scholarly journals Wearable Electronic Tongue for Non-Invasive Assessment of Human Sweat

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7311
Author(s):  
Magnus Falk ◽  
Emelie J. Nilsson ◽  
Stefan Cirovic ◽  
Bogdan Tudosoiu ◽  
Sergey Shleev
Keyword(s):  
Principal Component Analysis ◽  
Chemical Composition ◽  
Electronic Tongue ◽  
Principal Component ◽  
The Body ◽  
Circuit Board ◽  
Metal Electrodes ◽  
Non Invasive ◽  
Wearable Electronic ◽  
Voltammetric Electronic Tongue

Sweat is a promising biofluid in allowing for non-invasive sampling. Here, we investigate the use of a voltammetric electronic tongue, combining different metal electrodes, for the purpose of non-invasive sample assessment, specifically focusing on sweat. A wearable electronic tongue is presented by incorporating metal electrodes on a flexible circuit board and used to non-invasively monitor sweat on the body. The data obtained from the measurements were treated by multivariate data processing. Using principal component analysis to analyze the data collected by the wearable electronic tongue enabled differentiation of sweat samples of different chemical composition, and when combined with 1H-NMR sample differentiation could be attributed to changing analyte concentrations.

scholarly journals Ripening Changes of the Chemical Composition, Proteolysis, and Lipolysis of a Hair Sheep Milk Mexican Manchego-Style Cheese: Effect of Nano-Emulsified Curcumin

Foods ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1579
Author(s):  
Mariam Sardiñas-Valdés ◽  
Hugo Sergio García-Galindo ◽  
Alfonso Juventino Chay-Canul ◽  
José Rodolfo Velázquez-Martínez ◽  
Josafat Alberto Hernández-Becerra ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Antioxidant Activity ◽  
Chemical Composition ◽  
Phenolic Content ◽  
Principal Component ◽  
Total Phenolic ◽  
Hair Sheep ◽  
Dairy Foods ◽  
Ripening Time ◽  
Sheep Milk

The influence of nano-emulsified curcumin (NEC) added to the hair sheep milk, prior to cheese-making, on the chemical composition, lipolysis, and proteolysis of manchego-style cheeses were evaluated throughout 80 days of ripening. The addition of NEC to the milk resulted in cheeses with the same moisture content (42.23%), total protein (23.16%), and water activity (0.969) (p > 0.05). However, it increased the fat and ash levels from 26.82% and 3.64% in B 10 ppm to 30.08% and 3.85% in C 10 ppm, respectively, at the end of the ripening (p < 0.05). The total phenolic content and antioxidant activity of experimental cheeses increased during ripening, and the fatty acid groups showed significant changes occurred to a greater extent in the first days of ripening (p < 0.05). The lipolysis increased consistently in all cheeses until day 40 of ripening, to decrease at the end, while proteolysis increased during all ripening time in all samples (p < 0.05); the addition of NEC did not alter the primary proteolysis of manchego-style cheeses, but it modified secondary proteolysis and lipolysis (p < 0.05). Principal component analysis was useful for discriminating cheeses according to their chemical composition and classified into four groups according to their ripening time. This research highlights the potential of CNE to fortify dairy foods to enhance their functionality.

scholarly journals Identification of Umami Taste in Sous-Vide Beef by Chemical Analyses, Equivalent Umami Concentration, and Electronic Tongue System

Foods ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 251 ◽  
Author(s):  
Young-Hwa Hwang ◽  
Ishamri Ismail ◽  
Seon-Tea Joo
Keyword(s):  
Amino Acids ◽  
Principal Component Analysis ◽  
Food Processing ◽  
Free Amino Acids ◽  
Free Amino ◽  
Electronic Tongue ◽  
Principal Component ◽  
Chemical Analyses ◽  
Umami Taste ◽  
Sous Vide

