Nutrition is well outside my area of expertise although my first degree was in Agriculture in which Animal Physiology and nutrition was an important part of the course. More recently at UTas we have had several research projects the aim of which was to discover microbial sources of polyunsaturated fatty acids. Thraustochytrids were the most promising organisms and an interesting outcome was that these grew in media with no added salt without affecting PUFA production. Several studies have optimised PUFA production by varying media composition, salinity and temperature. Optimum growth rates were at 25e30 oC and continued to a minimum of 5e10 oC, similar to many other marine organisms including bacteria. That is they fit into the thermal category of psychrotropic organisms which merge with mesophiles as temperatures increase. Temperature plays a major role in the rate at which biological populations develop and potentiates the effect of other factors such as oxygen availability, salinity, hydrostatic pressure and pH. In microbiology time scales range from milliseconds for enzyme catalysed reactions to doubling times of ~7 minutes for Clostridium perfringens, to days, weeks or months for psychrophilic bacteria growing optimally, to > 3.5 billion years to reach the current level of evolutionary adaptation. The temperature dependence of biological process rates requires knowledge of microbial ecology (rate of population increase) and physiology (biochemical reaction rates and physiological control in individual cells). The integration of these disciplines into ecophysiological studies supported by omics technologies is necessary to underpin advances in understanding how to inhibit or stimulate microbial growth. At UTas we have studied the ecophysiology of food borne bacteria including pathogens and spoilage organisms for 40 years. The original aim was to produce mathematical models to predict the rate of growth or decline of populations in foods, and this continues but in the last decade we have expanded into other ecosystems. The field of Predictive Microbiology has changed the paradigm of foodmicrobiology from one of testing and retrospective reporting of results to prospective reporting based on the temperature history of a process interpreted by a predictive model. A major outcome of this work was mandating the use of the Refrigeration Index by The Australian Quarantine Inspection Service in the revised Export Control Meat and Meat Products) Order, AQIS 2005(http://www.daffa.gov.au/aqis/export/meat/elmer-3). The models developed and validated to that time were empirical and the current state of the art can be found in Corkrey et.al 2014, the abstract of which is reproduced below: “Life on Earth is capable of growing from temperatureswell below freezing to above the boiling point of water, with some organisms preferring cooler and others hotter conditions. The growth rate of each organism ultimately depends on its intracellular chemical reactions. Here we show that a thermodynamic model based on a single, rate-limiting, enzyme-catalysed reaction accurately describes population growth rates in 230 diverse strains of unicellular and multicellular organisms. Collectively these represent all three domains of life, ranging from psychrophilic to hyperthermophilic, and including the highest temperature so far observed for growth (122 C). The results provide credible estimates of thermodynamic properties of proteins and obtain, purely from organism intrinsic growth rate data, relationships betweenparameterspreviously identifiedexperimentally, thusbridgingagap between biochemistry and whole organism biology. We find that growth rates of both unicellular and multicellular life forms can be described by the same temperature dependence model. The model results provide strong support for a single highly-conserved reaction present in the last universal common ancestor (LUCA). This is remarkable in that itmeans that the growth rate dependence on temperature of unicellular and multicellular life forms that evolved over geological time spans can be explainedby the samemodel”. Progress in integrating applications in food quality, safety and security will be reported in November.