Recent CO2 levels promote increased production of the toxin parthenin in an invasive Parthenium hysterophorus biotype.

Recent carbon dioxide (CO2) concentrations promoted higher parthenin concentrations in an invasive Parthenium hysterophorus biotype. Mean concentrations of parthenin, an allelopathic and defensive sesquiterpene lactone, were 49% higher at recent (~400 ppm) than at mid-twentieth-century (~300 ppm) CO2 concentrations, but did not vary in a non-invasive biotype, suggesting that recent increases in atmospheric CO2 may have already altered the chemistry of this destructive weed, potentially contributing to its invasive success.

Adaptation of SUBSTOR for controlled-environment potato production with elevated carbon dioxide.

The SUBSTOR crop growth model was adapted for controlled-environment hydroponic production of potato (Solanum tuberosum L. cv. Norland) under elevated atmospheric carbon dioxide concentration. Adaptations included adjustment of input files to account for cultural differences between the field and controlled environments, calibration of genetic coefficients, and adjustment of crop parameters including radiation use efficiency. Source code modifications were also performed to account for the absorption of light reflected from the surface below the crop canopy, an increased leaf senescence rate, a carbon (mass) balance to the model, and to modify the response of crop growth rate to elevated atmospheric carbon dioxide concentration. Adaptations were primarily based on growth and phenological data obtained from growth chamber experiments at Rutgers University (New Brunswick, N.J.) and from the modeling literature. Modified-SUBSTOR predictions were compared with data from Kennedy Space Center's Biomass Production Chamber for verification. Results show that, with further development, modified-SUBSTOR will be a useful tool for analysis and optimization of potato growth in controlled environments.

An optimal control strategy for crop growth in advanced life support systems.

A feedback control method for regulating crop growth in advanced life support systems is presented. Two models for crop growth are considered, one developed by the agricultural industry and used by the Ames Research Center, and a mechanistic model, termed the Energy Cascade model. Proportional and pointwise-optimal control laws are applied to both models using wheat as the crop and light intensity as the control input. The control is particularly sensitive to errors in measurement of crop dry mass. However, it is shown that the proposed approach is a potentially viable way of controlling crop growth as it compensates for model errors and problems associated with applying the desired control input due to environmental disturbances. Grant numbers: NGT5-50229.