computer recognizing the signals obtained from these taste sensors in the form of patterns so called pattern recognition. Session N. -134-. Taste sensing-system ...
Taste sensing-system for objective evaluation of taste. Kobayashi Yoshikazu 1, Akira Taniguchi
I,
Hidekazu Ikezaki
J,
Kiyoshi Toko 2
I:Anritsu Corporation,1800 Onna, Atsugi, Kanagawa,243-8555, Japan 2:Kyushu University, Hakozaki,. Fukuoka, 812-8581, Japan
Summary We had developed a multichannel taste sensor using lipid/polymer membranes. This sensor has "the global selectivity", an intelligent sensitivity of chemical substances to classify five basic taste qualities of sourness, saltiness, sweetness, bitterness and umami. The sensor has been applied to many foods/drinks such as beer, coffee, tea, mineral water, and sake. Its discrimination ability, durability and sensitivity are superior to those of human. This' paper reports quantification of taste of green tea and astringency (important taste in tea). We used multiple regression analysis and found high correlation of outputs of the taste sensor with the results of sensory test. The taste sensor responds not only to amino acids and tannin, both of which are key taste in green tea, but also to many other taste substances. The taste sensor can detect the astringent synergistic/suppression effect as well as sensory evaluation. Hence it contains much more taste information than conventional chemical analyses. We anticipate that the system will find applications in new areas, such as medicine and the checking of water quality. Keyword taste sensor, Lipid/polymer membrane, Taste qu~ntification Introduction Evaluation of food taste in food manufacturing still largely depends on sensory tests carried out by a panel who actually tastes foods. However, the obtained data have problems in terms of low objectivity and low repeatability due to the individual differences and health conditions of the panel. And also the sensory test taxes exhausting and professional work to panels. 11te other hand, for the chemical analysis, it is very difficult to evaluate taste due to enormous kinds of taste substances and also interaction between taste substances. In this background, there is a strong demand for development of a taste sensing system in place of human sensory test and supporting the panel in food manufacturing. One of solution is a multichannel taste sensor using lipid/polymer membranes which mimics the living organisms. When a taste substance touches the human tongue, it is adsorbed by the microvilli of the taste cell. The surface of the taste cell is covered by the bilayer lipid membrane. When taste substances are adsorbed by the lipid membrane on the taste cell, the electric characteristics such as electric potential of the membrane change. And different output signals which are electric impulses are obtained from the taste cells having different characteristics. It is thought that the neural network of the brain calculates them by pattern recognition and discriminates the various tastes.. Figure 1 shows taste sensing system. Development of taste sensing system which mimics the taste sensing mechanism of living organisms had been attempted. Taste sensors were made by fixing the lipids which play an important role in taste detection, using a polymer. And data is obtained on the electric potential changes of the lipid membranes, when the taste substances are adsorbed on the membrane. At that time, instead of taste cells with different characteristics, different lipids were selected as membrane materials to make taste sensors with different properties. Taste discrimination was carried out by computer recognizing the signals obtained from these taste sensors in the form of patterns so called pattern recognition.
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This taste sensor has "the global selectivity", an intelligent sensitivity of chemical substances to classify five basic taste qualities of sourness, saltiness, sweetness, bitterness and umami. The sensor has been applied to many foods/drinks such as beer, coffee, tea, mineral water, milk and sake. Its discrimination ability, durability and sensitivity are superior to those of humans. This paper reports quantification of taste of green tea and astringency (important taste in tea).
Artificial lipid membrane sensors. . ",th different characteristics Computer
Electric potential change of rnerrbrane by taste swstances
Figure 1. Outline of taste sensing system
Material and method The measurement was performed using the taste sensing system SA402. Membranes of the reception part of the sensor are constructed from lipid, polyvinyl chloride and a plasticizer. The lipid membrane is a transparent, colorless, films with about 200 J1 m thickness. Electrolyte is composed of 3.3moVI KCl and saturated AgCl. The difference of the electric potential between lipid membrane electrode and reference electrode was obtained by means of a high impedance amplifier connected to a computer. CPA measuring algorithm is shown in Figure 2. High selectivity is expected to be improved with respect to bitter, umami and astringent tastes, which are highly adsorptive. The electric potential changes of the membrane against the references solution before and after sample measurements (Vr' -Vr ) is thought to be due to changes in the electric changes of the membrane caused by adsorption of the taste substances. In the case of washing completely human beings, this corresponds to the bitter taste Vr' - Vr=CPA value which remains in the mouth after drinking beer. Figure 2. CPA measuring procedure Here, (Vr' -Vr ) is called the CPA(Change of membranes Potential caused by Adsorption) value. For instance, the bitter substances having a positive charge produced selectivity in the negative charged membrane, and the bitter and astringent substances having negative electric charges triggered selectivity in the positive charged membrane.
