Zone-Specific Application Map Generation for Agricultural Fields
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Solution Overview
Problem
Current agricultural field treatment models do not account for local variations, resulting in inefficient use of products and potential over-application, which affects yield and increases costs.
Innovation Solution
A hypermodel-based method that combines subordinate models, including a product recommendation model and a biophysical parameter model, to generate a zone-specific application map, optimizing product application based on local conditions within an agricultural field.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If uniform product application is used across the entire agricultural field, then the treatment process is simple and fast, but local variations are not addressed leading to inefficient product use and potential over-application
Solution Approach 1:
The agricultural field is divided into multiple zones based on local variations in soil properties, topography, and crop conditions. Each zone is then treated with appropriate product amounts tailored to its specific characteristics, rather than applying uniform treatment across the entire field. This segmentation enables precise product application that matches local needs.
Solution Approach 2:
Different zones within the agricultural field receive different product application rates and compositions based on their specific local conditions. The system determines optimal product types and amounts for each zone individually, ensuring that areas with higher needs receive more product while areas with lower needs receive less, thereby eliminating over-application in suitable zones.
2Loss of substance
If zone-specific product application is implemented, then product use efficiency is optimized and costs are reduced, but the complexity of the treatment system increases
Solution Approach 1:
The system performs preliminary analysis of the agricultural field by collecting and processing data on soil properties, topography, and crop conditions before product application. This preliminary action creates a treatment plan that divides the field into zones and specifies optimal product application for each zone, allowing the actual application process to follow a pre-determined efficient pattern.
Solution Approach 2:
A computational model acts as an intermediary between field data and product application decisions. The model processes various input parameters (soil properties, topography, crop conditions) and generates zone-specific treatment recommendations, simplifying the complexity by providing a systematic decision-making framework rather than requiring direct complex control of application equipment.
Data Source
AI summary
A method for generating a zone specific application map (8) for treating an agricultural field with products is provided. The method comprises providing a hypermodel (1) comprising a product recommendation model, PRM (2) and a biophysical parameter model, BPM (3). The method further comprises providing PRM input parameters (4) for the product recommendation model (2) and generating PRM output (5) by the product recommendation model (2). The method also comprises providing BPM input parameters (6) for the biophysical parameter model (3) and generating BPM output (7) by the biophysical parameter model (3). Finally, the method comprises generating the zone specific application map (8) by the hypermodel (1), using at least parts of the PRM output (5) and parts of the BPM output (7). Further, a system (19) for generating a zone specific application map (8), a computer program element, a use of a zone specific application map (8) and an agricultural equipment (23) are provided.