Progress 09/01/19 to 08/31/22
Outputs
Target Audience:The targeted audiences for this project including scientific professionals, agricultural industry stakeholders, and tree fruit growers. We have been reaching out to them through(i) technical presentations in professional meetings, (ii) presentations during stakeholder meetings, (iii) demos and presentations during extension events, and (iv) research and extension publications. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? One graduate student in this project had the opportunity to get professional research training. A technical from Penn State Fruit Research and Extension Center had the opportunity to get training on operating the intelligent sprayer. An undergraduate student had the opportunity to work at Fruit Research and Extension Center in 2021 summer for spraying data process and imaging processing. PIs and students working on the project attended multiple professional meetings and stakeholder meetings to present project results. How have the results been disseminated to communities of interest? The results of the project were dissminated to the professional communities through scientific publications and presentations (see the Product and Other Product sections). The outcomes of the project were also dissminated to commercial growers through extension events and activities (see the details in the accomplishment under Objective #3). What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Objective #1 An intelligent sprayer was integrated with a LiDAR sensor and solenoid valve controlled nozzles, and it was tested in the field in both 2021 and 2022 crop season. An iris damper-basedairflow control system was built and integrated to the intelligent sprayer, which can control the inlet airflow based on the canopy density. The field test results showed that significant reduction of spray drift was achieved with this airflow control system. A UAV imaging system was developed to measure the canopy specifications such as canopy volume and height, which can be used for guiding the spraying system. A deep learning based apple fire blight detection algorithm was developed to segment infestation areas in the tree canopy, the outcomes can provide guidance for site-specific disease management. Objective #2 In 2021, afield trail of testing the intelligent sprayer was conducted in two apple orchards for the apple scab control. Fourtreatments were implemented for both orchards, including intelligent sprayer (chemical and water) and conventional sprayer(chemical and water). We found that the chemical saving ranged from 36% to 50% throughout the season by using the intelligent sprayer, while the disease control remained similar as comparing to the conventional spraying. In 2022, we continued the apple scab control trial with the intelligent sprayer, and also conducted another chemical thinning test with the sprayer. The results show similar results as in 2021 season for the apple scab control. For the peach chemical thinning, the intelligent sprayer saved around 63% thinners (32 Gallon/Acre to 86 Gallon per Acre,due to large gap between trees), while maintained similar thinning performance as conventional sprayer (10 fruitsset per meter limb to 9 fruits per meter limb). Objective #3 Two extension articles related to the intelligent/precision spraying (2019 and 2022). Organized a workshop on precision sprayer technology including a field demonstration of the intelligent sprayer at 2022 Penn State Fruit Research and Extension Center (FREC) Grower Field Day (Industry and grower attendance: ~120). Presented the results outcomes on the precision orchard spraying to reduce chemical usage and drift at 2022 Penn State Winter Fruit School series (Adams County - 150participants, Franklin County - 40 participants, Lancaster/York County - 30 Participants, and Martinsburg - 30 participants). Invited presentation at 2022 MarylandSprayer and Pesticide Application Twilight Meeting (Extension educator and growers: 25). The graduate student presented the research results at 2022Mid-Atlantic Fruit and Vegetable Conventionwith the topicof UAV based fire blight disease detection of apple trees(grower attendance: ~50). The graduate student presented the research results at 2021Mid-Atlantic Fruit and Vegetable Conventionwith the topicof measuring accurate tree canopy density for developing a precision spraying system (grower attendance: ~50). Invited Dr. Heping Zhu from USDA-ARS and Mr. Steve Booher from Smart Guided Systems to present at 2021 Mid-Atlantic Fruit and Vegetable Convention to discuss the benefit to growers and environment by utilizing intelligent sprayers(Grower attendance: ~50). Presented the research updates on intelligent sprayer at 2020 Penn State Extension Winter Fruit School series (Adams County - 125 participants, Franklin County - 35 participants, and Berks County - 63 participants).
Publications
- Type:
Journal Articles
Status:
Awaiting Publication
Year Published:
2022
Citation:
Mahmud, M.S., Zahid, A., He, L., Zhu, H., Choi, D., Krawczyk, G. and Heinemann, P. 2022. Development of An Automatic Airflow Control System for Precision Sprayers Based on Tree Canopy Density. Journal of the ASABE, p.0.
- Type:
Journal Articles
Status:
Under Review
Year Published:
2022
Citation:
Mahmud, M.S., He, L., Heinemann, P., Choi, D., and Zhu, H. 2022. Unmanned Aerial Vehicle based Tree Canopy Characteristics Measurement for Precision Spray Applications. Smart Agricultural Technology.
