Techniques for modeling phenological development of weed populations

Abstract

Research was conducted to formulate techniques for modeling phenological development of weed populations. Techniques which are currently used for modeling development rate of insect populations were reviewed and tested for use in plant development models. Seed germination data collected under constant temperature conditions were used to formulate a two-component seed germination model for each of 10 plant data sets. A nonlinear poikilotherm rate equation was used to describe germination rate as a function of temperature and a temperature-independent Weibull function was used to distribute germination times for the population. The two-component models provided accurate prediction of germination times for some data sets but unacceptable for others. Errors were generally attributable to small sample size and/or long sample intervals associated with the constant temperature data from which the models were formulated. Experiments were conducted to determine the effect of temperature, nitrogen availability, and water availability on Johnsongrass (Sorghum halepense (L.) Pers.) development rate. Johnsongrass development rate was most sensitive to temperature. Only extremes in water or nitrogen availability has a consistent and measurable effect on Johnsongrass development rate. A population-level, two-component, temperature-dependent model which predicts date of Johnsongrass flowering was formulated. The model was tested against three independent field data sets, and provided accurate prediction of flowering dates for each data set.