• Title/Summary/Keyword: partial least square-regression (PSLR)

Search Result 3, Processing Time 0.023 seconds

Sensory Properties and Consumer Acceptance of Dasik (Korean Traditional Confectioneries) (다식의 관능적 특성 및 소비자 기호도 분석)

  • Yang, Jeong-Eun;Lee, Ji-Hyeon;Choi, Soon-Ah;Chung, Lana
    • Journal of the East Asian Society of Dietary Life
    • /
    • v.22 no.6
    • /
    • pp.836-850
    • /
    • 2012
  • This study was conducted to identify the sensory characteristics of the Korean traditional confectionery, dasik, prepared under different conditions and to compare their consumer acceptance in Korea. To accomplish this, descriptive analysis of eight samples prepared using two types of rice cake powder, dasik (Rflour, Rflour_Omija), brown rice powder red ginseng dasik (Brice_Ginseng_P), pinepollen dasik (PineP), black sesame dasik (BSesame), bean dasik (Rbean), and two types of mungbean starch dasik (Starch_Omija, Starch_Greentea), was conducted by ten trained panelists. In addition, 81 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, as well as the perceived intensities of sesame flavor, sweetness, and hardness using a 9-point just-about-right (JAR) scale. Partial least square- regression (PLSR) indicated that the BSesame and Rbean samples, which had significantly (p<0.05) high roasted sesame, burnt, greasy, glossy, and cooked chestnut flavor scores, had the highest acceptability and consumer desire scores. Additionally, the PineP and Rflour_Omija samples, which had relatively high particle size, transparency, roughness, spoiled tofu, fermentation and raw rice flavor scores, were the least preferred samples. Therefore, roasted sesame, burnt, greasy, glossy, and cooked chestnut flavor attributes were considered drivers of "liking" whereas particle size, transparent, roughness, spoiled tofu, fermentation, and raw rice flavor attributes acted as drivers of "disliking" among consumers.

Sensory Properties and Drivers of Liking Sanchae namul (seasoned dish with wild edible greens) (산채나물의 관능적 특성에 근거한 소비자 기호도 유도 인자 분석)

  • Yang, Jeong Eun;Lee, Ji Hyeon;Kim, Da Yoon;Choe, Eunok;Chung, Lana
    • Korean journal of food and cookery science
    • /
    • v.30 no.2
    • /
    • pp.200-211
    • /
    • 2014
  • 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.

Comparison of Performance of Measuring Method of VIS/NIR Spectroscopic Spectrum to Predict Soluble Solids Content of 'Shingo' Pear (VIS/NIR 스펙트럼 측정모드에 따른 신고 배의 당도 예측성능 비교)

  • Suh, Sang-Ryong;Lee, Kyeong-Hwan;Yu, Seung-Hwa;Yoo, Soo-Nam;Choi, Yeong-Soo
    • Journal of Biosystems Engineering
    • /
    • v.36 no.2
    • /
    • pp.130-139
    • /
    • 2011
  • Three modes of VIS/NIR spectroscopic measurement (interactance and two modes of transmission) were compared for their ability to estimate soluble solids content (SSC) of 'Shingo' pear non-destructively. The two transmission modes are named as full- and semi-transmission, where full-transmission stands for passing of light through abdomen of pear and semi-transmission is for transit of light mainly through flesh of pear. For comparison of the modes, prediction models developed from the collected spectroscopic data by the three modes were developed and tested for comparison of their performance. Partial least square regression (PSLR) was used to develop the models and various pre-processing methods were applied to develop models of high accuracy. The experiment was repeated three times with pears produced in different regions. The experiments resulted that selection of pre-processing is very important to attain accurate models, and multiplicative scatter correction (MSC) was selected as a pre-processor of high accuracy for the three modes of spectroscopic measurement in every experiment. Except for MSC, different group of pre-processing methods were selected for the three modes of measurement in every experiment without any tendency to the tested modes of measurement and pears of different produced region. Root-mean-square error of prediction (RMSEP) of prediction models of the three modes of measurement using prepreocessor of MSC were compared for their ability to estimate SSC. The models resulted in ranges of $0.37{\sim}0.57^{\circ}Brix$, $0.65{\sim}0.72^{\circ}Brix$, $0.39{\sim}0.51^{\circ}Brix$ for interactance, full- and semi-transmission, respectively. As shown, modes of semi-transmission and interactance resulted about the same level of prediction accuracy and were noted as modes of high performance to predict SSC.