Literature DB >> 17965324

A comparison of methods of fitting several models to nutritional response data.

D Vedenov1, G M Pesti.   

Abstract

A variety of models have been proposed to fit nutritional input-output response data. The models are typically nonlinear; therefore, fitting the models usually requires sophisticated statistical software and training to use it. An alternative tool for fitting nutritional response models was developed by using widely available and easier-to-use Microsoft Excel software. The tool, implemented as an Excel workbook (NRM.xls), allows simultaneous fitting and side-by-side comparisons of several popular models. This study compared the results produced by the tool we developed and PROC NLIN of SAS. The models compared were the broken line (ascending linear and quadratic segments), saturation kinetics, 4-parameter logistics, sigmoidal, and exponential models. The NRM.xls workbook provided results nearly identical to those of PROC NLIN. Furthermore, the workbook successfully fit several models that failed to converge in PROC NLIN. Two data sets were used as examples to compare fits by the different models. The results suggest that no particular nonlinear model is necessarily best for all nutritional response data.

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Year:  2007        PMID: 17965324     DOI: 10.2527/jas.2007-0536

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  2 in total

1.  Digestible lysine requirements of male broilers from 1 to 42 days of age reassessed.

Authors:  Henrique Scher Cemin; Sergio Luiz Vieira; Catarina Stefanello; Marcos Kipper; Liris Kindlein; Ariane Helmbrecht
Journal:  PLoS One       Date:  2017-06-21       Impact factor: 3.240

2.  Threonine Requirements in Dietary Low Crude Protein for Laying Hens under High-Temperature Environmental Climate.

Authors:  Mahmoud Mostafa Azzam; Rashed Alhotan; Abdulaziz Al-Abdullatif; Saud Al-Mufarrej; Mohammed Mabkhot; Ibrahim Abdullah Alhidary; Chuntian Zheng
Journal:  Animals (Basel)       Date:  2019-08-21       Impact factor: 2.752

  2 in total

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