Food composition data are needed for uncooked and cooked forms of foods. The USDA (United States Department of Agriculture) Table of Nutrient Retention Factors is the major source of nutrient retention data for US and international food composition databases. The dataset has retention factors for 16 vitamins, 8 minerals, and alcohol for approximately 290 foods. Nutrient retention factors are given for a range of cooking and preparation methods such as, but not limited to, baked, boiled, reheated, broiled, pared, and drained. Methods applied were based on food type.
Nutrient data are frequently lacking for cooked foods. The nutrient composition of a cooked food may be calculated from the uncooked food by applying nutrient retention factors. True retention is the term USDA has defined as “the measure of the proportion of the nutrient remaining in the cooked food in relation to the nutrient originally present in the raw food”. Most public and private sector databases use these retention factors to calculate nutrient values when analytical data for cooked foods are unavailable. The resulting values account for the nutrient content retained in a food after losses due to heating or other food preparation steps.
USDA’s nutrient retention factors are based on data from USDA research contracts, data reported in scientific publications, and USDA publications. Most retention factors were calculated by the True Retention Method (%TR). This method, as shown below, requires data on the weights of food before and after cooking, as well as the content of the nutrient of raw and cooked food.
%TR = (Nc*Gc) / (Nr*Gr) * 100
If weights of food before and after cooking are unavailable, the retention factor can be calculated on a moisture-free basis, the Apparent Retention Method (%AR):
%AR = [Nc (dry wt basis)] / [Nr (dry wt basis)] * 100
Nc = nutrient content per g of cooked food,
Gc = g of cooked food,
Nr = nutrient content per g of raw food, and
Gr = g of food before cooking.
By applying retention factors to ingredients in a recipe, the estimated nutrient value will be more accurate.