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扬州鹅产蛋曲线数学模型分析

Analyses of mathematical models for Yangzhou geese egg-laying curves.

作者信息

Guo Binbin, Zhao Sanqin, Shao Xibing, Ding Weimin, Shi Zhendan, Tang Zhongliang

机构信息

College of Engineering, Nanjing Agricultural University, Nanjing, 210031, China.

Key Laboratory of Protected Agriculture Engineering in the Middle and Lower Yangtze Reaches, Ministry of Agriculture, Institute of Animal Science, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China.

出版信息

Anim Reprod Sci. 2019 Apr;203:10-24. doi: 10.1016/j.anireprosci.2019.02.003. Epub 2019 Feb 8.

Abstract

Mathematical models of the egg-laying curves for Yangzhou geese exposed to both natural and artificial photoperiods were established to optimise the parameters for maximising geese reproductive performance and for the development of precision feeding methods. With the natural photoperiod, egg-laying starts in autumn when daily photoperiod decreases, but accelerates after the winter solstice, and reaches the peak in spring when photoperiod increases. An accumulating model was constructed based on the hypothesis that the egg-laying capacity of geese was determined by two components of the photoperiod: photo-stimulation and photo-inhibition. In addition, a second segmented model was constructed based on the hypothesis that the photo-stimulation only occurred with lengthening photoperiods after the winter solstice, and the lesser laying rate in autumn could be attributed to the non-photo-dependent animal-husbandry technologies. This model consists of a logistic model before the winter solstice, and an accumulating model after this solstice. The use of the logistic and accumulating resulted in more precise predictions that occurred with use of Model 1 with a greater R and lesser RMSE, AIC and BIC. Likewise, the egg-laying curves when there was consideration of artificial photoperiods could also be constructed with consideration of stimulatory and inhibitory photoperiodic effects. The model consists of an initial logistic and subsequently a quadratic polynomial model. With use of this model, there is consideration of changes in egg-laying patterns when there is a fixed photoperiod, with the model parameters reflecting the effects by photoperiod control-programs and age of the geese. In conclusion, new mathematical models have been developed to best fit egg-laying curves when there are both natural and artificial photoperiods. These models can contribute to development of precision-feeding technologies for breeding geese in future.

摘要

建立了扬州鹅在自然光照和人工光照条件下的产蛋曲线数学模型,以优化参数,最大限度地提高鹅的繁殖性能,并开发精准饲养方法。在自然光照条件下,产蛋始于秋季,此时日照时间逐渐减少,但在冬至后加速,并在春季日照时间增加时达到峰值。基于鹅的产蛋能力由光照周期的两个组成部分决定的假设构建了一个累积模型:光刺激和光抑制。此外,基于冬至后光刺激仅在光照时间延长时发生,秋季产蛋率较低可归因于非光照依赖的畜牧技术这一假设构建了第二个分段模型。该模型由冬至前的逻辑模型和冬至后的累积模型组成。与模型1相比,使用逻辑模型和累积模型进行预测更精确,其R值更大,RMSE、AIC和BIC值更小。同样,考虑人工光照条件下的产蛋曲线也可以通过考虑光刺激和光抑制效应来构建。该模型由初始逻辑模型和随后的二次多项式模型组成。使用该模型时,考虑了固定光照条件下产蛋模式的变化,模型参数反映了光照控制程序和鹅龄的影响。总之,已经开发出了新的数学模型,以最佳拟合自然光照和人工光照条件下的产蛋曲线。这些模型有助于未来种鹅精准饲养技术的发展。

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