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Proceedings Paper

Coupling sensing to crop models for closed-loop plant production in advanced life support systems
Author(s): James Cavazzoni; Peter P. Ling
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Paper Abstract

We present a conceptual framework for coupling sensing to crop models for closed-loop analysis of plant production for NASA's program in advanced life support. Crop status may be monitored through non-destructive observations, while models may be independently applied to crop production planning and decision support. To achieve coupling, environmental variables and observations are linked to mode inputs and outputs, and monitoring results compared with model predictions of plant growth and development. The information thus provided may be useful in diagnosing problems with the plant growth system, or as a feedback to the model for evaluation of plant scheduling and potential yield. In this paper, we demonstrate this coupling using machine vision sensing of canopy height and top projected canopy area, and the CROPGRO crop growth model. Model simulations and scenarios are used for illustration. We also compare model predictions of the machine vision variables with data from soybean experiments conducted at New Jersey Agriculture Experiment Station Horticulture Greenhouse Facility, Rutgers University. Model simulations produce reasonable agreement with the available data, supporting our illustration.

Paper Details

Date Published: 14 January 1999
PDF: 12 pages
Proc. SPIE 3543, Precision Agriculture and Biological Quality, (14 January 1999); doi: 10.1117/12.336910
Show Author Affiliations
James Cavazzoni, Rutgers Univ. (United States)
Peter P. Ling, The Ohio State Univ. (United States)

Published in SPIE Proceedings Vol. 3543:
Precision Agriculture and Biological Quality
George E. Meyer; James A. DeShazer, Editor(s)

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