Gene A Giacomelli

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.

Abstract:

The foundation of all plant production systems is the effective, efficient and dependable means of nutrient delivery to the plant. The nutrient delivery system directly influences the physical components and the plant culture tasks of the plant management technique within the controlled environment agriculture system. The nutrient delivery system can be described in terms of its mechanism for water delivery to the plant. Examples of an aeroponic root growth system, and a traditional tomato production system, within the controlled environment facilities at the University of Arizona, Controlled Environment Agriculture Center are provided.

Abstract:

CEA (Controlled Environment Agriculture) is an advance technology for the production of biological materials, such as, food, flowers, and plant byproducts for commercial application. To establish successful operations, education, training, and experience for the system operators are required. In fact, assuming good system design, it is experience which may be the most important factor in the success of a CEA operation. Decision support from off-site consultants or other support groups can be beneficial to help the operation, but to provide an effective response, they require environmental information and plant status, as well as easy access to sufficient data about the current and recent history of operations of the mechanical systems and the biological components. Telepresence procedures, which can be defined as practices which provide a representative environment for humans who then control devices and hardware within distant, hostile, or unique environments, can improve remote decision support of CEA facilities. The CEAC (Controlled Environment Agriculture Center) at the University of Arizona in Tucson not only includes CEA classes for the on-campus education of undergraduate and graduate students, as well as postgraduate growers and industry professionals, but also technologies for telepresence activities. To leverage educational reach, to complement research goals, and to utilize collective expertise which is not always onsite or available, a number of non-traditional decision-support activities have been established. Telepresence practices can substantially sustain or improve distant production systems through environmental monitoring, controlling, decision-support of operations, crop diagnostics, system diagnostics, and distance education, by using web cameras, climate control computers, and email. These procedures provide the information that grower operators often omit or overlook, and provide experiences and information for improvements of distance-education and support practices. Furthermore, these practices have provided effective support despite the inter-personal challenges of remote operations where operator (on site) and advisors (located elsewhere in the world) may have never met, nor have previously developed a level of mutual confidence and trust.

Abstract:

An aeroponic system was developed for the production of root crops used in the herbal and phytopharmaceutical industries. The variability in the phytochemical quality of botanical products precludes the ability to administer uniform dosing in clinical studies. Aeroponic systems allow the producer to precisely control root zone nutrient and water regimes and environmental conditions, as well as have complete access to the roots throughout the life of the crop. This control promises a more uniform harvest. An A-frame aeroponic system was designed to maximize root yields and permit free access to the roots for monitoring. Burdock (Arctium lappa L.) plants were grown in aeroponics with controls grown in a greenhouse soilless potting mix for ten weeks in a research greenhouse in Tucson, Arizona. The plants were harvested and the dry weights of aerial parts and roots were determined, as well as the chloro-genic acid concentration in the dried roots. Chlorogenic acid is a caffeoylquinic acid derivative known to have antioxidant activity. The biomass yields of the aerial parts were significantly higher in the aeroponically grown plants compared to the controls. The root biomass yields showed no significant difference between treatments. The chlorogenic acid concentrations were also not significantly different, however the plant-to-plant variability was significantly lower in the aeroponically grown plants, suggesting the potential for more consistent phytochemical yields using this production technique.