Wolfberry tree dual-model detection method and orchard target-oriented fertilization system based on photoelectric sensors

Abstract

Orchard target-oriented fertilizing with on-board sensor technology can improve fertilizer efficiency and reduce environmental pollution. Photoelectric sensors are widely used for object detection because of their low cost and fast response time. This paper presents a Wolfberry tree dual-model detection method and the design of an orchard target-oriented variable-rate fertilization system based on photoelectric sensors. The dual-model detection method includes the Trunk Detection Model (TDM) and Canopy Detection Model (CDM), which can be applied for Wolfberry orchards at the green cluster and mature stages, respectively. A target-oriented fertilization system was designed using the dual-model method, and tested in the lab and Chinese Wolfberry orchard. The laboratory test results showed that the average center offset distances on the condition of detecting trunks, continuous canopies, and discontinuous canopies were 4.1 cm, 9.1 cm and 13.1 cm, respectively. The system could ignore the signals from canes when their diameters were less than 16 mm, and also could determine the gaps within a tree when they were less than 21 cm. The orchard test results showed that the system accomplished target-oriented fertilization 95 times for 92 trees at the mature stage. The results indicated that the dual-model detection method could be used for Wolfberry trees or other trees with similar canopy changes at different growth stages.