Готові списки джерел за темами / Sensory evaluation

Добірка наукової літератури з теми "Sensory evaluation"

Автор: Grafiati
Опубліковано: 4 червня 2021
Оновлено: 9 березня 2023

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Статті в журналах з теми "Sensory evaluation":

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 well as presenting an analysis of brainwaves using EEG and finally a proposal of a new method for sensory evaluation. In this paper, the researchers have conducted a sensory evaluation whereas a maximum of nine points were accumulated by purchasing eight types of rice wine. These eight types ofMakgeolliwere generalized by generating multidimensional data with the use of TS-5000z, thus learning mapping points and scaling them. The contribution of this paper, therefore, is to overcome the disadvantages of the sensory evaluation with the usage of the suggested taste biological sensor system.
2

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 developing low-cost and highly sensitive water flow sensors while analyzing the design of wearable smart devices to assess underwater environmental emotion perception evaluation schemes. In this paper, we propose a sensory data acquisition technique for event coverage detection of underwater environmental emotions, observing that an event may correspond to deviations from the normal sensory range of sensory data from multiple adjacent sensor nodes. Distributed edge computing is introduced to assume part of the cloud computing pressure, and an edge prediction-based data acquisition and sensing scheme for underwater sensor networks is proposed to realize the conversion of the acoustic communication transmission part of underwater data into data prediction transmission, thus reducing the energy consumption caused by acoustic communication. The model established in this paper effectively reduces sensor energy consumption while ensuring accurate data transmission and can respond to the underlying demand promptly, which is significantly better than the already existing schemes.
3

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 (January 1, 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.
4

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

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5

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 (December 15, 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 of normal processed cheese, one type containing aged cheese, and two types containing blue cheese), and one type of natural cheese were used as samples. The sensor values obtained using the electronic nose, which measured sample aroma non-destructively, and five sensory evaluation scores related to aroma (aroma intensity before intake, during mastication, and after swallowing; taste intensity during mastication; and remaining flavor after swallowing (lasting flavor)) determined by six panelists, were compared. The e-nose values of many of the tested cheese types were significantly different, whereas the sensory scores of the one or two types of processed cheese containing blue cheese and those of the natural cheese were significantly different. Significant correlations were observed between the means of e-nose values and the medians of aroma intensity scores derived from the sensory evaluation testing before intake, during mastication, and after swallowing. In particular, the aroma intensity score during mastication was found to have a linear relationship with the e-nose values (Pearson’s R = 0.983). In conclusion, the e-nose values correlated with the sensory scores with respect to cheese aroma intensity and could be helpful in predicting them.
6

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 (October 27, 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 planted greenery on the reduction in air pollution. The sensor network currently covers an open field on the outskirts of Ostrava, between Liberty Ironworks and the nearby ISKO1650 monitoring station, where some of the worst air pollution levels in the Czech Republic are regularly measured. In the future, trees should be allowed to grow over the sensors, enabling assessment of the green barrier effect on air pollution. As expected, the service life of the sensors varies from 1 to 3 years; therefore, checks are necessary both prior to the measurement and regularly during operation, verifying output stability and overall performance. Results of the PMx sensory measurements correlated well with the reference method. Concentration values measured by NO2 sensors correlated poorly with the reference method, although timeline plots of concentration changes were in accordance. We suggest that a comparison of timelines should be used for air quality evaluations, rather than particular values. The results showed that the sensor measurements are not yet suitable to replace the reference methods, and dense sensor networks proved useful and robust tools for indicative air quality measurements (AQM).
7

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.
8

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 (September 15, 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 are emphasized and a general evaluation is made about the usability of seafood processing technology in terms of food safety.
9

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 collective evaluations for each object; dynamic aggregation; sensory evaluation and quality certification with global evaluation result.
10

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 development of accredited sensory evaluation methods, 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; dynamic aggregation; sensory evaluation and quality certification with global evaluation result.
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Статті в журналах Дисертації Книги

Дисертації з теми "Sensory evaluation":

1

Deans, Gillian A. "Design and analysis of sensory evaluation experiments." Thesis, University of Newcastle Upon Tyne, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.240734.

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2

Rose, Grenville John, of Western Sydney Hawkesbury University, Faculty of Science and Technology, and School of Food Science. "Sensory aspects of food preferences." THESIS_FST_SFS_Rose_G.xml, 1999. http://handle.uws.edu.au:8081/1959.7/130.

