Space Food Bayesian Modeling RFP

Description: Project informs a shelf-life food testing strategy and provides assessment on the risk assumed by extrapolating the results of the tested foods to untested foods. This statistical analysis may justify expanding testing to more of the food system, as needed. Mandatory Expertise: 1.Bayesian Statistics Decision Theory 3. Data Science 4. Experience with NASA nutrition testing 5. Food science /testing background Nasa has nutrient data and sensory data on 24 foods/beverages and sensory data on 9 condiments at 3 temperatures and 4 storage length timepoints over 5 years, with very limited data on a few foods at a 4th temperature and at 7 years. With plans for over 200 foods/beverages on the final menu, a statistical assessment based on the data and the foods that need to be tested to have statistical confidence in making extrapolated predictions for the food menu.