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NASA scientists have previously researched biomass production units for the purpose of bioregenerative life support systems (BLSS). The University of Arizona, Controlled Environment Agriculture Center (UA-CEAC) in cooperation with Sadler Machine Company (SMC) designed, constructed and assisted real-time operations of the South Pole Food Growth Chamber (SPFGC). The SPFGC is a semi-automated, hydroponic, multiple salad crop production chamber located within the U.S. National Science Foundation New Amundsen-Scott South Pole Station. Fresh vegetables are grown for the Station crew during the annual eight-month period of isolation in one of the most extreme and remote environments on Earth. An empirical mathematical model was developed from data monitored onsite and remotely by Internet and telecommunications during the winter of 2006.

During the period July 2001 to March 2002, the performance of a water-jacketed high intensity discharge lamp of advanced design was evaluated within a lamp test stand at The University of Arizona (UA), Controlled Environment Agriculture Center (CEAC) in Tucson, Arizona. The lamps and test stand system were developed by Mr. Phil Sadler of Sadler Machine Company, Tempe, Arizona, and supported by a Space Act Agreement between NASA-Johnson Space Center (JSC) and UA. The purpose was for long term testing of the prototype lamp and demonstration of an improved procedure for use of water-jacketed lamps for plant production within the close confines of controlled environment facilities envisioned by NASA within Bioregenerative Life Support Systems. The lamp test stand consisted of six, 400 watt water-cooled, high pressure sodium HID lamps, mounted within a framework.

The primary objective of the investigation was to evaluate the effects of induced perturbations in air temperature on the development of the tomato plant, while correlating a plant feature for use with machine vision non-contact sensing technologies, and allow for eventual integration into a non-invasive plant-based environmental control system. Real-time information of plant growth responses to steady-state and changing air temperature regimes were measured (i.e. dry weight). There was a positive correlation of the profile machine vision images with dry weight. Therefore, machine vision could be used for plant developmental predictions and development of a control system for maintaining plant schedules.