NOTE: Element change to Human Health Countermeasures; previously Space Human Factors & Habitability (Ed., 1/18/17)

At the conclusion of the 2-year storage lifetime, vitamin B1 was generally most stable in thermally processed brown rice, less so in split pea soup, and drastically less in BBQ beef brisket, based on NASA’s formulation. Although degradation of B1 was slowest and less influenced by temperature in the thermally processed rice, B1 was more abundant in the split pea soup product at the end of the 2-year storage period at any temperature tested, compared to the more stable brown rice product. B1 in BBQ beef brisket was undetectable at the end of the storage period at 37°C storage and approaching an undetectable limit for the two other storage temperatures.

The process of freeze-drying these foods resulted in unique differences of vitamin B1 stability compared to the non-freeze-dried versions. Freeze-dried brown rice demonstrated better resistance to vitamin B1 degradation at higher temperatures, but a diminished protective effect in refrigeration conditions, comparing the final vitamin B1 concentrations between thermally processed and freeze-dried brown rice. This same trend (of decreased temperature dependence on degradation rate) was observed in the split pea soup, but not in the BBQ beef brisket, where differences in food matrix composition and chemistry are though to play a role on vitamin B1 degradation differentially.

Vitamin B1 was also quantified in brown rice, split pea soup, and BBQ beef brisket that were either thermally processed or freeze-dried, and then stored at either -20°C or -80°C for 2 years as a quality control measure.

For vitamin C, freeze-drying preserved the vitamin better throughout all foods under all temperatures except 37°C. The degradation rate was the most noticeable difference because in many cases freeze-drying caused the food to approach a zero residual concentration quicker than the thermally processed foods. However, the freeze-drying concentration started with a higher vitamin C amount. As long as the vitamin C was detectable or had a nonzero concentration, freeze-drying still had more vitamin C than the thermally processed foods. This finding stressed how the initial concentration and an elevated storage temperature can influence vitamin C degradation. Sugar snap peas had many bewildering findings for the thermally processed and freeze-dried foods. Specifically for thermally processed sugar snap peas, the vitamin concentration considerably declined for all temperatures and was undetectable for all temperatures before the end of the two-year storage study. The stability was better during freeze-drying, but a sharp drop occurred at 12 mo for 20°C freeze-dried sugar snap peas, which seemed valid considering the remaining time points stabilize near that concentration. The cause of the dropped has yet to be determined, and we assume there had to be some form of phenomenon that increased vitamin C dissolved oxygen leading to a more rapid degradation.

All the acidic foods, all rhubarb applesauce foods and strawberries had higher stability during thermal processing and freeze-drying, especially freeze drying where 4 and 20°C had negligible degradation during the two-year storage study. However, rhubarb applesauce at pH4 experienced a more rapid degradation rate due to the increased pH level. There was a similar trend with rhubarb applesauce at pH3, except reduced degradation rate, due to the lower pH level.

Testing four previously established models (generated from vitamin content measures made following 37°C and 20°C storage for 3, 6, 9, or 12 months and 4°C storage for 4, 8, and 12 months) by comparing experimentally measured vitamin content and the model-predicted values at each relevant time point, <10% prediction error was observed at 2 years using data from 9 and 12 months of storage for vitamin B1 in the majority of food products. In two cases, <15% error was observed at the conclusion of storage. For vitamin C, models developed using data of low acid foods produced the lowest % error in predicting final vitamin C content. High acid foods were observed developing an emerging resistance to degradation late into the storage lifetime which caused divergence between original models and the experimental trend. By adding a factor into our models, representing significant non-zero asymptotic behavior, vitamin C predictive models improved significantly. Following inclusion of this factor, vitamin C predictive models were within 10% of the experimental trend at 2 years of storage.

Food products were also differentially thermally processed and measured for their vitamin content. The time-temperature profiles from each thermal process (conducted in triplicate and probed in quadruplicate) were recorded and used together with the resulting vitamin concentration to produce predictive models based on a non-isothermal version of the Endpoints Method used above. For vitamin B1 modelling, <5% error was observed across the board. After analyzing vitamin C concentration before and after thermal processing and thereby determining the kinetic degradation parameters of each food, our model demonstrated less than 9% residual average difference between experimental and predicted concentration values showing a 2.7% difference for rhubarb applesauce and a 7.8% difference for sugar snap peas.