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Little is known about how liking for different foods develops from birth to adulthood. Although there are both cultural and sensory aspects to the development of food preferences, the focus of this study is on the sensory aspects of food preference development, in particular, preferences for meat. Two main aims are addressed : 1/. To develop a robust methodology that can be used to determine pre-literate and recently literate children's liking for different foods and the determinants of that liking. 2/. To investigate the effects of early experience with foods on later food preferences.Several tests were conducted and results noted. Overall the results of this thesis show that it is possible to gather reliable hedonic data from young, even pre-school children, and that it is possible that very early feeding experience has some influence on adults' food preferences.
Doctor of Philosophy (PhD)
3

Ismail, Baraem. "Dates : physico-chemical characteristics, total quality and nutritional significance." Thesis, University of Central Lancashire, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275924.

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4

Krishnamurthy, Raju Chemical Sciences &amp Engineering Faculty of Engineering UNSW. "Prediction of consumer liking from trained sensory panel information: evaluation of artificial neural networks (ANN)." Awarded by:University of New South Wales. Chemical Sciences & Engineering, 2007. http://handle.unsw.edu.au/1959.4/40746.

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This study set out to establish artificial neural networks (ANN) as an alternate to regression methods (multiple linear, principal components and partial least squares regression) to predict consumer liking from trained sensory panel data. The study has two parts viz., I) Flavour study - evaluation of ANNs to predict consumer flavour preferences from trained sensory panel data and 2) Fragrance study ??? evaluation of different ANN architectures to predict consumer fragrance liking from trained sensory panel data. In this study, a multi-layer feedforward neural network architecture with input, hidden and output layer(s) was designed. The back-propagation algorithm was utilised in training of neural networks. The network learning parameters such as learning rate and momentum rate were optimised by the grid experiments for a fixed number of learning cycles. In flavour study, ANNs were trained using the trained sensory panel raw data as well as transformed data. The networks trained with sensory panel raw data achieved 98% correct learning, whereas the testing was within the range of 28 -35%. A suitable transformation methods were applied to reduce the variations in trained sensory panel raw data. The networks trained with transformed sensory panel data achieved between 80-90% correct learning and 80-95% correct testing. In fragrance study, ANNs were trained using the trained sensory panel raw data as well as principal component data. The networks trained with sensory panel raw data achieved 100% correct learning, and testing was in a range of 70-94%. Principal component analysis was applied to reduce redundancy in the trained sensory panel data. The networks trained with principal component data achieved about 100% correct learning and 90% correct testing. It was shown that due to its excellent noise tolerance property and ability to predict more than one type of consumer liking using a single model, the ANN approach promises to be an effective modelling tool.
5

Cerff, Jeanne. "Optimisation of kefir biomass and metabolite production in conjunction with sensory evaluation." Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/52979.

