Application of signal analysis and nonlinear system identification methods to modelling dry matter production in winter wheat

摘要: Abstract A procedure is outlined for the use of stochastic signal analysis and nonlinear system identification methods to model dry matter production in winter wheat crops. In this model, intercepted radiation treated as input crop weight output. Intercepted depends on incident solar leaf area per unit ground (LAI). It shown that observed temporal patterns LAI can be represented by empirical orthogonal functions derived from their respective auto-covariance functions. Standard procedures then used identify linear quadratic kernels linking