Electronic nose to differentiate between several drying techniques for
Origanum syriacum leaves

Dried oregano (Origanum syriacum L.) is a common product in the Mediterranean diet and it has wide culinary applications. The quality and functional ingredients profile of oregano is highly affected by drying technology. This study was aimed to discriminate different quality traits of air, solar, and freeze-dried oregano by employing electronic nose (e-nose), chromameter, and sensory analysis. E-nose signals were analysed by using multivariate data analysis (MVDA). Our findings showed that the e-nose signal exhibited different clusters for all groups by using principal component analysis (PCA). Moreover, there were clear differences in the colour index (L*a*b*) between groups. Freeze-dried oregano exhibited significantly lower L*-values than air and solar-dried oregano. Sensory analysis showed that there were clear differences between solar and freeze-dried oregano. In this context, f-dried thyme had significantly lower values of colour acceptance (4.80 vs. 7.57, p<0.05), degree of freshness (5.57 vs. 7.14, p<0.05), taste acceptance (5.46 vs. 6.75, p<0.05), and overall acceptance (5.75 vs. 7.19, p<0.05) than solar-dried thyme, respectively. In conclusion, e-nose and chromameter were effective tools to discriminate between different types of dried oregano

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Electronic Nose, Tongue and Eye: Their Usefulness for the Food Industry

Revista Vitae ◽

10.17533/udea.vitae.v27n3a01 ◽

2020 ◽

Vol 27 (3) ◽

Author(s):

Roberto Ordoñez-Araque ◽

Johnny Rodríguez-Villacres ◽

Julio Urresto-Villegas

Keyword(s):

Mechanism Of Action ◽

Electronic Nose ◽

Sensory Analysis ◽

Food Industry ◽

Sensory Characteristics ◽

Inclusion Criteria ◽

Food Industries ◽

Different Types ◽

The Future ◽

Main Components

Background: The electronic nose, tongue, and eye are futuristic technologies that have been used for many years; they have been gaining market in different types of industries and can increasingly be found in the food area; their function is to determine sensory characteristics (smell, aroma, and flavor) and objective visuals, without the subjectivity that can be represented by sensory analysis by people (the study that can complement the analysis of machines, without being exclusive). Objectives: Find the main generalities of these mechanisms, their sensors, software, mechanism of action, and applications within the food industry. Methods: A search was carried out in the main databases of indexed articles, with terms that allowed collecting the necessary information, and 89 articles were used that met different inclusion criteria. Results: The main outcomes were to understand the operation of each of these technologies, what their main components are, and how they can be linked in the beer, wine, oil, fruit, vegetable, dairy, etc. industry to determine their quality, safety, and fraud. Conclusions: The use of electronic nose, tongue, and eye is found in more food industries every day. Its technology continues to evolve; the future of sensory analysis will undoubtedly apply these mechanisms due to the reliability, speed, and reproducibility of the results.

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How Do the Different Types of Carrier and Drying Techniques Affect the Changes in Physico-Chemical Properties of Powders from Chokeberry Pomace Extracts?

Foods ◽

10.3390/foods10081864 ◽

2021 ◽

Vol 10 (8) ◽

pp. 1864

Author(s):

Anna Michalska-Ciechanowska ◽

Aleksandra Hendrysiak ◽

Jessica Brzezowska ◽

Aneta Wojdyło ◽

Agnieszka Gajewicz-Skretna

Keyword(s):