Results and Discussion First, we explain application for green tea (1) • We have investigated the relationship between the output of the taste sensor, sensory evaluation and chemical analysis to shows the possibility of quantifying the taste of green tea. 22 samples were selected in the point of wide quality. Some are high quality leaves and others are leaves for oolong tea and black tea. The sensory evaluation was based on the average of the parameters of tastiness, fragrance and color. We used multiple regression analysis and found high correlation of outputs of the taste sensor with the results of sensory test (Fig.3). One reason for the high correlation with the sensory evaluation is that the taste sensor has good sensitivity for tannin (astringent taste) and theanine (urnami taste), both of which are key items in sensory evaluation of green tea. On the other hand, the sensory evaluation cannot be expressed well by those 2 terms. The taste sensor responds
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not only to amino acids and tannin, but also to many other taste substances, and hence it contains much more taste information than conventional chemical analyses. Next, we explain the detection of synergistic/suppression effect (2) on astringent taste by using the taste sensor. Figure 4 shows the results of astringent taste evaluation using a sensory test and taste sensor for a mixture of tannic acid and other basic taste substances. The sensor output is CPA value, which has high 1.10..,.....--------------------
multiple correlation coefficient R=O.97 iso-alpha-acid(bittemess)
Regression coefficient
R=O.98
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Astrigent strength calculated from the sensor
Sensory evaluation
Figure.3 Correlation between sensory evaluation and estimated value calcurated from taste sensor
Figure.4 The synergistic/suppression effect in adding the four basic substances to the tannic acid
sensitivity to tannin acid and no sensitivity to other basic taste substances. All samples contain tannic acid concentration of 0.05%, which is the typical concentration found in tea drinks. If sample contains salt, sweet, acid or umami taste substance, taste sensor response is smaller than that to pure tannic acid sample like sensory evaluations. It is suppression effect. On the other hand, If sample contains bitter taste substance, taste sensor response is bigger than that to pure tannic acid sample like sensory evaluations. It is a synergistic effect. The taste sensor can detect synergistic/suppression effect on the astringent taste.
Future Outlook So far, the taste sensor has been applied to green tea, beer, Japanes~ sake, coffee, etc., and has been able recognize both brand and lot differences while achieving good consistency with the results of sensory evaluations(3-8). In addition, the amount of data obtained from green tea, coffee, beer and sake using the new developments in measuring methods(9) has increased to 5 to 6 dimensions compared to the 1 to 2 dimensions to date. Moreover, high correlations have been obtained from multiple regression analysis of sensory evaluations based on these data(lO-ll). At the present, development of the taste sensor continues to be focused of liquid foods but its merits could also be applied to the environmental and pharmaceutical fields. The pharmaceutical industry uses human sensory testing of bitterness. Bitterness can also be quantified by taste sensor, and the pharmaceutical industry has good expectations for quantifying the bitterness suppression effect of medicines. We are putting a great deal of effort into ensuring that taste sensors are put to practical use in as many new fields as possible. Acknowledgment We are thankful to the Shizlloka Tea Experiment Station for the chemical analyses and sensory evaluation of the tea samples. Quantification of astringency was performed within the framework of a National Project for Development of Biosensor Systems for Food Industry sponsored by STAFF.
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References (1) H. Ikezaki, A. Taniguchi, and K. Toko, Trans. lEE ofJapan, Vol. 117-E, 465-470( 1997) (2) R. Toukubo, K. Sato, H. Ikezaki, A. Taniguchi, and K. Toko: The Japanese J oumal of Taste and Smell Research, Vol.7 No.3, 361-364(2000) (3) K. Toko and K.Miyagi, "sensa kougaku", baifukan(1995) (4) K. Toko, "syoku to kansei", kourin(1999) (5) K. Toko, "BIOMIMETIC SENSOR TECHNOLOGY", CAMBRIGE UNNERSITY PRESS(1999) (6) K. Toko, "Umai meshi niha wake ga aru", kadokawa syoten, 2001 (7) H. Ikezaki, H. Komai, Y. Naito, R. Toukubo, K. 5ato, N. Maeda, Anritsu Technical, 71, 159166(1996) (8) T. Imamura, K. Toko, S. Yanagisawa, and T. Kume, Sense Actuators, B37, 179-185(1996) (9) H. Ikezalki, A. Taniguchi, and K. Toko, Trans. lEE ofJapan, Vol. 118-E, 506-512(1998) (10) K. Toko, T. Iyota, Y. Mizota, T. Matsuno, T. Yoshioka, T. Doi, 5. Iiyama, T. Kato, K. Yamafuji, and R. Watanabe, Jpn.J.Appl.Phys., 34,6287-6291(1995) (11) K. 5ato, R. Toukubo, H. Ikezaki, A. Taniguchi, K. Toko, and 5. Furusho, Proceedings of 65th American Society ofBrewing Chemists, 59, p.17( 1999)
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