Jean Costa | Food Microbiology | Best Researcher Award

Assist Prof Dr. Jean Costa | Food Microbiology | Best Researcher Award

Assist Prof Dr. Jean Costa, University of Lleida, Spain

Assist. Prof. Dr. Jean Costa is a distinguished food engineer with a PhD in Biosciences and Agri-food Sciences from the University of Córdoba, Spain (2020). His expertise lies in predictive microbiology, food safety, and biopreservation. Currently, Dr. Costa serves as an Assistant Professor at the University of Lleida, teaching food microbiology and safety, while contributing to research on fungal spoilage and mycotoxins under climate change. He has extensive experience in microbial modeling and emerging food preservation technologies. Dr. Costa has actively managed projects on food safety and preservation strategies funded by European and private institutions. 🌾🔬📚

 

Publication profile

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Education

Dr. Jean Costa has an impressive academic background. He completed a PhD in Biosciences and Agri-food Sciences at the University of Córdoba, Spain (2015-2020), focusing on predictive microbiology, specifically microbial interactions in fishery products. His education also includes a Master’s in Food Engineering from the Federal University of Santa Catarina, Brazil, and a Degree in Food Engineering from the Pontifical Catholic University of Goiás, Brazil. Recently, he completed a Postdoctoral Fellowship (2022-2023) under a competitive grant from the Ministry of Universities, Spain, enhancing his expertise in predictive microbiology.

Research Contributions

Dr. Costa has contributed significantly to predictive microbiology. His projects on bio-protective cultures, risk quantification, and novel preservation technologies highlight his applied research. He has supervised students in food safety and microbiology, underscoring his academic leadership. Notably, his role in projects like BIOPROTECT and POSEIDON demonstrates his ability to combine science with real-world applications, particularly in prolonging shelf-life and improving the safety of food products.

Publication Top Notes

  • Modelling the interaction of the sakacin-producing Lactobacillus sakei CTC494 and Listeria monocytogenes in filleted gilthead sea bream (Sparus aurata) under modified … | Cited by: 49 | Year: 2019 🐟📊
  • Modelling the growth of Listeria monocytogenes in Mediterranean fish species from aquaculture production | Cited by: 25 | Year: 2018 🐟🌊
  • Phoretic dispersal on bumblebees by bromeliad flower mites (Mesostigmata, Melicharidae) | Cited by: 23 | Year: 2012 🐝🌸
  • Evaluation of the effect of Lactobacillus sakei strain L115 on Listeria monocytogenes at different conditions of temperature by using predictive interaction models | Cited by: 22 | Year: 2020 🌡️🦠
  • Quantifying the bioprotective effect of Lactobacillus sakei CTC494 against Listeria monocytogenes on vacuum packaged hot-smoked sea bream | Cited by: 16 | Year: 2021 🐟🚫
  • Study of the microbiological quality, prevalence of foodborne pathogens and product shelf-life of Gilthead sea bream (Sparus aurata) and sea bass (Dicentrarchus labrax) from … | Cited by: 15 | Year: 2020 🐟🧫
  • A mathematical model to predict the antilisteria bioprotective effect of Latilactobacillus sakei CTC494 in vacuum packaged cooked ham | Cited by: 11 | Year: 2022 🍖📊
  • Modeling the Growth of Six Listeria monocytogenes Strains in Smoked Salmon Pâté | Cited by: 8 | Year: 2023 🐟📈
  • Characterization of foodborne pathogens and spoilage bacteria in Mediterranean fish species and seafood products | Cited by: 8 | Year: 2016 🦠🦑
  • Predictive Modeling of the Growth of Lactobacillus viridescens under Non-isothermal Conditions | Cited by: 6 | Year: 2016 🌡️📉


Conclusion

Dr. Jean Costa’s extensive academic background, impactful research contributions, and leadership in predictive microbiology make him a strong candidate for the Best Researcher Award. His work, particularly in addressing food safety challenges under climate change and advancing preservation technologies, aligns well with the award’s criteria for scientific excellence and innovation in research.