Gene A Giacomelli

Abstract:

Passive ventilation in greenhouse production systems is predominant worldwide, limiting its usability and profitability to specific regions or for short production cycles. Evaporative fogging systems have increasingly been implemented in Arid and Semi-Arid regions to extend the production cycle during the warmest season, and also to achieve near-optimum environments for year-round production. However, appropriate control strategies for evaporative fogging systems are still lacking or limited despite its reported benefits in terms of environmental uniformity and potential savings in water and energy usage, when compared to fan and pad systems. The present research proposes a neural network predictive control approach for optimizing water and energy usage in a naturally ventilated and fog cooled greenhouse while providing a near-optimum and uniform environment for plant growth. As a first step the dynamic behavior of the greenhouse environment, defined by air temperature and relative humidity, was characterized by means of system identification using a recurrent dynamic network (NARMX). The multi-step ahead prediction capability of NARMX allows for the optimization of the control actions (vent configuration and fogging rate) for its implementation in the NN predictive control scheme. Greenhouse environmental data from a set of experiments consisting of several vent configurations (0/50, 0/100, 50/50, 50/100 and 100/100, percent opening of the side/roof vents) and three fogging rates (17.5, 22.3 and 27.0 g m^-2 min^-1) during several days throughout the year were used in the system identification process. The resulting NN model accurately predicted the dynamic behavior of the greenhouse environment, having coefficients of determination (R²) of 0.99 for each parameter (air temperature and relative humidity). These NN model will be incorporated into the NN predictive control scheme and its feasibility is in a naturally ventilated greenhouse equipped with a variable-rate fogging system is discussed, while achieving a greenhouse environment within defined permissible ranges of air temperature and relative humidity.

Abstract:

The Microgravity Pocket (MGP) was designed for continuous production of root crops in microgravity within a controlled environment. The MGP is intended to provide NASA with a "Salad Machine" to grow carrot and radish for consumption by astronauts. Attributes of the pocket system, include light weight; ease of planting, monitoring, and harvesting; no free water; and low energy requirements. The MGP system uses porous sheets of plastic to wick water to the plant roots, which are enclosed within a watertight pouch. An experiment was conducted growing carrot and radish root crops in a horizontal orientation adjacent to a water-cooled high-pressure sodium lamp. The hydrophilic property of the porous sheet provided nutrient solution to the root zone of the plants, but the small size of the pores prevented root growth into the sheet. The MGP was successful in growing both carrot and radish to harvestable size.

Abstract:

Water availability is a common concern in semi-arid regions, such as Southern Arizona, USA, where more greenhouses are operating due to high solar radiation. Hydroponic greenhouse crop production greatly reduces irrigation water use; however, there is currently no information demonstrating water use of an evaporative cooling system. This project investigated water use by a pad and fan (P&F) cooling system under semi-arid climate conditions. Data were collected for two physically identical, side-by-side, double-layer polyethylene film-covered arched-roof greenhouses (28 m x 9.8 m x 6.3 m) during summer conditions (38.5°C, 15% RH, 845 W m^-2). One greenhouse had mature tomato plants (2.3 plants m^-2) and the other had no plants. Water use was primarily affected by air exchange rate. The average water use by the P&F system was 0.145, 0.182, 0.265, 0.325, and 0.387 g m^-2 s ^-1 for greenhouse air exchange rates of 0.017, 0.037, 0.051, 0.067, and 0.079 m³ m^-2 s^-1, respectively. In the empty greenhouse, the lowest ventilation rate produced the highest average greenhouse air temperature (Tin=33.8°C) and lowest RH (40%). Tin and RH were nearly equal for the three highest air exchange rates. In the greenhouse with plants, the lowest ventilation rate produced the highest Tin (31.1°C) but also the highest RH (69.4%). In general, RH decreased with increasing air exchange rate and the minimum Tin of 27.6°C (RH: 52%) was achieved at the middle air exchange rate (0.051 m³ m^-2 s^-1). It is believed that the lower cooling efficiency of the P&F system at higher ventilation rates caused a reduction in cooling. However, the lower ventilation rates limited air exchange and effectively reduced cooling. If a higher pad cooling efficiency could be maintained at high ventilation rates, a cooler air temperature and higher relative humidity may be achieved, though water use would increase. Finally, when the air exchange rate was controlled to maintain the GH at 24°C/18°C during day and night, water use by the P&F cooling system (14.8 L m^-2 day^-1) was greater than the tomato irrigation system (8.9 L m^-2 day^-1) assuming 100% drainage recovery, which is typical for many high-technology greenhouse facilities.

Abstract:

The porous tube is a nutrient delivery system that was developed to grow plants in microgravity. Most of the research studies with the porous tubes have been completed with lettuce, radish, wheat and sweet potato. The NJ-NSCORT at Rutgers University has focused on root crops and fruiting plants which can be grown on the porous tube. Carrots were grown to maturity on the porous tube with support methods tested to increase yields. Strawberry plants and fruit were also grown on the porous tube from the successful establishment of transplanted runners, but with marginally successful seed germination.

Abstract:

A procedure for studying the profitability of greenhouse potted plant production systems subject to resource constraints was developed. The constrained condition and resources were the crop production schedule, greenhouse space, labor, and budget. A database containing the information for determining the required resources and operating costs for growing various crops was established. The database also provides the estimated revenue from sales of the crops, on a per pot basis. An algorithm was developed to determine first the feasibility of a given production plan and then determine the quantities of crops to be grown in order to yield an optimum profit. The result of this algorithm may serve to optimize allocation of resources for year-round production. The algorithm along with the crop database was incorporated into a user-friendly micro-computer program.