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Determination of methionine requirement for Pekin ducks: an integrated linear broken line and quadratic polynomial regression approach

文献类型： 外文期刊

作者： Yongbao Wu;Junting Cao;Jing Tang;Yiwen Yang;Shuisheng Hou;Zhiguo Wen

作者机构：

关键词： intercept of broken line and quadratic polynomial;linear broken line regression;methionine requirement;Pekin duck;quadratic polynomial regression

期刊名称： Frontiers in Animal Science

ISSN：

年卷期： 2026 年 6 卷

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收录情况： ESCI（2025版）

摘要： This study evaluated the effects of dietary methionine (Met) levels on the growth performance of Pekin ducks and estimated their Met requirements during the starter (1 to 14 days; Exp. 1) and grower (15 to 35 days; Exp. 2) phases. In Exp. 1, 288 one-day-old male ducklings were randomly assigned to six diets containing analyzed Met levels of 0.291%, 0.343%, 0.392%, 0.438%, 0.483%, and 0.521% (six replicates; eight birds each). In Exp. 2, 150 ducks at 15 days of age were allocated to five diets with analyzed Met levels of 0.271%, 0.342%, 0.421%, 0.501%, and 0.566% (six replicates; five birds each). Growth performance was recorded in both experiments, and Met requirements were estimated using linear broken-line and quadratic polynomial models. During the starter phase, increasing Met intake resulted in linear and quadratic improvements in weight gain and a linear reduction in feed/gain (F/G). For the grower phase, weight gain showed a quadratic response, with the highest gain at 0.421% Met, while F/G decreased linearly and quadratically. Estimated Met requirements for the starter phase were 0.404% (linear broken-line) and 0.532% (quadratic polynomial), and for the grower phase were 0.371% and 0.473%, respectively. Using the intercept of the two models, recommended Met levels were 0.455% for starter ducks and 0.411% for growing ducks. These integrative values likely provide more practical and economically relevant recommendations than relying on a single model, as broken-line analysis may underestimate and quadratic models may overestimate actual nutrient requirements.

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