Ultrasonic sensing of pistachio canopy for low-volume precision spraying

• Precision control system for the estimation of tree canopy dimensions was designed.
• Three ultrasonic ranging sensors were utilized to estimate the target distance.
• A MLP neural network was used for volume estimation of tree sections.
• Consistency of spray distribution was represented in selective application.
• Variable-rate spraying showed a reduction in pesticide usage of about 34.5%.

Effective volume rate of pesticide application on a site-specific basis can reduce the amount of agrochemicals used in precision horticulture. The prototype sprayer used in this study provided volume application rate adapted to the canopy volume in pistachio orchards on a real-time and continuous basis. An electronic control system for the detection and estimation of tree canopy dimensions was designed for application rate adjustment. Three ultrasonic ranging USS3 sensors were utilized to estimate the distance to the target at three different heights. A MLP neural network with gradient-descent back-propagation algorithm, tangent-sigmoid transfer function, and 3-7-6 topology was used for volume estimation of tree sections. Training and validation errors as well as R2 values indicated the reliability of the network for volume prediction. Results of T-test for comparing the number of spray droplet impacts, coverage of (artificial) target, spray quality parameter and relative span factor between variable-rate and conventional spraying were not significant which indicates the consistency of spray distribution in selective application. Experiments showed a reduction in pesticide usage of about 34.5% by means of variable-rate technology (41.3, 25.6 and 36.5, respectively for the top, middle, and bottom sections of tree canopy). Precise application of agrochemicals reduces both costs and environmental pollution by supporting a decrease in the amount of delivered spray.