TY - JOUR
T1 - Real-time control of high-resolution micro-jet sprayer integrated with machine vision for precision weed control
AU - Raja, Rekha
AU - Slaughter, David C.
AU - Fennimore, Steven A.
AU - Siemens, Mark C.
N1 - Funding Information: This research is supported by grants from the USDA NIFA Specialty Crops Research Initiative USDA-NIFA-SCRI-004530 , the California Tomato Research Institute , and the California Leafy Greens Research Program . The USDA NIFA Specialty Crops Research Initiative funding programme had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors would like to thank Leland Neilson, Burt Vannucci, John Rachuy, Jedediah Roach, and Tom Bell, University of California, Davis, for their technical assistance in conducting this research. The authors would also like to thank and recognize Victor Godiez Jr., Ron Gayler and Mazin Saber, University of Arizona for their contributions towards the development of the precision sprayer used in this study. Publisher Copyright: © 2023 The Author(s)
PY - 2023/4
Y1 - 2023/4
N2 - The advent of automated technology in agriculture employing robots allows researchers and engineers to automate many of the tasks in a semi-structured, natural farming environment where these tasks need to be performed. Here we propose a fast-intelligent weed control system using a crop signalling concept with machine vision and a precision micro-jet sprayer to target in-row weeds for precision herbicide application. Crop signalling is a novel technology invented to read crop plants by machine to simplify the task of differentiating vegetable crops from weeds for selective weed control in real-time. In-row weed control in vegetable crops like lettuce requires a very precise herbicide spray resolution with a fast response time. A novel, accurate, high-speed, centimetre precision spray targeting actuator system was designed and experimentally validated in synchronization with a machine vision system to spray detected weeds located between lettuce plants. The system processed an image, representing a 120 mm × 180 mm region of row-crop in 80 ms, which allowed the micro-jet sprayer to successfully function at a travel speed of 3.2 km h−1 and selectively deliver herbicide to the weed targets. The analysis of the overall performance of the system to kill weeds in indoor experimental trials is discussed and presented. Findings indicate that 98% weeds were correctly sprayed which indicates the efficacy and robustness of the proposed systems.
AB - The advent of automated technology in agriculture employing robots allows researchers and engineers to automate many of the tasks in a semi-structured, natural farming environment where these tasks need to be performed. Here we propose a fast-intelligent weed control system using a crop signalling concept with machine vision and a precision micro-jet sprayer to target in-row weeds for precision herbicide application. Crop signalling is a novel technology invented to read crop plants by machine to simplify the task of differentiating vegetable crops from weeds for selective weed control in real-time. In-row weed control in vegetable crops like lettuce requires a very precise herbicide spray resolution with a fast response time. A novel, accurate, high-speed, centimetre precision spray targeting actuator system was designed and experimentally validated in synchronization with a machine vision system to spray detected weeds located between lettuce plants. The system processed an image, representing a 120 mm × 180 mm region of row-crop in 80 ms, which allowed the micro-jet sprayer to successfully function at a travel speed of 3.2 km h−1 and selectively deliver herbicide to the weed targets. The analysis of the overall performance of the system to kill weeds in indoor experimental trials is discussed and presented. Findings indicate that 98% weeds were correctly sprayed which indicates the efficacy and robustness of the proposed systems.
KW - Artificial intelligence
KW - Crop signalling
KW - Micro-jet sprayer
KW - Precision agriculture
KW - Robotic weed control
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U2 - https://doi.org/10.1016/j.biosystemseng.2023.02.006
DO - https://doi.org/10.1016/j.biosystemseng.2023.02.006
M3 - Article
SN - 1537-5110
VL - 228
SP - 31
EP - 48
JO - Biosystems Engineering
JF - Biosystems Engineering
ER -