Ultrasonic sensing of pistachio canopy for low-volume precision spraying

Maghsoudi, Hossein; Minaei, Saeid; Ghobadian, Barat; Masoudi, Hassan

doi:10.1016/j.compag.2014.12.015

Cited by 67 publications

(42 citation statements)

References 23 publications

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“…This would represent a savings of 109.2 mL or 72% of the conventional spraying method. Similar values were reported by [10,12,17,46], who gave a pesticide reduction of 34.5%, 58%, 64% and 66%, respectively, when compared to a conventional homogeneous spraying. The result of these tests confirmed that an inexpensive precision system could confer significant reductions in the use of herbicides.…”

supporting

confidence: 75%

3D Imaging with a Sonar Sensor and an Automated 3-Axes Frame for Selective Spraying in Controlled Conditions

et al. 2017

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Autonomous selective spraying could be a way for agriculture to reduce production costs, save resources, protect the environment and help to fulfill specific pesticide regulations. The objective of this paper was to investigate the use of a low-cost sonar sensor for autonomous selective spraying of single plants. For this, a belt driven autonomous robot was used with an attached 3-axes frame with three degrees of freedom. In the tool center point (TCP) of the 3-axes frame, a sonar sensor and a spray valve were attached to create a point cloud representation of the surface, detect plants in the area and perform selective spraying. The autonomous robot was tested on replicates of artificial crop plants. The location of each plant was identified out of the acquired point cloud with the help of Euclidian clustering. The gained plant positions were spatially transformed from the coordinates of the sonar sensor to the valve location to determine the exact irrigation points. The results showed that the robot was able to automatically detect the position of each plant with an accuracy of 2.7 cm and could spray on these selected points. This selective spraying reduced the used liquid by 72%, when comparing it to a conventional spraying method in the same conditions.

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supporting

confidence: 75%

3D Imaging with a Sonar Sensor and an Automated 3-Axes Frame for Selective Spraying in Controlled Conditions

et al. 2017

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“…Likewise, the built maps could be used by the novel variable rate application machinery to implement more precise and efficient application of, for example, fertiliser and fungicide. Examples of variable dosage of pesticides in different crops based on ultrasound and 3D sensors have been reported (Maghsoudi et al , Dammer , Tackenberg et al ). In the case of viticulture, the innovation of vineyard machinery with the variable rate technology (Llorens et al , Gil et al , Palleja and Landers ) relies on automated and accurate assessment of the grapevine canopy growth and development, including an assessment of the canopy porosity and amount of exposed leaves.…”

Section: Discussionmentioning

confidence: 99%

On‐the‐go assessment of vineyard canopy porosity, bunch and leaf exposure by image analysis

Diago

Aquino

Millán

et al. 2019

Australian Journal of Grape and Wine Research

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Background and Aims Canopy assessment of the fruiting zone can lead to more informed vineyard management decisions. A non‐destructive, image‐based system capable of operating on‐the‐go was developed to assess canopy porosity, and leaf and bunch exposure of red grape cultivars in the vineyard. Methods and Results On‐the‐go (7 km/h) night time images of a vertically shoot positioned commercial vineyard canopy were acquired with an automated red green blue imaging system, coupled to a GPS and controlled artificial lighting. The reference method was point quadrat analysis. Sound correlations between the image analysis and point quadrat analysis results for the proportion of gaps (R2 > 0.85; P < 0.001) and leaf to canopy area ratio (R2 > 0.57; P < 0.001) were obtained for both sides of the canopy. For the bunch to canopy area ratio the best relationship was found on the western side of the canopy (R2 = 0.79; P < 0.001). Also maps of the three canopy variables were built in a commercial vineyard to compare their spatial variability on the east and west sides across the whole vineyard plot. Conclusions The developed imaging system, capable of operating on‐the‐go, can yield quantitative, objective and reliable knowledge of what a grapegrower would assess by subjective, qualitative visual inspection of the grapevine canopy. The information can be used to help make better informed decisions about leaf removal, and if mapped may help to delineate zones amenable to homogeneous management. Significance of the Study The new developed computer vision system can be mounted on any vehicle, such as a tractor, all terrain vehicle and robot, for a rapid and objective monitoring of the vineyard canopy around the fruiting zone in red cultivars and vertically shoot positioned trained vines. Moreover, the maps generated could be used by a new generation of variable rate viticultural machinery to spatially optimise vineyard cultural practices.

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“…Similar to targeted weed‐spraying robots, autonomous pollinators are being developed to target and spray crops directly to improve the efficiency of growing quality fruit (Amador & Hu, ; Berman, Kumar, & Nagpal, ; Kurosaki, Ohmori, & Takaichi, ; Maghsoudi, Minaei, Ghobadian, & Masoudi, ). A kiwifruit pollinator has been developed in conjunction with the presented kiwifruit harvester, and has been shown to be capable of individually pollinating 80% of flowers in an orchard and producing kiwifruit of commercial quality (Duke et al, ; H. Williams et al, ).…”

Section: Related Workmentioning

confidence: 99%

“…Similar to targeted weed-spraying robots, autonomous pollinators are being developed to target and spray crops directly to improve the efficiency of growing quality fruit (Amador & Hu, 2017;Berman, Kumar, & Nagpal, 2011;Kurosaki, Ohmori, & Takaichi, 2011;Maghsoudi, Minaei, Ghobadian, & Masoudi, 2015).…”

Section: Related Workmentioning

confidence: 99%

Improvements to and large‐scale evaluation of a robotic kiwifruit harvester

Williams

Ting

Nejati

et al. 2019

Journal of Field Robotics

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The growing popularity of kiwifruit orchards in New Zealand is increasing the already high demand for seasonal labourers. A novel robotic kiwifruit harvester has been designed and built to help meet this demand [H. A. Williams et al. Biosystems Eng. 181 (2019), pp. 140–156]. Early evaluations of the platform have shown good results with the system capable of harvesting 51.0% of 1,456 kiwifruit in four bays with an average cycle‐time of 5.5 s/fruit. However, the harvester's high cycle‐time, and high fruit loss rate at 23.4%, prevent it from being commercially viable. This paper presents two new developments for the harvesting system, a new vision system and two new gripper variations designed to overcome the harvester's previous limitations. Furthermore, we have designed and conducted the largest real‐world evaluation of a robotic fruit harvesting system published to date with over 12,000 kiwifruit involved. The results of this trial demonstrated that our kiwifruit harvester is one of the most effective selective fruit harvesters in the world capable of successfully harvesting 86.0% of reachable fruit, and 55.8% of all kiwifruit with a cycle‐time of 2.78 s/fruit.

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Ultrasonic sensing of pistachio canopy for low-volume precision spraying

Cited by 67 publications

References 23 publications

3D Imaging with a Sonar Sensor and an Automated 3-Axes Frame for Selective Spraying in Controlled Conditions

3D Imaging with a Sonar Sensor and an Automated 3-Axes Frame for Selective Spraying in Controlled Conditions

On‐the‐go assessment of vineyard canopy porosity, bunch and leaf exposure by image analysis

Improvements to and large‐scale evaluation of a robotic kiwifruit harvester

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