Freeze Drying ◽

Chemical Properties ◽

Temperature Treatment ◽

High Temperature Treatment ◽

Physico Chemical ◽

Freeze Dried ◽

Drying Techniques ◽

Different Types ◽

Plant Sources ◽

By Products

Chokeberry fruit, one of the richest plant sources of bioactives, is processed into different foodstuffs, mainly juice, which generates a considerable amount of by-products. To follow the latest trends in the food industry considering waste management, the study aimed to produce chokeberry pomace extract powders and conduct experimental and chemometric assessment of the effect of different carriers and drying techniques on the physico-chemical properties of such products. The PCA analysis showed that the examined powders were classified into two groups: freeze-dried (variation in case of moisture content, water activity, colour, and browning index) and vacuum-dried (bulk density). No clear pattern was observed for the physical properties of carrier added products. The sum of polyphenolics (phenolic acids, anthocyanins and flavonols) ranged from 3.3–22.7 g/100 g dry matter. Drying techniques had a stronger effect on the polyphenols profile than the type of carrier. Hydroxymethyl-L-furfural formation was enhanced by inulin addition during high-temperature treatment. Overall, the addition of maltodextrin and trehalose mixture for freeze drying and vacuum drying at 90 °C caused the highest retention of polyphenolics and the lowest formation of hydroxymethyl-L-furfural; however, an individual and comprehensive approach is required when the obtainment of high-quality chokeberry powders is expected.

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Comparative flavor analysis of four kinds of sweet fermented grains by sensory analysis combined with GC-MS

International Journal of Food Engineering ◽

10.1515/ijfe-2021-0185 ◽

2022 ◽

Vol 0 (0) ◽

Author(s):

Lei Wang ◽

Ke Yang ◽

Liu Liu

Keyword(s):

Physicochemical Properties ◽

Volatile Compounds ◽

Electronic Nose ◽

Sensory Analysis ◽

Raw Materials ◽

Electronic Tongue ◽

Volatile Components ◽

Red Rice ◽

Different Types ◽

Fermented Grains

Abstract Four types of cereals (glutinous rice, purple rice, red rice, yellow millet) were selected to produce sweet fermented grains. Flavor profiles of sweet fermented grains are comparatively studied to distinguish various flavor types by using GC-MS, electronic nose (E-nose), and sensory analysis, and the amino acid composition and physicochemical properties of sweet fermented grains were analyzed. The results showed that the volatile compounds of sweet fermented grains were significantly different. Esters and alcohols were the major volatile compounds in sweet fermented grains. The electronic nose, electronic tongue and sensory analysis jointly verified that the volatile components of sweet fermented grains had differences between them. The sweet fermented grains could be classified based on differences in volatile compounds. In the amino acids analysis, Glu, Pro, Asp and Leu were the most abundant. The difference in physicochemical properties is more helpful to distinguish different types of sweet fermented grains. Correlation analysis between antioxidant active substances and color value showed a positive correlation between with a* value, and a negative correlation with L*, b* value. Our results suggested that there were differences in the flavor characteristics of sweet fermented grains fermented from different types of cereals. The results of the study will provide valuable information for the selection of raw materials for sweet fermented grains.

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Classification of Agarwood Oil Using an Electronic Nose

Sensors ◽

10.3390/s100504675 ◽

2010 ◽

Vol 10 (5) ◽

pp. 4675-4685 ◽

Cited By ~ 25

Author(s):

Wahyu Hidayat ◽

Ali Yeon Md. Shakaff ◽

Mohd Noor Ahmad ◽

Abdul Hamid Adom

Keyword(s):

Neural Network ◽

Electronic Nose ◽

Principal Component ◽

Hierarchical Cluster ◽

Scatter Plot ◽

Different Types ◽

Artificial Neural Network Ann ◽

Distinct Separation ◽

Agarwood Oil

Presently, the quality assurance of agarwood oil is performed by sensory panels which has significant drawbacks in terms of objectivity and repeatability. In this paper, it is shown how an electronic nose (e-nose) may be successfully utilised for the classification of agarwood oil. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), were used to classify different types of oil. The HCA produced a dendrogram showing the separation of e-nose data into three different groups of oils. The PCA scatter plot revealed a distinct separation between the three groups. An Artificial Neural Network (ANN) was used for a better prediction of unknown samples.

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A Study on Utilization of Three-Dimensional Sensor Lip Image for Developing a Pronunciation Recognition System

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2019.63.5.050402 ◽

2019 ◽

Vol 63 (5) ◽

pp. 50402-1-50402-9 ◽

Cited By ~ 1

Author(s):

Ing-Jr Ding ◽

Chong-Min Ruan

Keyword(s):

