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

Machine Learning in Image Analysis and Pattern Recognition

This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition

Smart Gas Sensors: Materials, Technologies, Practical ‎Applications, and Use of Machine Learning – A Review

The electronic nose, popularly known as the E-nose, that combines gas sensor arrays (GSAs) with machine learning has gained a strong foothold in gas sensing technology. The E-nose designed to mimic the human olfactory system, is used for the detection and identification of various volatile compounds. The GSAs develop a unique signal fingerprint for each volatile compound to enable pattern recognition using machine learning algorithms. The inexpensive, portable and non-invasive characteristics of the E-nose system have rendered it indispensable within the gas-sensing arena. As a result, E-noses have been widely employed in several applications in the areas of the food industry, health management, disease diagnosis, water and air quality control, and toxic gas leakage detection. This paper reviews the various sensor fabrication technologies of GSAs and highlights the main operational framework of the E-nose system. The paper details vital signal pre-processing techniques of feature extraction, feature selection, in addition to machine learning algorithms such as SVM, kNN, ANN, and Random Forests for determining the type of gas and estimating its concentration in a competitive environment. The paper further explores the potential applications of E-noses for diagnosing diseases, monitoring air quality, assessing the quality of food samples and estimating concentrations of volatile organic compounds (VOCs) in air and in food samples. The review concludes with some challenges faced by E-nose, alternative ways to tackle them and proposes some recommendations as potential future work for further development and design enhancement of E-noses

Management of intrinsic quality characteristics for high-value specialty coffees of heterogeneous hillside landscapes

