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Growing wheat in Biosphere 2 under elevated CO2: Observations and modeling

pmid: 11542248
Spring wheat (Triticum aestivum L., cv. Yecora Rojo) was grown in the intensive agricultural biome (IAB) of Biosphere 2 during the l995-l996 winter/spring season. Environmental conditions were characterized by a day/night temperature regime of 27/17 degrees C, relative humidity (RH) levels around 45%, mean atmospheric CO2 concentration of 450 ppmv, and natural light conditions with mean intensities about half of outside levels. Weekly samples of above-ground plant matter were collected throughout the growing season and phenological events recorded. A computer model, CERES-Wheat, previously tested under both field and controlled conditions, was used to simulate the observed crop growth and to help in data analysis. We found that CERES-Wheat simulated the data collected at Biosphere 2 to within 10% of observed, thus suggesting that wheat growth inside the IAB was comparable to that documented in other environments. The model predicts phenological stages and final dry matter (DM) production within l0% of the observed data. Measured DM production rates, normalized for light absorbed by the crop. suggested photosynthetic efficiencies intermediate between those observed under optimal field conditions and those recorded in NASA-Controlled Ecological Life-Support Systems (CELSS). We suggest that such a difference can be explained primarily in terms of low light levels inside the IAB, with additional effects due to elevated CO2 concentrations and diffuse light fractions.
- University of Chicago United States
- Oracle (United States) United States
- Harvard University United States
- Colorado State University United States
- Goddard Institute for Space Studies United States
Light, Temperature, Agriculture, Carbon Dioxide, Environment, Controlled, Models, Biological, Predictive Value of Tests, Computer Simulation, Biomass, Ecological Systems, Closed, Life Support Systems, Triticum
Light, Temperature, Agriculture, Carbon Dioxide, Environment, Controlled, Models, Biological, Predictive Value of Tests, Computer Simulation, Biomass, Ecological Systems, Closed, Life Support Systems, Triticum
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