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Thesis (MSc)--Stellenbosch University, 2002.
ENGLISH ABSTRACT: Developing countries such as South Africa are in dire need of nutritionally adequate dairy food and beverage sources that are ambient stable due to minimal access to refrigeration. One such product is Kefir, a naturally fermented milk beverage that originated in Caucasian China many centuries ago. The microorganisms responsible for fermentation of the milk are held together in a carbohydrate matrix in the form of small grains. These grains are then removed from the beverage prior to consumption, and added to fresh milk for new fermentations. This beverage holds great potential for large scale development due to the self-propagating nature of the grains, the lack of sophisticated equipment and knowledge necessary for production, and the appealing sensory characteristics of this beverage. This study was therefore performed as an initial investigation to determine the optimum fermentation conditions for large-scale grain production and optimal sensory appeal. Kefir grain production was found to be proportional to incubation temperature in the range studied (18°, 22°, 25° and 30°C), with maximum grain biomass increases of 500% for the Kefir incubated at 30°C over the 10 d trial. During fermentation of Kefir grains in milk, lactic acid and other metabolites are produced. Lactic acid results in coagulation of the milk, necessary to provide the characteristic texture and flavour of Kefir, as well as exerting a preservative effect. Lactic acid production was found to be strongly proportional to both incubation temperature and inoculum concentration. The samples containing 2% (w/v) Kefir grain inoculum concentration that were incubated at 25°C for 24 h were found to have optimum lactic acid levels for good quality Kefir (pH of 4.4 - 4.6 and TA of 1.0 - 1.15%). The other metabolites produced during Kefir fermentation are responsible for the specific flavour of Kefir, and include acetaldehyde, diacetyl, ethanol, acetone and 2-butanone. These compounds were studied using headspace gas chromatography over the fermentation period, which yielded good resolution and separation of all these compounds, however, only acetaldehyde, ethanol and acetone were found to be major metabolites in this study, These analytical results were then further compared to sensory results for key identified attributes, as obtained from a trained sensory panel, to enable recommendations for optimum fermentation conditions to be made. The studied attributes included sourness, sweetness, butteriness, creaminess, yoghurt flavour, cowiness, effervescence, yeastiness, smoothness and overall acceptability. It was apparent from this study that correlations between analytical and sensory data could be drawn, and that panellists were particularly accurate in detecting the attribute sourness resulting from the accumulated lactic acid in the Kefir. Overall acceptability also seemed to be intricately linked to the attribute creaminess, hence the regular literature references to full-cream Kefir as optimum for best sensory appeal. From this study, it was evident that Kefir with optimal sensory appeal is obtained with incubation for 18 h at moderate temperatures (22° or 25°C) and grain inoculum concentrations (0.8% w/v).
AFRIKAANSE OPSOMMING: In ontwikkelende lande soos Suid-Afrika, bestaan daar 'n groot behoefte aan voedsame suiwelprodukte wat stabiel is by kamer temperatuur aangesien 'n groot deel van die bevolking beperkte toegang tot verkoelingsfasiliteite het. Een so 'n produk is Kefir, 'n natuurlike gefermenteerde suiwelproduk wat sy oorsprong eeue gelede in China gehad het. Die mikroorganismes wat verantwoordelik is vir die fermentasie, is saamgebind in 'n koolhidraat matriks in die vorm van klein korrels. Hierdie korrels word verwyder uit die drankie voordat dit gedrink word, en word dan weer by vars melk bygevoeg vir 'n verdere fermentasie. Hierdie gefermenteerde produk het baie potensiaal vir massa-produksie, omdat die korrels natuurlik vermeerder, geen gesofistikeerde toerusting of kennis nodig is nie, en die finale produk hoogs aanvaarbare sensoriese eienskappe het. Die doel van die studie was om 'n inleidende ondersoek uit te voer om die optimum fermentasie toestande vir massakweking van korrels en die mees aanvaarbare sensoriese eienskappe te bepaal. Uit hierdie studie is gevind dat Kefirkorrel vermeerdering proporsioneel is tot die verhoging in inkubasie temperatuur in die gebied 18°, 22°, 25° en 30°C, met maksimum biomassa toenames van tot 500% vir Kefir wat vir 10 dae by 30°C geïnkubeer was. Gedurende fermentasie van Kefirkorrels in melk, word melksuur en ander metaboliete gevorm. Melksuur lei tot die verlaging van die pH van die melk, en veroorsaak stolling, wat noodsaaklik is vir die kenmerkende tekstuur en geur van Kefir, maar dien ook as 'n preserveermiddel. Daar is ook gevind dat melksuur produksie 'n direkte verband het met die inkubasie temperatuur en inokulum konsentrasie. Die monsters met Kefirkorrel inokulum konsentrasie van 2% (miv) wat vir 24 h by 25°C geïnkubeer is, het die optimale melksuur konsentrasies vir goeie kwaliteit Kefir bevat (pH van 4.4 - 4.6 en TA van 1.0 - 1.15%). Ander metaboliete wat belangrike geurkomponente van Kefir is, is asetaldehied, diasetiel, etanol, asetoon en 2-butanoon. Hierdie metaboliete is bepaal en geëvalueer met bodamp gaschromatografiese tegnieke gedurende die fermentasie, wat 'n goeie resolusie en skeiding gelewer het. In hierdie studie is slegs asetaldehied, etanol en asetoon as hoof Kefir metaboliete gevind. Die analitiese data is verder vergelyk met die sensoriese data van die hoof sensoriese komponente, soos bepaal deur 'n opgeleide sensoriese paneel, om die mees gunstigde fermentasie parameters te bepaal. Die geëvalueerde eienskappe was suurheid, soetheid, botterigheid, romerigheid, joghurt geur, koeismaak, gas inhoud, gisagtigheid, gladheid en algehele aanvaarbaarheid. Uit hierdie data is gevind dat daar wel 'n sterk korrelasie bestaan tussen die analitiese en sensoriese resultate, en dat paneellede in staat was om die suurheid, as gevolg van die gevormde melksuur, te bepaal. Algehele aanvaarbaarheid is definitief gekoppel aan romerigheid, daarom word volroommelk Kefir verkies bo die wat met afgeroomde melk berei is. Die data uit hierdie studie het ook getoon dat Kefir met optimale sensoriese eienskappe verkry is na 'n inkubasietyd van 18 h by "matige temperature" (22° of 25°C) en 'n Kefirkorrel inokulum van 0.8% (mIv).
6

