Analysis and evaluation of a dynamic model for greenhouse lettuce growth

Abstract

Aim of study: We analyzed and evaluated a nonlinear dynamic crop growth model called NICOLET B3, which can predict the dry and fresh matter content of lettuce in greenhouses. Area of study: Calibration was performed using experimental data obtained from the literature. The experiment was carried out in Saltillo, Mexico, and in a greenhouse in Beijing, China. Material and methods: We identified and discussed the feasibility of the studied model with multi-dimensional evaluation criteria. Meanwhile, a sensitivity analysis of input variables was conducted. After that, the least square identification method was used to calibrate the most sensitive parameter values to improve the robustness of the model. Main results: Results demonstrate that: i) the NICOLET B3 model is able to predict the fresh and dry matter production of lettuce with satisfactory accuracy verified (R2 = 0.9939 for fresh matter and R2 = 0.9858 for dry matter); ii) temperature has the most obvious impact on the model performance, compared with photosynthetically active radiation and CO2 concentration; iii) the model could perform well with only two inputs. Research highlights: Simulation results of evaluated NICOLET B3 model have a perfect goodness-of-fit. A method of calibrating parameters of the model and sensitivity analysis of three input variables of the model can facilitate its application.