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A multi-inverse approach for a holistic understanding of applied animal science systems

Published online by Cambridge University Press:  30 April 2020

L. M. Vargas-Villamil Open the ORCID record for L. M. Vargas-Villamil [Opens in a new window] ,
L. O. Tedeschi ,
S. Medina-Peralta ,
F. Izquierdo-Reyes ,
J. Navarro-Alberto  and
R. González-Garduño
L. M. Vargas-Villamil*
Affiliation:
Department of Animal Science, Kleberg, Texas A&M University, College Station, TX7743-2471, USA
L. O. Tedeschi
Affiliation:
Department of Animal Science, Kleberg, Texas A&M University, College Station, TX7743-2471, USA
S. Medina-Peralta
Affiliation:
Facultad de Matemáticas, Universidad Autónoma de Yucatán, Anillo Periférico Norte, Tablaje Cat. 13615, Col. Chuburná Hidalgo Inn, Mérida, Yucatán97203, México
F. Izquierdo-Reyes
Affiliation:
Campus Tabasco, Colegio de Postgraduados, Apartado postal 24, Cárdenas, Tabasco86500, México
J. Navarro-Alberto
Affiliation:
Facultad de Medicina Veterinaria y Zootecnia, Universidad Autónoma de Yucatán, km 15.5 Carretera Mérida-Xmatkuil, Mérida, Yucatán, 97100, México
R. González-Garduño
Affiliation:
Unidad Regional Universitaria Sursureste, Universidad Autónoma Chapingo, Km. 7, Carretera Teapa-Vicente Guerrero, Teapa, Tabasco86800, México
*
†E-mail: luis@avanzavet.com
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Abstract

Technological and mathematical advances have provided opportunities to investigate new approaches for the holistic quantification of complex biological systems. One objective of these approaches, including the multi-inverse deterministic approach proposed in this paper, is to deepen the understanding of biological systems through the structural development of a useful, best-fitted inverse mechanistic model. The objective of the present work was to evaluate the capacity of a deterministic approach, that is, the multi-inverse approach (MIA), to yield meaningful quantitative nutritional information. To this end, a case study addressing the effect of diet composition on sheep weight was performed using data from a previous experiment on saccharina (a sugarcane byproduct), and an inverse deterministic model (named Paracoa) was developed. The MIA successfully revealed an increase in the final weight of sheep with an increase in the percentage of corn in the diet. Although the soluble fraction also increased with increasing corn percentage, the effective nonsoluble degradation increased fourfold, indicating that the increased weight gain resulted from the nonsoluble substrate. A profile likelihood analysis showed that the potential best-fitted model had identifiable parameters, and that the parameter relationships were affected by the type of data, number of parameters and model structure. It is necessary to apply the MIA to larger and/or more complex datasets to obtain a clearer understanding of its potential.

Keywords

animal nutritionevaluationnutritive evaluationruminantssheep nutrition
Type
Research Article
Information
animal , Volume 14 , Issue S2: 9th Workshop on Modelling Nutrient Digestion and Utilization in Farm Animals (MODNUT) , August 2020 , pp. s238 - s249
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of The Animal Consortium

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Footnotes

a

Present address: Campus Tabasco, Colegio de Postgraduados, Apartado postal 24, Cárdenas, Tabasco, 86500, México.

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