Mukai Junji, Miyanaga Yohko, Ishizaka Toshihiko, Asaka Kiyokazu, Nakai Yuka, Tsuji Eriko, Uchida Takahiro
School of Pharmaceutical Sciences, Mukogawa Women's University, 11-68 Koshien 9-Bancho, Nishinomiya 663-8179, Japan.
Chem Pharm Bull (Tokyo). 2004 Dec;52(12):1416-21. doi: 10.1248/cpb.52.1416.
The purpose of this study was to evaluate quantitatively the taste of the various total enteral nutrients marketed in Japan using human gustatory sensation tests and an artificial taste sensor. In the human gustatory sensation test, four basic taste intensities (sweetness, saltiness, sourness, and bitterness), as well as 15 kinds of palatability scales, were evaluated according to the semantic differential (SD) method. Among 15 palatability items, the item; difficult to drink/easy to drink, was adopted as an overall palatability since it shows the highest factor loading by factor analysis. The overall palatability was found to be highly positively correlated with sweetness and sourness, but negatively correlated with bitterness and saltiness. Addition of a flavour to the amino acid-based enteral nutrient AminolebanEN significantly improved its palatability. This effect is presumably due to sour components of the flavour, such as citric acid, which reduce the bitterness intensity of branched-chain amino acids in the product. The sweetness and sourness intensities predicted by the taste sensor showed a high correlation with the results obtained in the human gustatory sensation tests. The taste sensor was able to predict the overall palatability of the total enteral nutrients with high accuracy. The products could be classified into three groups (peptide-based, amino-acid-based, and protein-based) by principal component analysis using sensor output of 8 channels. The products could be also classified into four groups; peptide-based, amino-acid-based, and protein-based and flavor addition group by principal component analysis using sensor output of channels 1, 3, 4 and 7, which are specific to basic tastes. The taste sensor could therefore be useful in predicting the taste or palatability of total enteral nutrients, and could contribute to attempts to improve compliance for such products and for enteral nutrients.
本研究旨在通过人体味觉测试和人工味觉传感器，对日本市场上销售的各种肠内营养剂的味道进行定量评估。在人体味觉测试中，根据语义差异（SD）法评估了四种基本味觉强度（甜味、咸味、酸味和苦味）以及15种适口性量表。在15个适口性项目中，“难喝/易喝”这一项目因在因子分析中显示出最高的因子负荷，被用作整体适口性指标。结果发现，整体适口性与甜味和酸味呈高度正相关，但与苦味和咸味呈负相关。在基于氨基酸的肠内营养剂AminolebanEN中添加香料可显著改善其适口性。这种效果可能归因于香料中的酸味成分，如柠檬酸，它降低了产品中支链氨基酸的苦味强度。味觉传感器预测的甜味和酸味强度与人体味觉测试结果高度相关。味觉传感器能够高精度地预测肠内营养剂的整体适口性。通过使用8通道传感器输出进行主成分分析，这些产品可分为三组（基于肽的、基于氨基酸的和基于蛋白质的）。通过使用对基本味觉具有特异性的通道1、3、4和7的传感器输出进行主成分分析，这些产品也可分为四组：基于肽的、基于氨基酸的、基于蛋白质的和添加香料组。因此，味觉传感器可用于预测肠内营养剂的味道或适口性，并有助于提高此类产品和肠内营养剂的顺应性。
