Impact of Leaf Occlusions on Yield Assessment by Computer Vision in Commercial Vineyards

Yield assessment has been identified as critical topic for grape and wine industry. Computer vision has been applied for assessing yield, but the accuracy was greatly affected by fruit occlusion affected by leaves and other plant organs. The objective of this work was the consistent, continuous eval...

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Bibliographic Details
Published in:Agronomy (Basel) 2021-05, Vol.11 (5), p.1003
Main Authors: Íñiguez, Rubén, Palacios, Fernando, Barrio, Ignacio, Hernández, Inés, Gutiérrez, Salvador, Tardaguila, Javier
Format: Article
Language:English
Subjects:
Agricultural production
Algorithms
Automation
Berries
Cameras
Computation
Computer vision
Defoliation
digital agriculture
Digital cameras
grapevine
Harvest
Image acquisition
image analysis
Leaves
Machine vision
Morphology
Occlusion
Organs
precision viticulture
proximal sensing
Vineyards
Vision systems
Wineries & vineyards
Wines
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Summary:Yield assessment has been identified as critical topic for grape and wine industry. Computer vision has been applied for assessing yield, but the accuracy was greatly affected by fruit occlusion affected by leaves and other plant organs. The objective of this work was the consistent, continuous evaluation of the impact of leaf occlusions in different commercial vineyard plots at different defoliation stages. RGB (red, green and blue) images from five Tempranillo (Vitis vinifera L.) vineyards were manually acquired using a digital camera under field conditions at three different levels of defoliation: no defoliation, partial defoliation and full defoliation. Computer vision was used for the automatic detection of different canopy features, and for the calibration of regression equations for the prediction of yield computed per vine segment. Leaf occlusion rate (berry occlusion affected by leaves) was computed by machine vision in no defoliated vineyards. As occlusion rate increased, R2 between bunch pixels and yield was gradually reduced, ranging from 0.77 in low occlusion, to 0.63.
ISSN:2073-4395
2073-4395
DOI:10.3390/agronomy11051003