Kupongsak, Sasikan. "Food process control based on sensory evaluations /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3115564.

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7

Chanadang, Sirichat. "Sensory evaluation and consumer acceptability of novel fortified blended foods." Diss., Kansas State University, 2017. http://hdl.handle.net/2097/35459.

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Анотація:
Doctor of Philosophy
Food, Nutrition, Dietetics and Health
Edgar Chambers IV
Fortified blended foods (FBFs), which are the mixture of cereals and legumes fortified with micronutrients, have been widely used as supplementary foods for vulnerable populations such as infants and young children in developing countries around the world. The evaluation of current FBFs showed limited evidence on their effectiveness in treating childhood malnutrition, resulting the several recommendations on processing and formulation changes to improve their quality and ability to meet nutritional needs. Sensory properties are one of the important determinants for the success of the new FBFs. Therefore, sensory testing was conducted to determine the potential of novel FBFs to be used as supplementary food compared with FBF currently used in food aid programs. Descriptive sensory analysis was performed on novel FBFs along with the traditional FBF (Corn soy blend plus; CSB+) to determine sensory characteristics of each FBF. Results showed that novel FBFs had more pronounced toasted characteristics and higher sweetness than CSB+, due to the higher temperature during extrusion process and the addition of sugar in the novel formulation. In addition, novel FBFs that had higher amount of legumes (e.g. soybean, cowpea) in their formulations, especially for all sorghum cowpea blends, showed higher intensity in beany characteristics. Sensory shelf-life testing showed that novel FBFs could have shelf lives at least 2 years with no detection of off-note characteristics and these was comparable to the shelf life of the current FBF (CSB+). Sensory testing was also performed with target populations: children who eat the food and care givers who prepare it, during a 20-week field trial to determine the acceptability and preference of novel FBFs and current FBF. Results showed that all novel FBFs were highly preferred or accepted by children, even though, some of them might need longer time and more exposures to allow children to have more experience and be familiar with the food before being satisfied or preferred that food. In contrary, CSB+ that had bland flavor tended not to be well accepted and highly preferred by children compared to novel FBFs. Moreover, giving children more opportunities to consumed food prepared from CSB+ did not help to improve its acceptability or preference. Data from household visits and interview sessions showed that porridges prepared from novel FBFs required less cooking time than CSB+ and no additional ingredients needed to be added compared to CSB+ where sugar and milk were common additions. Finding from this research indicated that novel FBFs have high potential to be used successfully as supplementary food with comparable shelf life, and higher acceptability and preference to FBF currently used in food aid programs. In addition, the simple cooking of novel FBFs make them valuable to caregivers who have limited time and access to energy sources and nutrient-rich ingredients.
8

Kim, Joseph. "Quantitative sensory testing for evaluation chronic arthritis or local anesthesia." Thesis, Boston University, 2013. https://hdl.handle.net/2144/12136.

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Thesis (M.A.)--Boston University
Background: Properly functioning sensory systems are crucial in perception of external stimuli. Different modalities such as touch, temperature, and pain can only be appreciated with intact sensory pathways from the peripheral receptors to the cerebral cortex via the spinal cord. Pain is a sensory response to noxious, tissue damaging stimuli. It is an essential protective response for survival. However, abnormalities in sensory function may lead to hyposensitization or hypersensitization to a stimulus, which may cause numbness or pain respectively. Juvenile Idiopathic Arthritis (JIA) is a condition characterized by inflammation of the joints, resulting in stiffness and pain. The etiology of JIA is not well known, and little is understood about the associated changes in sensory function that may be present. In this study, we use quantitative sensory testing (QST) as a validated measure to assess local and global changes in sensory function in JIA patients. [TRUNCATED]
9

Katzir, Irena. "Sensory and dietary quality of fiber-beef blends." Thesis, Virginia Tech, 1989. http://hdl.handle.net/10919/43898.

