Multivariate Statistical Techniques: A New Approach to Identify the Commercial Properties of Mixtures of Flours of Lentinula edodes and Cocoa Pod Husk

Abstract

Lentinula edodes is known to show high nutritional and organoleptic properties and can be mixed with different by-products in the production of new foods with important functional characteristics. Cocoa pod husk (CPH) is the main by-product in the cocoa industry and presents important bioactivities. In this research, two mixtures were applied based on Lentinula edodes mushroom flour from fifty different strains (strain 1 to strain 50) and cocoa pod husk flour (CPHF): 60% Lentinula edodes mushroom flour from each strain mixed with 40% CPHF (Mixture 1), and 80% Lentinula edodes mushroom flour from each strain mixed with 20% CPHF (Mixture 2). The parameters evaluated were moisture, proteins, fat, total dietary fiber (TDF), ash, carbohydrates, antioxidant capacity, antimicrobial activity, pH and water activity (aw). The multivariate statistical techniques evaluated those samples that exhibited the highest degree of correlation with the distinct chemical and commercial parameters, showing that sample 13 of both mixture flours (M1 and M2) obtained by the mushrooms of L. edodes (strain 13) with CPH indicated the higher significant of the parameters. In addition, the sensory test of the best flour (sample 13) was applied to 50 panelists, presenting the best sensory characteristics, such as color, aroma, texture and general acceptability.