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首页> 外文期刊>Poultry Science >Application of adaptive neuro-fuzzy inference systems to estimate digestible critical amino acid requirements in young broiler chicks
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Application of adaptive neuro-fuzzy inference systems to estimate digestible critical amino acid requirements in young broiler chicks

机译：适应性神经模糊推理系统在年轻肉鸡雏鸡中估算消化临界氨基酸要求的应用

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This study aimed to find the digestible lysine (d.Lys), digestible sulfur amino acids (d.SAA), and digestible threonine (d.Thr) requirements to optimize body weight gain (BWG) and feed conversion ratio (FCR) via adaptive neuro-fuzzy inference systems (ANFIS) using either the Genetic algorithm (ANFIS-GA) or Particle Swarm Optimization algorithm (ANFIS-PSO) in Cobb-500 chicks from 1 to 10 d of age. The range of amino acids was 90 to 115% of the recommendations for male Cobb-500 chicks. The estimated dietary d.Lys, d.SAA, and d.Thr requirements by ANFIS-GA and ANFIS-PSO to optimize BWG were the same and were 12.10, 8.98, and 7.89 g/kg, respectively. The optimum BWG predicted by ANFIS-GA and ANFIS-PSO were 270 and 266 g, respectively for the 1 to 10 d period. The estimated dietary requirements of d.Lys, d.SAA, and d.Thr to minimize FCR at 0.995 by ANFIS-GA were 12.10, 8.98, and 7.89 g/kg, respectively. Although the estimated d.Lys and d.SAA requirements by ANFIS-PSO and ANFIS-GA were identical, the predicted d.Thr requirement by ANFIS-PSO was 0.01 g/kg higher than by ANFIS-GA to minimize FCR at 0.963. Comparison of goodness of fit in term of root mean square error revealed that the ANFIS-GA prediction was more accurate than ANFIS-PSO. This study demonstrates that the hybrid methodology of ANFIS-GA is as an effective and accurate approach to modeling and optimizing nutrient requirements.
机译：本研究旨在找到可消化的赖氨酸（D.Lys），可消化的硫氨基酸（D.SAA），可消化的苏氨酸（D.Thr）要求，以通过适应性优化体重增加（BWG）和饲料转化率（FCR） Neuro-Fuzzy推理系统（ANFIS）使用1至10d的COBB-500小鸡中的遗传算法（ANFIS-GA）或粒子群优化算法（ANFIS-PSO）。氨基酸的范围为雄性COBB-500雏鸡的建议的90至1​​15％。 ANFIS-GA和ANFIS-PSO优化BWG的估计膳食D.Lys，D.SAA和D.THR要求分别为12.10,8.98和7.89g / kg。 ANFIS-GA和ANFIS-PSO预测的最佳BWG分别为270％和266g，分别为1至10d时段。 D.Lys，D.SAA和D.TR的估计膳食要求分别通过ANFIS-GA在0.995下最小化FCR为12.10,8.98和7.89g / kg。尽管ANFIS-PSO和ANFIS-GA的估计的D.Lys和D.SAA要求是相同的，但ANFIS-PSO的预测D.Tr行为要求比ANFIS-GA更高0.01g / kg，以最小化0.963的FCR。在均方根误差期间拟合良好的比较显示，ANFIS-GA预测比ANFIS-PSO更准确。本研究表明，ANFIS-GA的混合方法是建模和优化营养需求的有效和准确的方法。

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