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Parameter Adjustment to a Crop Model Using a Sensor-based Decision Support System

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Transactions of the ASAE. 36(1): 205-213. (doi: 10.13031/2013.28332) @1993
Authors:   S. J. Thomson, R. M. Peart, J. W. Mishoe
Keywords:   Sensors, Expert systems, Modeling

A knowledge-based system was developed to adjust input parameters to the soil-water and rooting components of PNUTGRO, a process-oriented peanut growth model. The system was developed to provide a better representation of temporal water status in the root zone of a growing crop. Soil water sensors provided input to adjust appropriate parameters based on interpretation of their readings. These interpretations were programmed using human expertise combined with data from peanuts grown in lysimeters. A separate expert system screened sensor readings to insure their validity before using their readings to adjust parameters. Tests of the system over one season showed that model-based representations of soil-water status converged on sensor-based representations in the soil water regulation zone as the adjusted input parameters converged on new static values early in the season.

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