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Recently, there has been an increased interest in manufacturing high fiber Foods. Beef patties containing 1% Lupran (sweet lupin bran flour), 2% barley and 3% of both fibers (1% Lu + 2% Ba) and a control all-beef pattie were manufactured and comparatively evaluated by visual and sensory panels. Hypocholesterolemic effects were tested by in vivo studies. Rats were fed diets containing meat or meat-blends as the sole source of protein, fat, fiber and cholesterol. All the diets were isocaloric. At the point of purchase, the meat blends were different (P < 0.05) from the in their apparent amount exudate, fat to lean ratio and integrity. Less significant was the difference in color, both visual and objective, with the beef-barley blend tending to be darker and the beef-lupran product tending to be brighter within 14 days oF storage. The sensory panel scored meat-blends as significantly less beefy, more beany and grainy (P> 0.05). The grainy flavor of barley was especially detectable. Mouthfeel was not significantly altered (P> 0.05) but there was a tendency for the panel to score the barley blend as dryer and tougher than the control. However, these results were not confirmed by objective measurements. Cooking losses and quantity of measured exudate For meat blends were similar to the control. Neither lupran nor barley had a significant antioxidative effect. The meat blend with 3% fiber lowered the LDL fraction in rats relative to that of rats on control diets. However, the amount of added fiber was too low to significantly affect serum or liver cholesterol.
Master of Science

10

Nakano, Kumiko. "Study on sensory evaluation instrument for describing comprehensive palatability and preference." Kyoto University, 2014. http://hdl.handle.net/2433/185213.

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Анотація:
Kyoto University (京都大学)
0048
新制・課程博士
博士(農学)
甲第17988号
農博第2035号
新制||農||1019(附属図書館)
学位論文||H26||N4813(農学部図書室)
80832
京都大学大学院農学研究科食品生物科学専攻
(主査)教授 伏木 亨, 教授 保川 清, 教授 安達 修二
学位規則第4条第1項該当
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Книги з теми "Sensory evaluation":

1

Kemp, Dr Sarah E., Dr Tracey Hollowood, and Dr Joanne Hort. Sensory Evaluation. West Sussex, United Kingdom: John Wiley & Sons Ltd,., 2009. http://dx.doi.org/10.1002/9781118688076.

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Ruan, Da, and Xianyi Zeng, eds. Intelligent Sensory Evaluation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-07950-8.

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3

Stone, Herbert. Sensory evaluation practices. Boston: Elsevier Academic Press, 2004.

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4

Meilgaard, Morten. Sensory evaluation techniques. Boca Raton, Fla: CRC Press, 1987.

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5

Meilgaard, Morten. Sensory evaluation techniques. 4th ed. Boca Raton: Taylor & Francis, 2007.

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6

Stone, Herbert. Sensory evaluation practices. San Diego: Academic Press, 1993.

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7

Stone, Herbert. Sensory evaluation practices. Orlando: Academic Press, 1985.

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8

Meilgaard, Morten. Sensory evaluation techniques. 3rd ed. Boca Raton, Fla: CRC Press, 1999.

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9

Meilgaard, Morten. Sensory evaluation techniques. 2nd ed. Boca Raton: CRC Press, 1991.

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10

Lawless, Harry T., and Hildegarde Heymann. Sensory Evaluation of Food. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-7843-7.

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Частини книг з теми "Sensory evaluation":

1

Kemp, Dr Sarah E., Dr Tracey Hollowood, and Dr Joanne Hort. "Sensory Perception." In Sensory Evaluation, 4–10. West Sussex, United Kingdom: John Wiley & Sons Ltd,., 2013. http://dx.doi.org/10.1002/9781118688076.ch2.

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2

Kemp, Dr Sarah E., Dr Tracey Hollowood, and Dr Joanne Hort. "Introduction." In Sensory Evaluation, 1–3. West Sussex, United Kingdom: John Wiley & Sons Ltd,., 2013. http://dx.doi.org/10.1002/9781118688076.ch1.

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Kemp, Dr Sarah E., Dr Tracey Hollowood, and Dr Joanne Hort. "Planning your Sensory Project." In Sensory Evaluation, 11–29. West Sussex, United Kingdom: John Wiley & Sons Ltd,., 2013. http://dx.doi.org/10.1002/9781118688076.ch3.

