Study of the suitability of the central composite design to predict the inactivation kinetics by pulsed electric fields (PEF) in Escherichia coli, Staphylococcus aureus and Pseudomonas fluorescens in milk

• Published in: Food and bioproducts processing 2015-07, Vol.95, p.313-322
• Main Authors: Cregenzán-Alberti, O., Halpin, R.M., Whyte, P., Lyng, J.G., Noci, F.
• Format: Article
• Language: English
• Subjects: ccRSM; Design engineering; E. coli; Electric fields; Escherichia coli; Inactivation; Mathematical models; Microorganisms; Milk; P. fluorescens; Pseudomonas fluorescens; Pulsed electric fields; S. aureus; Staphylococcus aureus
• ISSN: 0960-3085; 1744-3571
• DOI: 10.1016/j.fbp.2014.10.012

•Central composite design using response surface model was used to assess the microbial inactivation kinetics in milk.•A maximum reduction of c. 5log10 cycles was achieved for the studied bacteria.•Accurate statistical models were derived from the experimental design (R2≥0.91).•Pulsed electric field technology was reported as a suitable alternative of thermal treatment. The kinetics of inactivation of Escherichia coli K12, Staphylococcus aureus and Pseudomonas fluorescens due to pulsed electric fields (PEF) was investigated in the present study. The effects of treatment inlet temperature (20–45°C), electric field strength (EFS; 20–42.5kV/cm) and treatment time (68–170μs, as a function of the flow rate) on microbial inactivation were studied with a central composite design using a response surface model (ccRSM). Reductions of 5 and 5.2log10 cycles were achieved for E. coli and S. aureus, respectively, at 32.5°C, 40kV/cm and 89μs. Viability of P. fluorescens was reduced by 5.3log10 cycles at 32.5°C, but at slightly higher EFS (42.5kV/cm) and a longer treatment time (106μs). Statistical models describing microbial inactivation by PEF (R2≥0.91) were derived from the design. The study of the sum of square values after regression analysis showed that EFS was the factor with greatest effect on microbial inactivation. The present study confirms the suitability of using ccRSM as a tool for investigating and predicting microbial inactivation.