In-field apple size and location tracking using machine vision to assist fruit thinning and harvest decision-making

Monitoring of fruit size development has important implications for apple orchard management decision making such as scheduling for fruitlet chemical thinning and allocating resources for harvest. The current method for tracking fruit size development is by tagging a sample of fruits and using calipers or sizing rings to make measurements, which can be labor-intensive and time-consuming. In this study, a stereo vision system was developed which sized fruits on a tree and kept track of their growth during the season by matching fruit in images across time. Neural network models including Faster R-CNN and Mask R-CNN were used for fruit detection and on-tree fruit sizing. Camera pose estimation using feature matching of apples was used for tracking individual fruit growth. The best performance on fruit matching for the ‘Golden Delicious’ variety during the growing season in an apple orchard was observed in September and October; 74% of all detected fruits which were fully visible were matched between the two months. Fruitlets averaging 25 mm in diameter also had a matching accuracy of 73% during two imaging trials performed on the same day for the month of June.

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Work Title In-field apple size and location tracking using machine vision to assist fruit thinning and harvest decision-making
Access
Open Access
Creators
  1. Omeed Mirbod
  2. Daeun Choi
  3. Paul Heinemann
  4. Long He
  5. James R Schupp
Keyword
  1. Camera Pose Estimation
  2. Feature Matching
  3. Apple Fruit Thinning
  4. Precision Agriculture
  5. Stereo vision
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. ASABE
Publication Date January 1, 2021
Publisher Identifier (DOI)
  1. https://doi.org/10.13031/aim.202100831
Deposited August 12, 2024

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Version 1
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  • Created
  • Added Mirbod_et_al_ASABE_paper_no._2100831.docx
  • Added Creator Omeed Mirbod
  • Added Creator Daeun Choi
  • Added Creator L He
  • Added Creator Paul Heinemann
  • Added Creator Long He
  • Added Creator P Heinemann
  • Added Creator R Marini
  • Added Creator James R Schupp
  • Published
  • Updated
  • Updated Keyword Show Changes
    Keyword
    • Camera Pose Estimation, Feature Matching, Apple Fruit Thinning, Precision Agriculture, Stereo vision
  • Updated Publisher Show Changes
    Publisher
    • ASABE
  • Deleted Creator L He
  • Deleted Creator P Heinemann
  • Deleted Creator R Marini
  • Updated Creator Paul Heinemann
  • Updated Creator Long He
  • Updated Creator James R Schupp