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KMID : 1011620140300020200
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Korean Journal of Food and Cookey Science
2014 Volume.30 No. 2 p.200 ~ p.211
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Sensory Properties and Drivers of Liking Sanchae namul(seasoned dish with wild edible greens)
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양정은:Yang Jeong-Eun
이지현:Lee Ji-Hyeon/김다윤:Kim Da-Yoon/최은옥:Choe Eun-Ok/정라나:Chung La-Na
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Abstract
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This study was conducted to identify the sensory characteristics of four kinds of wild vegetables (samnamul, miyeokchwi, daraesoon and bangpung namul), which were prepared through three different soaking methods: SBS (soaking both before and after boiling), BS (soaking only after boiling) and B (never soaking). Moreover, it also compared the consumer acceptance of these samples in Korea. A descriptive analysis was performed on 12 samples (Sam_SBS, Sam_BS, Sam_B, Miyeokchwi_SBS, Miyeokchwi_BS, Miyeokchwi_B, Daraesoon_SBS, Daraesoon_BS, Daraesoon_B, Bangpung_SBS, Bangpung_BS and Bangpung_B) by 10 trained panelists. Furthermore, 115 consumers evaluated the overall acceptance (OL), acceptance of appearance (APPL), odor (ODL), flavor (FLL), and texture (TXTL) of the samples using a 9-point hedonic scale; they also rated the perceived intensities of toughness, roughness and moistness using a 9-point just-about-right (JAR) scale. According to the results of the PLSR data, the Sam_SBS sample, which had significantly (p<0.05) high muddiness, moistness, brightness, redness, oily appearance, sesame oil flavor, softness and greasy attribute scores, presented the highest acceptability and consumer desire scores for consumers. On the other hand, the Miyeokchwi_B and Bangpung_B samples, which had relatively high toughness, crispiness, roughness, bitterness and, astringent attributes scores, were the least preferred samples. Therefore, the muddiness, moistness, brightness, oily appearance, sesame oil flavor, softness and greasy attributes were drivers of “liking,” whereas toughness, crispiness, roughness, bitterness, astringent attributes acted as drivers of “disliking” for consumers.
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KEYWORD
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wild edible greens, consumer acceptance test, multivariate analysis of variance (MANOVA), Partial least square-regression(PSLR), check-all-that-apply (CATA)
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