Behaviour of umami compounds that are associated with non-volatile compounds on slow cooking regimes remains less explored. This study aims to assess the ability of the electronic tongue system on the umami taste from sous-vide beef semitendinosus. The identification was based on the taste-enhancing synergism between umami compounds 5’-nucleotides (IMP, GMP, AMP, inosine, and hypoxanthine) and free amino acids (glutamic and aspartic acid) using the estimation of equivalent umami concentration (EUC) and electronic tongue system. Sous-vide cooked at 60 and 70 °C for 6 and 12 h and cooked using the conventional method at 70 °C for 30 min (as control) were compared. The temperature had a significant effect on 5’-nucleotides, but aspartic and glutamic acid were not influenced by any treatments applied. Sous-vide cooked at 60 °C tended to have higher inosine and hypoxanthine. Meanwhile, desirable 5’-nucleotides IMP, AMP, and GMP were more intensified at the temperature of 70 °C. The principal component analysis predicted a good correlation between EUC and the electronic tongue, with sous-vide at 70 °C for 12 h presenting the most umami. Therefore, the electronic tongue system is a useful tool in food processing, particularly in determining complex sensory properties such as umami, which cannot be evaluated objectively.

scholarly journals Optimization of Sensors to be Used in a Voltammetric Electronic Tongue Based on Clustering Metrics

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4798
Author(s):  
Munmi Sarma ◽  
Noelia Romero ◽  
Xavier Cetó ◽  
Manel del Valle
Keyword(s):  
A Priori ◽  
Electronic Tongue ◽  
Principal Component ◽  
Canonical Variate ◽  
Ann Model ◽  
Inclusion Removal ◽  
Discrimination Ability ◽  
Improved Performance ◽  
Voltammetric Electronic Tongue ◽  
The Impact

Herein we investigate the usage of principal component analysis (PCA) and canonical variate analysis (CVA), in combination with the F factor clustering metric, for the a priori tailored selection of the optimal sensor array for a given electronic tongue (ET) application. The former allows us to visually compare the performance of the different sensors, while the latter allows us to numerically assess the impact that the inclusion/removal of the different sensors has on the discrimination ability of the ET. The proposed methodology is based on the measurement of a pure stock solution of each of the compounds under study, and the posterior analysis by PCA/CVA with stepwise iterative removal of the sensors that demote the clustering when retained as part of the array. To illustrate and assess the potential of such an approach, the quantification of paracetamol, ascorbic acid, and uric acid mixtures were chosen as the study case. Initially, an array of eight different electrodes was considered, from which an optimal array of four sensors was derived to build the quantitative ANN model. Finally, the performance of the optimized ET was benchmarked against the results previously reported for the analysis of the same mixtures, showing improved performance.

Evaluation of Sweet Sauce Characteristic Taste Based on Electronic Tongue Technology

2012 ◽  
Vol 554-556 ◽  
pp. 1593-1601
Author(s):  
Ming Quan Huang ◽  
Lu Wang ◽  
Bao Guo Sun ◽  
Hong Yu Tian
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Reducing Sugars ◽  
Electronic Tongue ◽  
Amino Nitrogen ◽  
Physicochemical Characterization ◽  
Principal Component ◽  
On Line

A commercial electronic tongue (ET) with specific sensors was applied on taste distinction and physicochemical characterization of seven kinds of sweet sauces. The response signals of ET sensors were analyzed by Principal Component Analysis (PCA) and Discriminant Factor Analysis (DFA). Meanwhile, these signals were transformed into the four relative taste scores (sourness, saltiness, umami and sweetness) by macro operation, followed by comparing with the corresponding four physiochemical indexes (total acids, sodium chloride, amino nitrogen and reducing sugars) which were determined by the methods in GB/T. The results show that ET can be used to distinguish different kinds of sweet sauces according to overall taste. Moreover, the intensity order of taste scores that obtained from ET is basically matched with the sequence of the corresponding physicochemical indexes, which proves that ET technique can be an effective approach to monitor and guarantee the quality of sweet sauce on line.

