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An agriprecision decision support system for weed management in pastures
Digital Document
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Peer Review Status
Peer Reviewed
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Persons |
Author (aut): Chegini, Hossein
Author (aut): Naha, Ranesh
Author (aut): Mahanti, Aniket
Author (aut): Gong, Mingwei
Author (aut): Passi, Kalpdrum
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Funder (fnd): Library OA fund
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Abstract |
Abstract
Pastures are a vital source of dairy products and cattle nutrition, and as such, play a significant role in New Zealand’s agricultural economy. However, weeds can be a major problem for pastures, making it a challenge for dairy farmers to monitor and control them. Currently, most of the tasks for weed management are done manually, and farmers lack persistent technology for weed control. This motivated us to design, implement, and evaluate a Decision Support System (DSS) to detect weeds in pastures and provide decisions for the cleanup of weeds. Our proposed system uses two primary inputs: weeds and bare patches. We created a synthetic dataset to train a weed detection model and designed a fuzzy inference system to assess a pasture. We also used a neuro-fuzzy system in our DSS to evaluate our fuzzy model and tune its parameters for better functioning and accuracy. Our work aims to assist dairy farmers in better weed monitoring, as well as to provide 2D maps of weed density and yield score, which can be of significant value when no digital and meaningful images of pastures exist. The system can also support farmers in scheduling, recommending prohibitive tasks, and storing historical data for pasture analysis, collaborated by stakeholders. |
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Publication Number
Volume 11
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Physical Description Note |
Physical Description Note
PUBLISHED
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DOI |
DOI
10.1109/ACCESS.2023.3307311
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ISSN |
ISSN
2169-3536
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Keywords |
Keywords
fuzzy systems
object detection
pasture management
decision making
decision support systems
fuzzy neural networks
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Subject Topic |
Cite this
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English
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An agriprecision decision support system for weed management in pastures
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Authored on |
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application/pdf
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6188905
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