Performance evaluation of multiple ground based sensors mounted on a commercial wild blueberry harvester to sense plant height, fruit yield and topographic features in real-time

Site-specific crop management can increase profitability and reduce environmental risks of wild blueberry crop having large spatial variation in soil/plant characteristics and topographic features which may affect fruit yield. An integrated automated system comprising of an ultrasonic sensor, a digital color camera, a slope sensor, a real-time kinematics GPS (RTK-GPS), custom software and ruggedized computer was developed. The system was incorporated onto a commercial wild blueberry harvester, to measure plant height, fruit yield, slope and elevation simultaneously while harvesting. Two wild blueberry fields were selected in central Nova Scotia, Canada to evaluate the performance of the system. Field boundaries, bare spots, weeds and grass patches were mapped with a RTK-GPS prior to start the experiment. Linear regression was used to calibrate the actual fruit yield with the percentage of blue pixels (R-2 = 0.91-0.92; P < 0.001; n = 40) using a 0.91 x 0.70 m quadrat at selected points from both fields. The output voltage of the ultrasonic sensor was significantly correlated with manually measured plant height (R-2 = 0.94; P < 0.001; n = 13). Comprehensive surveys were conducted in both fields to measure plant height, fruit yield, slope and elevation rapidly in real-time at the same time of harvest. The maps for the measured parameters were developed in ArcGIS 10. Maps showed substantial variability in measured parameters across the fields, suggesting more fruit yield and lower plant height in low lying areas (mild slope) and vice versa. A negative relationship among fruit yield and plant height and the results of zonal statistics in ArcGIS 10 also supported the results identified by the maps. Overall, the results of calibration and mapping indicated that the developed system was an accurate, reliable and efficient to map plant height, fruit yield, slope and elevation in real-time. This information can be used to develop site-specific fertilization, based on easily measured field parameters, to optimize productivity while minimizing the environmental impacts. (C) 2013 Elsevier B.V. All rights reserved.