Percival, David
Permanent URI for this collectionhttps://hdl.handle.net/10222/37757
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Item Open Access Delineating Management Zones for Site Specific Fertilization in Wild Blueberry Fields(2012-01) Farooque, A. A.; Zaman, Q. U.; Schumann, A. W.; Madani, A.; Percival, D. C.The concept of management zones has been proposed as a solution to the problems associated with the soil variability to more efficiently apply agricultural inputs on a site-specific basis. This study was designed to characterize and quantify the spatial variation in soil properties and wild blueberry fruit yield and to delineate management zones for site-specific fertilization. Two wild blueberry fields were selected in central Nova Scotia, and a grid pattern (15 xis m) was established at experimental sites to collect soil and fruit yield samples. The soil samples were analyzed for ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3--N), pH, electrical conductivity (EC), texture, and soil organic matter (SOM). The volumetric moisture content (theta(nu)) and ground conductivity data including horizontal coplanar geometry (HCP) and perpendicular coplanar geometry (PRP) were also recorded at the same grid points. The location of the sampling points were marked with a differential global positioning system (DGPS), and field boundary, bare spots, weeds, and grass patches were also mapped. The cluster analysis was performed to group the soil and fruit yield data into five zones termed as 'very poor,' 'poor,' 'medium,' 'good,' and 'very good' without prior knowledge of productivity potential with the internal homogeneity and external heterogeneity at a similarity level of greater than 70%. The coefficient of variation, geostatistical range of influence, and kriged maps suggested moderate to high variability of soil properties and fruit yield except soil pH and silt. The results of correlation matrix suggested significant relationships among the fruit yield and the soil properties. The results of ANOVA indicated that the fruit yield, HCP, PRP, theta(v), SOM, and inorganic nitrogen were significantly different in developed management zones except poor and very poor zones. The significant positive correlations of HCP and PRP with soil properties and fruit yield suggested that the ground conductivity data can be used to develop management zones for site-specific fertilization.Item Open Access Detecting Bare Spots in Wild Blueberry Fields using Digital Color Photography(2010-09) Zhang, F.; Zaman, Q. U.; Percival, D. C.; Schumann, A. W.Wild blueberry fields are developed from native stands on deforested land by removing competing vegetation The majority of fields are situated in naturally acidic and non-fertile sods that have high proportions of bare spots, weed patches, and gentle to severe topography Producers presently apply agrochemicals uniformly without considering bare spots The unnecessary or over-application of agrochemicals in bare spots may increase cost of production and environmental pollution An automated cost-effective machine vision system using digital color photography was developed and tested to detect and map bare spots for site-specific application of agrochemicals within wild blueberry fields The experiment was conducted at a 4-ha wild blueberry field in central Nova Scotia The machine vision system consisting of a digital color camera, differential global positioning system, and notebook computer was mounted on a specialized farm vehicle Custom software for grabbing and processing color images was developed m Delphi 5 0 and C++ programming languages The images taken by the digital camera were stored in the notebook computer automatically and then processed in red, green, and blue (RGB), and hue, saturation, and value (HSV) color spaces to detect bare spots in real-tune within blueberry fields The best results were achieved in hue image color space with 99% accuracy and a processing speed of 661 ms per image The results indicated that bare spots could be identified and mapped with this cost-effective digital photography technique in wild blueberry fields This information is useful for site-specific application, and has the potential to reduce agrochemical usage and associated environmental impacts in the wild blueberry production systemItem Open Access Automated, Low-Cost Yield Mapping of Wild Blueberry Fruit(2010-03) Zaman, Q. U.; Swain, K. C.; Schumann, A. W.; Percival, D. C.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- x 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-tune, 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. A linear regression model through the origin (y = bx) was highly significant in field 1 (R(2) = 0.90; P < 0.001) and field 2 (R(2) = 0.97; P < 0.001). The correlation between actual and predicted fruit yield (validation, using the equation from field 2) in field 1(R(2) = 0.95; P < 0.001; RMSE = 3.29 Mg/ha) and field 2 (validation, using the equation from field 1) (R(2) = 0.97; P < 0.001; RMSE = 2.69 Mg/ha) was also highly significant. The best results were obtained by using site-specific calibration of <20 points for every field, using a representative range of fruit yield. Maps showed substantial variability in fruit yield in both fields. The bare spots coincided with no or low yielding areas in the fields. The yield maps could be used for site-specific fertilization in wild blueberry fields.