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Evaluation of Computer Vision Systems and Applications to Estimate Trunk Cross-Sectional Area, Flower Cluster Number, Thinning Efficacy and Yield of Apple

by Luis Gonzalez Nieto, Anna Wallis, Jon Clements, Mario Miranda Sazo, Craig Kahlke, Thomas M. Kon, and Terence L. Robinson

Edited by Mike Basedow, the full original article can be accessed here.

Precision crop load management of apple requires measuring trunks, counting flowers, fruitlets, or fruit at various times during the year to guide management decisions. While previous studies have found ways to incorporate these manual measurements into helpful orchard tools, time has often been a limiting factor in the adoption of these practices. There are an increasing number of tech companies working in agriculture that are incorporating these models into their portfolio. Our hopes are that the time required to collect the necessary data can be minimized so that more growers can have actionable information to manage their orchard more precisely.

Read more on Mike Basdedow’s blog here…