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ENReT: An open-source R-based tool for non-linear modelling specifically implemented for Food Science and Technology applications

Riccardo De Flaviis, Giampiero Sacchetti

Research Square | Nov 3, 2026

Abstract

Abstract Food scientists often use nonlinear regression as a common statistical analysis within all those projects whose ultimate goal is to improve food quality. These models have been developed for a wide variety of chemical, microbiological, physical, and biochemical phenomena that occur in food. Fitting these models is not always easy due to a series of theoretical, technical, and usability limitations that can affect researchers. ENReT was created to facilitate this type of analysis and is intended to be used by everyone from university students to researchers or professionals in the field of food science and technology, but not only. The main objective was to obtain an easy-to-use tool without sacrificing statistical formalism and advanced methodologies. This work explains all the reasons why ENReT was created and its possible applications.

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Authors

Researchers on this paper

Riccardo De Flaviis

first | University of Teramo | ORCID 0000-0002-6054-3133

Giampiero Sacchetti

last | University of Teramo | ORCID 0000-0002-2494-3658

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Latest Data Analysis with R research Latest Spectroscopy and Chemometric Analyses research Latest Advanced Statistical Methods and Models research

Citation

BibTeX

@article{Flaviis2026ENReT,
  title = {ENReT: An open-source R-based tool for non-linear modelling specifically implemented for Food Science and Technology applications},
  author = {Riccardo De Flaviis and Giampiero Sacchetti},
  journal = {Research Square},
  year = {2026},
  doi = {10.21203/rs.3.rs-11577802/v1},
  url = {https://doi.org/10.21203/rs.3.rs-11577802/v1}
}

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