Sensory Characteristics and Consumer Preference for Cooked Chicken Breasts from Organic, Corn-fed, Free-range and Conventionally Reared Animals

International Journal of Poultry Science(2003)

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摘要
The sensory characteristics of cooked chicken breasts from organic (n=4), corn-fed (n=1), free range (n=5) and conventionally (n=5) reared animals from conventional origins were determined. Twelve trained assessors described the sensory characteristics of all samples using twenty-one attributes. One-way analysis of variance showed significant (P<0.05) differences between samples for all appearance, one odour, one flavour, and all texture attributes. Principal component analysis (PCA), on significan t discriminating attributes, found that three significant (P<0.05) principal components, explaining 74% of the experimental variance, described the differences in sensory character between samples. A subset of eight chicken samples was selected for consumer preference testing. One-hundred naïve consumers rated their preference for each sample using a nine-point hedonic scale. Hierarchical cluster analysis identified five segments of consumers who had different preferences demonstrating the heterogeneous nature of consumer preferences. Partial least squares regression, determined relationships between the sensory attributes and each of the five segments. Three segments of consumers, totaling 67% of all sampled consumers, preferred the sensory attributes of meat from conventionally reared animals. Consumers in these segments also liked the sensory attributes of certain organic and free-range samples. The sensory attributes of a free-range sample including "processed" odour, "cream" appearance, "firmness" and "high oral breakdown" texture were preferred by 48% of consumers. However, the sensory attributes of the organic and corn-fed chicken samples were not the most preferred of any consumer segments.
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关键词
reared animals,cooked chicken breasts,sensory characteristics,hierarchical cluster analysis,principal component analysis,analysis of variance,principal component,partial least square regression
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