Project Details
Description
The purpose of this proposal is to develop a comprehensive weed control system for sugarcane cultivation, with the aim of enhancing efficiency and sustainability in weed management for this significant agricultural crop.
Firstly, the proposal seeks to establish a procedure for gathering information using active and passive sensors. These sensors will be employed to characterize weed types and their emergence patterns during the early stages of sugarcane cultivation. The collected information will include data on weed density, height, and location, as well as the phenological stage of the sugarcane. This detailed characterization will provide a better understanding of weed dynamics and their interaction with the crop, which will be crucial for the subsequent design of the weed control system.
Next, the most suitable recognition technique will be determined to identify the weeds present in sugarcane cultivation. Spatial analysis and machine learning methods will be employed to validate and process the information captured by the sensors. These intelligent algorithms will identify patterns and distinctive features of the weeds, facilitating their detection and differentiation from sugarcane plants. This will enable more precise and effective weed control, minimizing excessive herbicide use and reducing associated environmental impact.
In addition, the implementing variable control in ground application equipment. Utilizing the characterized and processed information, customized prescriptions will be created for differentiated weed control in sugarcane cultivation. This means the control system will automatically adjust the application of herbicides and other weed management methods based on the density and type of weed present in each area of the field. In this way, unnecessary chemical usage will be avoided, optimizing control efficacy, and resulting in more sustainable and cost-effective crop management.
Finally, a project viability evaluation will be conducted. Economic and environmental indicators will be analyzed to determine the benefits generated by implementing the variable weed control system. Implementation costs of the system will be assessed, along with potential savings in agricultural inputs, especially herbicides. Additionally, the environmental impact of the system will be measured, considering the reduction in the quantity of applied chemicals and its effect on conserving natural resources and the agricultural environment.
Firstly, the proposal seeks to establish a procedure for gathering information using active and passive sensors. These sensors will be employed to characterize weed types and their emergence patterns during the early stages of sugarcane cultivation. The collected information will include data on weed density, height, and location, as well as the phenological stage of the sugarcane. This detailed characterization will provide a better understanding of weed dynamics and their interaction with the crop, which will be crucial for the subsequent design of the weed control system.
Next, the most suitable recognition technique will be determined to identify the weeds present in sugarcane cultivation. Spatial analysis and machine learning methods will be employed to validate and process the information captured by the sensors. These intelligent algorithms will identify patterns and distinctive features of the weeds, facilitating their detection and differentiation from sugarcane plants. This will enable more precise and effective weed control, minimizing excessive herbicide use and reducing associated environmental impact.
In addition, the implementing variable control in ground application equipment. Utilizing the characterized and processed information, customized prescriptions will be created for differentiated weed control in sugarcane cultivation. This means the control system will automatically adjust the application of herbicides and other weed management methods based on the density and type of weed present in each area of the field. In this way, unnecessary chemical usage will be avoided, optimizing control efficacy, and resulting in more sustainable and cost-effective crop management.
Finally, a project viability evaluation will be conducted. Economic and environmental indicators will be analyzed to determine the benefits generated by implementing the variable weed control system. Implementation costs of the system will be assessed, along with potential savings in agricultural inputs, especially herbicides. Additionally, the environmental impact of the system will be measured, considering the reduction in the quantity of applied chemicals and its effect on conserving natural resources and the agricultural environment.
General Objective
Generar una metodología de detección remota para la identificación y el control localizado de malezas en caña de azúcar, en la región Central de Costa Rica
Research Lines
Información y Tecnologías para la producción
| Short title | Weed caña |
|---|---|
| Acronym | W-caña |
| Status | Finished |
| Effective start/end date | 1/01/25 → 31/12/25 |
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