Zone-Specific Seeding Parameters Using Field and Weather Data
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Solution Overview
Problem
Farmers face challenges in determining optimal field- or zone-specific seeding rate, depth, and time for planting crops due to the lack of a systematic approach despite having available data on field features, leading to inefficient yield and increased use of crop protection agents.
Innovation Solution
A computer-implemented method that uses crop, field, yield, weather, and soil data to determine seeding rate, depth, and time, enabling efficient decision-making and minimizing crop protection agent use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If farmers use available field data (altitude, soil texture, moisture, historical yield) to determine seeding parameters, then seeding precision and yield potential improve, but decision-making complexity and data processing requirements increase
Solution Approach 1:
The patent divides the agricultural field into multiple zones based on spatial variability of soil properties, altitude, and historical yield data. Each zone receives customized seeding parameters (rate, depth, time) rather than uniform treatment, resolving the contradiction by segmenting the complex decision problem into manageable zone-specific decisions while maintaining high precision
Solution Approach 2:
The system performs preliminary data collection and processing before the actual seeding operation. Field data (soil texture, moisture, altitude, historical yield) is gathered and analyzed in advance to pre-determine optimal seeding parameters for each zone, reducing on-the-spot decision complexity while maintaining precision
2Productivity
If farmers select inappropriate seeding rate, depth, or time due to lack of systematic approach, then crop yield and crop value decrease, but the complexity of the seeding decision process remains high
Solution Approach 1:
The patent systematically varies key seeding parameters (seeding rate, seeding depth, seeding time) based on zone-specific conditions. By establishing clear relationships between field conditions and optimal parameter values, the system improves crop yield while providing a structured rather than arbitrary approach to parameter selection
Solution Approach 2:
The system incorporates historical yield data and soil monitoring data to continuously refine seeding parameter recommendations. This feedback mechanism improves productivity over time while maintaining a manageable level of complexity through data-driven rather than trial-and-error approaches
3Ease of operation
If farmers use uniform seeding approach across the entire field, then decision-making simplicity is maintained, but yield potential and resource efficiency are lost
Solution Approach 1:
The patent applies the principle of local quality by assigning different seeding parameters to different zones within the field based on their specific characteristics (soil texture, moisture, altitude, historical yield). This allows the system to maintain operational simplicity through standardized procedures while achieving high yield potential through location-specific parameter optimization
Data Source
AI summary
A computer-implemented method for determining at least one of the treatment parameters selected from the group consisting of: (a) at least one rate (seeding rate) for planting at least one crop in a field or a sub-field zone, (b) at least one depth (seeding depth) for planting at least one crop in a field or a sub-field zone, and (c) at least one time window (seeding time) for planting at least one crop in a field or a sub-field zone, comprising the following steps: (step 1) receiving by the computing unit—from a database and/or from user input and/or from real-time measurements—crop data relating to the at least one crop to be planted in the field or in the sub-field zone and static field data relating to the field or the sub-field zone, (step 2) receiving by the computing unit—from a database and/or from user input and/or from real-time measurements—at least one type of additional data selected from the group consisting of: (A) yield data relating to the field or the sub-field zone, (B) weather data relating to the field or the sub-field zone, and (C) soil data relating to the field or the sub-field zone, (step 3) at least based on the crop data, and the static field data, and the at least one type of additional data, initiating and/or performing data processing in at least one database and/or database system containing (i) data related to crop data and/or data related to static field data, (ii) data related to the at least one treatment parameter, and (iii) data related to at least one type of additional data selected from the group consisting of: yield data, weather data, and soil data, (step 4) outputting the at least one treatment parameter based on the result of the data processing.