On top of having pathogenic effects, the presence of microorganisms on the surface of food raw materials is at the origin of a major loss in agricultural production for end consumer consumption. The main current solution is the massive use of fungicides and bactericides which are directly applied on fruits and vegetables, but also on industrial food process contact surfaces or used to treat wash waters of food raw materials. However, this solution induces major environmental and toxicological issues. Thus, the search for sustainable alternative solutions or technologies has become a major concern.
The GreenDeconta project proposes to develop knowledge on the response of microorganisms (bacteria and fungi) to their exposure to certain wavelengths of the visible light (photo-oxidation) and on the cellular damages induced by such treatments. This knowledge could then be used to develop a reasoned and sustainable process for food raw material and surface decontamination from pathogenic and alteration microbiological flora. The microorganisms studied in the project will be bacteria (Escherichia coli and Bacillus cereus) and fungi (Saccharomyces cerevisiae and Penicillium digitatum). For spore-forming microorganisms, the resistance to light treatments of the vegetative form will be compared with that of spores. The GreenDeconta project is divided into 3 work packages (WP) to allow the identification of the possible application fields of such a technology. WP1 first deals with the identification of the wavelength of the visible light impacting the viability of the microorganisms but also the characterization of the cellular consequences for every wavelength. At the end of this WP, a light reactor using LED technology will be developed in order to treat samples with several wavelengths simultaneously. WP2 will then integrate the air relative humidity as a control parameter during the light treatment. This parameter could increase de decontaminating effect of the light treatments. On the one hand, a decrease in air humidity could affect microorganism physiology, and especially, their resistance to perturbations; on the other hand, a decrease in vapor content in the air, which decreases the light diffusion between the source and the samples, could improve the efficacy of the treatment. WP3 will then model the microbial inactivation for every microorganism of the project. For that, inactivation curves obtained in different conditions (liquid media and on inert or fruit surfaces) will be treated thanks to linear and non-linear models. The ideal model, i.e. presenting an optimal adjustment versus the experimental data, will be selected. These data will be of particular interest for the identification of the possible application fields of light treatments based on the combination of several wavelengths of the visible light. Finally, preliminary trials will be performed on fruits (apples and lemons) which would have beforehand been inoculated with different microorganisms.
This project will develop knowledge on the response and the resistance of microorganisms to photo-oxidation induced by visible light. In an original way, the affected cellular structures will be identified according to the wavelength used. This knowledge will allow the development of a LED reactor combining several wavelengths of the visible light. The impact of the control of air relative humidity on the efficacy of the treatment will also be characterized. The achieved results will allow the Young Researcher, who will coordinate the project, to develop a new research theme within its laboratory. These results will also be at the basis of a future development of a sustainable process for microbial decontamination.
Monsieur Sébastien Dupont (Procédés Alimentaires et Microbiologiques)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
PAM Procédés Alimentaires et Microbiologiques
Help of the ANR 161,784 euros
Beginning and duration of the scientific project: February 2019 - 24 Months