Document Type
Article
Publication Date
12-2025
Publication Title
Smart Agricultural Technology
Publisher
Elsevier
DOI
https://doi.org/10.1016/j.atech.2025.101339
Abstract
Planting peach trees shallow on berms is a short-term Armillaria root rot management strategy to facilitate root collar excavation for about two years after planting. Leveling of berms between trees planted in rows helps improve worker and machine mobility during orchard operations and reduces soil erosion caused by adjacent furrows on either side of the berm. The berm leveling mechanism in a prior study used tractor operator input to avoid trees during field operations. This research aimed to automate the actuation of the berm leveling machine around peach trees and to evaluate the effectiveness of a finger weeder attachment in breaking the berm mounds left around the trees. Three sensing systems, including a tactile (feeler) mechanism, single and dual infrared sensors, and a LiDAR sensor, were separately integrated into the berm leveling machine for tree detection. The developed tree sensing systems were tested over experimental berms and assessed for consistency of berm mound length left around trees using Fligner-Killeen and Levene's variability tests. Results showed no significant difference in berm mound length among sensing systems at a 95% confidence level. The finger weeder test yielded no observable impact on berm mound shape and caused no visible damage to tree roots. This study automated tree detection and actuation to reduce reliance on operator and risk of tree damage. Sensing choice for berm leveling machine may depend on availability, expertise, environment, and tree trunk sturdiness. Further testing of the sensing systems and the finger weeder attachment in peach orchards can provide a more comprehensive assessment.
Recommended Citation
Shubham Singh, A. Bulent Koc, Guido Schnabel, Juan Carlos Melgar, Michael Vassalos, Jasanmol Singh, Tactile and Photoelectric Sensing for Leveling Berms in Peach Tree Rows, Smart Agricultural Technology, Volume 12, 2025, 101339, ISSN 2772-3755, https://doi.org/10.1016/j.atech.2025.101339.