Identification of Tea Storage Times by Linear Discrimination Analysis and Back-Propagation Neural Network Techniques Based on the Eigenvalues of Principal Components Analysis of E-Nose Sensor Signals

An electronic nose (E-nose) was employed to detect the aroma of green tea after different storage times. Longjing green tea dry leaves, beverages and residues were detected with an E-nose, respectively. In order to decrease the data dimensionality and optimize the feature vector, the E-nose sensor response data were analyzed by principal components analysis (PCA) and the five main principal components values were extracted as the input for the discrimination analysis. The storage time (0, 60, 120, 180 and 240 days) was better discriminated by linear discrimination analysis (LDA) and was predicted by the back-propagation neural network (BPNN) method. The results showed that the discrimination and testing results based on the tea leaves were better than those based on tea beverages and tea residues. The mean errors of the tea leaf data were 9, 2.73, 3.93, 6.33 and 6.8 days, respectively

Improved Classification of Orthosiphon stamineus by Data Fusion of Electronic Nose and Tongue Sensors

An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together

Classification and Identification of Volatile Organic Solvents based on Functional Groups using Electronic Nose

The Metal Oxide Semiconductor gas sensors based on SnO2 indicate cross sensitivity to many volatile organic compounds. Therefore, this study is focused on developing a methodology to distinguish organic solvents based on the functional groups present using an array of Metal Oxide Semiconductor gas sensors. Here, representative compounds for aliphatic, aromatic hydrocarbons, carbonyl groups, esters, alcohols and dichloromethane were used to evaluate gas sensors. Then data were analyzed using Principal Component Analysis and k-Nearest Neighbor methods. Finally, k-Nearest Neighbor best model was developed to predict the chemicals based on the sensor data. The overall results of this study sufficiently explain that the developed electronic nose system can distinguish the chemicals tested with Principal Component Analysis (96.6 percentage) and can predict with k-Nearest Neighbor (k=5) (90 percentage) the chemicals based on the sensor responses. These results demonstrate that the developed electronic nose can be used to classify and identify chemicals based in different functional groups

Decoding Complex Chemical Mixtures with a Physical Model of a Sensor Array

Combinatorial sensor arrays, such as the olfactory system, can detect a large number of analytes using a relatively small number of receptors. However, the complex pattern of receptor responses to even a single analyte, coupled with the non-linearity of responses to mixtures of analytes, makes quantitative prediction of compound concentrations in a mixture a challenging task. Here we develop a physical model that explicitly takes receptor-ligand interactions into account, and apply it to infer concentrations of highly related sugar nucleotides from the output of four engineered G-protein-coupled receptors. We also derive design principles that enable accurate mixture discrimination with cross-specific sensor arrays. The optimal sensor parameters exhibit relatively weak dependence on component concentrations, making a single designed array useful for analyzing a sizable range of mixtures. The maximum number of mixture components that can be successfully discriminated is twice the number of sensors in the array. Finally, antagonistic receptor responses, well-known to play an important role in natural olfactory systems, prove to be essential for the accurate prediction of component concentrations

Electronic sensor technologies in monitoring quality of tea: A review

Tea, after water, is the most frequently consumed beverage in the world. The fermentation of tea leaves has a pivotal role in its quality and is usually monitored using the laboratory analytical instruments and olfactory perception of tea tasters. Developing electronic sensing platforms (ESPs), in terms of an electronic nose (e-nose), electronic tongue (e-tongue), and electronic eye (e-eye) equipped with progressive data processing algorithms, not only can accurately accelerate the consumer-based sensory quality assessment of tea, but also can define new standards for this bioactive product, to meet worldwide market demand. Using the complex data sets from electronic signals integrated with multivariate statistics can, thus, contribute to quality prediction and discrimination. The latest achievements and available solutions, to solve future problems and for easy and accurate real-time analysis of the sensory-chemical properties of tea and its products, are reviewed using bio-mimicking ESPs. These advanced sensing technologies, which measure the aroma, taste, and color profiles and input the data into mathematical classification algorithms, can discriminate different teas based on their price, geographical origins, harvest, fermentation, storage times, quality grades, and adulteration ratio. Although voltammetric and fluorescent sensor arrays are emerging for designing e-tongue systems, potentiometric electrodes are more often employed to monitor the taste profiles of tea. The use of a feature-level fusion strategy can significantly improve the efficiency and accuracy of prediction models, accompanied by the pattern recognition associations between the sensory properties and biochemical profiles of tea

