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Fernando Pérez-Rodríguez

Researcher at University of Córdoba (Spain)

Publications -  143
Citations -  2495

Fernando Pérez-Rodríguez is an academic researcher from University of Córdoba (Spain). The author has contributed to research in topics: Population & Biology. The author has an hindex of 25, co-authored 129 publications receiving 1923 citations. Previous affiliations of Fernando Pérez-Rodríguez include Instituto Politécnico Nacional & University of Santiago de Compostela.

Papers
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Journal ArticleDOI

Understanding and modelling bacterial transfer to foods: a review

TL;DR: It is concluded that high levels of moisture, contact time and pressure could result in higher transfer between surfaces and the identification and elimination of certain tasks or activities involving higher levels of these factors could be helpful to prevent bacterial transfer.
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Modelling the growth boundaries of Staphylococcus aureus: Effect of temperature, pH and water activity.

TL;DR: The microbial behaviour of five enterotoxigenic strains of Staphylococcus aureus was studied in the growth/no growth domain and model predictions agreed with published data in 94% of growth cases and in 62% of no growth cases.
Book

Predictive Microbiology in Foods

TL;DR: Predictive microbiology is still growing but is turning into an important tool for improving food safety and quality because models can provide rapid responses to specific questions.
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Electrochemical disinfection: an efficient treatment to inactivate Escherichia coli O157:H7 in process wash water containing organic matter.

TL;DR: The equipment showed potential for water disinfection and organic matter reduction even without adding NaCl, and different mathematical models were assessed to account for microbial inactivation curves obtained from the electrochemical treatments.
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Growth of Escherichia coli O157:H7 and Listeria monocytogenes in packaged fresh-cut romaine mix at fluctuating temperatures during commercial transport, retail storage, and display.

TL;DR: This large-scale U.S. study-the first using commercial time/temperature profiles to assess the microbial risk of leafy greens-should be useful in filling some of the data gaps in current risk assessments for Leafy greens.