A parsimonious, multiple-regression model of wheat yield response to environment

A database of nearly 2000 yield observations from winter wheat crops grown in UK trials between 1976 and 1993 was used to develop a new model of effec ts of weather on wheat yield. The intention was to build a model which was parsimonious (i.e., has the minimum number of parameters and maximum predic tive power), but in which every parameter reflected a known climate effect on the UK crop-environment system to allow mechanistic interpretation. To t his end, the model divided the effects of weather into phases which were pr edicted by a phenology model. A maximum set of possible weather effects in different phenological phases on yield was defined from prior knowledge. Tw o-thirds of the database was used to select which effects were necessary to include in the model and to estimate parameter values. The final model was tested against the independent data in the remaining third of the data set (246 aggregated yield observations) and showed predictive power (r=0.41), which was improved when comparing against mean annual yields (r=0.77). The final model allowed the relative importance of the 17 explanatory variables , and the weather effects they represent (defined before fitting), to be as sessed. The most important weather effects were found to be: ( 1) negative effects of rainfall on agronomy before and during anthesis, during grain-fi lling and in the spring (2) winter frost damage (3) a positive effect of th e temperature-driven duration of grain-filling and (4) a positive effect of radiation around anthesis, probably due to increased photosynthesis. The m odel developed here cannot be applied outside the UK, but the same approach could be employed for applications elsewhere, using appropriate yield, wea ther and management data. (C) 2000 Elsevier Science B.V. All rights reserve d.