Published online by Cambridge University Press: 20 January 2017
Itchgrass is an aggressive weed species in tropical agroecosystems. Because of phytosanitary restrictions to exports, pineapple producers must use a zero tolerance level for this species. An understanding of itchgrass seedling emergence would help producers to better time POST control. The objective of the present study was to characterize itchgrass seedling emergence patterns and develop a predictive model. Multiple field experiments were conducted in four agricultural fields in Costa Rica between 2010 and 2011 for a total of 9 site-years. Itchgrass consistently showed a biphasic emergence pattern, with a first emergence phase that was faster and more consistent across site-years than the second one. Weibull + logistic models based on chronological time (R2adj = 0.92) and thermal time with Tbase = 20 C (R2adj = 0.92) provided the best fit for the combined emergence data for two experimental locations in 2010. Both models predicted itchgrass seedling emergence adequately for most site-years, but the thermal-time model was more accurate (R2adj = 0.64 to 0.86) than the chronological model (R2adj = 0.31 to 0.74), especially when temperatures were high. Both models showed high accuracy in the first emergence phase but tended to underestimate emergence rate during the second phase. The models predicted 50% emergence at 14 d or 80 growing degree days and the stabilization of the first emergence phase at approximately 25 d or 200 growing degree days. Thus, these models can be used to properly time itchgrass POST control. More research is needed to understand the regulatory mechanisms responsible for the variability of the second emergence phase.