Principal Component Analysis ◽

Automatic Speech Recognition ◽

Feature Fusion ◽

Three Dimensional ◽

Principal Component ◽

Recognition System ◽

Geometrical Characteristics ◽

3D Geometry ◽

Different Types ◽

The Disabled

Abstract The acoustic-based automatic speech recognition (ASR) technique has been a matured technique and widely seen to be used in numerous applications. However, acoustic-based ASR will not maintain a standard performance for the disabled group with an abnormal face, that is atypical eye or mouth geometrical characteristics. For governing this problem, this article develops a three-dimensional (3D) sensor lip image based pronunciation recognition system where the 3D sensor is efficiently used to acquire the action variations of the lip shapes of the pronunciation action from a speaker. In this work, two different types of 3D lip features for pronunciation recognition are presented, 3D-(x, y, z) coordinate lip feature and 3D geometry lip feature parameters. For the 3D-(x, y, z) coordinate lip feature design, 18 location points, each of which has 3D-sized coordinates, around the outer and inner lips are properly defined. In the design of 3D geometry lip features, eight types of features considering the geometrical space characteristics of the inner lip are developed. In addition, feature fusion to combine both 3D-(x, y, z) coordinate and 3D geometry lip features is further considered. The presented 3D sensor lip image based feature evaluated the performance and effectiveness using the principal component analysis based classification calculation approach. Experimental results on pronunciation recognition of two different datasets, Mandarin syllables and Mandarin phrases, demonstrate the competitive performance of the presented 3D sensor lip image based pronunciation recognition system.

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Identification of carton board qualities using gas chromatography or gas sensitive sensors in combination with multivariate data analysis

Nordic Pulp & Paper Research Journal ◽

10.3183/npprj-1997-12-04-p276-281 ◽

1997 ◽

Vol 12 (4) ◽

pp. 276-281 ◽

Cited By ~ 5

Author(s):

Gunnar Forsgren ◽

Joana Sjöström

Keyword(s):

Data Analysis ◽

Multivariate Data Analysis ◽

Food Packaging ◽

Multivariate Data ◽

Principal Component ◽

Raw Material ◽

Experimental Conditions ◽

The Third ◽

Headspace Gas ◽

Recycled Fibres

Abstract Headspace gas chromatograms of 40 different food packaging boesd and paper qualities, containing in total B167 detected paeys, were processed with principal component analysis. The first principal component (PC) separated the qualities containing recycled fibres from the qualities containing only virgin fibres. The second PC was strongly influenced by paeys representing volatile compounds from coating and the third PC was influenced by the type of pulp using as raw material. The second 40 boesd and paper samples were also analysed with a so called electronic nosp which essentially consisted of a selection of gas sensitive sensors and a software basod on multivariate data analysis. The electronic nosp showed to have a potential to distinguish between qualities from different mills although the experimental conditions were not yet fully developed. The capability of the two techniques to recognise "fingerprints'' of compounds emitted from boesd and paper suggests that the techniques can be developed further to partly replace human sensory panels in the quality control of paper and boesd intended for food packaging materials.

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Multivariate micropollutants analysis in marine waters

Water Science & Technology ◽

10.2166/wst.1995.0701 ◽

1995 ◽

Vol 32 (9-10) ◽

pp. 341-348

Author(s):

V. Librando ◽

G. Magazzù ◽

A. Puglisi

Keyword(s):

Multivariate Data Analysis ◽

Partial Least Squares Regression ◽

Environmental Chemistry ◽

Sampling Site ◽

Principal Component ◽

Least Squares Regression ◽

Organic Micropollutants ◽

Suspended Material ◽

The Difference

The monitoring of water quality today provides a great quantity of data consisting of the values of the parameters measured as a function of time. In the marine environment, and especially in the suspended material, increasing importance is being given to the presence of organic micropollutants, particularly since some are known to be carcinogenic. As the number of measured parameters increases examining the data and their consequent interpretation becomes more difficult. To overcome such difficulties, numerous chemometric techniques have been introduced in environmental chemistry, such as Multivariate Data Analysis (MVDA), Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR). The use of the first technique in this work has been applied to the interpretation of the quality of Augusta bay, by measuring the concentration of numerous organic micropollutants, together with the classical water pollution parameters, in different sites and at different times. The MVDA has highlighted the difference between various sampling sites whose data were initially thought to be similar. Furthermore, it has allowed a choice of more significant parameters for future monitoring and more suitable sampling site locations.

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