2018 AIChE Annual Meeting
(191e) Linking Metabolizable Energy to Chemical Oxygen Demand
Authors
The purpose of this study was to develop a correlation between COD and energy values in common food items. We developed a framework to convert between COD and ME in four steps. First, we gathered food items representing the three macronutrients -- carbohydrates, protein, and fat â and classified them according to their complexity: monomers, polymers, or complex ingredients. Using the carbohydrate macronutrient as an example, glucose is classified as a monomer, resistant starch as a polymer, and maple syrup as a complex ingredient. Second, we developed a chemical formula of each food item to calculate the theoretical COD. The monomers and polymers have known formulas. We calculated the complex ingredientsâ formulas from nutrient data on the USDA food database: The macronutrient composition of the food items listed in the database can be used to determine the molar ratio of carbon, hydrogen, oxygen, and nitrogen atoms to derive a molecular formula. Third, we compared the theoretical COD with the experimental COD values measured using a commercial COD measurement kit. For the complex ingredients, the measured COD was used to confirm accuracy of the developed molecular formula. Fourth, the ME of the food was calculated using the Atwater equations. The result of this framework is a value for the ME and the COD for each of the food items. This methodology was completed for representative food items. The results were used to establish a correlation between ME and COD values.
Our results show that the developed molecular formulas accurately predicted the measured COD. For example, the theoretical and measured COD of egg whites agreed within ±1%. When the COD values were compared with the energy values, the best fit was linear. We observed an R2 value calculated using the Pearson correlation of 0.992, a slope of 3.4 kcal/gCOD, and an intercept of 0.15 kcal/g. These results demonstrate that accurate conversion between ME and COD is possible for many food items. By providing a rubric for linking energy (kcal) measurements with electron equivalents (COD), we establish a framework to connect the bioenergetic interactions of humans and their microbiomes. This is an essential first step towards integrating microbial and human mathematical models and interpreting clinical results.