scholarly journals Variability in size and shape in muscovy duck with age: Principal component analysis

2014 ◽  
Vol 30 (1) ◽  
pp. 125-136 ◽  
Author(s):  
D.M. Ogah ◽  
M. Kabir
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Principal Component ◽  
Component Analysis ◽  
The Body ◽  
Dependence Structure ◽  
Muscovy Duck ◽  
Body Measurements ◽  
Male And Female ◽  
Size And Shape

Body weight and six linear body measurements, body length (BL), breast circumference (BCC), thigh length (TL), shank length (SL), total leg length (TLL) and wing length were recorded on 150 male and female muscovy ducklings and evaluated at 3, 5, 10, 15 and 20 weeks of age. Principal component analysis was used to study the dependence structure among the body measurements and to quantify sex differences in morphometric size and shape variations during growth. The first principal components at each of the five ages in both sexes accounted between 71.54 to 92.95% of the variation in the seven measurements and provided a linear function of size with nearly equal emphasis on all traits. The second principal components in all cases also accounted for between 6.7 to 16.17% of the variations in the dependence structure of the system in the variables as shape, the coefficient for the PCs at various ages were sex dependent with males showing higher variability because of spontaneous increase in size and shape than females. Contribution of the general size factor to the total variance increase with age in both male and female ducklings, while shape factor tend to be stable in males and inconsistent in females.

scholarly journals Principal component analysis of the exterior traits in dairy cows

2017 ◽  
Vol 19 (79) ◽  
Author(s):  
S. Kramarenko ◽  
N. Kuzmicheva ◽  
A. Kramarenko
Keyword(s):  
Principal Component Analysis ◽  
Dairy Cows ◽  
Principal Component ◽  
Component Analysis ◽  
The Body ◽  
Chest Circumference ◽  
State Enterprise ◽  
Body Measurements ◽  
Generalized Variance ◽  
Diagonal Length

The present study was undertaken to study the relationship between different body measurements and to develop unobservable factors (latent) to define which of these measurements best represent body conformation in the dairy cows. Biometrical observations were recorded on 109 Red Steppe dairy cows randomly selected from State Enterprise «Breeding reproducer «Stepove» (Mykolayiv region, Ukraine) during the 2001–2014. Principal Component Analysis (PCA) was used to account for the maximum portion of variation present in the original set of variables (body traits in cow) with a minimum number of composite variables through STATISTICA software. Most of the pairwise phenotypic correlations among the exterior traits in dairy cows were positive and significant. The Pearson’s correlation coefficients of the body measurements ranged from 0.215 (chest depth – cannon circumference) to 0.889 (height at withers – rump height). In factor solution of the Principal Component Analysis, two (latent) which explained 48.5% of the generalized variance were extracted. The first principal component (PC1) explained general body confirmation and explained 33.5% variation. It was represented by significant positive loading for height at withers, rump height, diagonal length from point of shoulder to pin bone, chest depth, chest circumference etc.). The second principal component (PC2) accounted for an additional 15.0% of the generalized variance and was interpreted as an indicator of body shape (e.g., endomorphic vs. ectomorphic). It was represented by significant negative loadings for height at withers, rump height, diagonal length from point of shoulder to pin bone, but significant positive loadings for chest width, chest depth, chest circumference and cannon circumference. The study also revealed that factors extracted from the present investigation could be used in breeding programs of the dairy cattle.

scholarly journals Assessment of body weight and morphological traits of two breed of grower pigs using principal component analysis

2021 ◽  
Vol 48 (5) ◽  
pp. 1-11
Author(s):  
P.O. Akporhuarho ◽  
O. Iriakpe
Keyword(s):  
Principal Component Analysis ◽  
Body Weight ◽  
Body Length ◽  
Principal Component ◽  
Component Analysis ◽  
The Body ◽  
Head Length ◽  
Large White ◽  
Poids Corporel ◽  
The Mean

