Stalk Sensor Assemblies for Row-Level Missing Plant Detection
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Solution Overview
Problem
Existing yield maps in agriculture do not accurately detect missing or late-emerged plants, leading to incorrect assessment of yield issues and potential economic losses, as they treat missing plants as lower yields rather than distinct problems requiring different corrective actions.
Innovation Solution
Implementing stalk sensors on combine harvesters to count and measure corn stalks row-by-row, using wheels with pulse sensors to determine stalk size and engage brakes or proximity sensors to accurately differentiate between healthy and late-emerged stalks, coupled with a data visualization system to display yield data on a per-row basis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional yield maps are used to assess crop performance, then overall yield data is obtained, but missing or late-emerged plants cannot be accurately detected
Solution Approach 1:
The yield assessment system is segmented into multiple independent detection channels, each equipped with stalk sensors that independently monitor individual rows. This segmentation allows the system to identify missing or late-emerged plants in specific rows without affecting the monitoring of other rows, thereby preventing information loss while maintaining overall system functionality.
Solution Approach 2:
Stalk sensors serve as intermediary devices mounted on the corn head that directly contact and detect the presence of plant stalks during harvest. These sensors translate physical plant presence into detectable signals, enabling the system to accurately identify missing or late-emerged plants that traditional yield maps cannot detect.
2Measurement precision
If stalk sensors are added to detect missing plants, then plant detection accuracy improves, but device complexity increases
Solution Approach 1:
The stalk sensors mounted on the corn head serve multiple functions: they detect the presence of stalks, determine row-by-row yield data, and identify missing or late-emerged plants. This multi-functionality reduces the need for separate dedicated devices for each task, thereby improving measurement precision without proportionally increasing device complexity.
Solution Approach 2:
The system utilizes the natural harvesting process itself to enable detection. As the corn head naturally engages with stalks during harvest, the stalk sensors passively detect plant presence without requiring additional active mechanisms. The harvesting action serves the dual purpose of both crop collection and data collection, reducing system complexity.
3Loss of information
If row-by-row stalk measurement is implemented, then yield information accuracy improves, but data processing requirements increase
Solution Approach 1:
The system performs preliminary data organization and filtering at the source during harvest. Stalk sensors continuously monitor and immediately categorize stalk data by row, identifying missing or late-emerged plants in real-time. This preliminary processing reduces the burden on subsequent data analysis stages, maintaining high yield information accuracy while minimizing data processing time delays.
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
Enables precise identification and quantification of missing and late-emerged plants, allowing farmers to take targeted corrective actions to improve yield, reducing economic losses by accurately distinguishing between different yield issues.
Implementation Method 1
The one or more wheels engage with stalks so as to rotate
Implementation Method 2
the agricultural system estimates the size of the stalks via the wheel rotation
Implementation Method 3
the one or more wheels is operationally coupled to one or more pulse sensors
Implementation Method 4
the one or more wheels is operationally coupled to one or more brakes
Data Source
AI summary
Agricultural systems have stalk sensor assemblies and/or data visualization systems. The stalk sensor assemblies are configured for assessing the size and other characteristics about crops, such as corn and other grains entering an agricultural implement, such as a harvester. The stalk sensor assemblies may use an estimation of the stalk perimeter to establish stalk size and therefore further features about the crop. The visualization system utilizes data from the stalk sensor assemblies to calculate and display relevant information about the crop.