Search

Sustainable and on-going technological developments in the field of materials require the establishment of methods and tools for assessing, comparing environmental impacts and providing solutions to the problem of “resource criticality” by identifying a policy of an economic and ecological plan. Therefore, there is a clear need for prevention and provision of additional knowledge beyond the defined protocols to achieve the reduction of impacts. For this reason, Life Cycle Assessment (LCA) has been developed as a scientific technique that systematically assesses and evaluates the environmental impacts associated with all stages of a product's life. In this work, LCA was applied in a part of a highly innovative process of production of advanced Iron-Aluminum (Fe-Al) based intermetallics. LCA role is particularly crucial, since the produced intermetallics are bound to substitute stainless steel, in specific applications, providing solution in the problem of Cr and Ni; as a result, the environmental burdens and impacts, as well as application of alternative solutions to minimize them, will decide if such an innovative, from the technical point of view, approach is also applicable/sustainable in large scale.

Katiki Domokou is a traditional Greek cheese, which has received the Protected Designation of Origin recognition since 1994. Its microfloras have not been studied although its structure and composition may enable (or even favor) the survival and growth of several pathogens, including Listeria monocytogenes. The persistence of L. monocytogenes during storage at different temperatures has been the subject of many studies since temperature abuse of food products is often encountered. In the present study, five strains of L. monocytogenes were aseptically inoculated individually and as a cocktail in Katiki Domokou cheese, which was then stored at 5, 10, 15, and 20 degrees C. Pulsed-field gel electrophoresis was used to monitor strain evolution or persistence during storage at different temperatures in the case of the cocktail inoculum. The results suggested that strain survival of L. monocytogenes was temperature dependent since different strains predominated at different temperatures. Such information is of great importance in risk assessment studies, which typically consider only the presence or absence of the pathogen.

In the present work, survival of Listeria monocytogenes in the traditional Greek soft, spreadable cheese Katiki was studied throughout the shelf life of the product. Samples of finished cheese were inoculated with a cocktail of five L. monocytogenes strains (ca. 6 log CFU g(-1)) and stored at 5, 10, 15, and 20 degrees C. Acid-stress adaptation or cross-protection to the same stress was also investigated by inoculation of acid-adapted cells in the product. The results showed that pathogen survival was biphasic. Various mathematical equations (Geeraerd, Cerf, Albert-Mafart, Whiting, Zwietering, and Baranyi models) were fitted to the experimental data. A thorough statistical analysis was performed to choose the best model. The Geeraerd model was finally selected, and the results revealed no acid tolerance acquisition (no significant differences, P > 0.05, in the survival rates of the non-acid-adapted and acid-adapted cells). Secondary modeling (second-order polynomial with a(0) = 0.8453, a(1) = -0.0743, and a(2) = 0.0059) of the survival rate (of sensitive population), and other parameters that were similar at all temperatures (fraction of initial population in the major population = 99.98%, survival rate of resistant population = 0.10 day(-1), and initial population = 6.29 log CFU g(-1)), showed that survival of the pathogen was temperature dependent with bacterial cells surviving for a longer period of time at lower temperatures. Finally, the developed predictive model was successfully validated at two independent temperatures (12 and 17 degrees C). This study underlines the usefulness of predictive modeling as a tool for realistic estimation and control of L. monocytogenes risk in food products. Such data are also useful when conducting risk assessment studies.