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Broiler responses to digestible threonine at different ages: a neural networks approach
Author(s) -
Faridi A.,
Gitoee A.,
Donato D. C. Z.,
France J.,
Sakomura N. K.
Publication year - 2016
Publication title -
journal of animal physiology and animal nutrition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.651
H-Index - 56
eISSN - 1439-0396
pISSN - 0931-2439
DOI - 10.1111/jpn.12373
Subject(s) - broiler , zoology , feed conversion ratio , feather , threonine , biology , chemistry , body weight , biochemistry , endocrinology , ecology , serine , enzyme
Summary Three experiments were conducted with broiler chickens to evaluate the effects of digestible threonine ( DT hr) and crude protein ( CP ) on their performance at three different phases of age: 1–14, 15–28 and 29–42 days. The measured traits included the following: average daily gain ( ADG ), feed intake ( FI ), feed conversion ratio ( FCR ), carcass crude protein ( CCP ), body lipid ( BL ), feather weight gain ( FWG ), protein deposited in feather ( FCP ), carcass plus feather protein ( CFCP ), carcass Thr deposition ( CDT hr) and nitrogen excretion ( NE ). A dilution technique was used to create seven diets (with eight replicates) increasing the DT hr content from 1.5 to 10 g/kg of diet for phase 1, 1.3–8.9 g/kg of diet for phase 2, and 1.2–8.2 g/kg of diet for phase 3. Data measured were imported into neural networks ( NN s) to: (i) predict the measured traits in response to DT hr and CP , (ii) rank the importance of DT hr and CP on these traits through sensitivity analysis and (iii) find the optimal levels of DT hr and CP that lead to the desired (maximum or minimum) responses. For each trait investigated, 50 different random groups of data were generated using a bootstrapping method. These 50 data groups were then used to develop 50 separate NN s which were subsequently combined to construct the final ensemble NN model. In general, accuracy of the models constructed was acceptable, although models of high ( ADG , FCR , CFCP , BL , DT hr and NE ; 0.64 ≤ R 2 ≤ 0.99) and low ( CCP , FWG and FCP ; 0.26 ≤ R 2 ≤ 0.79) accuracy were obtained. All models developed showed the greatest sensitivity to DT hr. This may be explained by the dilution technique diet preparation used in these experiments. Optimization results showed decreases in optimal values of DT hr and CP with increasing age for all traits. The highest level of DT hr was suggested for minimum BL , followed by minimum FCR , maximum ADG , maximum CFCP , minimum NE and maximum CCP respectively. Results showed that the optimal values of DT hr for minimum FCR in phases 1–3 were 8.5, 7.4 and 6.4 g/kg of diet, while these values for maximum ADG were 8.2, 7.2 and 6.4 g/kg of diet respectively.