Crop Drying Score Forecasting for Harvest Timing
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Solution Overview
Problem
Current tools lack the capability to forecast the drying rate of agricultural crops, such as hay, leading to risks associated with limited and variable time periods between rains and varying drying rates, which complicates the harvesting process.
Innovation Solution
A system and method utilizing an electronic processor to receive weather data and agricultural field parameters, calculating a drying score for each harvest time to determine a recommended harvest time, and outputting a forecast that includes the drying score and recommended harvest time for display to users, thereby aiding in the decision-making process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If farmers rely on local weather forecasts to estimate time between rains, then they can predict rainfall timing, but they cannot forecast how fast the crop will dry at a given time and location
Solution Approach 1:
The system performs preliminary calculations of drying scores for multiple future harvest times before the actual harvest decision is made. By pre-calculating drying forecasts for several time periods ahead, farmers can plan harvest timing in advance with confidence, addressing the information gap about drying rates without compromising reliability
Solution Approach 2:
The system incorporates field sensor data (soil moisture, crop moisture) as feedback to continuously update and refine drying score calculations. This feedback mechanism ensures that the drying forecasts remain accurate and reliable by adjusting predictions based on actual field conditions rather than relying solely on weather data
2Adaptability or versatility
If farmers harvest based on variable drying rates, then they can adapt to different conditions, but they face increased risk due to limited and variable time periods between rains
Solution Approach 1:
The system changes the parameter of drying rate prediction by calculating drying scores that incorporate multiple factors (weather data, field parameters, crop type, soil type) rather than relying on a single variable. This multi-parameter approach allows the system to adapt to varying conditions while maintaining reliable harvest timing recommendations through comprehensive analysis
Solution Approach 2:
By pre-calculating drying scores for multiple potential harvest times, the system provides farmers with advance knowledge of optimal harvest windows. This preliminary action allows farmers to plan ahead and choose the best harvest time that balances adaptability to conditions with reliability of successful harvest, reducing the risk associated with variable drying rates
3Device complexity
If no drying forecast tool is available, then farmers have simple decision-making processes, but they experience increased risk and reduced success in providing dry agricultural crop
Solution Approach 1:
The system introduces an intermediary processing layer that takes complex inputs (weather data, field sensor data, crop parameters) and transforms them into a simple, actionable output (drying score and recommended harvest time). This intermediary function maintains device complexity at an acceptable level while significantly improving reliability by systematically processing multiple factors that affect crop drying
Solution Approach 2:
The system transforms multiple complex parameters (weather conditions, soil moisture, crop moisture, evaporation rates) into a single simplified parameter - the drying score. This parameter transformation maintains ease of use for farmers while improving reliability by incorporating comprehensive data analysis to predict crop dryness with greater accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution mitigates the risks of providing a dry agricultural crop by providing a reliable forecast, improving the chances of successfully harvesting a dry crop by indicating the relative dryness and probability of success at different harvest times.
Implementation Method 1
forecasting how fast an agricultural crop will dry at a given time and location
Data Source
AI summary
A system for forecasting the drying of an agricultural crop includes an electronic processor configured to receive weather data associated with an agricultural field and receive an agricultural field parameter from a field sensor associated with the agricultural field. The electronic processor is also configured to determine a drying score for each of a plurality of harvest times based on the weather data and the agricultural field parameter. The electronic processor is also configured to determine a recommended harvest time for harvesting the agricultural crop based on the drying score, wherein the recommended harvest time is included in the plurality of harvest times. The electronic processor is also configured to output a forecast for the agricultural crop for display to a user, wherein the forecast includes the drying score and the recommended harvest time for harvesting the agricultural crop.