76 research outputs found

    Optimization and validation of the protocol used to analyze the taste of traditional Chinese medicines using an electronic tongue

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    Tools to define the active ingredients and flavors of Traditional Chinese Medicines (TCMs) are limited by long analysis times, complex sample preparation and a lack of multiplexed analysis. The aim of the present study was to optimize and validate an electronic tongue (E‑tongue) methodology to analyze the bitterness of TCMs. To test the protocol, 35 different TCM concoctions were measured using an E‑tongue, and seven replicate measurements of each sample were taken to evaluate reproducibility and precision. E‑tongue sensor information was identified and classified using analysis approaches including least squares support vector machine (LS‑SVM), support vector machine (SVM), discriminant analysis (DA) and partial least squares (PLS). A benefit of this analytical protocol was that the analysis of a single sample took \u3c15 min for all seven sensors. The results identified that the LS‑SVM approach provided the best bitterness classification accuracy (binary classification accuracy, 100%; ternary classification accuracy, 89.66%). The E‑tongue protocol developed showed good reproducibility and high precision within a 6 h measurement cycle. To the best of our knowledge, this is the first study of an E‑tongue being applied to assay the bitterness of TCMs. This approach could be applied in the classification of the taste of TCMs, and serve important roles in other fields, including foods and beverages

    Assessment of E-Senses Performance through Machine Learning Models for Colombian Herbal Teas Classification

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    This paper describes different E-Senses systems, such as Electronic Nose, Electronic Tongue, and Electronic Eyes, which were used to build several machine learning models and assess their performance in classifying a variety of Colombian herbal tea brands such as Albahaca, Frutos Verdes, Jaibel, Toronjil, and Toute. To do this, a set of Colombian herbal tea samples were previously acquired from the instruments and processed through multivariate data analysis techniques (principal component analysis and linear discriminant analysis) to feed the support vector machine, K-nearest neighbors, decision trees, naive Bayes, and random forests algorithms. The results of the E-Senses were validated using HS-SPME-GC-MS analysis. The best machine learning models from the different classification methods reached a 100% success rate in classifying the samples. The proposal of this study was to enhance the classification of Colombian herbal teas using three sensory perception systems. This was achieved by consolidating the data obtained from the collected samples

    Emergent quality issues in the supply of Chinese medicinal plants: A mixed methods investigation of their contemporary occurrence and historical persistence

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    Quality issues that emerged centuries ago in Chinese medicinal plants (CMP) were investigated to explore why they still persist in an era of advanced analytical testing and extensive legislation so that a solution to improve CMP quality could be proposed. This is important for 85% of the world’s population who rely on medicinal plants (MP) for primary healthcare considering the adverse events, including fatalities that arise from such quality issues. CMP are the most prevalent medicinal plants globally. This investigation used mixed-methods, including 15 interviews with CMP expert key informants (KI), together with thematic analysis that identified the main CMP quality issues, why they persisted, and informed solutions. An unexplained case example, Eleutherococcus nodiflorus (EN), was analysed by collection of 106 samples of EN, its known toxic adulterant Periploca sepium (PS), and a related substitute, Eleutherococcus senticosus (ES), across mainland China, Taiwan and the UK. Authenticity of the samples was determined using High-performance thinlayer chromatography. Misidentification, adulteration, substitution and toxicity were the main CMP quality issues identified. Adulteration was found widespread globally with 57.4% EN found authentic, and 24.6% adulterated with cardiotoxic PS, mostly at markets and traditional pharmacies. The EN study further highlighted that the reason CMP quality issues persisted was due to the laboratory-bound nature of analytical methods and testing currently used that leave gaps in detection throughout much of the supply chain. CMP quality could be more effectively tested with patented analytical technology (PAT) and simpler field-based testing including indicator strip tests. Education highlighting the long-term economic value and communal benefit of delivering better quality CMP to consumers was recommended in favour of the financial motivation for actions that lead to the persistence of well-known and recurrent CMP quality issues