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4

Kemp, Dr Sarah E., Dr Tracey Hollowood, and Dr Joanne Hort. "Requirements for Sensory Testing." In Sensory Evaluation, 30–65. West Sussex, United Kingdom: John Wiley & Sons Ltd,., 2013. http://dx.doi.org/10.1002/9781118688076.ch4.

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5

Kemp, Dr Sarah E., Dr Tracey Hollowood, and Dr Joanne Hort. "Sensory Test Methods." In Sensory Evaluation, 66–137. West Sussex, United Kingdom: John Wiley & Sons Ltd,., 2013. http://dx.doi.org/10.1002/9781118688076.ch5.

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6

Kemp, Dr Sarah E., Dr Tracey Hollowood, and Dr Joanne Hort. "Completing the Project." In Sensory Evaluation, 138–41. West Sussex, United Kingdom: John Wiley & Sons Ltd,., 2013. http://dx.doi.org/10.1002/9781118688076.ch6.

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7

Setser, C. S. "Sensory evaluation." In Advances in Baking Technology, 254–91. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-7256-9_10.

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8

Ruan, Da, and Xianyi Zeng. "Intelligent Sensory Evaluation: An Introduction." In Intelligent Sensory Evaluation, 1–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-07950-8_1.

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9

Ioannou, Irina, Nathalie Perrot, Corinne Curt, Irène Allais, Laure Agioux, Gilles Mauris, and Gilles Trystram. "The Fuzzy Symbolic Approach for the Control of Sensory Properties in Food Processes." In Intelligent Sensory Evaluation, 175–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-07950-8_10.

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10

Guillaume, Serge, and Brigitte Charnomordic. "Fuzzy Inference Systems to Model Sensory Evaluation." In Intelligent Sensory Evaluation, 197–216. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-07950-8_11.

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Тези доповідей конференцій з теми "Sensory evaluation":

1

Zhang, Lijian, and Wenqi Shen. "Sensory Evaluation of Commercial Truck Interiors." In International Truck & Bus Meeting & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1999. http://dx.doi.org/10.4271/1999-01-1267.

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2

Lokki, Tapio. "Sensory evaluation of concert hall acoustics." In ICA 2013 Montreal. ASA, 2013. http://dx.doi.org/10.1121/1.4800481.

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3

Li, Tao, Daping Liu, Xiangqian Ding, Hongwei Liu, and Xiaoliang Yuan. "Sensory Evaluation Based on Ensemble Learning." In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.867.

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4

Luo, Bin. "A evaluation model of experiement system in sensory evaluation." In International Conference on Intelligent Systems and Knowledge Engineering 2007. Paris, France: Atlantis Press, 2007. http://dx.doi.org/10.2991/iske.2007.251.

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5

Wincheski, Buzz, John Simpson, Terryl Wallace, Andy Newman, Paul Leser, and Rob Lahue. "Electromagnetic characterization of metallic sensory alloy." In REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION: VOLUME 32. AIP, 2013. http://dx.doi.org/10.1063/1.4789226.

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6

Guedes, Alan L. V., Roberto G. de A. Azevedo, Pascal Frossard, Sergio Colcher, and Simone Diniz Junqueira Barbosa. "Subjective Evaluation of 360-degree Sensory Experiences." In 2019 IEEE 21st International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2019. http://dx.doi.org/10.1109/mmsp.2019.8901743.

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7

Figueiredo, Fernanda Otilia, Adelaide Maria Figueiredo, and Maria Ivette Gomes. "Design of sampling plans for sensory evaluation." In INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2018 (ICCMSE 2018). Author(s), 2018. http://dx.doi.org/10.1063/1.5079170.

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8

YANG, NING, RONGGANG GONG, and SHUO SHI. "CIGARETTE SENSORY EVALUATION CLASSIFIER PREDICTION CONTROL ALGORITHM." In Proceedings of the 9th International FLINS Conference. WORLD SCIENTIFIC, 2010. http://dx.doi.org/10.1142/9789814324700_0119.

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9

Martinez, Luis, Macarena Espinilla, and Luis G. Perez. "Sensory Evaluation Model with Unbalanced Linguistic Information." In International Conference on Intelligent Systems and Knowledge Engineering 2007. Paris, France: Atlantis Press, 2007. http://dx.doi.org/10.2991/iske.2007.111.

