Biomedical subjects

J Cavazzoni

Publications and source records attributed to J Cavazzoni.

6 recordsLinked to original sources

PubMed2004

Using explanatory crop models to develop simple tools for Advanced Life Support system studies.

System-level analyses for Advanced Life Support require mathematical models for various processes, such as for biomass production and waste management, which would ideally be integrated into overall system models. Explanatory models (also referred to as mechanistic or process models) would provide the basis for a more robust system model, as these would be based on an understanding of specific processes. However, implementing such models at the system level may not always be practicable because of their complexity. For the area of biomass production, explanatory models were used to generate parameters and multivariable polynomial equations for basic models that are suitable for estimating the direction and magnitude of daily changes in canopy gas-exchange, harvest index, and production scheduling for both nominal and off-nominal growing conditions.

Algorithms↗

PubMed1999

Phasic temperature and photoperiod control for soybean using a modified CROPGRO model.

A modified CROPGRO model is applied to phasic temperature and photoperiod control in order to optimize soybean production for NASA's program in Advanced Life Support. Baseline model simulations were established using data from soybean temperature experiments conducted at elevated CO2 levels (1100 micromol mol-1) at Utah State University (USU). The model simulations show little advantage in using phasic temperature control alone to increase average seed yield rate over the USU experimental values. However, simulations that combine phasic control of temperature (two phases) and photoperiod (two phases) do indicate the potential to improve seed yield (in g m-2 day-1) by approximately 15% over those currently obtained experimentally at USU for soybean cultivar Hoyt. This temperature and photoperiod phasing is experimentally practical. The simulations suggest extending photoperiods over those typically used experimentally during later phases of the crop life cycle, which would lengthen grain fill duration and thereby increase mass per seed. The model simulations indicate that the timing, and duration of extended photoperiods would be very important due to possible reductions in seed number m-2. Besides affecting seed yield directly, the model simulations suggest that such reductions may also cause feedback inhibition of photosynthesis due to low seed sink strength at elevated CO2 levels.

Biomass↗

PubMed1999

Coupling machine vision and crop models for closed-loop plant production in advanced life support systems.

We present a conceptual framework for coupling nondestructive sensing to crop models for closed-loop plant production for NASA's program in advanced life support. Coupling is achieved by comparing nondestructive observations 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. We illustrate this concept using canopy height and machine vision measured top projected canopy area (TPCA), and the CROPGRO crop growth model. Model simulations of soybean TPCA and canopy height were evaluated against data for hydroponic soybean grown under two separate light/dark cycle temperature regimes (23/19 degrees C and 26/22 degrees C). Our results suggest that TPCA and canopy height are potentially useful variables for closed-loop plant production in controlled environments during the first few weeks of growth, before canopy closure.

Biomass↗

PubMed1997

A modified CROPGRO model for simulating soybean growth in controlled environments.

The CROPGRO crop growth model is adapted in order to analyze experimental data from a soybean (cv. Hoyt) experiment conducted at elevated CO2 levels (1200 micromol mol-1) at Kennedy Space Center, FL. The following adaptations to original CROPGRO produced model agreement with gas-exchange data: the input of square-wave temperature and photosynthetically active radiation (PAR) profiles; the input of the appropriate hydroponic substrate PAR albedo; modified biomass partitioning and developmental parameters; an increased leaf area expansion rate through the fifth vegetative node; a decreased specific leaf area after the fifth vegetative node; and an increased incident diffuse PAR fraction over typical field values. The model demonstrated here suggests that with continued development, modified CROPGRO will be a useful tool in the analysis and eventual optimization of legume production in bioregenerative life support systems.

Biomass↗

PubMed1996

Assessing long-term impacts of increased crop productivity on atmospheric CO2.

A full assessment of the impacts of land clearance and crop production on atmospheric CO2 requires a systems approach. By considering long-term soil carbon changes and fossil fuel energy inputs, we show that increased crop productivity will alleviate CO2 release to the atmosphere primarily by preventing additional land cultivation. Each hectare of cropland undergoing a simulated threefold crop productivity increase here prevents a net release on the order of 150-200 Mg C to the atmosphere over 100 years by avoiding additional land cultivation which would otherwise be required. This effective carbon sink would slowly diminish with time due to fossil fuel energy input requirements. However, future self-containment of the energy needs of high-yield crop production may displace on the order of 1.0 Pg C per year of fossil fuel carbon, in addition to the carbon sink attributable to avoided land cultivation. By avoiding land cultivation, high yield crop systems also preserve natural ecosystems.

Agriculture↗

PubMedDate not supplied

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.

Biomass↗