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Recognition of environmental contaminant and pathogenic bacteria by means of redox potential methodology.
Yakdhane, Eya; Tozsér, Dóra; Haykir, Oktay; Yakdhane, Asma; Labidi, Sabrine; Kiskó, Gabriella; Baranyai, László.
Afiliación
  • Yakdhane E; Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), Budapest 1118, Hungary.
  • Tozsér D; Department of Food Hygiene, University of Veterinary Medicine, H-1078 Budapest, István u. 2., Hungary.
  • Haykir O; Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), Budapest 1118, Hungary.
  • Yakdhane A; Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), Budapest 1118, Hungary.
  • Labidi S; Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), Budapest 1118, Hungary.
  • Kiskó G; Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), Budapest 1118, Hungary.
  • Baranyai L; Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), Budapest 1118, Hungary.
MethodsX ; 13: 102811, 2024 Dec.
Article en En | MEDLINE | ID: mdl-39022177
ABSTRACT
The time-consuming nature of culturing methods has urged the exploration of rapid modern technologies. One promising alternative utilizes redox potential, which describes the oxidative changes within complex media, indicating oxygen and nutrient consumption, as well as the production of reduced substances in the investigated biological system. Redox potential measurement can detect microbial activity within 16 h, what is significantly faster than the minimum 24 h incubation time of the reference plate counting technique. The redox potential based method can be specific with selective media, but bacterial strains have unique kinetic pattern as well. The proposed method suggests evaluation of the curve shape for the differentiation of environmental contaminant and pathogenic microbial strains. Six bacterial species were used in validation (Escherichia coli, Pseudomonas aeruginosa, Salmonella enterica, Listeria innocua, Listeria monocytogenes, and Listeria ivanovii). Descriptive parameters reached 98.2 % accuracy and Gompertz model achieved 91.6 % accuracy in classification of the selected 6 bacteria species.•Mathematical model (Gompertz function) and first order descriptive parameters are suggested to describe the specific shape of redox potential curves, while Support Vector Machine (SVM) is recommended for classification.•Due to the concentration dependent time to detection (TTD), pre-processing applies standardization according to the inflection point time.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: MethodsX Año: 2024 Tipo del documento: Article País de afiliación: Hungria Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: MethodsX Año: 2024 Tipo del documento: Article País de afiliación: Hungria Pais de publicación: Países Bajos