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10

Curteza, Antonela, Valentin Buliga, and Ramona Budeanu. "SOFTWARE APPLICATION FOR THE SUBJECTIVE EVALUATION OF TEXTILE PRODUCTS." In eLSE 2014. Editura Universitatii Nationale de Aparare "Carol I", 2014. http://dx.doi.org/10.12753/2066-026x-14-278.

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Анотація:
Consumer preferences for textile products are largely determined by sensory characteristics. In this context, the tactile senses are among the most important. Various sensory evaluation methods have been developed to characterize the tactile feeling from the consumer's point of view. However, sensory assessments are time-consuming and expensive. Therefore, reliable and practical methods are needed in order to predict sensory tactile attributes in an accurate manner so as to improve both student education and industrial product development and quality control stages. From a subjective angle, the evaluation of sensory comfort can be done by conducting tests of feeling and touching the assessed material or, in a more complex manner, by actually wearing the fabric. The degree to which the test subjects perceive comfort requires further rating of those descriptors that are considered to capture the essence of several fabric properties. These properties are being selected so that they would be the most relevant for the garment testing and evaluation process. The assessment of the perceived sensation can be done by granting marks that rate its intensity, by comparing it to a designated standard sample or by comparing the samples subjected to evaluation among them. One of the proposed and used methods is based on differentiating sensations by granting marks on a scale from 1 to 5, using the corresponding symbol that was previously established. However, this particular method requires a lot of work and a large volume of processed information because of the amount of samples and the range of subjects involved. In order to simplify and render the subjective evaluation procedure more effective, we are suggesting the use of a certain software application. The users involved will upload input data, such as the qualifiers granted to each sample depending on the evaluation of the perceived sensation. Thus, individual matrices are being created, which represent a starting point for calculating the average values according to the marks granted to each and every sample by the group of subjects. The final matrix that results will be displayed for all users to see. By using the final matrices, it will be determined the minimum and maximum values corresponding to the batch of assessed samples. The software allows determining the position of every assessed sample on a minimized scale from 0 to 1, called the sensory scale, depending on the subjective evaluations. The final results will be featured in a table and in a chart too in order to facilitate their observation and interpretation by users.

Звіти організацій з теми "Sensory evaluation":

1

Simon, James E., Uri M. Peiper, Gaines Miles, A. Hetzroni, Amos Mizrach, and Denys J. Charles. Electronic Sensing of Fruit Ripeness Based on Volatile Gas Emissions. United States Department of Agriculture, October 1994. http://dx.doi.org/10.32747/1994.7568762.bard.

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Анотація:
An electronic sensory system for the evaluation of headspace volatiles was developed to determine fruit ripeness and quality. Two prototype systems were designed, constructed, and later modified. The first is an improved version of our original prototype electronic sniffer using a single head sensing unit for use as a single or paired unit placed on an individual fruit surface for applications in the field, lab, or industry. The second electronic sniffer utilizes a matrix of gas sensors, each selected for differential sensitivity to a range of volatile compounds. This system is more sophisticated as it uses multiple gas sensors, but was found to enhance the ability of the sniffer to classify fruit ripeness and quality relative to a single gas sensor. This second sniffer was designed and constructed for the sampling of fresh-cut or whole packs of fruits such as packaged strawberries and blueberries, and can serve as a prototype for research or commercial applications. Results demonstrate that electronic sensing of fruit ripeness based on aromatic volatile gas emissions can be used successfully with fresh frits. Aroma sensing was successful for classifying ripeness in muskmelons, including different cultivars, apples, blueberries, strawberries, and in a complimentary BARD project on tomatoes. This system compared favorably to the physicochemical measurements traditionally employed to assess fruit maturity. This nondestructive sensory system can detect the presence of physically damaged fruits and shows excellent application for use in quality assessment. Electronic sensors of the tin oxide type were evaluated for specificity toward a wide range of volatiles associated with fruit ripeness. Sensors were identified that detected a broad range of alcohols, aldehydes, esters, hydrocarbons, and volatile sulfur compounds, as well as individual volatiles associated with fruit ripening across a wide concentration range. Sensors are not compound specific, thus, the matrix of sensors coupled with discrimination analysis provides a fingerprint to identify the presence of compounds and to assess alterations in fresh products due to alterations in volatile emissions. Engineering developments led to the development of a system to compensate for temperature and relative humidity relative to on-line aroma sensing with melons for ripeness determination and to reduce response time, thus permitting the electronic sniffer to be used for monitoring both fresh and processed food products. The sniffer provides a fast, reliable and nondestructive tool to assess fruit ripeness and quality. We hope that our work will foster the introduction and utilization of this emerging technology into the agricultural and horticultural
2

Sun, Jian-Qiao. Sample Concentration Systems for Fast Laboratory Evaluation of Sensory Materials for Chemical and Biological Agent Detection in Water. Fort Belvoir, VA: Defense Technical Information Center, February 2003. http://dx.doi.org/10.21236/ada412618.

