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Inexpensive, Automated Pruning Weight Estimation in Vineyards

Jonathan Jaramillo, Aaron Wilhelm, Nils Napp, Justine Vanden Heuvel, Kirstin Hagelskjaer Petersen

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Abstract

Pruning weight is indicative of a vine’s ability to produce a crop the following year, informing vineyard management. Current methods for estimating pruning weight are costly, laborious, and/or require specialized know-how and equipment. In this paper we demonstrate an affordable, simple, computer vision-based method to measure pruning weight using a smartphone camera and structured light which produces results better than state-of-the-art techniques for vertical shoot position (VSP) vines and demonstrate initial steps towards estimating pruning weight in high cordon procumbent (HC) vines such as Concord. The simplicity and affordability of this technique lends its self to deployment by farmers today or on future viticulture robotics platforms. We achieved an R2=.80 for VSP vines (better than state-of-the-art computer vision-based methods) and R2=.29 for HC vines (not previously attempted with computer vision-based methods).

Index terms

Agricultural Automation Robotics and Automation in Agriculture and Forestry Computer Vision for Automation