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Journal articles on the topic 'Sensory evaluation'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Kim, Yong-Sung, and Yong-Suk Kim. "Biometrics Analysis and Evaluation on KoreanMakgeolliUsing Brainwaves and Taste Biological Sensor System." BioMed Research International 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/918631.

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There are several methods available in measuring food taste. The sensory evaluation, for instance, is a typical method for panels to test of taste and recognize smell with their nose by measuring the degree of taste characteristic, intensity, and pleasure. There are many issues entailed in the traditional sensory evaluation method such as forming a panel and evaluation cost; moreover, it is only localized in particular areas. Accordingly, this paper aimed to select food in one particular area, and compare and review the content between sensory evaluations using a taste biological sensor, as we

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Han, Xiao, Hongwei Yan, Baojian Liu, and Wen Liu. "Emotional Feeling Evaluation Model in Underwater Environment Based on Wearable Sensor." Mathematical Problems in Engineering 2022 (March 16, 2022): 1–12. http://dx.doi.org/10.1155/2022/2104465.

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Underwater sensor network technologies, as well as devices, are developing rapidly, and underwater IoT devices have been widely used in energy surveys, environmental indicator detection, military surveillance, and disaster event monitoring. The transmission of massive amounts of underwater data to the cloud for processing and analysis has become the dominant processing paradigm, and cloud computing has become a dominant computing paradigm. The preparation strategy of elastomer-coated hydrogel optical fibers for stable optical sensing proposed in this work opens up a new method and approach for

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3

Fujioka, Kouki. "Comparison of Cheese Aroma Intensity Measured Using an Electronic Nose (E-Nose) Non-Destructively with the Aroma Intensity Scores of a Sensory Evaluation: A Pilot Study." Sensors 21, no. 24 (2021): 8368. http://dx.doi.org/10.3390/s21248368.

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Cheese aroma is known to affect consumer preference. One of the methods to measure cheese aroma is the use of an electronic nose (e-nose), which has been used to classify cheese types, production areas, and cheese ages. However, few studies have directly compared the aroma intensity scores derived from sensory evaluations with the values of metal oxide semiconductor sensors that can easily measure the aroma intensity. This pilot study aimed to investigate the relationship between sensory evaluation scores and e-nose values with respect to cheese aroma. Five types of processed cheese (two types

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4

Najeh Nemah, Mohammed, Cheng Yee Low, Pauline Ong, and Noor Ayuni Che Zakaria. "Development and Evaluation of a Spot Sensor Glove for the Tactile Prosthetic Hand." International Journal of Engineering & Technology 7, no. 4.26 (2018): 63–69. http://dx.doi.org/10.14419/ijet.v7i4.26.22139.

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A tactile glove sensory system of the haptic feedback stimulation system for the upper limb prostheses was developed in this work to enable the patients of the upper limb amputation to recover the sense of touch and slippage. The system features six of a spot piezoresistive force sensors of type Quantum tunnelling compositesÂ (QTC) with 10 mm diameter, in order to measure the contact pressure between the hand and the objects. Five sensors were distributed on each fingertip and an extra sensor was mounted on the handâ€™s palm to cover all the critical point and increase the probability of detec

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5

Muir, D. D. "Sensory Evaluation Techniques." International Journal of Dairy Technology 60, no. 4 (2007): 305. http://dx.doi.org/10.1111/j.1471-0307.2007.00330.x.

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6

Zhang, Dong Ling, Xiao Mei Xu, Yang Liu, and Peng Fei Mu. "Research on the Sensory Quality Evaluation of Agricultural Food Based on Linguistic Information." Advanced Materials Research 424-425 (January 2012): 560–63. http://dx.doi.org/10.4028/www.scientific.net/amr.424-425.560.

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It presents a proposed method for the development of accredited sensory evaluation methods for agricultural food, and shows the application of the linguistic 2-tuple representation model and its advantages. It involved several steps: gathering of sensory information from experts; computing a collective evaluation for each feature; computing collective evaluations for each object; sensory evaluation and quality certification with global evaluation result.

