Development of infrared spectroscopy for assessing bacterial quality in foods

Rapid and specific detection of foodborne bacteria that can cause food spoilage or illness associated to its consumption is an increasingly important task in food industry. Bacterial detection, identification, and classification are generally performed using traditional methods based on biochemical or serological tests and the molecular methods based on DNA or RNA fingerprints. However, these methodologies are expensive, time consuming and laborious. Infrared spectroscopy is a reliable, rapid, and economic technique which could be explored as a tool for bacterial analysis in the food industry. In this thesis it was evaluated the potential of IR spectroscopy to study the bacterial quality of foods. In Chapter 2, it was developed a calibration model that successfully allowed to predict the bacterial concentration of naturally contaminated cooked ham samples kept at refrigeration temperature during 8 days. In this part, it was developed the methodology that allowed the best reproducibility of spectra from bacteria colonies with minimal sample preparation, which was used in the subsequent work. Several attempts trying different resolutions and number of scans in the IR were made. A spectral resolution of 4 cm-1, with 32 scans were the settings that allowed the best results. Subsequently, in Chapter 3, it was made an attempt to identify 22 different foodborne bacterial genera/species using IR spectroscopy coupled with multivariate analysis. The principal component analysis, used as an exploratory technique, allowed to form distinct groups, each one corresponding to a different genus, in most of the cases. Then, a hierarchical cluster analysis was performed to further analyse the group formation and the possibility of distinction between species of the same bacterial genus. It was observed that IR spectroscopy not only is suitable to the distinction of the different genera, but also to differentiate species of the same genus, with the simultaneous use of principal component analysis and cluster analysis techniques. The utilization of IR spectroscopy and multivariate statistical analysis were also investigated in Chapter 4, in order to confirm the presence of Listeria monocytogenes and Salmonella spp. isolated from contaminated foods, after growth in selective medium. This would allow to substitute the traditional biochemical and serological methods that are used to confirm these pathogens and that delay the obtainment of the results up to 2 days. The obtained results allowed the distinction of 3 different Listeria species and the distinction of Salmonella spp. from other bacteria that can be mistaken with them. Finally, in chapter 5, high pressure processing, an emerging methodology that permits to produce microbiologically safe foods and extend their shelf-life, was applied to 12 foodborne bacteria to determine their resistance and the effects of pressure in cells. A treatment of 300 MPa, during 15 minutes at room temperature was applied. Gram-negative bacteria were inactivated to undetectable levels and Gram-positive showed different resistances. Bacillus cereus and Staphylococcus aureus decreased only 2 logs and Listeria innocua decreased about 5 logs. IR spectroscopy was performed in bacterial colonies before and after HPP in order to investigate the alterations of the cellular compounds. It was found that high pressure alters bands assigned to some cellular components as proteins, lipids, oligopolysaccharides, phosphate groups from the cell wall and nucleic acids, suggesting disruption of the cell envelopes. In this work, bacterial quantification and classification, as well as assessment of cellular compounds modification with high pressure processing were successfully performed. Taking this into account, it was showed that IR spectroscopy is a very promising technique to analyse bacteria in a simple and inexpensive manner.

Assessing the effectiveness of chemical treatment with nanomaterials in improving the quality of different industrial effluents

Industrial activities are the major sources of pollution in all environments. Depending on the type of industry, various levels of organic and inorganic pollutants are being continuously discharged into the environment. Although, several kinds of physical, chemical, biological or the combination of methods have been proposed and applied to minimize the impact of industrial effluents, few have proved to be totally effective in terms of removal rates of several contaminants, toxicity reduction or amelioration of physical and chemical properties. Hence, it is imperative to develop new and innovative methodologies for industrial wastewater treatment. In this context nanotechnology arises announcing the offer of new possibilities for the treatment of wastewaters mainly based on the enhanced physical and chemical proprieties of nanomaterials (NMs), which can remarkably increase their adsorption and oxidation potential. Although applications of NMs may bring benefits, their widespread use will also contribute for their introduction into the environment and concerns have been raised about the intentional use of these materials. Further, the same properties that make NMs so appealing can also be responsible for producing ecotoxicological effects. In a first stage, with the objective of selecting NMs for the treatment of organic and inorganic effluents we first assessed the potential toxicity of nanoparticles of nickel oxide (NiO) with two different sizes (100 and 10-20 nm), titanium dioxide (TiO2, < 25 nm) and iron oxide (Fe2O3, ≈ 85x425 nm). The ecotoxicological assessment was performed with a battery of assays using aquatic organisms from different trophic levels. Since TiO2 and Fe2O3 were the NMs that presented lower risks to the aquatic systems, they were selected for the second stage of this work. Thus, the two NMs pre-selected were tested for the treatment of olive mill wastewater (OMW). They were used as catalyst in photodegradation systems (TiO2/UV, Fe2O3/UV, TiO2/H2O2/UV and Fe2O3/H2O2/UV). The treatments with TiO2 or Fe2O3 combined with H2O2 were the most efficient in ameliorating some chemical properties of the effluent. Regarding the toxicity to V. fischeri the highest reduction was recorded for the H2O2/UV system, without NMs. Afterwards a sequential treatment using photocatalytic oxidation with NMs and degradation with white-rot fungi was applied to OMW. This new approach increased the reduction of chemical oxygen demand, phenolic content and ecotoxicity to V. fischeri. However, no reduction in color and aromatic compounds was achieved after 21 days of biological treatment. The photodegradation systems were also applied to treat the kraft pulp mill and mining effluents. For the organic effluent the combination NMs and H2O2 had the best performances in reduction the chemical parameters as well in terms of toxicity reduction. However, for the mine effluent the best (TiO2/UV and Fe2O3/UV) were only able to significantly remove three metals (Zn, Al and Cd). Nonetheless the treatments were able of reducing the toxicity of the effluent. As a final stage, the toxicity of solid wastes formed during wastewater treatment with NMs was assessed with Chironomus riparius larvae, a representative species of the sediment compartment. Certain solid wastes showed the potential to negatively affect C. riparius survival and growth, depending on the type of effluent treated. This work also brings new insights to the use of NMs for the treatment of industrial wastewaters. Although some potential applications have been announced, many evaluations have to be performed before the upscaling of the chemical treatments with NMs.