Tropical hillsides are ecologically and socially diverse with a multitude of small- to medium-sized farms that offer a potential treasure chest of high-value market crops. Specialty coffees, for example, earn a substantial price premium and are therefore a promising opportunity for farmers. Coffee quality is determined by the natural environment and farm management practices. To sell high-priced coffee, farmers must produce beans desired by consumers who are willing to pay more for specific quality profiles. A targeting of the production practices to suit the continuously-changing market demands is necessary; the focus must be on controlling the processes that determine the quality characteristics. The present research aimed to develop a framework to manage the intrinsic coffee quality of heterogeneous hillside landscapes. In a two-tiered approach, firstly spatial prediction models were developed and tested to identify the comparative advantage of environmental niches and secondly systematic farm management practices were developed and tested to turn the comparative advantage of farmers into a competitive advantage. Commercial sensorial data of the two Colombian departments of Cauca and Antioquia, of the Veracruz department in Mexico and of the five coffee growing regions in Honduras were used to develop and test the framework. The results suggest that the framework is highly viable; the information generated is highly novel, is high-medium actionable and is medium deliverable to stakeholders. The specific conclusions derived are: (1) The production environment of coffee (natural environment, agronomic management and post-harvest processes) is variable over space. (2) Beverage quality of coffee is dependent on the production environment. The combination of decisive quality factors varies from location to location, and so does the contribution of each factor. (3) Production factors can be identified and their impact quantified. Subsequently the factors can be systematically controlled and managed to improve product quality. (4) Site-specific systematic and cyclic quality control processes are required to decrease produce variability and deliver a product sought by the market. (5) The approach is twofold, firstly the identification of suitable environmental niches followed by definition of site-specific management. (6) Farm management interventions are not always statistically significant but often relevant for farmers. (7) Qualitative quality-control methods using commercial data are viable indicators for quality measurements so long as consistent, skilled evaluators (cuppers) are selected in preliminary testing.Management der intrinsischen Qualitätscharakteristiken von hochwertigen Spezialitätenkaffees aus heterogenen Hanglagen Der Kaffeeanbau in tropischen Hanglagen variiert ökologisch sehr stark und ist sozial besonders geprägt durch eine Vielzahl von kleinen und mittleren landwirtschaftlichen Betrieben, welche ein hohes Potential für die Produktion von hochwertigen Agrarprodukten haben. Spezialitätenkaffees werden mit einem Mehrwert belohnt und sind deshalb eine vielversprechende Option für diese Bauern. Kaffeequalität ist wesentlich durch die natürlichen Umweltbedingungen und die agronomischen Praktiken bestimmt. Um hochwertige Kaffees vermarkten zu können, müssen die Bauern einen Rohkaffee produzieren, welcher vom Markt nachgefragt wird und für welchen der Konsument bereit ist, einen entsprechenden Aufpreis zuzahlen. Deshalb ist eine kontrollierte gezielte Produktion notwendig um mit den sich konstant ändernden Marktpräferenzen Schritt halten zu können. Die vorliegende Arbeit hat zum Ziel ein Rahmenwerk vorzulegen, welches es erlaubt, die Kaffeequalität aus heterogenen Hanglagen einschätzen, kontrollieren und beeinflussen zu können. Im ersten Teil der Dissertation werden räumliche Vorhersagemodelle entwickelt und getestet, um den komparativen Vorteil von Umweltnischen zu bestimmen. Im zweiten Teil erfolgt die Analyse der systematischen Anbaupraktiken, um den komparativen Standortvorteil der Bauern auch kompetitiv nutzen zu können. Kommerzielle sensorische Daten von Kaffees aus den kolumbianischen Departamentos (entspricht Bundesländern in Deutschland) Cauca und Antioquia, aus dem Departamento Veracruz in Mexiko, und aus den fünf Kaffeebauzonen in Honduras wurden verwendet, um das Rahmenwerk zu entwickeln und zu testen. Die Ergebnisse zeigen, dass das Rahmenwerk höchst brauchbar und die mit dem Rahmenwerk generierte Information höchst neuartig, hoch bis mittelmässig umsetzbar, und mittelmässig zugänglich ist. Insgesamt lassen sich folgende Schlussfolgerungen ziehen: (1) Das Produktionsumfeld (natürliche Umwelt, agronomisches Umfeld und Nachernteverfahren) ist standortsvariable. (2) Die Tassenqualität hängt vom Produktionsumfeld ab. Die Kombination der qualitätsbeeinflussenden Faktoren variiert von Standort zu Standort und ebenfalls der Beitrag der einzelnen Faktoren. (3) Limitierende Produktionsfaktoren konnten identifiziert und deren Einfluss quantifiziert werden. Dies erlaubt eine systematische Kontrolle und Beeinflussung einzelner Faktoren, um die Produktqualität verbessern zu können. (4) Ortsspezifische, systematische und zyklische Qualitätskontrollprozesse sind notwendig, um die Variabilität der Produktqualität zu verringern und ein vom Markt nachgefragtes Produkt herzustellen zu können. (5) Die Herangehensweise beinhaltet zwei Teilschritte. Zuerst werden geeignete Nischen identifiziert und darauf basierend das ortspezifische Qualitätsmanagement definiert. (6) Managementinterventionen sind nicht immer statistisch signifikant, aber trotzdem oft relevant für den Bauern. (7) Qualitative Methoden zur Qualitätskontrolle, basierend auf kommerziellen Daten, sind brauchbare Indikatoren für die Erfassung der Tassenqualität, so lange gut ausgebildete Verkoster in Voruntersuchungen ausgewählt wurden

Implementation of Digital Technologies on Beverage Fermentation

In the food and beverage industries, implementing novel methods using digital technologies such as artificial intelligence (AI), sensors, robotics, computer vision, machine learning (ML), and sensory analysis using augmented reality (AR) has become critical to maintaining and increasing the products’ quality traits and international competitiveness, especially within the past five years. Fermented beverages have been one of the most researched industries to implement these technologies to assess product composition and improve production processes and product quality. This Special Issue (SI) is focused on the latest research on the application of digital technologies on beverage fermentation monitoring and the improvement of processing performance, product quality and sensory acceptability

Columbia Chronicle (02/03/2014)

Student newspaper from February 3, 2014 entitled The Columbia Chronicle. This issue is 44 pages and is listed as Volume 49, Number 17. Cover story: Conquering Chi-beria Editor-in-Chief: Lindsey Woodshttps://digitalcommons.colum.edu/cadc_chronicle/1897/thumbnail.jp

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Chinese elements : a bridge of the integration between Chinese -English translation and linguaculture transnational mobility

[Abstract] As the popularity of Chinese elements in the innovation of the translation part in Chinese CET, we realized that Chinese elements have become a bridge between linguaculture transnational mobility and Chinese-English translation.So, Chinese students translation skills should be critically improved; for example, on their understanding about Chinese culture, especially the meaning of Chinese culture. Five important secrets of skillful translation are introduced to improve students’ translation skills