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7

Nuyen Ti Tu, Hong, H. Valentová, J. Velíšek, J. Čepička, J. Pokorný, and F. Pudil. "Evaluation of beer quality by sensory analysis." Czech Journal of Food Sciences 18, No. 4 (2000): 137–42. http://dx.doi.org/10.17221/8332-cjfs.

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The flavour of pasteurised and stored beer was evaluated by a panel of 12 assessors. The sensory analysis consisted of combined hedonic evaluation and sensory profiling using unstructured graphical scales and 31 descriptors. The obtained results were evaluated by multivariate statistical methods (principal components analysis and linear discrimination analysis) which allow visualisation of relations between individual descriptors and samples and enable classification of samples to groups according to pasteurisation intensity and storage time.

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8

Zhang, Dong Ling, Xiu Zhi Zhu, Lian Qun Xing, and Xue Yang. "A Determination of the Engineering Characteristics in QFD Based on Sensory Quality Evaluation." Advanced Materials Research 711 (June 2013): 713–18. http://dx.doi.org/10.4028/www.scientific.net/amr.711.713.

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Quality function deployment is an important product development method, dedicated to translating client requirements into activities to develop products and services. The determination of customer need and engineering characteristics include sensory quality evaluation. This paper presents a proposed method for the sensory evaluation methods in QFD planning system, and shows the application of the linguistic information processing model and its advantages. It involved several steps: gathering of sensory information from experts; computing a collective evaluation for each feature; computing coll

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9

Zhang, Dong Ling. "A Dynamic Sensory Quality Evaluation Model Based on Panel Data and Linguistic Information Processing." Applied Mechanics and Materials 44-47 (December 2010): 3741–45. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3741.

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The sensory quality evaluation processes are widely used for many industrial products, which is evaluated according to the knowledge acquired via human senses (such as sight, taste, touch, smell). Because the evaluation information acquired by our senses is involving uncertainty, vagueness and imprecision, and the sensory quality information of products always has the panel data characteristic, so the sensory quality evaluation and certification is a multi-feature group decision-making problem based on panel linguistic information processing. This paper presents a proposed method for the devel

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10

Duman, Elifcan, Can Altınelataman, and Adnan Tokaç. "The role and importance of photonic sensors in seafood safety applications." Ege Journal of Fisheries and Aquatic Sciences 37, no. 3 (2020): 319–24. http://dx.doi.org/10.12714/egejfas.37.3.16.

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Microbiological, chemical, sensory analyses known as traditional methods are used for determination of fish quality including many concepts such as microbiological quality, sensory quality, nutritional properties, product specific properties, freshness, species-specific physical properties. With the developing technology; these time-consuming and error-free analyzes have been replaced by sensor technology, which is very suitable for quality measurements in order to achieve the expected speed and high standard and to be open to improvement. In this study, optical sensors and their applications

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11

Bílek, Jiří, Ondřej Bílek, Petr Maršolek, and Pavel Buček. "Ambient Air Quality Measurement with Low-Cost Optical and Electrochemical Sensors: An Evaluation of Continuous Year-Long Operation." Environments 8, no. 11 (2021): 114. http://dx.doi.org/10.3390/environments8110114.

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Sensor technology is attractive to the public due to its availability and ease of use. However, its usage raises numerous questions. The general trustworthiness of sensor data is widely discussed, especially with regard to accuracy, precision, and long-term signal stability. The VSB-Technical University of Ostrava has operated an air quality sensor network for more than two years, and its large sets of valid results can help in understanding the limitations of sensory measurement. Monitoring is focused on the concentrations of dust particles, NO2, and ozone to verify the impact of newly plante

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12

Ikejima, Toshiki, Koji Mizukoshi, and Yoshimune Nonomura. "Predicting Sensory and Affective Tactile Perception from Physical Parameters Obtained by Using a Biomimetic Multimodal Tactile Sensor." Sensors 25, no. 1 (2024): 147. https://doi.org/10.3390/s25010147.

