Abstract:

With the development of digital agriculture, the visualization expression of plant growth process is very important. Quantifying the dynamic process of leaf color is the basic part of plant growth visualization. At present, the study on plant leaf color visualization at home and abroad is emphasized on reversing and rebuilding crop virtual growth with the figure identifying technique in computer, however, simulation model and visualization technique based on leaf color dynamic process have not been established successfully.
Modeling leaf color dynamics in rice is an important task for realizing virtual and digital plant growth. Based on time-course observations on leaf color changes at different leaf positions of stem and tillers under different nitrogen rates and water conditions with four rice cultivars, we developed a simulation model on leaf color dynamic changes in rice in relation to GDD. Leaf color changes in the model were described with SPAD in three phases. The first phase during leaf growth period was based on the exponential relationship of leaf color to cumulative GDD; the second phase during leaf function period was represented with a relative stable SPAD; the third phase during leaf senescence period was described in a quadratic equation between SPAD and GDD. In addition, the effects of nitrogen and water conditions on leaf color were quantified through the effectiveness values of leaf nitrogen concentration and water content in relation to SPAD. Then, the RGB values were further predicted from the changing SPAD. The model was validated with the independent field experiment data involving different rice cultivars and nitrogen rates. The average RMSEs between the simulated and observed SPAD dynamics at different leaf positions were 2.58, 3.69, and 3.82, respectively, for three leaf color phases on main stem, 4.65, 4.39, 3.51, and 4.25, respectively, for four individual tillers in rice, and 2.98, 3.25, respectively, for SPAD and R, G values.
The results indicate that the present model has a good performance in predicting leaf color changes at different leaf positions in rice under different growth conditions, and thus lays a foundation for further constructing digital and visual rice growth system.

Key words: Rice, Leaf color, dynamic Changes, Simulation model