A New Approach for Timing Post-Emergence Weed Control Measures in Crops: The Use of the Differential Form of the Emergence Model

Models based on thermal or hydrothermal time are used to predict the seedling emergence pattern of weeds. These models rely on sigmoidal functions such as Gompertz, Weibull or logistic, in which daily soil temperature and moisture data are inputs and the percentage of total expected emergences is the output. The models give good predictions at local and regional scales but they lose accuracy when extrapolated to different geographic areas from where the equations were developed. They also must be validated prior to their release and have subjectivity of the date to start the accumulation of the degree-days. We propose the use of the differential form of the function rather than the integrated form. Under this approach, the starting date to accumulate degree-days is set to the week before the first weed emergence is recorded (if recorded on a weekly basis) and emergence predictions only rely on the current sigmoidal relationship between data recordings. When the weed emergence rate in the field decreases, the relationship between data recordings and time, measured either as thermal or hydrothermal degrees, starts to decrease. When the derivative of the emergence over time falls below a threshold that should be set up based on our knowledge of the economic threshold of the species, a post-emergence weed control measure should be carried out. Under this approach, weekly counts of weeds must be recorded until the derivative reaches the threshold. This approach has been checked on 39 data sets of different weeds in different crops and seasons by applying the differential form of the Gompertz function, obtaining a correlation of 0.99 between the predicted and the observed emergence. The methodology could be particularly useful when timing control measures in cropping areas with unknown or very little knowledge of the species and their emergence pattern.