首页    期刊浏览 2024年10月06日 星期日
登录注册

文章基本信息

  • 标题:Development of Nano Soy Milk through Sensory Attributes and Consumer Acceptability
  • 本地全文:下载
  • 作者:Seyoung Ju ; Sooji Song ; Jeongnam Lee
  • 期刊名称:Foods
  • 电子版ISSN:2304-8158
  • 出版年度:2021
  • 卷号:10
  • 期号:12
  • DOI:10.3390/foods10123014
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:Nanotechnology is currently applied in food processing and packaging in the food industry. Nano encapsulation techniques could improve sensory perception and nutrient absorption. The purpose of this study was to identify the sensory characteristics and consumer acceptability of three types of commercial and two types of laboratory-developed soy milk. A total of 20 sensory attributes of the five different soy milk samples, including appearance, smell (odor), taste, flavor, and mouthfeel (texture), were developed. The soy milk samples were evaluated by 100 consumers based on their overall acceptance, appearance, color, smell (odor), taste, flavor, mouthfeel (texture), goso flavor (nuttiness), sweetness, repeated use, and recommendation. One-way analysis of variance (ANOVA), principal component analysis (PCA), and partial least square regression (PLSR) were used to perform the statistical analyses. The SM_D sample generally showed the highest scores for overall liking, flavor, taste, mouthfeel, sweetness, repeated consumption, and recommendation among all the consumer samples tested. Consumers preferred sweet, goso (nuttiness), roasted soybean, and cooked soybean (nuttiness) attributes but not grayness, raw soybean flavor, or mouthfeel. Sweetness was closely related to goso (nuttiness) odor and roasted soybean odor and flavor based on partial least square regression (PLSR) analysis. Determination of the sensory attributes and consumer acceptance of soymilk provides insight into consumer needs and desires along with basic data to facilitate the expansion of the consumer market.
  • 关键词:sensory attributes; consumer acceptability; laboratory-developed soy milks; partial least square regression (PLSR) analysis
国家哲学社会科学文献中心版权所有