    Progress in Analytical Methods for the Characterization, Quality and Safety of the Beehive Products

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    This reprint presents some recent results from applying original analytical methods to the most renowned hive matrices. Particular consideration was given to methods devoted to the attribution of the origin of honey and propolis, but also studies dealing with the chemical characterization of honey and other hive matrices are here reported. Attention has also been paid to the use of optimized methods of elemental analysis in several hive products for quality and safety purposes, but also for environmental biomonitoring. The treatment of the data was often achieved through multivariate analysis methods, which made it possible to obtain reliable classifications of honeys and propolis according to their botanic or geographical origin

    Advanced Materials in Drug Release and Drug Delivery Systems

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    Development of new drug molecules is costly and requires longitudinal, wide-ranging studies; therefore, designing advanced pharmaceutical formulations for existing and well-known drugs seems to be an attractive device for the pharmaceutical industry. Properly formulated drug delivery systems can improve pharmacological activity, efficacy and safety of the active substances. Advanced materials applied as pharmaceutical excipients in designing drug delivery systems can help solve problems concerning the required drug release—with the defined dissolution rate and at the determined site. Novel drug carriers enable more effective drug delivery, with improved safety and with fewer side effects. Investigations concerning advanced materials represent a rapidly growing research field in material/polymer science, chemical engineering and pharmaceutical technology. Exploring novel materials or modifying and combining existing ones is now a crucial trend in pharmaceutical technology. Eleven articles included in the the Special Issue “Advanced Materials in Drug Release and Drug Delivery Systems” present the most recent insights into the utilization of different materials with promising potential in drug delivery and into different formulation approaches that can be used in the design of pharmaceutical formulations

    Implementation of Digital Technologies on Beverage Fermentation

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    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

    Screening, Identification, and Quantification of Nutritional Components and Phytochemicals in Foodstuffs

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    This book provides readers with a good overview of the status and exciting developments in the identification of health-promoting properties and potential applications of nutraceutical substances. It includes papers focused on modern analytical instrumentation and new methods and biological tests applied to the evaluation of plant foods, derived products, herbal products, and food supplements and the phytochemical characterization of innovative natural sources of bioactive compounds and relative health-promoting properties

    Investigation of Volatile Organic Compounds (VOCs) released as a result of spoilage in whole broccoli, carrots, onions and potatoes with HS-SPME and GC-MS

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    Vegetable spoilage renders a product undesirable due to changes in sensory characteristics. The aim of this study was to investigate the change in the fingerprint of VOC composition that occur as a result of spoilage in broccoli, carrots, onions and potatoes. SPME and GC-MS techniques were used to identify and determine the relative abundance of VOC associated with both fresh and spoilt vegetables. Although a number of similar compounds were detected in varying quantities in the headspace of fresh and spoilt samples, certain compounds which were detected in the headspace of spoilt vegetables were however absent in fresh samples. Analysis of the headspace of fresh vegetables indicated the presence of a variety of alkanes, alkenes and terpenes. Among VOCs identified in the spoilt samples were dimethyl disulphide and dimethyl sulphide in broccoli; Ethyl propanoate and Butyl acetate in carrots; 1-Propanethioland 2-Hexyl-5-methyl-3(2H)-furanone in onions; and 2, 3-Butanediol in potatoes. The overall results of this study indicate the presence of VOCs that can serve as potential biomarkers for early detection of quality deterioration and in turn enhance operational and quality control decisions in the vegetable industry

    Authenticity of Honey: Characterization, Bioactivities and Sensorial Properties

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    Honey is a very complex food that requires multiple analytical, statistical and mathematical methods to guarantee honey authentication. This Special Issue contains innovative research on different analytical procedures for the determination of chemical compounds, functional properties, sensory characteristics and pollen profiles for the interpretation of the botanical and geographical origin of honey. This book compiles twelve original studies that address these issues and improve the knowledge of honeys of multiple botanical and geographical origins
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