In conclusion, we were able to quantify vitamin B1 and C in several NASA formulations prior to and following thermal processing, as well as prior to and during long-term storage for foods which were thermally stabilized or freeze-dried. The benefit from freeze-drying was assessed, and revealed differences based on the food matrix. We successfully produced predictive models that were able to generate predictions of vitamins B1 and C content at 2 years, generated from data gathered during the first year of the storage lifetime of all foods. Modelling vitamin B1 loss during thermal processing by the non-isothermal version of the Endpoints Method provided estimations within 5% error, lending promising results for the utilization of this model in food processing environments for the development of optimal thermal processes as well as estimating nutritional destruction by such processes without cumbersome analysis. Vitamin C degradation in foods during thermal processing was also highly modellable, producing estimations with <5% error in rhubarb applesauce, <10% error in sugar snap peas, and 12% error or less in strawberries.

NOTE: Element change to Human Health Countermeasures; previously Space Human Factors & Habitability (Ed., 1/18/17)

We sought to obtain all necessary ingredients to produce large quantities of food that could then be made shelf-stable for long periods of time, if not indefinitely, by thermal stabilization (destruction of spoilage organisms by heat) and by freeze drying (inactivation of spoilage organisms by low water activity). These foods would be stored in varying temperature conditions so that when the vitamin content is measured, we would be able to understand the effect of temperature on the rate at which our target vitamins degrade. This effect would be discerned using a mathematical model which would then be used to make accurate predictions about the vitamin content in that food at times and temperatures not yet determined. Through this process we can also gain insight into the effect of food matrix properties and water activity on the degradation of vitamins. We also studied the nature of vitamin degradation during thermal stabilization, by recording the temperature of the process, measuring the vitamin content at the end of the process, and using a model that can accept this type of data to determine the degradation behavior.

Currently, we are near the end of our 2 year storage study. All vitamin C and B1 analysis to date has been performed and vitamin retention has been reported. Time-grouped modelling has been conducted using data from 37°C and 20°C stored samples at 3, 6, 9, or 12 months with 4°C stored samples at 4, 8, and 12 months to reveal the parameters that describe the degradation behavior of the vitamins of interest. We collected a plethora of kinetic parameters, which are “kTref”,” the degradation rate constant, and “c,” temperature sensitivity term. These parameters are the degradation rate constant “kTref” and temperature sensitivity term “c.” These terms were used to build a model of the vitamin’s retention over time for up to 2 years of storage.

Overall, the thiamine (vitamin B1) stability in the brown rice (BR) and pea soup (PS) product seemed high, while in the beef brisket (BB) the vitamin seemed less stable, even at low storage temperatures. Also, the original vitamin content in the brown rice and pea soup recipes were very similar. Throughout analysis, beef brisket was noted to have a drastic range of texture and compositional variation, possibly due to heterogeneous fat deposition and muscle density. Storage at 37°C for 18 months has demonstrated drastically accelerated vitamin degradation across all foods, leading to the elimination of detectable thiamine in beef brisket.

For ascorbic acid (vitamin C), there has been a consistent degradation in all foods; however, not all time points decrease in vitamin content. Most noticeable at 4°C in strawberries (ST) and at 20°C in rhubarb applause at pH 3 (RApH3). When standard deviation is taken into consideration, it is prevalent that the degradation is low among those timepoints. Another noticeable phenomenon is sugar snap peas (SP) rapid degradation for 4, 20, and 37°C. Both 20 and 37°C SP vitamin C content was undetectable at 15 mo and undetectable at 20 mo for 4°C. The food matrix complexity and higher pH most likely led to the rapid degradation. It is also important to note that the limit of detection was limited due to the lack of separation at lower concentration in sugar snap peas. Most likely, small residual amounts of vitamin C could be remaining, but are not detectable using the current method and prior vitamin C analysis conditions for SP.

Additionally, all vitamin analysis to date has been performed and vitamin retention has been reported for freeze dry foods. We are in the process of analyzing vitamin content for 18 months. It is evident that the lower water content had a significant role on improving vitamin C stability for all temperatures. With vitamin C foods, 37°C was much more rapid during freeze drying compared to retort thermoprocessing. For both food processes, modelling was utilized and a variety of predictive curves were constructed using different experimental timepoints kTref and c values.