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3

Gurtowski, Luke A., Joshua J. LeMonte, Jay Bennett, Matt Middleton, and Brandon J. Lafferty. Evaluation of multiparameter water meter for Environmental Toolkit for Expeditionary Operations. U.S. Army Engineer Research and Development Center, June 2022. http://dx.doi.org/10.21079/11681/44520.

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A new, commercially available, field-portable water sensor was evaluated for efficacy during operation and compatibility with current Environmental Toolkit for Expeditionary Operations (ETEO) software. The ETEO provides sensors to Soldiers to rapidly identify and quantify environmental contamination in soil, air, and water at potential new base sites during initial reconnaissance to ensure Soldier safety and minimize unnecessary remediation efforts by the Army. The primary objective of this study was to enhance ETEO performance by providing the capability to evaluate multiple water quality properties simultaneously.
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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Анотація:
The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
5

Merchant, Bion J., and Kyle D. McDowell. MB3a Infrasound Sensor Evaluation. Office of Scientific and Technical Information (OSTI), November 2014. http://dx.doi.org/10.2172/1165050.

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6

Kennedy, Chris. Embedded Sensor Technology Evaluation. Office of Scientific and Technical Information (OSTI), January 2010. http://dx.doi.org/10.2172/1074255.

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7

Slad, George William, and Bion J. Merchant. USGS VDP Infrasound Sensor Evaluation. Office of Scientific and Technical Information (OSTI), October 2016. http://dx.doi.org/10.2172/1331426.

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8

Kamai, Tamir, Gerard Kluitenberg, and Alon Ben-Gal. Development of heat-pulse sensors for measuring fluxes of water and solutes under the root zone. United States Department of Agriculture, January 2016. http://dx.doi.org/10.32747/2016.7604288.bard.

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The objectives defined for this study were to: (1) develop a heat-pulse sensor and a heat-transfer model for leaching measurement, and (2) conduct laboratory study of the sensor and the methodology to estimate leaching flux. In this study we investigated the feasibility for estimating leachate fluxes with a newly designed heat-pulse (HP) sensor, combining water flux density (WFD) with electrical conductivity (EC) measurements in the same sensor. Whereas previous studies used the conventional heat pulse sensor for these measurements, the focus here was to estimate WFD with a robust sensor, appropriate for field settings, having thick-walled large-diameter probes that would minimize their flexing during and after installation and reduce associated errors. The HP method for measuring WFD in one dimension is based on a three-rod arrangement, aligned in the direction of the flow (vertical for leaching). A heat pulse is released from a center rod and the temperature response is monitored with upstream (US) and downstream (DS) rods. Water moving through the soil caries heat with it, causing differences in temperature response at the US and DS locations. Appropriate theory (e.g., Ren et al., 2000) is then used to determine WFD from the differences in temperature response. In this study, we have constructed sensors with large probes and developed numerical and analytical solutions for approximating the measurement. One-dimensional flow experiments were conducted with WFD ranging between 50 and 700 cm per day. A numerical model was developed to mimic the measurements, and also served for the evaluation of the analytical solution. For estimation WFD, and analytical model was developed to approximate heat transfer in this setting. The analytical solution was based on the work of Knight et al. (2012) and Knight et al. (2016), which suggests that the finite properties of the rods can be captured to a large extent by assuming them to be cylindrical perfect conductors. We found that: (1) the sensor is sensitive for measuring WFD in the investigated range, (2) the numerical model well-represents the sensor measurement, and (2) the analytical approximation could be improved by accounting for water and heat flow divergence by the large rods.
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WASHINGTON UNIV SEATTLE APPLIED PHYSICS LAB. Electrode and Electric Field Sensor Evaluation. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada397369.

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10

Merchant, Bion John. Hyperion 5113/A Infrasound Sensor Evaluation. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1221711.

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