A Machine Learning Approach to Predict Listeria monocytogenes Growth by Integrating FSSP and PMP Simulations: A Focus on t(100) as a Possible Endpoint Parameters for Predictive Models.

Terlizzi M, Speranza B, Racioppo A, Sinigaglia M, Corbo MR, Altieri C, Bevilacqua A

Open source

DOI
10.3390/foods15203640
Published
2026 Oct 14
Container
Foods (Basel, Switzerland)
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.3390/foods15203640,
  title = {A Machine Learning Approach to Predict Listeria monocytogenes Growth by Integrating FSSP and PMP Simulations: A Focus on t(100) as a Possible Endpoint Parameters for Predictive Models.},
  author = {Terlizzi M and Speranza B and Racioppo A and Sinigaglia M and Corbo MR and Altieri C and Bevilacqua A},
  year = {2026},
  journal = {Foods (Basel, Switzerland)},
  doi = {10.3390/foods15203640},
  url = {https://doi.org/10.3390/foods15203640}
}

RIS

TY  - JOUR
TI  - A Machine Learning Approach to Predict Listeria monocytogenes Growth by Integrating FSSP and PMP Simulations: A Focus on t(100) as a Possible Endpoint Parameters for Predictive Models.
AU  - Terlizzi M
AU  - Speranza B
AU  - Racioppo A
AU  - Sinigaglia M
AU  - Corbo MR
AU  - Altieri C
AU  - Bevilacqua A
PY  - 2026
JO  - Foods (Basel, Switzerland)
DO  - 10.3390/foods15203640
UR  - https://doi.org/10.3390/foods15203640
ER  -

APA

M, T., B, S., A, R., M, S., MR, C., C, A., & A, B. (2026). A Machine Learning Approach to Predict Listeria monocytogenes Growth by Integrating FSSP and PMP Simulations: A Focus on t(100) as a Possible Endpoint Parameters for Predictive Models.. Foods (Basel, Switzerland). https://doi.org/10.3390/foods15203640

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