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The rise of unhealthy lifestyles and diets among Americans is leading to an influx of health-conscious consumers on the search for more nutritious, health-promoting food options that match their taste preferences. The aim of this research is to determine consumer preferences and specific attributes of whole grain and high fiber products that drive acceptability through descriptive analysis and preference mapping on whole wheat breads and an extruded pinto bean and brown rice flour snack puff.
Commercial whole wheat breads, characterized by 26 appearance, aroma, flavor, and texture attributes, were separated into two distinct groups. The first group consisted of attributes similar to white bread: sweet, moist, and sticky. While the second group, had attributes associated with traditional wheat breads: wheaty, earthy, bitter. Consumers were clustered into three groups for clearer understanding of market segmentation. The first cluster liked all breads equally, while the second liked the breads associated with white bread attributes and the third cluster liked the classic wheat breads more. This was confirmed through partial least squares (PLS) regression, which showed if each attribute positively or negatively affected overall liking for each respective cluster.
In the second study, composite flours were extruded with varying pinto bean flour levels and feed moisture conditions to produce an acceptable puffed snack product. The
level of bean flour affected the majority of the fifteen descriptive attributes, while feed moisture only affected texture and appearance attributes. Consumers found the extruded puffs with up to 15% bean flour to be the most acceptable. Preference mapping and PLS regression showed higher overall liking scores for samples characterized by rice flavor and larger diameter and lower scores for extrudates with higher bean flavor and grittier textures.
Overall, these studies were successful in determining descriptive attributes as well as their relationship to consumer acceptability through preference mapping. These data may be helpful for future researchers when developing new whole grain and high fiber products.
Advisor: Devin J. Rose