Development of a Thermal-Time-Based Emergence Model for Echinochloa crus-galli

Climate change-driven increases in temperature and changes in precipitation regimes are altering the timing and patterns of weed emergence in agricultural systems. Consequently, accurately predicting weed emergence and selecting the best timing for control are becoming more crucial over time. Weeds such as Echinochloa crus-galli (barnyardgrass) are particularly problematic due to their widespread adaptability and competition across varying cultivation environments, making an accurate prediction of the timing of emergence crucial for management. The objective of this study was to characterize the emergence pattern of E. crus-galli under diverse environmental conditions and to develop and evaluate a Gompertz-based thermal-time model for predicting seedling emergence. Increased temperatures enhanced emergence rates and speeds in both growth chamber and greenhouse conditions. The effective accumulated temperature required for 50% emergence was relatively consistent (54–69 °C·d). Furthermore, high emergence percentages were maintained at soil moisture levels of 80% or greater. Across years, emergence responses differed substantially under field conditions. Independent validation using a field dataset collected in 2026 demonstrated that the model developed from the 2025 dataset successfully reproduced observed emergence patterns under field conditions (RMSE = 2.7%p, MAE = 2.3%p). Regional emergence analyses suggested a tendency toward earlier emergence under recent temperature conditions, particularly in warmer regions, although these predictions were based on only two years of field observations. Overall, the present study provides a preliminary evaluation of the applicability of a thermal-time-based approach for describing E. crus-galli emergence under Korean environmental conditions. Additional validation across multiple locations and growing seasons would further strengthen the general applicability of the model.