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- W3106683537 abstract "The continued emergence of herbicide-resistant weeds and the increasing labor costs are threatening the ability of growers to manage weeds and maintain profits. The smart farm with the advantage of non-invasive and high-efficiency operation plays an important role in increasing the sustainability of agricultural system as it can optimize crop inputs such as herbicides while preserving resources including soil and water. An automatic weed control system requires a sensing subsystem capable of detecting and distinguishing crop plants from weeds. The overlapping plants remain a challenge for successful detection of weeds. Crop plant signaling is a new robot-plant interaction technique that allows the visualization of exogenous fluorescent signals applied to crop plants for crop/weed identification. Based on all published articles in the leading edge of knowledge, a comprehensive review of the mushrooming crop plant signaling for discriminations of weeds and crops is highlighted. The discussion outlines the significant progress that has been made in developing new and more robust automated systems along with the current challenges and future prospects. This paper details the promise of crop plant signaling for accurate and automated plant recognitions in cropping systems. There is no doubt that this review is of great significance to scholars in related research field to study the solutions to real-time weed control." @default.
- W3106683537 created "2020-12-07" @default.
- W3106683537 creator A5057470021 @default.
- W3106683537 date "2020-01-01" @default.
- W3106683537 modified "2023-10-02" @default.
- W3106683537 title "Crop plant signaling for real-time plant identification in smart farm: A systematic review and new concept in artificial intelligence for automated weed control" @default.
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- W3106683537 doi "https://doi.org/10.1016/j.aiia.2020.11.001" @default.
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