The study aimed at explaining objectively the relationship between morphologic traits of two breeds of pigs (Large-white and Duroc) using principal component analysis to determine the body size of grower pigs of two different breeds with a view of identifying components that best define body conformation. Body weight and five biometric variables namely head length, body length, body girth, ham length and ear length. The descriptive statistics showed that the mean body weight of Large-white was 13.14kg while the body measurements were 24.61cm, 71.35cm, 65.12cm, 43.13cm and 21.94cm for head length, body length, body girth, ham length and ear length respectively at 5 – 24 weeks of age. The mean body weight of Duroc was 12.87kg while the body measurements were 23.70cm, 57.93cm, 47.93cm, 22.90cm, 19.26cm for head length, body length, body girth, ham length and ear length respectively. The coefficient of correlation ranges from 0.08-0.424 and 0.01-0.402 for Large-white and Duroc respectively. The association between and were the highest for Duroc, body length r=0.402 and Large-white, body girth 0.424. Two components were identified for Large-white while those of Duroc were three components. The ratios of variance were 53.55 and 71.07% for Large-white and Duroc, respectively. The first factor in each case accounted for the biggest percentage of the total variation, and was designated the general size, the other factors (indices of body shape) offer forms of variation independent of the general size. The principal component based regression models which were chosen for selecting animals for optimal balance accounted for 58 and 76% of the variation in the body weight for Large-white and Duroc respectively. The study concluded that the use of principal component analysis techniques tends to explore the interdependence in the original five parameters measured: head length, body length, body girth, ham length and ear length of Large-white and Duroc     L'étude explique objectivement la relation entre les traits morphologiques de deux races de porcs (gros blanc et de Duroc) à l'aide d'une analyse de composants principaux afin de déterminer la taille du corps des porcs de producteurs de deux races différentes en vue d'identifier les composants qui définissent le mieux la conformation corporelle. Poids corporel et cinq variables biométriques, nommément longueur de la tête, longueur du corps, circonférence du corps, longueur du jambon et longueur de l'oreille. Les statistiques descriptives ont montré que le poids corporel moyen de gros blanc était de 13,14 kg tandis que les mesures du corps étaient de 24,61 cm, 71,35 cm, 65,12 cm, 43,13 cm et 21,94 cm pour la longueur de la tête, la longueur du corps, la circonférence du corps, la longueur du jambon et la longueur de l'oreille respectivement à 5 - 24 semaines. Le poids corporel moyen de Duroc était de 12,87 kg tandis que les mesures du corps étaient de 23,70 cm, 57,93 cm, 47,93 cm, 22,90 cm, 19,26 cm pour la longueur de la tête, la longueur du corps, la circonférence du corps, la longueur du jambon et la longueur de l'oreille respectivement. Le coefficient de corrélation varie de 0,08 à 0,424 et de 0,01 à 0,402 pour les gros blancs et Duroc respectivement. L'association entre et étaient les plus élevées pour Duroc, la longueur du corps R = 0,402 et de gros blancs, la circonférence du corps 0,424. Deux composants ont été identifiés pour les gros blancs tandis que ceux de Duroc étaient trois composants. Les ratios de variance étaient respectivement de 53,55 et 71,07% pour les gros blancs et Duroc. Le premier facteur de chaque cas représentait le plus gros pourcentage de la variation totale et a été désigné la taille générale, les autres facteurs (indices de la forme du corps) offrent des formes de variation indépendantes de la taille générale. Les principaux modèles de régression basés sur les composants choisis pour sélectionner des animaux pour un solde optimal représentaient 58 et 76% de la variation du poids corporel pour les grands blancs et Duroc respectivement. L'étude a conclu que l'utilisation de techniques d'analyse des composants principaux a tendance à explorer l'interdépendance dans les cinq paramètres d'origines mesurées: longueur de la tête, longueur du corps, circonférence corporelle, longueur du jambon et longueur de l'oreille de grosse blanc et de Duroc

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