Caracterización de la textura de muestras de plátano mediante el análisis no destructivo basado en el estudio de patrones laser

[ES] Los plátanos pertenecen a la familia Musaceae (género Musa) y son un cultivo altamente perecedero producido en áreas tropicales y subtropicales del mundo. Los plátanos se subdividen en cultivares cuyas prestaciones fundamentales son la cocción (Musa spp AAB y ABB) y cultivares para consumo en fresco (Musa spp AA y AAA), si bien estos últimos también pueden ser transformados. Tras la recolección, el plátano sufre cambios madurativos muy rápidos que afectan a su calidad. Entre estos, el principal es la perdida de textura. La pérdida de dureza genera rechazos en los consumidores cuando este es consumido en fresco, pero también afecta directamente a su procesado (cocción, fritura, deshidratación, etc.). Las técnicas texturales utilizadas se basan en ensayos destructivos a partir de la medida de la dureza mediante ensayos con texturómetros. Estas técnicas son muy fiables, pero destruyen la muestra lo que impide que esta pueda ser utilizada posteriormente para otro ensayo o su procesado y, por tanto, este tipo de ensayos se realizan sólo sobre un segmento de muestras representativas de la producción y, no, sobre cada una de las muestras. Es por ello que en el presente trabajo se plantea la utilización de la técnica del análisis de imagen de patrones láser para la caracterización de la textura de plátanos. Esta técnica ha demostrado su capacidad tanto en la caracterización de productos (galletas, aceites, etc.) como de procesos de transformación (fermentación del yogurt, queso, fusión de aceites, etc.). Para llevar a cabo la experiencia se van a utilizar plátanos de canarias de indicación geográfica protegida variedad Cavendish. El estudio se centrará en, periódicamente, analizar mediante la técnica láser, textural y brix, la maduración de los plátanos a lo largo de su período de comercialización. A tal fin, los plátanos serán cortados en rodajas de aproximadamente 1 cm a lo largo de estos, midiéndose de forma individualizada cada uno de ellos. Mediante el estudio se evaluará cada una de las muestras mediante las tres técnicas a fin de poder correlacionar tanto la textura como los brix con la expresión láser y poder obtener un modelo que nos permita predecir la textura sin la necesidad de destruir la muestra.[EN] Bananas belong to the Musaceae family (genus Musa) and are a highly perishable crop produced in tropical and subtropical areas of the world. Bananas are subdivided into cultivars; the main benefits are cooking (Musa spp AAB and ABB) and cultivars for fresh consumption (Musa spp AA and AAA), although the latter can also be transformed. After harvesting, the banana undergoes very rapid ripening changes that affect its quality. Among these, the main one is the loss of texture. The loss of hardness generates rejections in consumers when it is consumed fresh, but it also directly affects its processing (cooking, frying, dehydration, etc ...). The textural techniques used are based on destructive tests from the measurement of hardness through tests with texturometers. These techniques are very reliable, but they destroy the sample, which prevents it from being used later for another test or its processing, and therefore this type of test is carried out only on a segment of representative samples of production and not on each one. of the samples. It is for this reason that in the present work the use of the technique of image analysis of laser patterns for the characterization of the texture of bananas is proposed. This technique has demonstrated its ability both in the characterization of products (biscuits, oils, etc.) and of transformation processes (fermentation of yogurt, cheese, melting of oils, etc.). To carry out the experiment, bananas from the Canary Islands of the protected geographical indication variety Cavendish will be used. The study will periodically focus on analyzing, using the laser, textural and brix technique, the ripening of bananas throughout their marketing period. To this end, the bananas will be cut into slices of approximately 1 cm along these, each one being measured individually. Through the study, each of the samples will be evaluated using the three techniques in order to be able to correlate both the texture and the brix with the laser expression and be able to obtain a model that allows us to predict the texture without the need to destroy the sample.Martí Sala, A. (2021). Caracterización de la textura de muestras de plátano mediante el análisis no destructivo basado en el estudio de patrones laser. Universitat Politècnica de València. http://hdl.handle.net/10251/171015TFG

Aproximación de la técnica de análisis de patrones láser para la caracterización de la textura de carne durante su maduración

