Abstract
The presence of weeds, bare spots, and variation in fruit yield within wild blueberry fields emphasizes the need for yield mapping for site-specific application of agrochemicals. An automated yield monitoring system (AYMS) consisting of a digital color camera, differential global positioning system, custom software, and a ruggedized laptop computer was developed and mounted on a specially designed Farm Motorized Vehicle (FMV) for real-time fruit yield mapping. Two wild blueberry fields were selected in central Nova Scotia to evaluate the performance of the AYMS. Calibration was carried out at 38 randomly selected data points, 19 in each field. The ripe fruit was hand-harvested out of a 0.5- 0.5-m quadrant at each selected point and camera images were also taken from the same points to calculate the blue pixel ratio (fraction of blue pixels in the image). Linear regression was used to calibrate the actual fruit yield with percentage blue pixels. Real-time yield mapping was carried out with AYMS. Custom software was developed to acquire and process the images in real-time, and store the blue pixel ratio. The estimated yield per image along with geo-referenced coordinates was imported into ArcView 3.2 GIS software for mapping.
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