A reusable strawberry stem based on hot melt adhesives for robotic harvesting applications
Robotic strawberry harvesting has achieved significant progress, with decades of research leading to commercial deployments and prototypes capable of autonomous fruit detection, grasping, and stem cutting. However, its development remains limited by the lack of a reusable, realistic crop testbed, making system validation difficult due to limited field access, crop waste, and large sample requirements. Here, we present a reusable strawberry stem made from Hot Melt Adhesives (HMAs) enabling repeated cutting, healing, and detachment. We show that the artificial stem reproduces the static behavior of real stems when its diameter is increased by 2.0 × − 3.0 × , achieving curvature errors between 3.39% and 11.01% of stem length (normalized RMSD), confirming close agreement with their biological counterparts. Furthermore, the healing behavior is analyzed by evaluating the consistency of the cutting force required to sever the stem and the peak tensile load required to detach it across repeated cycles. Fabrication repeatability is assessed by measuring the variability of peak cutting force across independently fabricated stems from the same mold. Although HMA does not fully match the stem’s natural stiffness, the surrogate replicates its static behavior at a larger diameter, providing a practical, low-cost, reusable medium for standardized harvesting tests. Juan Espejel Flores and colleagues develop a reusable self-healing strawberry stem surrogate based on hot-melt adhesives for repeatable robotic harvesting experiments. The surrogate reproduces the static behavior of real strawberry stems through geometric scaling while enabling repeated cutting, healing, and reuse in a low-cost experimental platform.
Authors
- Leonardo Guevara (ORCID: https://orcid.org/0000-0002-1581-8943)
- Marcello Calisti (ORCID: https://orcid.org/0000-0002-2590-188X)
- Luis Arturo Soriano (ORCID: https://orcid.org/0000-0003-3299-9851)
- D A Perez-DeLaMora (ORCID: https://orcid.org/0000-0001-8626-3992)
- Srikishan Vayakkattil (ORCID: https://orcid.org/0009-0007-8873-0065)
- Carlos Juárez-Balderas (ORCID: https://orcid.org/0009-0007-2189-695X)
- Juan Pablo Espejel
Institutions
- Scuola Superiore Sant'Anna (IT)
- Universidad Iberoamericana (MX)
- Chapingo Autonomous University (MX)
- University of Lincoln (GB)
Publication Details
- Journal
- Communications Engineering
- Published
- 2026-10-18
- DOI
- https://doi.org/10.1038/s44172-026-00804-3
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00