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Collection and Identification of Pollen from Honey Bee Colonies
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Dataset for Hop varieties classification.

Pedro Castro1, Eduardo Luz1, Gladston Moreira1

  • 1Computing Department, Federal University of Ouro Preto, Ouro Preto-MG 35400-000, Brazil.

Data in Brief
|September 6, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a cost-effective method for identifying hop (Humulus lupulus L.) varieties using machine learning on leaf images. This approach aids brewers by offering accessible hop classification without expensive equipment.

Keywords:
Hop varietiesLeaf recognitionPlant recognition

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Area of Science:

  • Agricultural Science
  • Biotechnology
  • Food Science

Background:

  • Humulus lupulus L. (hops) are crucial in brewing for flavor, aroma, and preservation.
  • Hops possess antimicrobial and antioxidant properties, with applications in food preservation and cosmetics.
  • Over 250 hop varieties exist, differentiated by key compounds like alpha-acids, beta-acids, and essential oils.

Purpose of the Study:

  • To develop an accessible method for classifying hop varieties.
  • To leverage pattern recognition and machine learning for hop identification.
  • To provide a tool for brewers lacking access to complex analytical equipment.

Main Methods:

  • Compilation of a database with 1592 images of hop leaves.
  • Inclusion of 12 popular hop varieties from southeastern Brazil.
  • Application of pattern recognition and machine learning algorithms for classification.

Main Results:

  • Demonstrated the feasibility of classifying hop varieties using leaf imagery.
  • Established a foundation for accessible hop varietal analysis.
  • Highlighted the potential of machine learning in agricultural product identification.

Conclusions:

  • Hop variety classification is achievable through image analysis and machine learning.
  • This method offers a practical alternative to expensive traditional analytical techniques.
  • The developed approach can support brewers in quality control and product development.