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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationAmerican Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2021
PublisherAmerican Society of Agricultural and Biological Engineers
Pages2123-2128
Number of pages6
ISBN (Electronic)9781713833536
DOIs
StatePublished - 2021
Event2021 American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2021 - Virtual, Online
Duration: Jul 12 2021Jul 16 2021

Publication series

NameAmerican Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2021
Volume4

Conference

Conference2021 American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2021
CityVirtual, Online
Period7/12/217/16/21

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Agronomy and Crop Science

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