[ES] En el presente trabajo se ha evaluado la capacidad de la técnica de imagen basada en el reconocimiento de patrones de dispersión láser para la caracterización en continuo del proceso de maduración de la carne. Esta técnica se basa en hacer incidir la luz coherente de un láser sobre la muestra, de forma que este láser interacciona con la matriz del alimento, generando patrones de luz que se analizarán ulteriormente mediante el uso de descriptores y variables obtenidas de estos patrones y de los píxeles que componen las imágenes. El hecho de ser un análisis en continuo es un aspecto de crucial importancia, dado que el proceso de maduración de la carne es un proceso dinámico y continuo. Esto es posible gracias a que se trata de una técnica no destructiva, lo que supone una gran ventaja sobre las tradicionales técnicas destructivas. Para llevar a cabo la experiencia se utilizaron filetes de ternera de corte comercial, estos presentan una homogeneidad en su espesor. Con la finalidad de incrementar los cambios que sufre la carne durante su maduración, a un lote se le añadió superficialmente un enzima exógeno, papaína. Durante las 26 horas que duró la experiencia, se fueron tomando medidas periódicamente con la finalidad de analizar paralelamente la textura y la variación del patrón láser generado. El análisis de textura se realizó mediante el método de corte Warner-Bratzler. Para el análisis de imagen, las muestras fueron dispuestas de forma que dos láseres, no al unísono, incidían sobre la muestra. Uno dispuesto sobre la muestra con un ángulo de 45o respecto a la vertical entre la cámara y la muestra y el otro situado en la parte inferior de la muestra, en la misma vertical que la muestra y la cámara. Las imágenes tomadas registran los patrones láser y son procesadas extrayendo descriptores que las caracterizan, estos son analizados mediante análisis estadísticos multivariados y correlacionados con los resultados de textura. Los resultados han mostrado como el análisis de patrones de dispersión láser permite caracterizar el estado de maduración de la carne, aportando información sobre su textura de una forma continua y no destructiva, siempre y cuando la disposición del láser sea en la parte inferior de la muestra y en la misma vertical que ésta y la cámara. Además, han evidenciado como la aplicación del enzima incrementa la velocidad de los cambios en la carne, pero también la formación de un gel superficial que minimiza los cambios en los patrones del láser. Aun así, los descriptores obtenidos a partir de la información procedente del análisis de imagen, así como su reducción a una sola componente principal, se han correlacionado muy bien con los valores de textura de las muestras a lo largo del estudio, tanto para las muestras sin enzima añadido como en las añadidas, describiendo estas. Esto ha permitido poder obtener modelos teóricos que pueden minimizar el efecto gel superficial de las muestras con enzima exógeno añadido, caracterizando su textura al igual que con las muestras de carne control.[EN] The capacity of the image technique based on the recognition of laser dispersion patterns for the continuous characterization of the meat maturation process has been evaluated in this paper. This technique is based on involving the coherent light of a laser on the sample, so that this laser interacts with the food matrix, generating patterns of light that will be further analyzed by using descriptors and variables obtained from these patterns and the pixels that make up the images. As the process of meat maturation is a dynamic and continuous process, the continuous analysis is a crucial aspect. This is possible because it is a non-destructive technique, which is a great advantage over traditional destructive techniques. To carry out the experiment, commercial beef fillets were used, these have a homogeneity in their thickness. In order to increase the changes that the meat undergoes during its maturation, an exogenous enzyme, papain, was added superficially to a batch. During the 26 hours of the experiment, regular measurements were taken in order to analyze in parallel the texture and variation of the laser pattern generated. Texture analysis was performed using the Warner-Bratzler shear method. For image analysis, the samples were arranged so that two lasers, not in unison, affected the sample. One arranged on the sample at an angle of 45o relative to the vertical between the camera and the sample and the other located at the bottom of the sample, in the same vertical as the sample and the camera. The images taken record the laser patterns and are processed extracting descriptors that characterize them, these are analyzed by multivariate statistical analysis and correlated with texture results. The results have shown how the analysis of laser dispersion patterns allows to characterize the maturation state of the meat. This provides information about its texture in a continuous and non-destructive way, if the arrangement of the laser is in the lower part of the sample and in the vertical between the sample and the camera. In addition, they have shown how the application of the enzyme increases the speed of changes in meat, but also the formation of a surface gel that minimizes changes in laser patterns. However, descriptors obtained from image analysis, as well as their reduction to a single main component, have been well correlated with the texture values of the samples. This applies for both samples, that is the sample without added enzyme and the sample with added enzyme. Results obtained have allowed to obtain theoretical models that can minimize the surface gel effect of samples with added exogenous enzyme, characterizing their texture as in the case of control meat samples.Agradecer al MINISTERIO DE CIENCIA, INNOVACIÓN Y UNIVERSIDADES por la financiación parcial para la realización del presente Trabajo Final de Grado a través del proyecto de investigación de referencia RTI2018-098842-B-I00, de la convocatoria 2018, titulado “Avances en el diseño de alimentos con textura modificada (ALITEMO)”Hernández Torralba, S. (2019). Aproximación de la técnica de análisis de patrones láser para la caracterización de la textura de carne durante su maduración. Universitat Politècnica de València. http://hdl.handle.net/10251/123891TFG