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Tactile perception plays a crucial role in the perception of products and consumer preferences. This perception process is structured in hierarchical layers comprising a sensory layer (soft and smooth) and an affective layer (comfort and luxury). In this study, we attempted to predict the evaluation score of sensory and affective tactile perceptions of materials using a biomimetic multimodal tactile sensor that mimics the active touch behavior of humans and measures physical parameters such as force, vibration, and temperature. We conducted sensory and affective descriptor evaluations on 32 ma

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13

Nakamoto, Hiroyuki, Ryoga Nishimura, and Futoshi Kobayashi. "Effects of sensory combination on crispness and prediction of sensory evaluation value by Gaussian process regression." PLOS ONE 19, no. 2 (2024): e0297620. http://dx.doi.org/10.1371/journal.pone.0297620.

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Crispness contributes to the pleasantness and enjoyment of eating foods and is popular with people of wide ages in many countries. Hence, a quantitative evaluation method for crispness is required for food companies developing new food products. In this study, the effects of different sensory combinations on crispness were investigated through sensory evaluation, and a Gaussian process regression model was used to predict the evaluation values of crispness. First, four crispness descriptors in Japanese were selected, and sensory evaluations were conducted with ten participants using commercial

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14

Shukla, Renu, Nandita Sarkar, and Alpana Singh. "Nutritional and Sensory Evaluation of High Fiber Biscuit using Kodo Flour." RESEARCH REVIEW International Journal of Multidisciplinary 03, no. 07 (2018): 05–07. https://doi.org/10.5281/zenodo.1305339.

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Background: Healthy eating is the latent health benefits of precise foods and food ingredients. Supplementation of foods is current interest because of increasing nutritional awareness among consumers. Aim: The present study aims to evaluate the sensory and nutritional properties of high fiber biscuits using kodo flour. Method: Biscuits from kodo millet (paspalum scrobiculatum) were prepared by substituting kodo flour at various levels of substitution at 30%, 40% and 50% supplemented with refined wheat flour. Nutritional and Sensory evaluations of biscuit samples were evaluated by standard pro

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15

Santo, Edson Francisco do Espírito, Julia Eudoxia Decaris Rolim, Ytaiara Lima Pereira, Anne Caroline Dantas Tavares de Oliveira, and Washington Clementino Amorim Júnior. "Tambaqui's sausage: sensory evaluation." South Florida Journal of Development 1, no. 4 (2020): 186–93. http://dx.doi.org/10.46932/sfjdv1n4-001.

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16

Meshram, B. D. "Sensory evaluation of commercialDahi." Asian Journal of Dairy and Food Research 33, no. 3 (2014): 175. http://dx.doi.org/10.5958/0976-0563.2014.00597.1.

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17

Ronsheim, John, Edward Roessler, Maynard A. Amerine, D. Muscatine, M. A. Amerine, and B. Thompson. "Wines: Their Sensory Evaluation." Antioch Review 43, no. 2 (1985): 248. http://dx.doi.org/10.2307/4611476.

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18

ISHIWAKI, Tomohiro. "Sensory Evaluation of Coffee." Journal of Japan Association on Odor Environment 38, no. 5 (2007): 368–74. http://dx.doi.org/10.2171/jao.38.368.

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19

SAITO, Sachiko. "Sensory evaluation of odeur." JOURNAL OF THE BREWING SOCIETY OF JAPAN 84, no. 5 (1989): 280–86. http://dx.doi.org/10.6013/jbrewsocjapan1988.84.280.

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20

ISHIBASHI, Tokuo. "Sensory Evaluation of Beer." JOURNAL OF THE BREWING SOCIETY OF JAPAN 84, no. 6 (1989): 360–66. http://dx.doi.org/10.6013/jbrewsocjapan1988.84.360.

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21

YOSHIKAWA, Seiji. "Sensory Evaluation of Food." JOURNAL OF THE BREWING SOCIETY OF JAPAN 84, no. 10 (1989): 664–68. http://dx.doi.org/10.6013/jbrewsocjapan1988.84.664.

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22

FURUSHO, Shigeki. "Sensory Evaluation of Beer." JOURNAL OF THE BREWING SOCIETY OF JAPAN 97, no. 3 (2002): 178–87. http://dx.doi.org/10.6013/jbrewsocjapan1988.97.178.

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23

Kappel, F., E. Hogue, and B. Fisher-Fleming. "SENSORY EVALUATION OF PEARS." Acta Horticulturae, no. 367 (June 1994): 439. http://dx.doi.org/10.17660/actahortic.1994.367.71.

