Dynamic Crop Model Using In-Season Weather Data
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Solution Overview
Problem
Current crop management methods lack precision, as they do not effectively utilize in-season weather data to update crop management plans, leading to suboptimal crop yields and field parameters.
Innovation Solution
Implementing a method that uses a crop model to incorporate actual and projected weather data to adjust crop management plans mid-season, including parameters like fertilization and irrigation, to optimize yield and field performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional crop management methods are used without in-season weather data updates, then the management process is simpler and requires less data processing, but the crop yield and field parameters are suboptimal
Solution Approach 1:
The crop management plan is made dynamic by continuously updating it with in-season actual weather data. The system transitions from a static pre-season plan to a dynamic mid-season updated plan that adapts to actual growing conditions, thereby optimizing crop yield without requiring overly complex infrastructure
Solution Approach 2:
The system implements feedback by using actual weather data collected during the growing season to update the crop management plan. This feedback loop allows the system to adjust management parameters based on real conditions, improving productivity while maintaining manageable complexity through automated data processing
2Measurement precision
If a crop model uses only pre-season weather data, then the planning process is faster and requires less computational resources, but the accuracy of the crop management plan is reduced
Solution Approach 1:
The system performs preliminary actions by establishing the crop management plan before the growing season using pre-season weather data. This initial plan provides a foundation that can be quickly updated later, reducing the time burden of complete re-planning while maintaining high accuracy through mid-season updates with actual weather data
Solution Approach 2:
The system maintains continuity of useful action by continuously updating the crop management plan with in-season weather data throughout the growing season. This continuous refinement process improves accuracy without requiring complete replanning, as the existing model framework and historical data remain relevant and are simply updated with new information
Data Source
AI summary
The disclosure relates to methods and related systems for precision crop modeling and management using the same. Precision crop modeling and management can be incorporated into various methods for growing plants such as crop plants and various methods for managing the growth of such plants in a particular field. The methods generally utilize in-season information relating to weather conditions actually experienced by the field to prepare mid-season, updated crop management plans. A crop management plan is determined using a crop model incorporating a variety of inputs and plant-specific material and energy balances to specify one or more grower-controlled management parameters. An updated plan for a given field can be followed by a grower to increase crop yield and/or optimize one or more other crop or field parameters.