- Type:
Journal Articles
Status:
Under Review
Year Published:
2022
Citation:
Mahmud, MS., He, L., Zahid, A., Heinemann, P., Choi, D., Krawczyk, G. and Zhu, H. 2022. Detection and infected area segmentation of apple fire blight using image processing and deep transfer learning for site-specific management. Computers and Electronics in Agriculture.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Mahmud, M.S., Zahid, A., He, L., Choi, D., Krawczyk, G. and Zhu, H. 2021. LiDAR-sensed tree canopy correction in uneven terrain conditions using a sensor fusion approach for precision sprayers. Computers and Electronics in Agriculture, 191, p.106565.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2022
Citation:
Mahmud, M.S. and He, L. 2022. Unmanned Aerial Vehicle based Tree Canopy Characteristics Measurement for Precision Spray Applications. In 2022 ASABE Annual International Meeting (p. 1). American Society of Agricultural and Biological Engineers.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Mahmud, M.S., Zahid, A., He, L. and Martin, P. 2021. Opportunities and possibilities of developing an advanced precision spraying system for tree fruits. Sensors, 21(9), p.3262.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Mahmud, M.S., Zahid, A., He, L., Choi, D., Krawczyk, G., Zhu, H. and Heinemann, P. 2021. Development of a LiDAR-guided section-based tree canopy density measurement system for precision spray applications. Computers and Electronics in Agriculture, 182, p.106053.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Mahmud, M.S., Zahid, A., He, L. and Martin, P., 2021. Opportunities and possibilities of developing an advanced precision spraying system for tree fruits. Sensors, 21(9), p.3262.
- Type:
Other
Status:
Submitted
Year Published:
2022
Citation:
He, L., Peter, K, and Weber, D. 2022. Spray Based on Canopy Density Can Reduce Chemical Usage and Drift. Penn State Extension.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2020
Citation:
Mahmud, M.S. and He, L. 2020. Measuring Tree Canopy Density Using A Lidar-Guided System for Precision Spraying. In 2020 ASABE Annual International Virtual Meeting (p. 1). American Society of Agricultural and Biological Engineers.
- Type:
Other
Status:
Published
Year Published:
2019
Citation:
He, L. and Weber, D. (2019). Introduction of An Intelligent Spray System to PA Growers. Fruit Times.
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Progress 09/01/20 to 08/31/21
Outputs
Target Audience:During this period, we have reached out to 1) scientific professionals through conference presentations and scientific publications; and 2) commercial tree fruit growers and industry stakeholders through extension events such as 2021 Mid-Atlantic Fruit and Vegetable Convention and Pennsylvania Winter Fruit School. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? One graduate student in this project had the opportunity to get professional research training. A technical from Penn State Fruit Research and Extension Center had the opportunity to get training on operating the intelligent sprayer. An undergraduate student had the opportunity to work at Fruit Research and Extension Center in 2021 summer for spraying data process and imaging processing. How have the results been disseminated to communities of interest? The results of the project were dissminated to the professional communities through scientific publications and presentations. The outcomes of the project were also dissminated to commercial growers through extension events and activities. What do you plan to do during the next reporting period to accomplish the goals?In the following year, the following activities will be conducted to accomplish the goals. Initially, this reportingperiod is the final project period, while we have extended the project for another year due to the delay of our field evaluation in the first year. Therefore, for the next reporting period, we will mainly focus on the field evaluation of the intelligent spraying system. Continue field trials for the intelligent sprayer in the pest control of apple scab and japanese beatles. Rearch out to growers with presentations, extension articles, and demonstrations.
Impacts
What was accomplished under these goals?
Objective #1: The intelligent sprayer was integrated and tested in the orchard conditions. An airflow control system was built and added to the intelligent sprayer, which can control the inlet airflow based on the canopy density. A UAV imaging system was developed to measure the canopy specifications such as canopy volume and height, which can be used for guiding the spraying system. Objective #2: A field trail of testing the intelligent sprayer was conductedin two apple orchards for the apple scab control. Four treatments were implemented for both orchards, including intellgient sprayer (chemcial and water) and conventional sprayer (chemcial and water). Objective #3: Presented the research progresses on the intelligent spraying system at 2021 Penn State Extension Winter Fruit School (Grower attendence: ~100). The graduate student presented the research results at 2021 Mid-Atlantic Fruit and Vegetable Convention with the topic of measuring accurate tree canopy density for developing a precision spraying system (grower attendance: ~50). Invited Dr. Heping Zhu from USDA-ARS and Mr. Steve Booher from Smart Guided Systems to present at 2021 Mid-Atlantic Fruit and Vegetable Conventionto discuss the benefit to growers and environment by utilizing intelligent sprayers (Grower attendance: ~50).
