A Multistage Statistical Framework for Curve‐Family Model Selection

ABSTRACT Empirical models are widely used to represent families of experimental curves in chemical engineering phenomena, such as drying kinetics, thermal degradation kinetics, osmotic dehydration, and equilibrium moisture isotherms; however, the absence of coherent procedure exists for identifying the best performing models. Selection relies on the visual inspection of a small set of tabulated heterogeneous indicators, a practice especially limited in drying kinetics due to the large number of available models. An analysis of 52 studies published between 1999 and 2023 revealed persistent subjectivity in model‐selection practices and a marked underuse of available statistical tools. On the other hand, simulation‐based validation provided robust evidence of the consistency and reliability of this framework.

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Journal
Chemical Engineering & Technology
Published
2026-10-31
DOI
https://doi.org/10.1002/ceat.70335
Primary Topic
Food Drying and Modeling
Type
article
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article

A Multistage Statistical Framework for Curve‐Family Model Selection

Ignacio Ángel Angós Iturgaiz, Juan Carlos Gómez Daza, Alexis Manuel Faneite Noguera
Chemical Engineering & Technology
Food Drying and Modeling
article

A Multistage Statistical Framework for Curve‐Family Model Selection

Ignacio Ángel Angós Iturgaiz, Juan Carlos Gómez Daza, Alexis Manuel Faneite Noguera
article en

Abstract

ABSTRACT Empirical models are widely used to represent families of experimental curves in chemical engineering phenomena, such as drying kinetics, thermal degradation kinetics, osmotic dehydration, and equilibrium moisture isotherms; however, the absence of coherent procedure exists for identifying the best performing models. Selection relies on the visual inspection of a small set of tabulated heterogeneous indicators, a practice especially limited in drying kinetics due to the large number of available models. An analysis of 52 studies published between 1999 and 2023 revealed persistent subjectivity in model‐selection practices and a marked underuse of available statistical tools. On the other hand, simulation‐based validation provided robust evidence of the consistency and reliability of this framework.

Chemical Engineering & TechnologyVol. 49(11)
Universidad del Zulia (VE), Universidad Pública de Navarra (UPNA) (ES), Universidad del Valle (CO)
Openalex Percentile: Top 15%
Food Drying and Modeling
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