scholarly journals 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 ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8368
Author(s):  
Kouki Fujioka
Keyword(s):  
Pilot Study ◽  
Sensory Evaluation ◽  
Electronic Nose ◽  
Consumer Preference ◽  
Oxide Semiconductor ◽  
Taste Intensity ◽  
Processed Cheese ◽  
Blue Cheese ◽  
Evaluation Scores ◽  
Cheese Aroma

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.

The use of sensory evaluation and consumer preference for the selection of sweetpotato cultivars in East Africa

2004 ◽  
Vol 84 (8) ◽  
pp. 791-799 ◽  
Author(s):  
Keith Tomlins ◽  
Elizabeth Rwiza ◽  
Abdallah Nyango ◽  
Rahila Amour ◽  
Theresia Ngendello ◽  
...  
Keyword(s):  
East Africa ◽  
Sensory Evaluation ◽  
Consumer Preference ◽  
Selection Of

scholarly journals Relationship of electronic nose analyses and sensory evaluation of vegetable oils during storage

2001 ◽  
Vol 78 (9) ◽  
pp. 937-940 ◽  
Author(s):  
N. Shen ◽  
S. Moizuddin ◽  
L. Wilson ◽  
S. Duvick ◽  
P. White ◽  
...  
Keyword(s):  
Sensory Evaluation ◽  
Vegetable Oils ◽  
Electronic Nose ◽  
Relationship Of

Electronic nose to distinguish bladder cancer by urinary odour feature: A pilot study

2020 ◽  
Vol 28 (1) ◽  
pp. 33-39 ◽  
Author(s):  
Kazumasa Matsumoto ◽  
Yasukiyo Murakami ◽  
Yuriko Shimizu ◽  
Takahiro Hirayama ◽  
Wataru Ishikawa ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Pilot Study ◽  
Electronic Nose

scholarly journals Application of Electronic Nose for Evaluation of Wastewater Treatment Process Effects at Full-Scale WWTP

Processes ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 251 ◽  
Author(s):  
Grzegorz Łagód ◽  
Sylwia M. Duda ◽  
Dariusz Majerek ◽  
Adriana Szutt ◽  
Agnieszka Dołhańczuk-Śródka
Keyword(s):  
Wastewater Treatment ◽  
Gas Sensor ◽  
Electronic Nose ◽  
Sensor Array ◽  
Treatment Plant ◽  
Full Scale ◽  
Oxide Semiconductor ◽  
Pollution Level ◽  
Gas Sensor Array

This paper presents the results of studies aiming at the assessment and classification of wastewater using an electronic nose. During the experiment, an attempt was made to classify the medium based on an analysis of signals from a gas sensor array, the intensity of which depended on the levels of volatile compounds in the headspace gas mixture above the wastewater table. The research involved samples collected from the mechanical and biological treatment devices of a full-scale wastewater treatment plant (WWTP), as well as wastewater analysis. The measurements were carried out with a metal-oxide-semiconductor (MOS) gas sensor array, when coupled with a computing unit (e.g., a computer with suitable software for the analysis of signals and their interpretation), it formed an e-nose—that is, an imitation of the mammalian olfactory sense. While conducting the research it was observed that the intensity of signals sent by sensors changed with drops in the level of wastewater pollution; thus, the samples could be classified in terms of their similarity and the analyzed gas-fingerprint could be related to the pollution level expressed by physical and biochemical indicators. Principal component analysis was employed for dimensionality reduction, and cluster analysis for grouping observation purposes. Supervised learning techniques confirmed that the obtained data were applicable for the classification of wastewater at different stages of the purification process.

scholarly journals Electronic Nose Technologies in Monitoring Black Tea Manufacturing Process

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Tharaga Sharmilan ◽  
Iresha Premarathne ◽  
Indika Wanniarachchi ◽  
Sandya Kumari ◽  
Dakshika Wanniarachchi
Keyword(s):  
Neural Network ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Black Tea ◽  
Quality Parameters ◽  
Polyphenolic Compounds ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Optimum Level ◽  
Fermentation Stage

“Tea” is a beverage which has a unique taste and aroma. The conventional method of tea manufacturing involves several stages. These are plucking, withering, rolling, fermentation, and finally firing. The quality parameters of tea (color, taste, and aroma) are developed during the fermentation stage where polyphenolic compounds are oxidized when exposed to air. Thus, controlling the fermentation stage will result in more consistent production of quality tea. The level of fermentation is often detected by humans as “first” and “second” noses as two distinct smell peaks appear during fermentation. The detection of the “second” aroma peak at the optimum fermentation is less consistent when decided by humans. Thus, an electronic nose is introduced to find the optimum level of fermentation detecting the variation in the aroma level. In this review, it is found that the systems developed are capable of detecting variation of the aroma level using an array of metal oxide semiconductor (MOS) gas sensors using different statistical and neural network techniques (SVD, 2-NM, MDM, PCA, SVM, RBF, SOM, PNN, and Recurrent Elman) successfully.