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24

NORO, Kageyu. "Sensory evaluation and ergonomics." Japanese journal of ergonomics 22, no. 3 (1986): 115–19. http://dx.doi.org/10.5100/jje.22.115.

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25

NOGUCHI, Yosuke. "Sensory evaluation and industry." Japanese journal of ergonomics 22, no. 3 (1986): 127–36. http://dx.doi.org/10.5100/jje.22.127.

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26

TAKASHIMA, Yasuhiro. "Aroma and Sensory Evaluation." food preservation science 24, no. 3 (1998): 201–9. http://dx.doi.org/10.5891/jafps.24.201.

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27

TAKASHIMA, Yasuhiro. "Odor and Sensory Evaluation." Japanese Journal of Sensory Evaluation 1, no. 1 (1997): 10–17. http://dx.doi.org/10.9763/jjsse.1.10.

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28

Murakami, Hiroaki. "Sensory Evaluation of Matcha." Chagyo Kenkyu Hokoku (Tea Research Journal) 2022, no. 134 (2022): 31–38. https://doi.org/10.5979/cha.2022.134_31.

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29

Cione, Joseph A., and John Cozzarelli. "Neurometer Diagnostic Sensory Evaluation." Foot & Ankle Specialist 2, no. 2 (2009): 95–97. http://dx.doi.org/10.1177/1938640009331632.

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30

Wolins, Leroy, Maynard A. Amerine, and Edward B. Roessler. "Wines: Their Sensory Evaluation." Journal of the American Statistical Association 80, no. 390 (1985): 484. http://dx.doi.org/10.2307/2287929.

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31

SAKATA, Yoshitaro. "Sensory Evaluation of Color." Journal of The Surface Finishing Society of Japan 74, no. 11 (2023): 575–78. http://dx.doi.org/10.4139/sfj.74.575.

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32

Mizuki, Asato, and Hiroyuki Yasue. "Consumer Preferences for Low-Amylose Rice: A Sensory Evaluation and Best–Worst Scaling Approach." Foods 14, no. 12 (2025): 2128. https://doi.org/10.3390/foods14122128.

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This study investigates the influence of sensory evaluation results on consumer preference, specifically focusing on salted rice balls made from low-amylose rice, which is suitable for chilled rice applications. Sensory evaluations were conducted through home-use tests, and consumer behavior data were collected using the Best–Worst Scaling method. The results, analyzed via a conditional logit model, show that consumer preferences for new low-amylose rice varieties improved post-sensory evaluation, with stickiness and appearance exhibiting significant interaction effects. Although the preferenc

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33

Vilela, Alice, Eunice Bacelar, Teresa Pinto, et al. "Beverage and Food Fragrance Biotechnology, Novel Applications, Sensory and Sensor Techniques: An Overview." Foods 8, no. 12 (2019): 643. http://dx.doi.org/10.3390/foods8120643.

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Flavours and fragrances are especially important for the beverage and food industries. Biosynthesis or extraction are the two main ways to obtain these important compounds that have many different chemical structures. Consequently, the search for new compounds is challenging for academic and industrial investigation. This overview aims to present the current state of art of beverage fragrance biotechnology, including recent advances in sensory and sensor methodologies and statistical techniques for data analysis. An overview of all the recent findings in beverage and food fragrance biotechnolo

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34

Henderson, Jeffrey, Joan Condell, James Connolly, Daniel Kelly, and Kevin Curran. "Reliability and Validity of Clinically Accessible Smart Glove Technologies to Measure Joint Range of Motion." Sensors 21, no. 5 (2021): 1555. http://dx.doi.org/10.3390/s21051555.

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Capturing hand motions for hand function evaluations is essential in the medical field. For many allied health professionals, measuring joint range of motion (ROM) is an important skill. While the universal goniometer (UG) is the most used clinical tool for measuring joint ROM, developments in current sensor technology are providing clinicians with more measurement possibilities than ever. For rehabilitation and manual dexterity evaluations, different data gloves have been developed. However, the reliability and validity of sensor technologies when used within a smart device remain somewhat un

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35

Gao, Li-Bing, Uchechukwu Edna Obianwuna, Hai-Jun Zhang, et al. "A Comparison between the Egg Yolk Flavor of Indigenous 2 Breeds and Commercial Laying Hens Based on Sensory Evaluation, Artificial Sensors, and GC-MS." Foods 11, no. 24 (2022): 4027. http://dx.doi.org/10.3390/foods11244027.

