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ARS Home » Southeast Area » Raleigh, North Carolina » Market Quality and Handling Research » Research » Publications at this Location » Publication #90809

Title: CONSUMER ANALYSIS OF COMMERCIAL PEANUT BUTTER

Author
item MCNEILL, KAY - NCSU
item Sanders, Timothy

Submitted to: American Peanut Research and Education Society Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 7/10/1998
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Consumer research was conducted on fifteen commercial creamy peanut butters to assess the critical product attributes for consumer acceptance. The objectives of this study were to define consumer responses in terms of acceptance and intensity of attributes and to determine the relationship between consumer language and the perceived sensory properties that drive consumer acceptance. A descriptive analysis panel screened forty-two commercially available creamy peanut butters to select fifteen representative samples for consumer panels to evaluate. Prior to the quantitative consumer research, two focus groups of 8-10 participants generated consumer terminology for the consumer test questionnaire. One hundred sixty consumers rated the peanut butters over a two-day period following a balanced incomplete block design. Consumers rated liking and intensity for 18 attributes that included appearance, flavor and texture. The consumer panel results identified four groups of products with unique flavor and texture characteristics. Through the consumer-descriptive data relationships, examined using a variety of uni- and multivariate statistical methods, attributes that affect consumer liking and the attributes that signal consumer responses of interest were identified. These attributes included roasted peanutty, salty, sweet, smooth/rough texture, and color attributes. This study identified critical consumer attributes for creamy peanut butter as part of a large study to correlate consumer acceptance language and descriptive analysis. Defining consumer liking attributes in terms of descriptive attribute intensities will allow descriptive analysis to predict consumer response.