High-speed identification system for fresh tea leaves based on phenotypic characteristics utilizing an improved genetic algorithm.

Journal: Journal of the science of food and agriculture
Published Date: Dec 1, 2022

Abstract

BACKGROUND: High-quality tea requires leaves of similar size and tenderness. The grade of the fresh leaves determines the quality of the tea. The automated classification of fresh tea leaves improves resource utilization and reduces manual picking costs. The present study proposes a method based on an improved genetic algorithm for identifying fresh tea leaves in high-speed parabolic motion using the phenotypic characteristics of the leaves. During parabolic flight, light is transmitted through the tea leaves, and six types of fresh tea leaves can be quickly identified by a camera.

Authors

  • Ning Gan
    State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, China.
  • Mufang Sun
    State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, China.
  • Chengye Lu
    State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, China.
  • Menghui Li
    State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, China.
  • Yujie Wang
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, VIC, Australia.
  • Yan Song
    Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, China.
  • Jing-Ming Ning
    State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, China.
  • Zheng-Zhu Zhang
    State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, China.

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