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The focus of this study was to compare the yolk flavor of eggs from laying hens of Chinese indigenous and commercial, based on detection of volatile compounds, fatty acids, and texture characteristics determination, using sensory evaluation, artificial sensors (electronic nose (E-nose), electronic tongue (E-tongue)), and gas chromatography-mass spectrometry (GC-MS). A total of 405 laying hens (Hy-Line Brown (n = 135), Xueyu White (n = 135), and Xinyang Blue (n = 135)) were used for the study, and 540 eggs (180 per breed) were collected within 48 h of being laid and used for sensory evaluation

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36

Ito, Fumiya, and Kenjiro Takemura. "A Model for Estimating Tactile Sensation by Machine Learning Based on Vibration Information Obtained while Touching an Object." Sensors 21, no. 23 (2021): 7772. http://dx.doi.org/10.3390/s21237772.

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The tactile sensation is an important indicator of the added value of a product, and it is thus important to be able to evaluate this sensation quantitatively. Sensory evaluation is generally used to quantitatively evaluate the tactile sensation of an object. However, statistical evaluation of the tactile sensation requires many participants and is, thus, time-consuming and costly. Therefore, tactile sensing technology, as opposed to sensory evaluation, is attracting attention. In establishing tactile sensing technology, it is necessary to estimate the tactile sensation of an object from infor

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37

Tadesse, Melkie Getnet, R. Harpa, Y. Chen, L. Wang, V. Nierstrasz, and C. Loghin. "Assessing the comfort of functional fabrics for smart clothing using subjective evaluation." Journal of Industrial Textiles 48, no. 8 (2018): 1310–26. http://dx.doi.org/10.1177/1528083718764906.

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Sensory investigations of the functional textiles could be an alternative for the quality inspection and control of the products. The purpose of this research is to use subjective evaluation technique for assessing the tactile comfort of some functional textile fabrics based on AATCC Evaluation procedure 5-2011. Blind subjective evaluations and visual subjective evaluations were performed for sensory investigation. Ten fabric-skin-contact and comfort-related sensory properties were used to evaluate the handle of the functional textile fabrics. The reliability of the sensorial data obtained by

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38

Moreno, Raymund B., and Nick John B. Solar. "Development and Sensory Evaluation of Peanut-Pine Butterscotch Bar." Indian Journal of Science and Technology 15, no. 3 (2022): 107–14. http://dx.doi.org/10.17485/ijst/v15i3.2089.

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39

Dr. N.Sabitha, Dr N. Sabitha, and Yamunadevi Puraikalan. "Development and Sensory Evaluation of Sunflower Seed Fortified Cookies." International Journal of Scientific Research 3, no. 2 (2012): 214–15. http://dx.doi.org/10.15373/22778179/feb2014/70.

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40

Nguyen Thi Thu, Huong, H. Valentová, J. Velíšek, J. Čepička, J. Pokorný, and F. Pudil. "Evaluation of beer by sensory and gas chromatography analysis." Czech Journal of Food Sciences 18, No. 6 (2000): 245–49. http://dx.doi.org/10.17221/8349-cjfs.

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41

Albert, Anisha, and Yamunadevi Puraikalan. "Development and Sensory Evaluation of Cookies Using Grape Seed." Global Journal For Research Analysis 3, no. 8 (2012): 115–16. http://dx.doi.org/10.15373/22778160/august2014/37.

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42

Fatima, Rimsha, Muhammad Hassan Khan, Muhammad Adeel Nisar, Rafał Doniec, Muhammad Shahid Farid, and Marcin Grzegorzek. "A Systematic Evaluation of Feature Encoding Techniques for Gait Analysis Using Multimodal Sensory Data." Sensors 24, no. 1 (2023): 75. http://dx.doi.org/10.3390/s24010075.

