Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Classification of Titrimetric Analysis Based on Reaction Types01:01

Classification of Titrimetric Analysis Based on Reaction Types

Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
Titrations between an acid and a base lead to neutralization reactions that form...
Qualitative Analysis01:10

Qualitative Analysis

Qualitative analysis is the process of identifying elements, ions, or compounds in an unknown sample. It is the first and most fundamental type of analysis based on the hierarchy of analytical goals. This hierarchy is significant as it provides a structured approach to scientific research, with qualitative analysis serving as the initial step, providing essential information before moving on to quantitative or other forms of analysis.
There are two main approaches to qualitative analysis:...
Methods of Classification and Identification01:28

Methods of Classification and Identification

Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
Classifying Matter by Composition03:35

Classifying Matter by Composition

Matter: Pure Substances and Mixtures
According to its composition, the matter can be classified into two broad categories — pure substances and mixtures. 
A pure substance is a form of matter that has a constant composition throughout with uniform properties. For example, any sample of sucrose has the same composition and same physical properties, such as melting point, color, and sweetness, regardless of the source from which it is isolated. 
A mixture is composed of two or more types of...
Chromatographic Methods: Classification01:12

Chromatographic Methods: Classification

Chromatographic techniques are classified in three ways: the classification is based on the physical state of the stationary and mobile phases, how the mobile phase and the stationary phase contact each other, or through the chemical or physical processes that isolate the components of the sample. Typically, the mobile phase is either a liquid or gas, while the stationary phase is either a solid or a liquid layer applied to a solid surface.
Chromatographic techniques are typically named by...
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Estimation of dietary intake and target hazard quotients for metals by consumption of wines from the Canary Islands.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association·2017
Same author

Exploring sexual health among young Black men who have sex with men in New York City.

Health education research·2016
Same author

Characterization and quantification of 4-methylsterols and 4,4-dimethylsterols from Iberian pig subcutaneous fat by gas chromatography-mass spectrometry and gas chromatography-flame ionization detector and their use to authenticate the fattening systems.

Talanta·2013
Same author

Cylindrospermopsin determination in water by LC-MS/MS: optimization and validation of the method and application to real samples.

Environmental toxicology and chemistry·2012
Same author

Authentication of fattening diet of Iberian pigs according to their volatile compounds profile from raw subcutaneous fat.

Analytical and bioanalytical chemistry·2010
Same author

Intra-laboratory assessment of method accuracy (trueness and precision) by using validation standards.

Talanta·2010

Related Experiment Video

Updated: Jun 28, 2026

Tea Aroma Analysis Based on Solvent-Assisted Flavor Evaporation Enrichment
04:36

Tea Aroma Analysis Based on Solvent-Assisted Flavor Evaporation Enrichment

Published on: May 26, 2023

Classification of tea samples by their chemical composition using discriminant analysis.

P Valera, F Pablos, A Gustavo González

    Talanta
    |March 1, 1996
    PubMed
    Summary

    Multivariate analysis successfully classified green and black tea samples using chemical profiles. This method accurately distinguished tea types based on aqueous extracts and key compounds like polyphenols and caffeine.

    More Related Videos

    HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis
    07:29

    HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis

    Published on: November 11, 2022

    Source and Route of Pyrrolizidine Alkaloid Contamination in Tea Samples
    06:04

    Source and Route of Pyrrolizidine Alkaloid Contamination in Tea Samples

    Published on: September 28, 2022

    Related Experiment Videos

    Last Updated: Jun 28, 2026

    Tea Aroma Analysis Based on Solvent-Assisted Flavor Evaporation Enrichment
    04:36

    Tea Aroma Analysis Based on Solvent-Assisted Flavor Evaporation Enrichment

    Published on: May 26, 2023

    HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis
    07:29

    HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis

    Published on: November 11, 2022

    Source and Route of Pyrrolizidine Alkaloid Contamination in Tea Samples
    06:04

    Source and Route of Pyrrolizidine Alkaloid Contamination in Tea Samples

    Published on: September 28, 2022

    Area of Science:

    • Analytical Chemistry
    • Chemometrics
    • Food Science

    Background:

    • Tea classification is crucial for quality control and consumer information.
    • Chemical composition varies significantly between green and black tea varieties.
    • Objective analytical methods are needed to complement traditional sensory evaluations.

    Purpose of the Study:

    • To apply multivariate analysis and pattern recognition for the classification of green and black tea.
    • To identify key chemical descriptors that differentiate between tea types.
    • To validate the use of discriminant analysis for tea categorization.

    Main Methods:

    • Samples of green and black tea were analyzed.
    • Aqueous extracts were prepared and analyzed for chemical composition.
    • Key chemical descriptors included polyphenols, amino acids, caffeine, theobromine, and theophylline.
    • Multivariate statistical techniques, including discriminant analysis, were employed.

    Main Results:

    • Discriminant analysis effectively classified the tea samples into green and black tea groups.
    • Specific chemical profiles were identified as characteristic of each tea type.
    • The combination of chemical descriptors provided a robust basis for classification.

    Conclusions:

    • Multivariate analysis and pattern recognition are powerful tools for tea classification.
    • Chemical fingerprinting can reliably distinguish between green and black teas.
    • This approach offers an objective method for tea quality assessment and authentication.