Transactions of the Asae最新文献

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.

Growing plants in an enclosed controlled environment is crucial in developing bioregenerative life-support systems (BLSS) for space applications. The major challenge currently facing a BLSS is the extensive use of highly energy-intensive electric light sources, which leads to substantial energy wastes through heat dissipations by these lamps. An alternative lighting strategy is the use of a solar irradiance collection, transmission, and distribution system (SICTDS). Two types of fiber optic-based SICTDS, a Fresnel-lens Himawari and a parabolic-mirror optical waveguide (OW) lighting system, were evaluated. The overall efficiency for the OW SICTDS of 40.5% exceeded by 75% that for the Himawari of 23.2%. The spectral distributions of the light delivered by the Himawari and the OW SICTDS were almost identical and had practically no difference from that of terrestrial solar radiation. The ratios of photosynthetically active radiation (PAR) to total emitted radiation (k) of 0.39 +/- 0.02 for the Himawari and 0.41 +/- 0.04 for the OW SICTDS were statistically indistinguishable, were not significantly different from that of 0.042 +/- 0.01 for terrestrial solar radiation, and were comparable to that of 0.35 for a high-pressure sodium (HPS) lamp. The coefficients of variation (CV) of 0.34 and 0.39 for PPF distributions, both at 50 mm X 50 mm square grid arrays, corresponding to the Himawari and the OW SICTDS, respectively, were comparable with each other but were both significantly greater than the CV of 0.08 corresponding to the HPS lamp. The average fresh weight or dry weight of lettuce grown in the solar chamber with either the Himawari or the OW SICTDS showed no statistical difference from the average fresh weight or dry weight of lettuce grown in the reference chamber with the HPS lamp. The results of this study suggest that an SICTDS could help reduce the electric power demand in a BLSS.

A methodology was established for early, non-contact, and quantitative detection of plant water stress with machine vision extracted plant features. Top-projected canopy area (TPCA) of the plants was extracted from plant images using image-processing techniques. Water stress induced plant movement was decoupled from plant diurnal movement and plant growth using coefficient of relative variation of TPCA (CRV[TPCA)] and was found to be an effective marker for water stress detection. Threshold value of CRV(TPCA) as an indicator of water stress was determined by a parametric approach. The effectiveness of the sensing technique was evaluated against the timing of stress detection by an operator. Results of this study suggested that plant water stress detection using projected canopy area based features of the plants was feasible.

A decision model is presented that compares lighting systems for a plant growth scenario and chooses the most appropriate system from a given set of possible choices. The model utilizes a Multiple Attribute Utility Theory approach, and incorporates expert input and performance simulations to calculate a utility value for each lighting system being considered. The system with the highest utility is deemed the most appropriate system. The model was applied to a greenhouse scenario, and analyses were conducted to test the model's output for validity. Parameter variation indicates that the model performed as expected. Analysis of model output indicates that differences in utility among the candidate lighting systems were sufficiently large to give confidence that the model's order of selection was valid.