Selective Weed Control Spraying Using Image-Based Row Detection
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Solution Overview
Problem
Current agricultural practices for applying crop protection products, such as herbicides, lack precision, often treating entire fields without differentiation between crop plants and weeds, leading to adverse effects on crops.
Innovation Solution
A computer-implemented method and system that utilize image data and machine learning models to identify crop planting rows, detect weeds, and apply crop protection products only where needed, based on the distance between weeds and adjacent crop plants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional field-wide herbicide application is used, then weed control coverage is improved, but crop plant damage increases
Solution Approach 1:
The patent applies local quality by differentiating treatment based on spatial location relative to crop plants. The system identifies zones based on distance from crop plants and applies herbicides selectively: full application rate in zones远离 crops where weeds are uncontrolled, and reduced or no application in zones靠近 crops where weeds are controlled by proximity. This spatial differentiation allows effective weed control in field areas while protecting crop plants from harmful herbicide exposure.
Solution Approach 2:
The patent segments the agricultural field into multiple treatment zones based on distance from crop plants. The field is divided into inner zones (close to crops) and outer zones (away from crops), with each zone receiving different herbicide application rates. This segmentation enables the system to maintain effective weed control in outer zones while minimizing crop damage risk in inner zones, resolving the contradiction between comprehensive weed control and crop protection.
2Object-affected harmful factors
If selective herbicides are used, then crop protection is improved, but weed control effectiveness decreases
Solution Approach 1:
The patent applies dynamics by making the herbicide application rate variable rather than fixed. The system dynamically adjusts the application rate based on the identified zone and distance from crop plants. In zones away from crops, full application rates are used for maximum weed control effectiveness. In zones靠近 crops, the system reduces or eliminates application to protect crops. This dynamic adjustment allows the system to maintain both effective weed control and crop protection, overcoming the limitation of static selective herbicide use.
Solution Approach 2:
The patent changes the parameter of herbicide application rate based on spatial conditions. By modifying the application rate parameter according to the zone identification and distance from crop plants, the system achieves both effective weed control (in outer zones with higher rates) and crop protection (in inner zones with reduced or zero rates). This parameter change strategy resolves the contradiction between using selective herbicides for crop protection and maintaining effective weed control.
3Object-affected harmful factors
If zone-specific application is implemented, then crop protection is improved, but application complexity increases
Solution Approach 1:
The patent replaces complex mechanical differentiation systems with an image processing-based zone identification system. Instead of using complex mechanical devices to physically separate or target specific zones, the system uses cameras and image processing algorithms to identify zones based on visual data from the field. This substitution simplifies the overall system by replacing mechanical complexity with optical and computational methods, achieving zone-specific application while reducing device complexity.
Solution Approach 2:
The patent applies self-service by enabling the system to automatically identify zones and determine appropriate application rates without requiring manual intervention or complex pre-programming. The image processing system autonomously analyzes field conditions, identifies zones based on distance from crop plants, and determines herbicide application rates automatically. This self-service capability reduces the need for complex manual control systems while achieving precise zone-specific application, thereby reducing overall system complexity.
Data Source
AI summary
A computer-implemented method for selectively applying at least one crop protection product onto an agricultural field (40), comprising the following steps: —providing image data of at least a part of an agricultural field (40) which is to be treated with a crop protection product; —providing a crop planting row identification model (63) configured to identify crop planting rows (42) in the image data of the at least one part of the agricultural field (40); —providing a weed plant detection model (65) configured to detect weed plants (46) between the identified crop planting rows (42); —providing a crop and weed detection model (67) configured to detect crop plants (41) and weed plants (46) in the identified crop planting rows (42); —applying a first crop protection product (44) onto a weed plant (46) detected between the identified crop planting rows (42); —applying the first crop protection product (44) onto a weed plant (46) detected in the identified crop planting rows (42), if a distance between the weed plant and an adjacent crop plant is larger than a dynamic determined rows minimal distance.