The project remains a success, as processing, analysis, and modelling proved not only possible but sufficient to make determinations about vitamins B1 and C’s degradation behaviors. We are able to use model information from 3 to 12 months of storage to learn and anticipate how certain sets of data influence the model itself. As shown above, the model produces the smallest error, and therefore most accurate predictions, when the data being used is slightly delayed (after 3 or 4 months). However, these models from 3 and 4 month data tend to over-predict the degradation while the others are more forgiving or under-predict the vitamin degradation. For the purposes of staying ahead of the risk of malnutrition for the crew, this should be taken into consideration.

Freeze drying provided interesting results. The improvement to thiamine’s degradation after drying is not universal and does not abide by an obvious temperature dependency, although it does appear that the lower temperature storage has a stronger or nearly neutral impact on vitamin preservation. Interestingly, the freeze-dried versions of the vitamin B1 foods demonstrated lower vitamin B1 stability at the highest temperature tested compared to wet versions. This was also showcased in vitamin C foods too. With vitamin C, predictive curves fitted 4 and 37°C storage temperatures the best for all the foods with a few good fits at 20°C. Theoretically, the model is most reliable with multiple pair endpoints to generate multiple kTref and c values. Collectively, the average will give a better grasp of the kTref and c kinetic parameters compared to one kTref and c value. To improve model fit at room temperature, we believe collecting endpoints only at 20°C and changing timepoints could significantly improve the fit, although predictions for non-room temperature storage conditions would be less reliable. This is also applicable for retort thermoprocessing and vitamin B1.

Overall, much more vitamin retention data has been gathered and processed into separate, time-distinct, predictive models for use by NASA. The degradation parameters used to produce each model have been revealed for all foods. Based on raw content reports, the nutritional content can be assessed for thermoprocessed vitamin B1 foods for up to 18 months and for up to 21 months for vitamin C foods. Freeze-dried vitamin B1 foods can be assessed at 15 months and vitamin C foods can be assessed at 16 months.

In conclusion, we plan to continue our analyses to find the set of data for building the most effective and accurate model for making future predictions or interpolating to predict vitamin content if storage temperature is changed. At this point, analysis has been optimized and streamlined for all of our foods, wet or freeze dried. We also have a few publications pending on isothermal degradation and modelling of vitamin B1 and C. The literature review for vitamin C has been officially published in the Critical Reviews in Food Science and Nutrition called “Modeling the degradation kinetics of ascorbic acid.” [See 2017 Task Book Bibliography or Cumulative Bibliography link]

NOTE: Element change to Human Health Countermeasures; previously Space Human Factors & Habitability (Ed., 1/18/17)

We sought to obtain all necessary ingredients to produce large quantities of food that could then be made shelf-stable for long periods of time, if not indefinitely, by thermal stabilization (destruction of spoilage organisms by heat) and by freeze drying (inactivation of spoilage organisms by low water activity). These foods would be stored in varying temperature conditions so that when the vitamin content is measured, we would be able to understand the effect of temperature on the rate at which our target vitamins degrade. This effect would be discerned using a mathematical model which would then be used to make accurate predictions about the vitamin content in that food at times and temperatures not yet determined. Through this process we can also gain insight into the effect of food matrix properties and water activity on the degradation of vitamins. We also studied the nature of vitamin degradation during thermal stabilization, by recording the temperature of the process, measuring the vitamin content at the end of the process, and using a model that can accept this type of data to determine the degradation behavior.

We are currently approaching the first year of progress in relation to having processed, stored, analyzed, and modeled foods containing our vitamins of interest. At this same time last year, brown rice, split pea soup, BBQ beef brisket, rhubarb applesauce (varying in natural pH ± 0.5), strawberries, and sugar snap pea were produced to specifications according to their NASA recipe. In total, more than 3,000 pouches of food were made, entered into a tracking database, and stored. More than 100 lbs of brown rice, nearly 200 lbs of split pea soup, around 200 lbs of beef brisket, 130 lbs of strawberries, 400 lbs of rhubarb applesauce, and more than 100 lbs of sugar snap peas were produced and either thermally stabilized in retort according to their respective recipes or prepared for freeze drying in order to assess the degradation of their respective vitamin of interest. We have maintained stored wet and freeze-dried samples for nearly a year, performing regular analysis on stored samples for use in modeling. Explanation of the specific storage conditions, analysis, and modeling process is below.

