Estimation of Wild Blueberry Fruit Yield Using Digital Color Photography

2008 ◽  
Vol 51 (5) ◽  
pp. 1539-1544 ◽  
Author(s):  
Q. U. Zaman ◽  
A. W. Schumann ◽  
D. C. Percival ◽  
R. J. Gordon
Keyword(s):  
Fruit Yield ◽  
Color Photography ◽  
Wild Blueberry

ESTIMATION OF WILD BLUEBERRY FRUIT YIELD USING DIGITAL COLOR PHOTOGRAPHY

2009 ◽  
pp. 57-66
Author(s):  
Q.U. Zaman ◽  
D.C. Percival ◽  
R.J. Gordon ◽  
A.W. Schumann
Keyword(s):  
Fruit Yield ◽  
Color Photography ◽  
Wild Blueberry

Influence of Wild Blueberry Fruit Yield, Plant Height, and Ground Slope on Picking Performance of a Mechanical Harvester: Basis for Automation

2017 ◽  
Vol 33 (5) ◽  
pp. 655-666
Author(s):  
Aitazaz Ahsan Farooque ◽  
Qamar Uz Zaman ◽  
Travis Esau ◽  
Young Ki Chang ◽  
Arnold Walter Schumann ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Real Time ◽  
Plant Height ◽  
Fruit Yield ◽  
Operating Parameters ◽  
Profit Margins ◽  
Ground Speed ◽  
Ground Slope ◽  
Head Height ◽  
Wild Blueberry

Abstract. Spatial variability in fruit losses in relation to fruit yield, plant height, and ground slope can help to automate the wild blueberry harvester to improve picking performance. Currently, harvester operators adjust harvester’s head height, ground speed, and revolutions per minute (rpm) manually. This is not only laborious but also stressful for operators, as they encounter spatial variability during harvesting. The goal of this work was to identify the automation potential of the harvester to improve harvestable yield and reduce operator’s stress, keeping in view the spatial variability. Two fields were selected and test plots were constructed to examine the performance of the harvester in five zones of plant height, fruit yield, and ground slope. Fruit yield plant height and ground slope were recorded from each plot manually to examine their impact on total fruit loss. Keywords: Automation, Fruit losses, Spatial variability, Wild blueberry, Zonal analysis.Results confirmed significant variability in fruit yield, plant height, and ground slope. Fruit losses were significantly influenced by the spatial variations. Fruit losses increased with an increase in fruit yield and ground slope during mechanical harvesting. The picking performance of the blueberry harvester was significantly lower in short and very tall plants within selected fields. The dependence of fruit losses on fruit yield, plant height, and ground slope emphasize the need for real-time adjustments in machine operating parameters to improve berry recovery. Based on the results, it is concluded that there is a significant advantage of harvester’s automation to increase profit margins for growers with no additional cost. Keywords: Automation, Fruit losses, Spatial variability, Wild blueberry, Zonal analysis.

Computer vision system for wild blueberry fruit yield mapping

2010 ◽  
Vol 106 (4) ◽  
pp. 389-394 ◽  
Author(s):  
Kishore C. Swain ◽  
Qamar U. Zaman ◽  
Arnold W. Schumann ◽  
David C. Percival ◽  
Dionysis D. Bochtis
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Fruit Yield ◽  
Computer Vision System ◽  
Yield Mapping ◽  
Wild Blueberry

Machine vision for spot-application of agrochemical in wild blueberry fields

2017 ◽  
Vol 8 (2) ◽  
pp. 272-276 ◽  
Author(s):  
T. Esau ◽  
Q. Zaman ◽  
D. Groulx ◽  
Y. Chang ◽  
A. Schumann ◽  
...  
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Fruit Yield ◽  
Machine Vision System ◽  
Fungicide Application ◽  
Leaf Drop ◽  
Crop Disease ◽  
Wild Blueberry

The goal of the project was to supply growers with knowledge on how incorporation of machine vision technology can affect the wild blueberry crop, disease pressures, and the overall savings of select agrochemical inputs. A machine vision system was developed and mounted on a rear sprayer boom in front of the sprayer nozzles capable of targeting the agrochemical application on an as-needed basis. Results showed that plants that received the proper fungicide application were less prone to premature leaf drop resulting in larger stem diameters and higher bud counts and harvestable fruit yield. Fungicide application savings using the smart sprayer for spot-application was 12% as compared to a uniform application.

Detecting Bare Spots in Wild Blueberry Fields Using Digital Color Photography

2010 ◽  
Vol 26 (5) ◽  
pp. 723-728 ◽  
Author(s):  
F. Zhang ◽  
Q. U. Zaman ◽  
D. C. Percival ◽  
A. W. Schumann
Keyword(s):  
Color Photography ◽  
Wild Blueberry

Potential Use of Digital Photographic Technique to Examine Wild Blueberry Ripening in Relation to Time of Harvest

2018 ◽  
Vol 34 (2) ◽  
pp. 299-308
Author(s):  
Salamat Ali ◽  
Qamar Uz Zaman ◽  
Aitazaz Ahsan Farooque ◽  
Arnold Walter Schumann ◽  
Chibuike C Udenigwe ◽  
...  
Keyword(s):  
Fruit Quality ◽  
Fruit Yield ◽  
Harvesting Time ◽  
Farming Community ◽  
Yield And Quality ◽  
Wild Blueberries ◽  
Four Blocks ◽  
Wild Blueberry ◽  
Potential Use ◽  
Time Of Harvest

Abstract. Northeastern North America is the world’s leading producer of wild blueberry. Ripening of wild blueberry is the leading factor for fruit quality. Currently, there are no protocols available for the farming community related to wild blueberry fruit ripening and maturity. A nondestructive, rapid, and reliable digital photography technique could be used to examine the ripening of wild blueberries for appropriate harvesting time. Two wild blueberry fields were selected to examine the berry ripening levels using digital photographic techniques at different time of harvest (early, middle, and late seasons). The fields were divided into four blocks and each block was further divided into three classes of times of harvest. Fruit images from each block were acquired and processed to count blue pixels from each image. A significant correlation was found between percentage of blue pixels and actual fruit yield in Field A (R2 = 0.96; P < 0.001) and Field B (R2 = 0.97; P < 0.001). The results also indicated that the effect of time of harvest on fruit yield was significant and fruit yield increased gradually during early harvesting, reached maximum during mid-season, and then started to decrease in late harvesting. Results indicated that 90% of green-berries had turned blue at the end of middle season compared to early season (58%). Based on the results of this study, optical analysis could help to keep fruit quality by optimizing appropriate harvesting time of wild blueberries. It is also suggested that the optimum time to harvest wild blueberries is middle season to ensure high fruit yield and quality. Keywords: Blue pixels, Fruit yield, Harvesting season, Wild blueberry.

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