multivariate modeling strategies to predict nutritional requirements of essential amino acids in semiheavy second-cycle hens

An experiment with 23 diets was performed to evaluate the effect of digestible lysine (Lys), digestible methionine + cysteine (Met+Cys), and digestible threonine (Thr) on egg production of H&N Brown second-cycle laying hens (SCLH) for 20 weeks (92-111 weeks of age) in cages under environmental conditions. Body weight (BW), feed intake (FI), feed conversion ratio (FCR), egg weight (EW), number of hen-housed eggs, and livability were also evaluated during the experiment. Diets were formulated from a central composite design that combined five levels of Lys, Met+Cys, and Thr ranging from 727 to 1159, 662 to 1055, and 552 to 882 mg/kg, respectively. Egg production (EP) data were evaluated through three different modeling strategies: egg production models, multivariate polynomial models, and artificial neural networks (ANN). A cascade-forward neural network with logsigmoid transfer function was selected as the best model according to goodness-offit statistics in both identification and validation data. One of the best scenarios for EP of H&N Brown SCLH under specific outdoor conditions was established at Lys, Met+Cys, and Thr levels of 1138, 1031, and 717 mg/hen·day, respectively. The ANN model may be an appropriate tool to study and predict EP of H&N Brown SCLH based on the combination of three different levels of essential digestible amino acids. The strategies included in this work may contribute to improving poultry performance based on modeling techniques to study other production parameters in terms of different nutritional requirements and productive conditions.