All vitamin analysis to date has been performed and vitamin retention has been calculated for both vitamin B1 and C. Preliminary modeling has been conducted using data from 37°C and 20°C stored food samples at 3 months of storage and 4°C stored samples at 4 months to reveal the parameters that the model utilizes to describe the degradation behavior of the vitamins of interest. These parameters were successfully used to build a model of the vitamin’s retention over time, allowing for predictions of vitamin retention at time points already measured, to gauge accuracy of the model, as well as time points in the future, to be made. To demonstrate the strength of the model during interpolation, data from 37°C stored samples at 3 months and 4°C stored samples at 4 months was used to formulate a model that would then predict the vitamin content of 20°C stored samples at 3 and 6 months. This proved successful in producing a low degree of error between the predicted vitamin retention values and the real values that were measured.

The project remains a success, as processing, analysis, and modeling proved not only possible but sufficient to make some early conclusions. We are able to use model information to learn and anticipate how certain parameters influence the model’s predictions. We will soon be able to see, once data begins to come in for the end of the year, which isothermal model construction produces the most accurate portrayal of degradation throughout the food’s lifetime. As mentioned above, the model produces the smallest error, and therefore most accurate predictions, when it is being used to interpolate temperature and time points.

In terms of freeze-dried foods, all vitamin analysis to date has been performed and vitamin retention has been reported as well. We are in the process of analyzing vitamin content for 4 months for foods where vitamin B1 is of interest (therefore modeling is not yet available) but is complete in vitamin C foods. Regardless, vitamin retention was plotted against thermal processed retentions so that vitamin retention improvement due to drying, if any, could be assessed. The exact effect of drying on vitamin degradation at this point does not seem to conform to a specific paradigm. There needs to be more points to analyze to better understand this phenomenon. In vitamin C foods, there are enough data to determine initial degradation parameters via modeling, but not enough data time points to compare predictions with experimental values.

Freeze drying, at this stage, provided interesting results. The improvement to thiamine’s degradation after drying was not immediately evident, and will require more analysis points before the true effect can be discerned. It is possible that the process of freezing, drying, and repackaging led to some portion of the results observed by destruction or conversion of the compound. Data at 4°C for 4 months and beyond are expected to be gathered soon, wherein modeling can then be performed and the degradation parameters can be gathered. This will allow us to directly compare these parameters between wet and dried products’ thiamine degradation.

An additional experiment was conducted to study the effects of thermal processing conditions on vitamin degradation. We utilized a related method to our isothermal degradation parameters model that we can utilize varying temperature data (as opposed to a static storage temperature) to find kinetic parameters, which we can gather from our retort vessel. Our strategy was to produce three distinct temperature processes for each NASA recipe (low temperature-long time, moderate temperature-moderate time, and high temperature-short time), record the time and temperature data throughout the process, and conduct analysis on the vitamin content after processing, as the model still only requires vitamin concentration at the end of the process. Then, two of the three temperature profiles are entered into the model in order to produce values describing the vitamin degradation. These values are then maintained while one of the two temperature profiles are changed out with the third. The resulting degradation prediction is compared to the real value. We demonstrated that this method of constructing this model produces predictions with less error on average than the static storage model, with even less data.

Although at the outset, it would seem that building a model that is able to reveal the kinetic parameters of degradation during a non-isothermal process with only two data points would be quite difficult, it actually provided a clearer picture of the degradation in processing compared to the degradation in storage. The error in this model was typically lower than that of the stored recipes, which is a promising result. However, the results need to be repeated with a replicate experiment, which will be conducted soon. Care will be taken to procure the same exact recipe as in the first case.

We have also worked on two new publications which can offer insights on where to take this project in the future, specifically about accounting for the total vitamin C content as opposed to merely ascorbic acid:

[1] Peleg, M., Normand, M. D., Dixon, W. R. and Goulette, T. R. 2017. Modeling the degradation kinetics of ascorbic acid. Critical Reviews in Food Science and Nutrition. (In press – available on line)

[2] Peleg, M., Normand, M. D. and Corradini, M. G. 2017. A new look at kinetics in relation to food storage. Annual Reviews in Food Science and Technology 8:135-153.

Overall, the progress of the project has been good. Constant pull dates for analysis can prove demanding at times, but possible. However, we did choose to maintain reporting “time” in terms of days rather than months, in order to allow more granularity in modeling if a day or two passes before analysis is able to be done (although this has not yet occurred). There is still much more data to collect and process, which will shed light on the rest of the modeling that needs to be done.

