Gene A Giacomelli

Abstract:

Greenhouse crop production systems have been established throughout the world, including arid and semi-arid regions, to fulfill a market demand of locally grown produce consistently through the year. In these particular regions while they have the advantage of sunshine year-round, production during the summer is a challenge due to elevated air temperatures. Fog systems have proven to be a good economical alternative for evaporative cooling while potentially providing a more uniform environment when compared to fan and pad systems. High-pressure fogging systems equipped with variable frequency drives can be operated at different pressures to meet the varying cooling demands during the day. This feature adds the flexibility of varying the fog flow rate by operating at lower pressures or by changing the number of working fog lines accordingly to the cooling demands. These systems may offer the potential advantage of energy and water saving by operating at a low frequency while providing the proper amount of fog accordingly to the cooling loads. A variable pressure fogging systems operating in the range of 4.8 to 10.3 MPa (700 to 1500 psi) was recently installed in a greenhouse at the University of Arizona Controlled Environment Agriculture Center (UA-CEAC) for the purpose of developing advanced control strategies for optimum greenhouse environments. This study experimentally evaluated the dynamics of air and canopy temperatures, crop evapotranspiration rates, and climate uniformity in the greenhouses working under various fogging system operational pressures and greenhouse side/roof vent opening configurations.

Abstract:

Controlled environment, greenhouse cultivation of Sweet Charlie strawberries is technically an effective method to target niche winter markets. Supplemental lighting can help to accelerate fruit maturation, and to encourage a greater number of smaller fruit earlier in the season. Unless yield per plant can be drastically increased, achieving an economically viable system will require a planting density approaching 30 plants m^-2.

Abstract:

Balancing plant growth between vegetative and reproductive status is crucial for producing high quality greenhouse tomatoes while maintaining high productivity. The ability to change plant growth characteristics often associated with vegetative or reproductive growth status was demonstrated. Two greenhouse canopy environments were selected for inducing reproductive growth [high vapor pressure deficit (VPD) (2 kPa) and 27°C / 18°C day-night air temperature], and vegetative growth [low VPD (0.8 kPa) and 24°C / 22°C day-night air temperature]. Plant responses from the treatment environments were contrasted with those from a standard commercial greenhouse environment (24°C / 19°C). All environmental treatments were associated with two electrical conductivities (EC) of the nutrient solution: 2.5 dS m-1 (EC 2.5) and 8 dS m-1 (EC 8). Plants were grown under one of two treatment environmental conditions, until significant differences in plant growth characteristics were observed. Out of the five plant growth characteristics monitored, stem diameters were the most responsive to canopy environment and EC treatments. The major factor in changing plant growth responses was EC, for the range of VPD and day-night air temperature differences achieved in the present study, while canopy environment affected the magnitude of the change. Mean stem diameters (SD) were significantly higher under EC 2.5, than for plants growing under EC 8. IN5 cm and SD 15 cm are the plant growth responses most affected by EC treatments and canopy environment. Single leaf gas exchange measurements had significantly reduced transpiration rate at EC 8 under all canopy environments, while net photosynthetic rate was not affected. This suggests that decreased plant growth responses observed under high salinity treatments resulted from reduced water and nutrient uptake due to suppressed transpiration rate.

Abstract:

Despite the technological advances implemented in greenhouse crop production, greenhouse operation relies on human expertise to decide on the optimum values of each environmental control parameter. Most importantly, the selected values are determined by human observation of the crop responses. Greenhouse tomatoes often show a pattern of cycling between reproductive and vegetative growth modes. The growth mode is a practical visual characterization of the source-sink relationships of the plants resulting from the greenhouse environment (aerial and root zone). Experienced reenhouse tomato growers assess the growth mode based on morphological observations, including quantitative (length, diameter, elongation rates) and qualitative (shape and color) features of the plant head, stems, flowers, trusses, and leaves. Data from greenhouse environments and crop records from an experimental production in Tucson, Arizona, and from a large-scale commercial operation in Marfa, Texas, were used for modeling the growth mode of tomato plants with fuzzy logic. Data from the commercial operation were used to model weekly fluctuations of harvest rate, fruit size, and fruit developing time with dynamic neural networks (NN). The NN models accurately predicted weekly and seasonal fluctuations of the fruit-related parameters, having coefficients of determination(R ²) of 0.92, 0.76, and 0.88, respectively, for harvest rate, fruit fresh weight, and fruit developing time, when compared with a dataset used for independent validation. The fuzzy modeling of growth mode allowed discrimination of the reproductive and balanced growth modes in the experimental system, and modeling of the seasonal growth mode variation in the commercial application. Both modeling results might be applicable to commercial operations for making decisions on greenhouse climate control and overall crop management practices. Copyright © 2009 American Society of Agricultural and Biological Engineers ISSN 2151-0032.

Abstract:

SUBSTOR, a process-oriented crop growth and development field model included with DSSAT software, was modified for controlled environment hydroponic production of white potato (cv. Norland) under elevated carbon dioxide concentration. Modifications were primarily based on growth and phenological data obtained via in-house experiments in ebb and flood equipped growth chambers at Rutgers University. Results from published literature were also used for additional modification where appropriate. The adaptations made to SUBSTOR included adjustment of input files for hydroponic cultural conditions, calibration of genetic coefficients, parameter tuning such as for radiation use efficiency, and source code changes. The latter included accounting for the absorption of light reflected from the surface below the canopy, an increased senescence rate, adding a carbon (mass) balance to the model, and a modified response of crop growth rate to CO2 concentration. Modified-SUBSTOR predictions were then compared with data from in-house experiments and Kennedy Space Center's Biomass Production Chamber.