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item Kaspar, Thomas

Submitted to: ASAE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 8/4/2004
Publication Date: 8/4/2004
Citation: Abd Aziz, S., Stewart, B.L., Birrell, S.J., Kaspar, T.C., Shrestha, D.S. 2004. Ultrasonic sensing for corn plant canopy characterization. ASAE Annual International Meeting. St. Joseph, MI. Paper No. 04-041120.

Interpretive Summary: A major limitation to identifying and mapping yield-limiting factors in agricultural fields is the availability of appropriate on-the-go sensing technologies for plant growth during the growing season. The ability to map crop height and changes in crop height over time in agricultural fields would be a useful diagnostic tool to identify where and when crop stress is occurring. Additionally, plant height or rate of plant height change could be used to evaluate spatial crop response to inputs of fertilizers, herbicides, or insecticides. In this study we developed, tested, and compared a prototype system for measuring crop height. The system utilized an ultrasonic sensor and signal processing to measure corn growth stage, canopy development, and plant height. With further development this system will be capable of measuring and mapping crop height and canopy development on-the-go from a tractor-mounted platform. Farmers should be able to use this system to identify areas in their fields that are stressed and require management inputs such as fertilizer or water or areas that did not respond to inputs applied earlier, such as fertilizers, herbicides, or insecticides. In general, farmers will use this information to increase profitability and reduce environmental impacts. Scientists will use this system to identify the causes of variable crop growth in fields and to find management solutions to alleviate spatially variable crop stress.

Technical Abstract: Non-destructive measurement of crop growth stage, canopy development, and height may be useful for more efficient crop management practices. In this study, ultrasonic sensing technology was investigated as one approach for corn plant canopy characterization. Ultrasonic echo signals from corn plant canopies were collected using a lab-based sensor platform. Echo signal peak features were extracted from multiple scans of plant canopies. These features included peak amplitude, scan number, and time of flight. Feature vectors with similarities were clustered together to identify individual leaves of the canopy. The mean height of the clustered data of individual leaves was estimated. The growth stage of each plant was estimated based on the number of leaves detected. Regression analysis was used to describe the relationship between manually measured leaf heights and ultrasonic estimates. A leaf-signal interaction model was developed to predict which parts of leaf surfaces will result in echo signals detectable by the sensor. The aim of this research was to develop a sensing system which extracted information from an ultrasonic sensor that could be used for a variety of sensing operations in precision agriculture and to better understand the relationship between corn plant canopy and ultrasonic signals.