Emergence Pattern of Argemone mexicana, Brassica tournefortii, and Rapistrum rugosum in Eastern Australia

Abstract A study assessed the potential for using cumulative growing degree days (CGDD) to predict the weed emergence periodicity of three weed species:Argemone mexicana,Brassica tournefortii, andRapistrum rugosum. Weed emergence was monitored regularly by placing 200 fresh seeds of each weed species on the soil surface. Weed emergence data was fit using a three-parameter sigmoidal Gompertz model. The CGDD required for 50% emergence ofA. mexicanaranged from 3380 to 5302, depending upon the seasonal variation in temperature and rainfall. The majority of emergence appeared from March to June. The seeds ofA. mexicanaexhibited dormancy, as the majority of seeds germinated in the second season. The CGDD required for 50% emergence ofB. tournefortiiranged from 824 to 2311, depending upon the seasonal variation in temperature and intensity of rainfall. Most cohorts ofB. tournefortiiappeared in the first season from February to June, indicating little dormancy in seeds. The CGDD required for 50% emergence ofR. rugosumranged from 2242 to 2699, depending upon weather parameters (temperature and rainfall). The main cohorts ofR. rugosumappeared from February to June, and 60% of seeds germinated in the first season, while 40% germinated in the second season, indicating dormancy in seeds. The coefficients of determination for the model verification on the emergence pattern of three weeds were > 85%, suggesting that CGDD are good predictors for the emergence of these weeds. These results suggest that forecasting the emergence of three weed species on the basis of CGDD and rainfall patterns will help growers to make better weed management decisions.