Biosystems Engineering (2006) 95 (3), 323–337 doi:10.1016/j.biosystemseng.2006.07.006 IT—Information Technology and the Human Interface Evaluation of the Nicolet Model for Simulation of Short-term Hydroponic Lettuce Growth and Nitrate Uptake Jennifer Mathieu 1 ; Raphael Linker 2 ; Lanfang Levine 3 ; Louis Albright 4 ; A.J. Both 5 ; Roger Spanswick 4 ; Raymond Wheeler 6 ; Eileen Wheeler 7 ; David deVilliers 4 ; Robert Langhans 8 1 The MITRE Corporation, Bedford, MA 01730, USA; e-mail of corresponding author: jmatheu@mitre.org 2 Civil and Environmental Engineering, Technion, Haifa 32000, Israel 3 Dynamac Corporation, Space Life Sciences Laboratory, Kennedy Space Center, FL 32899, USA 4 Biological and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA 5 Bioresource Engineering, Rutgers University, New Brunswick, NJ 08901, USA 6 NASA, Space Life Sciences Laboratory, Kennedy Space Center, FL 32899, USA 7 Agricultural and Biological Engineering, Pennsylvania State University, University Park, PA 16802, USA 8 Horticulture, Cornell University, Ithaca, NY 14853, USA (Received 22 August 2005; accepted in revised form 18 July 2006; published online 25 September 2006) Accurate simulation models for short-term (hours) changes in hydroponic crop growth and nitrate uptake are needed for rapid fault detection in hydroponic systems. Comparison between model-predicted and measured values for crop growth and nitrate uptake is proposed as the basis for such a fault detection system. To this end, the Nitrate Control in Lettuce (NiCoLet) model was used to evaluate both short- and long- term changes in growth and nitrate accumulation. Three replicated experiments were conducted with lettuce (Lactuca sativa L. cv. Flandria), including: (1) plants subjected to either low or high nitrate concentration treatments for model calibration; (2) collection of growth data every 2 days for model validation; and (3) frequent (every 4 mol m 2 of accumulated light) collection of growth and shoot nitrate concentration data to validate short-term predictions. After a minor modification (maximum nitrogen uptake rate restricted) and calibration, the NiCoLet model accurately simulated lettuce crop growth and nitrate uptake on a long-term basis and provided evidence of short-term behaviour, including statistically significant predictions of diurnal patterns. This is a first step in realising fault detection systems based on mechanistic simulation models. r 2006 IAgrE. All rights reserved Published by Elsevier Ltd 1. Introduction Using crops to recycle carbon dioxide and generate oxygen is a promising strategy for maintaining sustain- able regenerative life support systems in closed habitats for space exploration (Wheeler et al., 2001). This study was designed to address fault or problem detection in hydroponic crop production systems, which is one of the main bio-regenerative system components being con- sidered by the National Aeronautics and Space Admin- istration (NASA). A fast and reliable fault detection system is necessary to warn the crew before there is irreversible crop damage in the hydroponic production system, as well as its possible effects on the entire life support system. Comparison between model-predicted and measured values for crop growth and nitrate uptake is proposed as the basis for such a fault detection system. Frequent (e.g. 1–2 days) plant harvests meet the NASA objective of producing salad-type crops for supplementing the crew’s diet in a space station or long duration mission, as well as providing plant fresh mass growth data for model comparison. Although plant tissue nitrate concentration data is needed to calibrate the model, once calibrated, measurement of nitrate uptake from solution using, for example, nitrate electrodes could be implemented for real-time fault detection. Alternatively, addition of individual nutrients is possible using measurements of electrical conductiv- ity, pH, nutrient ratios, and the quality of the source water (Savvas, 2002). Short-term (hours), accurate ARTICLE IN PRESS 1537-5110/$32.00 323 r 2006 IAgrE. All rights reserved Published by Elsevier Ltd