SATPC0042100 Tab 04 4 SOW Updated.pdf
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- Attached to
- Space Food Bayesian modeling Federal contract opportunity
- Solicitation number
- 80NSSC26939056Q
About this file
This is a Statement of Objectives (SOO) for a NASA shelf-life food testing statistical analysis project.
The project requires development of Bayesian statistical models and analysis to inform NASA's food testing strategy for long-duration space missions. NASA possesses nutrient and sensory data on 24 foods and beverages tested at three temperatures and four storage timepoints over five years, with limited data at a fourth temperature and seven-year mark, plus sensory data on nine condiments. The final food menu will contain over 200 items. The contractor must possess five mandatory competencies: Bayesian Statistics, Decision Theory, Data Science, experience with NASA nutrition testing, and food science/testing background. The foods tested span multiple categories (vegetables, fruits, fish, meat, bread, sides, mixed items) processed through various methods (retort, freeze-dried, dried, low moisture) with limited replicates and sparse nutrient testing across similar products.
The deliverables include Bayesian statistical models analyzing the existing test data and statistically-based recommendations identifying: additional foods requiring testing; required storage years and testing duration for nutrition parameters; and a detailed rationale report with statistical foundation demonstrating how the analysis extrapolates to the 200+ item final food menu. The analysis must address the risk assessment associated with extrapolating tested food results to untested foods within the expanded menu portfolio.
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Other files for this federal contract opportunity
| File | Type | Posted |
|---|---|---|
| SATPC0042100 Tab 10 RFQ Open Market.pdf |
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Text version
Proposed 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
2. 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.
The 24 foods range from vegetables, fruits, fish, meat, bread, sides, and mixed items. They are processed with different methods (retort, freeze dried, dried, low moisture). There are limited replicates. A few nutrients are tested in each food, so there are usually no similar products where we tested any one nutrient. For example, vitamin C might be tested in one freeze-dried fruit and in one powdered beverage.
Deliverables:
Bayesian Statistical Analysis / Models on the foods that have been testing
Statistically based recommendations on;
a. additional foods that need testing,
b. years of storage and testing needed such as nutrition
c. rationale/report on how this analysis extends to the two hundred foods/beverages including the statistical basis
File details come from the government source that posted it. Updated .