1. Development of modern method based on AOAC (association of analytical communities) Official Method 942.23 for vitamin B1 (Thiamine); 2. Utilization of AOAC Official Method 2012.21 for Vitamin C (Ascorbic Acid) using HPLC (high performance liquid chromatography) detection; 3. “Prediction of Isothermal Degradation by the Endpoints Method” to determine the kinetic parameters of vitamin B1 and C.

Results/Accomplishments

1. We have continued to modernize and optimize methods for sample preparation and bulk data collection, increased reproducibility and precision for thiamine detection and quantification.

• Compared to AOAC Official Method 942.2, column purification was updated to current equipment standard (Kimble Kontes FlexColumn) and current resin equivalent (Amberlite CG-50 Type I, H-form) to resin described in method. New resin and equipment demonstrated routine efficiency of >95% across tests after optimization (repeat sample addition step and repeat elution steps).

• Compared to AOAC Official Method 942.2, enzyme solution calibrated to minimize waste and still provide complete phosphorylysis of phosphate-bound thiamine in meat products. Method called for a 5% solution but was deemed more than sufficient by current research (Ndaw S. et al., 2000) and by independent testing.

• Compared to AOAC Official Method 942.2, oxidized thiamine (thiochrome) is resuspended in 4 mL isobutanol, rather than the depicted 13 mL. This is done to compensate for the change in equipment from a cuvette-style fluorescence detector to a 96-well plate reader which is more sensitive and offers higher statistical significance determination of data. The equation to calculate original concentration of thiamine still applies.

2. We have optimized the extraction efficiency, HPLC sensitivity, and ensured reproducibility for vitamin C before and after retort processing.

• Compared to AOAC Official Method 2012.12, stabilizers, TCEP hydrochloride and EDTA, were premixed prior to vitamin C extraction blend to enhance dehydroascorbic acid (DHAA) reduction effectiveness along with improving ascorbic acid (AA) stability.

o Both are key components to avoid degradation during HPLC analysis

• Preliminary standard data and processing data for vitamin C before and after retort processing.

3. We have successfully determined optimal retort time for our food matrices addressing high acid and low acid foods

• This information is essential for minimizing vitamin lost during processing to start off with a higher vitamin concentration during storage

• Reference https://www.dairyscience.info/lethalcomp.aspx for calculating Fo for low acid foods

4. We optimized our freeze drying protocol for all food matrices to ensure samples are sufficiently dried 5. We have obtained a source for all ingredients to produce in bulk quantities

• Source bulk of ingredients from Springfield Performance Food Group

• Source Strawberries Light in Syrup from Food Service Direct

• Smaller quantity size ingredients will be sourced from local grocery stores

6. We purchased all equipment/supplies needed to make recipes in bulk quantities

• Purchased a convection oven for beef brisket; • Purchased a deli slicer for beef brisket; • Many other equipment/supplies to optimize tasks (e.g., hole puncher, retort pouch holder, lids)

7. We also streamlined each recipe to be able to prepare and retort all samples in one day for each recipe

8. Development and validation of computational model for simulating vitamin degradation in spaceflight foods.

• Isothermal thiamine degradation

The literature indicates that thiamine degradation at storage and accelerated storage temperatures follows first order kinetics. This enabled simplification of our endpoint method to estimate the kinetic parameters from isothermal data. To do the calculations we wrote an interactive Wolfram Demonstration, which is freely downloadable from the Internet (open http://demonstrations.wolfram.com/PredictionOfIsothermalDegradationByTheEndpointsMethod/ ). This program enables fast estimation of the parameters by manually matching generated degradation curves with two experimental end-concentrations and using them to predict the degradation curves at temperatures not used in the parameters calculation.

The method and program were tested and validated with literature data on thiamine and the results published (See Bibliography below -- Food Research International, 79 (2016), 73-80).

• The successive points method. It has been shown that, at least theoretically, one can extract the parameters of a degradation reaction that follows fixed-order kinetics from two successive concentration ratios determined during non-isothermal storage. The calculation procedure is similar to that of the endpoints method except that a single curve ought to be passed through the two points instead of two – open the interactive freely downloadable Wolfram Demonstration http://demonstrations.wolfram.com/DegradationParametersFromConcentrationRatios/ . The method has been tested with computer simulations and with published data on the non-isothermal degradation of vitamin A, see Bibliography below--Food Research International, 75 (2015), 174-181.

