NDLI: Yield estimation in vineyards by visual grape detection

Content Provider	IEEE Xplore Digital Library
Author	Nuske, Stephen Achar, Supreeth Bates, Terry Narasimhan, Srinivasa Singh, Sanjiv
Copyright Year	2011
Description	Author affiliation: Cornell University, 6592 West Main Road, Portland, NY, USA, 14769 (Bates, Terry) \|\| Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA, 15213 (Nuske, Stephen; Achar, Supreeth; Narasimhan, Srinivasa; Singh, Sanjiv)
Abstract	The harvest yield in vineyards can vary significantly from year to year and also spatially within plots due to variations in climate, soil conditions and pests. Fine grained knowledge of crop yields can allow viticulturists to better manage their vineyards. The current industry practice for yield prediction is destructive, expensive and spatially sparse - during the growing season sparse samples are taken and extrapolated to determine overall yield. We present an automated method that uses computer vision to detect and count grape berries. The method could potentially be deployed across large vineyards taking measurements at every vine in a non-destructive manner. Our berry detection uses both shape and visual texture and we can demonstrate detection of green berries against a green leaf background. Berry detections are counted and the eventual harvest yield is predicted. Results are presented for 224 vines (over 450 meters) of two different grape varieties and compared against the actual harvest yield as groundtruth. We calibrate our berry count to yield and find that we can predict yield of individual vineyard rows to within 9.8% of actual crop weight.
Starting Page	2352
Ending Page	2358
File Size	2655634
Page Count	7
File Format	PDF
ISBN	9781612844541
ISSN	21530858
e-ISBN	9781612844565
DOI	10.1109/IROS.2011.6095069
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pipelines Agriculture Image color analysis Image edge detection Transforms Yield estimation Cameras
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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