Inactivation of polyphenol oxidase in Camellia sinensis for the production of high quality instant green tea

A concerning situation has developed over the past few years where several tea estates had to close down due to high labour costs and low profitability. Solutions are desperately required to save these estates from further regression and to prevent others from joining their ranks. One solution is to redirect the tea factories from the current production of black tea to producing a value added commodity such as a high quality green tea extract with an increased market value. The aim of this study was to find an economically viable PPO inactivation method that can be implemented in existing tea factories for the production of high quality instant green tea. Further enhancement of quality may then be achieved by high throughput cultivar screening where those with a higher natural catechin to caffeine content will be favourable. Six different PPO inactivation methods (steaming, blanching, fluid bed drying, panfrying, grilling over direct heat and grilling over indirect heat) were explored. Four independent experiments were performed in duplicate with these six methods using fresh tea leaves donated by a tea estate in Tzaneen, South Africa. All samples were dried in a fluid bed drier and milled after PPO inactivation. Biochemical analysis of specific quality parameters followed where extractions from these green tea leaf samples were tested for theaflavin content, caffeine content, flavan-3-ol content, total free amino acid content, colour and taste. The six PPO inactivation methods were compared by data evaluation of the individual quality parameters where certain quality parameters carried a higher weight than others. For the purpose of this project, the catechin to caffeine ratio was the most important quality determinant to yield a high value IGT. Also, to prove effectiveness of the PPO inactivation method, low TF content was compulsory. All PPO inactivation methods explored proved successful in rapidly inactivating PPO enzyme. As hypothesised, a significant difference in biochemical composition is brought about between green teas produced by employing different PPO inactivation methods. Blanching was found to be the most efficient PPO inactivation method as well as the method resulting in the highest catechin to caffeine ratio (16.67:1 for 4 min blanch vs. 5.72:1 for 17 min FBD as determined by HPLC analysis). A freeze dried extract from a 1.5 minute blanched sample (IGT) was compared with foreign IGTs originating from Sri-Lanka, Kenya, China and India by HPLC analysis. A more than two fold greater catechin to caffeine ratio was obtained for the sample originating from the blanching method (9.08:1 vs. 2.81-5.02:1). A high quality, naturally low caffeine, instant green tea can therefore be produced by utilizing the blanching method of PPO inactivation. To allow for inter and intra cultivar screening, tentative identification of novel catechins (digallated catechins) and their HPLC retention times was done using HPLC-ESI-MS/MS. Potential HPLC retention times for EC-digallate were detected at tR 62.0 ± 0.2, 70.7 ± 0.1 and 76.7 ± 0.2 minutes while tR 64.6 ± 0.1 and 65.8 ± 0.1 minutes were detected for EGC-digallate. With this information at hand, cultivars of a higher quality, hence increased economical potential, can be identified upon confirmation by NMR. HPLC-ESI-MS/MS screening coupled with NMR confirmation is to be continued to detect several other novel flavan-3-ols that could not be detected in the 4 IGTs of different origin used in this study. This study gives an overview of the biochemical differences between green tea leaves prepared using six different PPO inactivation methods. The aim of this study was met by identification of the significant increase in quality brought about by PPO inactivation using the blanching method, which is also economical for use in Africa. Blanching of tea leaves caused a significant decrease in caffeine. Therefore, the 1st hypothesis, stating that the six polyphenol oxidase inactivation methods investigated will produce instant green teas with different catechin to caffeine ratios, is accepted. Also, a means to perform large scale screening of individual tea trees in Africa for their novel flavan-3-ol content was provided by tentative identification of these novel catechins by LC-MS. Thus, the 2nd hypothesis, stating that application of LC-MS will aid in the identification of HPLC retention times of compounds (novel catechins) from a crude extract, is also accepted.Dissertation (MSc)--University of Pretoria, 2009.Biochemistryunrestricte