Mostrar el registro sencillo del recurso

dc.contributorLUIS O. TEDESCHI
dc.coverage.spatialGeneración de conocimiento
dc.creatorJORGE AUGUSTO NAVARRO ALBERTO
dc.creatorLUIS MANUEL VARGAS VILLAMIL
dc.creatorSALVADOR MEDINA PERALTA
dc.creatorFRANCISCO IZQUIERDO REYES
dc.creatorROBERTO GONZALEZ GARDUÑO
dc.date2020-04-30
dc.date.accessioned2021-06-22T17:38:16Z
dc.date.available2021-06-22T17:38:16Z
dc.identifierhttps://doi.org/10.1017/S1751731120000877
dc.identifier.urihttp://redi.uady.mx:8080/handle/123456789/5014
dc.description.abstractTechnological 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.
dc.languageeng
dc.publisherAnimal
dc.relationcitation:0
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.sourceurn:issn:1751-7311
dc.subjectinfo:eu-repo/classification/cti/2
dc.subjectBIOLOGÍA Y QUÍMICA
dc.subjectinfo:eu-repo/classification/cti/3
dc.subjectMEDICINA Y CIENCIAS DE LA SALUD
dc.subjectAnimal nutrition
dc.subjectEvaluation
dc.subjectNutritive evaluation
dc.subjectRuminants
dc.subjectSheep nutrition
dc.titleA multi-inverse approach for a holistic understanding of applied animal science systems
dc.typeinfo:eu-repo/semantics/article


Archivos en el recurso

Thumbnail

Este recurso aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del recurso