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This paper addresses the problem of feature encoding for gait analysis using multimodal time series sensory data. In recent years, the dramatic increase in the use of numerous sensors, e.g., inertial measurement unit (IMU), in our daily wearable devices has gained the interest of the research community to collect kinematic and kinetic data to analyze the gait. The most crucial step for gait analysis is to find the set of appropriate features from continuous time series data to accurately represent human locomotion. This paper presents a systematic assessment of numerous feature extraction tech

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43

Yamagata, Yoshie, and Yoshiaki Sugawara. "Sensory Evaluation Spectrum Method as a Descriptive Sensory Analysis." Psychology 05, no. 14 (2014): 1591–60. http://dx.doi.org/10.4236/psych.2014.514170.

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44

Naya, Carlos, Sara Dorregaray-Oyaregui, Fernando Alonso, Juan Luis Roquette, Jose María Yoldi, and César Martín-Gómez. "Transforming a Heritage Building into a Living Laboratory: A Case Study of Monitoring." Energies 18, no. 14 (2025): 3622. https://doi.org/10.3390/en18143622.

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This paper investigates integrating a sensory data model for managing an existing 50-year-old building. A primary challenge in retrofitting older structures is the optimal deployment of high-quality sensors, systematic data acquisition, and subsequent data management. To address this, the study implemented a network of over 50 sensors connected via 270 m of wired infrastructure, deliberately avoiding wireless transmission to ensure data reliability. This configuration generates 5568 data points daily, which are archived on a dedicated server. The data is planned for integration into the Campus

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45

Fregonezi-Nery, Marlene Maria, Sandra Helena Prudencio-Ferreira, Érika Maria Rosa Kedor, Marcela Maria Baracat, and Francis Fregonezi Brinholi. "Sensory evaluation of albendazole suspensions." Brazilian Archives of Biology and Technology 45, no. 4 (2002): 457–63. http://dx.doi.org/10.1590/s1516-89132002000600009.

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Sensory analysis was used in the albendazole suspension stability study. Three formulations were prepared and stored for 1, 3, and 6 months at 4 ±1, 26 ±1, 37, 50 and 65 ºC. Samples were evaluated through the difference from control sensory test using 24 trained judges in individual cabins. Although albendazole content was not altered in the conditions studied, sensory test showed differences between control and stored samples, except for one of the formulations stored under refrigeration for one month. These results have shown that the sensory evaluation is an important tool for quality contr

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46

Maurya, Neelesh Kumar. "Selection and Performance of Sensory Panelists: A Comprehensive Review of Factors Influencing Sensory Evaluation Outcomes." Nutrition and Food Processing 07, no. 15 (2024): 01–07. https://doi.org/10.31579/2637-8914/278.

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Sensory evaluation is a critical component in the development, refinement, and quality control of consumer products, particularly in food, beverage, cosmetics, and fragrance industries. This review provides a comprehensive exploration of sensory panelist selection criteria and the several factors that influence sensory measurements, aiming to enhance the reliability and validity of sensory data. Panelist selection involves assessing sensory acuity, availability, and reliability, and encompasses a diverse range of panel types, including trained, expert, and consumer panels. Ensuring panelist co

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47

Juyal, Dhruv. "Sensory evaluation of kinnow powder." INTERNATIONAL JOURNAL OF AGRICULTURAL ENGINEERING 11, no. 1 (2018): 90–94. http://dx.doi.org/10.15740/has/ijae/11.1/90-94.

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48

Masuyama, Eitarow. "Kansei and Sensory Evaluation Technique." Japanese journal of ergonomics 29, Supplement (1993): 98–99. http://dx.doi.org/10.5100/jje.29.supplement_98.

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49

JINGU, Hideo. "Sensory evaluation of computer software." Japanese journal of ergonomics 30, Supplement (1994): 32–33. http://dx.doi.org/10.5100/jje.30.supplement_32.

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50

Fernandes, S. A. A., de L. S. Ramos, E. M. Ramos, et al. "Sensory evaluation of buffalo butter." Italian Journal of Animal Science 6, sup2 (2007): 1140–42. http://dx.doi.org/10.4081/ijas.2007.s2.1140.

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