• Vitamin C degradation. Examination of the literatures on ascorbic acid degradation revealed that several reported data do not follow the assumed first order kinetics. In some publications this was most probably due to experimental errors. A typical example is that the increasing divergence of the reported degradation curves at different temperatures, which is expected from the Arrhenius equation (or exponential model), was not observed. One report showed that the ascorbic acid’s degradation only starts as an exponential decay, which followed first or approximately first order kinetics. Later the decay decelerated and appeared to approach what an asymptotic concentration. This might have been due to the oxygen disappearance, a factor that has not been always adequately monitored let alone or controlled. The problem was less severe in two frozen vegetables (which is consistent with the above suggested explanation). We have written a version of the isothermal endpoints method for frozen foods and intend to make it available as an addition to the already posted Wolfram Demonstration or as a new Demonstration. We will also attempt to modify the degradation model to account for residual concentration of the vitamin. Either way, control or knowledge of the oxygen tension during processing and storage will be essential for the development of a predictive kinetic degradation model.

• Storage criteria. It has been a common practice to determine a food or pharmaceutical product’s shelf life as the time at which the marker’s concentration or concentration ratio falls below (or surpasses) a critical concentration. In accelerated storage this time is shortened by the elevated temperature, which shortens the time to reach the set threshold. The question that arises is what happens when there are two markers instead of one, e.g., two vitamins in the same food that follow different degradation kinetics. Computer simulations show that, theoretically, the order in which two different markers cross their corresponding threshold concentrations (in either direction) can but need not always be reversed at different temperatures. In other words, at least in principle, it is possible that the results of accelerated storage experiments will not predict correctly the end of a product’s shelf life if determined by a more than a single criterion. The simulation program was posted on the Internet as a freely downloadable interactive Wolfram Demonstration open: ( http://demonstrations.wolfram.com/DeterminingShelfLifeByTwoCriteria/ ). A detailed discussion of the issue has been published--see Bibliography -- Food Research International, 78 (2015), 388-395. At least theoretically, the same order reversal can happen when there are more than two criteria – open the new Wolfram Demonstration http://demonstrations.wolfram.com/ThermalDegradationOfThreeNutrientsInFoods/ .

Reference

Ndaw, S.; Bergaentzlé, M.; Aoudé-Werner, D.; Hasselmann, C. Extraction procedures for the liquid chromatographic determination of thiamin, riboflavin and vitamin B6 in foodstuffs. Food Chemistry 2000 Vol. 71 No. 1 pp. 129-138.

2. Specific Aims & Approaches: Aim 1. Determine the degradation kinetics of vitamins B1 and K in spaceflight foods. The representative spaceflight foods will be produced and stored under appropriate conditions for 2 years, and the degradation kinetics of vitamins B1 and K will be systematically determined. Aim 2. Develop robust computational models to predict degradation of vitamins B1 and K in spaceflight foods. Mathematical models will be developed to simulate and predict the degradation of vitamins B1 and K in spaceflight foods, and their robustness will be assessed and validated. The results will be analyzed based on the nature of different spaceflight foods to develop guiding principles on how to minimize vitamin degradation in spaceflight foods.

2. Specific Aims & Approaches: Aim 1. Determine the degradation kinetics of vitamins B1 and K in spaceflight foods. The representative spaceflight foods will be produced and stored under appropriate conditions for 2 years, and the degradation kinetics of vitamins B1 and K will be systematically determined. Aim 2. Develop robust computational models to predict degradation of vitamins B1 and K in spaceflight foods. Mathematical models will be developed to simulate and predict the degradation of vitamins B1 and K in spaceflight foods, and their robustness will be assessed and validated. The results will be analyzed based on the nature of different spaceflight foods to develop guiding principles on how to minimize vitamin degradation in spaceflight foods.

3. Rationale, Novelty, & Significance: A considerable amount of research has been conducted on the stability of essential vitamins including vitamins B1 and K in different food systems. However, a detailed understanding is lacking on the degradation of essential vitamins under the unique conditions experienced by spaceflight foods. The significance of the proposed research is that it will provide fundamental knowledge that is currently lacking about the role of food processing, food matrix characteristics, and storage conditions on the degradation kinetics of vitamins B1 and K in spaceflight foods. A particularly innovative aspect of the project is that it utilizes robust mathematical modeling to simulate and predict degradation kinetics of essential vitamins, and also to help develop guiding principles to stabilize these vitamins in spaceflight foods. Successful completion of this project will provide critical information that can be used to produce more nutritious shelf-stable spaceflight foods to better maintain health & wellness of spaceflight crew.