پردیس کشاورزی و منابع طبیعی دانشگاه تهران علوم گیاهان زراعی ایران 2008-4811 48 ویژه نامه 2017 09 23 Prediction of emergence of Flixweed (Descurainia sophia) and Wild Oat (Avena fatua) using thermal time models in Winter Rapeseed (Brassica napus) Prediction of emergence of Flixweed (Descurainia sophia) and Wild Oat (Avena fatua) using thermal time models in Winter Rapeseed (Brassica napus) 55 65 63653 10.22059/ijfcs.2017.63653 FA Mohammad Ali Aboutalebian Assistant Professor, Department of Agronomy and Plant Breeding, Faculty of Agriculture, Bu Ali Sina University, Hamedan, Iran 0000-0001-5937-2501 Shahram Nazari Ph. D. Candidate, Department of Agronomy and Plant Breeding, Faculty of Agriculture, Bu Ali Sina University, Hamedan, Iran Farid Golzardi Assistant Professor, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran Journal Article 2016 04 06 A thermal time (TT) model was developed to simulate field emergence of two weed species (flixweed and wild oat) in winter rapeseed. Practical predictive weed emergence models can provide information about timing of weed emergence. Non-linear regression models are usually able to accurately predict field emergence under specific environmental conditions. In the present study, cumulative seedling emergence in response to TT was described by the Weibull, Logistic, Gompertz, Sigmoid and Chapman functions. Some criteria were used to describe the goodness of fit of the models. These criteria includ coefficient of determination (<em>r²_adj</em>), root mean square of error (<em>RMSE</em>) and Akaike index (<em>AIC</em>). In both species (<em>Descurainia sophia: RMSE= 3.65, r²_adj=0.97, AIC=88.87</em>; <em>Avena fatua: RMSE= 2.59, r²_adj=0.99, AIC=45.83</em>) the seedling emergence flushes were well described with the Weibull four-parameter function. To start emergence after sowing and to reach maximum emergence, lower TT requirements were observed in <em>A. fatua </em>than in <em>D. sophia.</em> Seedling emergence increased steadily and reached from 50% to 90% of total emergence at 315 and 543 TT, respectively for <em>D</em>. <em>sophia </em>and 70 and 286 TT, respectively for <em>A. fatua</em>. A thermal time (TT) model was developed to simulate field emergence of two weed species (flixweed and wild oat) in winter rapeseed. Practical predictive weed emergence models can provide information about timing of weed emergence. Non-linear regression models are usually able to accurately predict field emergence under specific environmental conditions. In the present study, cumulative seedling emergence in response to TT was described by the Weibull, Logistic, Gompertz, Sigmoid and Chapman functions. Some criteria were used to describe the goodness of fit of the models. These criteria includ coefficient of determination (<em>r²_adj</em>), root mean square of error (<em>RMSE</em>) and Akaike index (<em>AIC</em>). In both species (<em>Descurainia sophia: RMSE= 3.65, r²_adj=0.97, AIC=88.87</em>; <em>Avena fatua: RMSE= 2.59, r²_adj=0.99, AIC=45.83</em>) the seedling emergence flushes were well described with the Weibull four-parameter function. To start emergence after sowing and to reach maximum emergence, lower TT requirements were observed in <em>A. fatua </em>than in <em>D. sophia.</em> Seedling emergence increased steadily and reached from 50% to 90% of total emergence at 315 and 543 TT, respectively for <em>D</em>. <em>sophia </em>and 70 and 286 TT, respectively for <em>A. fatua</em>. https://ijfcs.ut.ac.ir/article_63653_a931d0be744fa4ca3eefd32116301534.pdf