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Mahmud, M.S., Zahid, A., He, L., Choi, D., Krawczyk, G., Zhu, H. and Heinemann, P., 2021. Development of a LiDAR-guided section-based tree canopy density measurement system for precision spray applications. Computers and Electronics in Agriculture, 182, p.106053.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Mahmud, M.S., Zahid, A., He, L. and Martin, P., 2021. Opportunities and Possibilities of Developing an Advanced Precision Spraying System for Tree Fruits. Sensors, 21(9), p.3262.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2021
Citation:
Mahmud, M.S., Zahid, A. and He, L., 2021. Development of An Automatic Airflow Control System for Precision Sprayers Based on Tree Canopy Density. In 2021 ASABE Annual International Virtual Meeting. American Society of Agricultural and Biological Engineers.
- Type:
Journal Articles
Status:
Submitted
Year Published:
2021
Citation:
Correction of LiDAR-Sensed Tree Canopy in Uneven Terrain Conditions using A Sensor Fusion Approach for Precision Sprayers. Transactions of the ASABE. (Submitted)
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Progress 09/01/19 to 08/31/20
Outputs
Target Audience:The targe audiences include:Comercial tree fruit growers; scientific professionals; pesticides service professionals Changes/Problems:As the proposal planned, we are going to have two seasons for field trials. However, due to the pandemic situation in the spring 2020, the sprayer and intelligent kit for our test system were delayed. We are going to ask one year no-cost extension to still evaluate the system for two seasons. What opportunities for training and professional development has the project provided? One graduate student in this project had the opportunity to get professional research training. A training is in a scheduling for project team members on gaining the knowledge of lidar based spray technologies as well as the installation and operation of intelligent sprayer. How have the results been disseminated to communities of interest? Presentations and field demonstration of precision sprayer were carried out to commercial growers and pesticide serviceindividials. The results of the project was dissminated to growers and professioanl societythrough professional publication and extension publication (see the publications). What do you plan to do during the next reporting period to accomplish the goals?In the coming year, the following activities will be conducted to accomplish the goals. Objective #1: Canopy density measurement with considering different canopy strucutes and growing stages, and also the terrain variation in the orchards. Integration of the intelligent sprayer system, and condcut functional test such as coverage rate, penetration, and drift in different canopies. Objective #2: A pest control evaluation will be conducted using the newly deveoped intelligent sprayer in apple/peach orchards for apple scab and japanese beetles control. Objective #3: Rearch out to growers with presentations, seminars, extension articles, and/or demonstrations. Work on scientific publications and extension fact sheets to widely disseminate the project results.
Impacts
What was accomplished under these goals?
Objective #1: A tree canopy density measurement unit was developed using a 3D Lidar sensor. The canopy foliage volume and density map were created to provide guidance for precision spraying in the orchards. An inertial navigation system (including an RTK GPS and an IMU) was integrated to the canopy density measurement system to recording the geo-reference for individual tree and correct the canopy point cloud data due to orchard terrain variation. Objective #2: The integrated intellgient sprayer system was delayed due to the current situation (the explanation was provided in the Changes/Problems), thus, we did not get chance to conduct field trials with the integrated sprayer. However, regular pest management for apple scab, Japanese beetles were conducted. Objective #3: On September 10th, 2019, a plant protection field day was held at Fruit Research and Extension Center. Around 30 participants attended this event, including tree fruit growers, chemcial industry, agricultural services personnel and extension specialists. Project team members gave serveral presentations at 'Precision Spray Technologies' and 'Pest Management in Fruit Orchards'. A workshop 'Intelligent Spray Technologies and Systems' along with a field demonstarionwas carried out on July 15th at Penn State FREC research orchard(this event was held before the project start date, but it was planned for this project). In total, 26 participants including comercial growers and extension agents participated in the presentations by project team members, and intellgient sprayer demonstration by our collaborator Dr. Heping Zhu.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2020
Citation:
Mahmud, M.S. and He, L., 2020. Measuring Tree Canopy Density Using A Lidar-Guided System for Precision Spraying. In 2020 ASABE Annual International Virtual Meeting (p. 1). American Society of Agricultural and Biological Engineers.
- Type:
Journal Articles
Status:
Under Review
Year Published:
2020
Citation:
Mahmud, M.S., Zahid, A. and He, L., 2020. Opportunities and Possibilities of Developing and Advanced Intelligent Spraying System for Apple Orchard. Computers and Electronics in Agriculture (Under review).
- Type:
Other
Status:
Published
Year Published:
2019
Citation:
He, L., & Weber, D. (2019). Introduction of An Intelligent Spray System to PA Growers. Fruit Times.
- Type:
Other
Status:
Published
Year Published:
2020
Citation:
Mahmud, M.S., & He, L.(2020). Poster: Development of an Image Processing Based Algorithm for Intelligent Sprayer Performance Analysis. 2020 NABEC meeting.
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