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

Quality Control01:05

Quality Control

3.0K
Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
3.0K
Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

5.2K
When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
Different compounds display unique properties due to their...
5.2K
Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

1.3K
Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...
1.3K
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

798
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
798
Wind Turbine Machine Models01:24

Wind Turbine Machine Models

614
In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
614
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

278
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
278

You might also read

Related Articles

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

Sort by
Same author

Dual-engineered extracellular vesicles enabling endothelial targeting and EphrinB2 delivery for pulp revascularization.

Journal of nanobiotechnology·2026
Same author

Porcine Deltacoronavirus M Protein Binds NLRP3 to Promote Inflammasome Assembly via Competition with TRIM31.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Deep Learning for Anticancer Drug Discovery Targeting Non-Apoptotic Regulated Cell Death Mechanisms.

Pharmaceuticals (Basel, Switzerland)·2026
Same author

ResSAT: enhancing spatial transcriptomics prediction from H&E-stained histology images with an interactive spot transformer.

Genome biology·2026
Same author

Characteristics of pulmonary perfusion and ventilation in healthy adults: a prospective observational study with phase-resolved functional lung magnetic resonance imaging.

BMC medical imaging·2026
Same author

Pseudo-obstruction on single-phase CTPA: unilateral pulmonary vein atresia as the cause of 50 years of hemoptysis.

BMC pulmonary medicine·2026

Related Experiment Video

Updated: Feb 14, 2026

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.6K

Non-Destructive Geographical Traceability and Quality Control of Glycyrrhiza uralensis Using Near-Infrared

Anqi Liu1,2, Zibo Meng1,2, Jiayi Ma1,3

  • 1Henan Provincial Key Laboratory of Grain Resources Conservation and Utilization, School of Biological Engineering, Henan University of Technology, Zhengzhou 450001, China.

Foods (Basel, Switzerland)
|February 13, 2026
PubMed
Summary

A new method using near-infrared (NIR) spectroscopy and Support Vector Machine (SVM) accurately identifies licorice origin. This rapid, non-destructive technique ensures quality control for functional foods.

Keywords:
Glycyrrhiza uralensis Fisch.machine learningnear-infrared spectroscopyorigin traceabilityspectral preprocessing

More Related Videos

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
06:50

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

Published on: November 8, 2019

7.0K
Atomic Force Microscopy Combined with Infrared Spectroscopy as a Tool to Probe Single Bacterium Chemistry
08:51

Atomic Force Microscopy Combined with Infrared Spectroscopy as a Tool to Probe Single Bacterium Chemistry

Published on: September 15, 2020

4.6K

Related Experiment Videos

Last Updated: Feb 14, 2026

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.6K
O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
06:50

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

Published on: November 8, 2019

7.0K
Atomic Force Microscopy Combined with Infrared Spectroscopy as a Tool to Probe Single Bacterium Chemistry
08:51

Atomic Force Microscopy Combined with Infrared Spectroscopy as a Tool to Probe Single Bacterium Chemistry

Published on: September 15, 2020

4.6K

Area of Science:

  • Agricultural Science
  • Analytical Chemistry
  • Food Science

Background:

  • Licorice (Glycyrrhiza uralensis) is a key functional food ingredient.
  • Origin and cultivation (wild vs. cultivated) significantly impact licorice quality.
  • Accurate traceability is crucial for standardization and quality control.

Purpose of the Study:

  • To develop a rapid and non-destructive method for licorice origin traceability.
  • To differentiate between wild and cultivated licorice from different regions.
  • To establish a scientific basis for licorice quality assessment.

Main Methods:

  • Near-infrared (NIR) spectroscopy was employed for spectral data acquisition.
  • Support Vector Machine (SVM) algorithms were utilized for classification.
  • A comprehensive dataset from Gansu, Inner Mongolia, and Xinjiang, China, was used for validation.

Main Results:

  • The integrated NIR-SVM framework achieved over 99% classification accuracy.
  • The method effectively distinguished licorice based on geographical origin and cultivation mode.
  • The approach proved to be rapid, efficient, and environmentally friendly.

Conclusions:

  • The proposed NIR-SVM method is a robust tool for licorice quality assessment.
  • This technology supports rigorous quality control and standardization in the functional food industry.
  • It provides a scientific foundation for verifying the authenticity and origin of licorice products.