Modelling the effect of light penetration and matrix colour on the inactivation of Listeria innocua by pulsed light

• Light penetration and matrix colour were used to model bacterial inactivation by PL.
• Listeria innocua was more resistant in coloured media than in non-coloured ones.
• The application of 0.525 J/cm2 achieved an 8 log cfu/plate reduction on the surface.
• A 1–1.5 log cfu/plate inactivation was achieved at 3.2 mm with 15.75 J/cm2.
• Fail-safe models were developed to predict inactivation by PL.

Pulsed light (PL) is generally considered a superficial decontamination technology. This study is an attempt to assess the influence of light penetration and substrate colour in microbial inactivation by PL, with the objective of generating predictive models for food sanitation purposes. Listeria innocua was inoculated in transparent coloured and non-coloured matrices at different depths. Inactivation was assessed in agar plates and models were validated in gelatin. Inactivation was sharply reduced when bacteria were located below the surface, although a 1–1.5 log cfu/plate reduction was achieved at 3.2 mm with 15.75 J/cm2. Bacteria were more resistant in coloured media. Fail-safe polynomial models were developed, where predicted D values (fluence required to achieve 1 log10 cfu/cm2 reduction) were higher than those observed. The number of survivors showed greater variability as fluence increased. These results offer information of interest on the suitability of PL for microbial decontamination in the food industry.Industrial relevanceThis study offers information of interest on the suitability of pulsed light for microbial decontamination in the food industry. Fail-safe polynomial models – in which light penetration and matrix colour were included – have been developed to predict the inactivation of Listeria in solid transparent coloured and colourless matrices. It has also been observed that the higher the fluence applied, the smaller the number of survivors, but the greater was its variability, a parameter that should be considered in quantitative microbial risk assessment.