In the cultivation of fruit trees and vines, plant architecture is a critical determinant of productivity. While there are considerable diversities in plant architecture, which can be modified through pruning in fruit production, a method for high-throughput measurement and recording of architecture has not yet been established, posing a limitation to research and development in this area. Here we evaluated Transformer-based architecture for detecting above-ground shoot network of grapevine in an outdoor vineyard condition. The problem here was defined as the detection of nodes (buds or branching points) and their physical relationships (internodes or edges) within plant images. We also developed an evaluation metric inspired by the inherent structure of plant shoots to efficiently smooth detected structures to more closely resemble realistic systems in plants. The proposed framework has been successfully applied to the detection task in outdoor condition with complex background. Through the application of this method, we have demonstrated that our proposed framework is capable of extracting topological parameters of dormant shoot architecture of grapevine that effectively models the shoot biomass in a large-scale vineyard.
