ahmad zare; maede malekpoor; maryam arabizadeh
Abstract
Regression models are a tool to quantify the weeds seed germination in response to temperature. In order to determinate the cardinal temperature of four weeds Brassicaceae family (Eruca sativa, Hirschfeldia incana, Sinapis arvensis, and Erysimum repandum), four separate experiments have been conducted ...
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Regression models are a tool to quantify the weeds seed germination in response to temperature. In order to determinate the cardinal temperature of four weeds Brassicaceae family (Eruca sativa, Hirschfeldia incana, Sinapis arvensis, and Erysimum repandum), four separate experiments have been conducted at nine temperatures (5, 10, 15, 20, 25, 30, 35, 40, and 45°C) as factorial, based on a complete randomized design (CRD) with three replications in Agricultural Science and Natural Resources University of Khuzestan during 2019. The First factor includes four weeds, and the second factor, weeds’ response to temperature. These have been different at 40°C only. H. incana displays some germination (38%), whereas the germination of other weeds has been completely inhibited. Based on the used models, the best models to determine cardinal temperature for E. sativa has been Beta, five parameter; for E. repandum, Beta, four parameter; and for S. arvensis, and H. incana, Dent-like model. The optimum temperature for germination of E. sativa and E. repandum are predicted to be 19.43 and 16.01 °C (Beta four and five parameter models), respectively. Moreover, the lower and upper optimum temperatures for germination of H. incana and Sinapis arvensis have been achieved at 27.22, 29.26, 23.23, and 27.86 °C, respectively (at Dent-like model). The maximum emergence of Eruca sativa, Hirschfeldia incana, and Sinapis arvensis is expected in November and from December to February for Erysimum repandum. Modeling germination in response to temperature can be considered in weed management, especially when determining the control time of weeds.