Monitoring Staling of Packaged Sliced Pan Breads: Physicochemical Properties, Sensory Evaluation, and Consumer Preference

2019 ◽  
Vol 18 (5) ◽  
pp. 396-412
Author(s):  
Anna Marinopoulou ◽  
Dimitrios Papadakis ◽  
Dimitris Petridis ◽  
Maria Papageorgiou
Keyword(s):  
Physicochemical Properties ◽  
Sensory Evaluation ◽  
Consumer Preference

scholarly journals A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2646 ◽  
Author(s):  
Henike Guilherme Jordan Voss ◽  
José Jair Alves Mendes Júnior ◽  
Murilo Eduardo Farinelli ◽  
Sergio Luiz Stevan
Keyword(s):  
Metal Oxide ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Alcohol Content ◽  
Electronic Noses

Due to the emergence of new microbreweries in the Brazilian market, there is a need to construct equipment to quickly and accurately identify the alcohol content in beverages, together with a reduced marketing cost. Towards this purpose, the electronic noses prove to be the most suitable equipment for this situation. In this work, a prototype was developed to detect the concentration of ethanol in a high spectrum of beers presents in the market. It was used cheap and easy-to-acquire 13 gas sensors made with a metal oxide semiconductor (MOS). Samples with 15 predetermined alcohol contents were used for the training and construction of the models. For validation, seven different commercial beverages were used. The correlation (R2) of 0.888 for the MLR (RMSE = 0.45) and the error of 5.47% for the ELM (RMSE = 0.33) demonstrate that the equipment can be an effective tool for detecting the levels of alcohol contained in beverages.

Discrimination of Chicken Seasonings and Beef Seasonings Using Electronic Nose and Sensory Evaluation

2014 ◽  
Vol 79 (11) ◽  
pp. S2346-S2353 ◽  
Author(s):  
Huaixiang Tian ◽  
Fenghua Li ◽  
Lan Qin ◽  
Haiyan Yu ◽  
Xia Ma
Keyword(s):  
Sensory Evaluation ◽  
Electronic Nose

scholarly journals Comparison of an Electronic Nose Based on Ultrafast Gas Chromatography, Comprehensive Two-Dimensional Gas Chromatography, and Sensory Evaluation for an Analysis of Type of Whisky

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Paulina Wiśniewska ◽  
Magdalena Śliwińska ◽  
Tomasz Dymerski ◽  
Waldemar Wardencki ◽  
Jacek Namieśnik
Keyword(s):  
Gas Chromatography ◽  
Sensory Evaluation ◽  
Electronic Nose ◽  
Quality Evaluation ◽  
Consumer Preferences ◽  
Function Analysis ◽  
Alcoholic Beverages ◽  
Two Dimensional ◽  
The Usa ◽  
Fast Gc

Whisky is one of the most popular alcoholic beverages. There are many types of whisky, for example, Scotch, Irish, and American whisky (called bourbon). The whisky market is highly diversified, and, because of this, it is important to have a method which would enable rapid quality evaluation and authentication of the type of whisky. The aim of this work was to compare 3 methods: an electronic nose based on the technology of ultrafast gas chromatography (Fast-GC), comprehensive two-dimensional gas chromatography (GC × GC), and sensory evaluation. The selected whisky brands included 6 blended whiskies from Scotland, 4 blended whiskies from Ireland, and 4 bourbons produced in the USA. For data analysis, peak heights of chromatograms were used. The panelists who took part in sensory evaluations included 4 women and 4 men. The obtained data were analyzed by 2 chemometric methods: partial least squares discriminant analysis (PLS-DA) and discrimination function analysis (DFA). E-nose and GC × GC allowed for differentiation between whiskies by type. Sensory analysis did not allow for differentiation between whiskies by type, but it allowed giving consumer preferences.

Sign in / Sign up

Export Citation Format

Share Document