Work measurement for estimating food preparation time of a bioregenerative diet.

During space missions, such as the prospective Mars mission, crew labor time is a strictly limited resource. The diet for such a mission (based on crops grown in a bioregenerative life support system) will require astronauts to prepare their meals essentially from raw ingredients. Time spent on food processing and preparation is time lost for other purposes. Recipe design and diet planning for a space mission should therefore incorporate the time required to prepare the recipes as a critical factor. In this study, videotape analysis of an experienced chef was used to develop a database of recipe preparation time. The measurements were highly consistent among different measurement teams. Data analysis revealed a wide variation between the active times of different recipes, underscoring the need for optimization of diet planning. Potential uses of the database developed in this study are discussed and illustrated in this work.

Optimized bioregenerative space diet selection with crew choice.

Previous studies on optimization of crew diets have not accounted for choice. A diet selection model with crew choice was developed. Scenario analyses were conducted to assess the feasibility and cost of certain crew preferences, such as preferences for numerous-desserts, high-salt, and high-acceptability foods. For comparison purposes, a no-choice and a random-choice scenario were considered. The model was found to be feasible in terms of food variety and overall costs. The numerous-desserts, high-acceptability, and random-choice scenarios all resulted in feasible solutions costing between 13.2 and 17.3 kg ESM/person-day. Only the high-sodium scenario yielded an infeasible solution. This occurred when the foods highest in salt content were selected for the crew-choice portion of the diet. This infeasibility can be avoided by limiting the total sodium content in the crew-choice portion of the diet. Cost savings were found by reducing food variety in scenarios where the preference bias strongly affected nutritional content.