Development and Validation of a Predictive Model for Seedling Emergence of Volunteer Canola (Brassica napus) Under Semi-Arid Climate
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Abstract
Volunteer canola (Brassica napus L.) can damage the production of subsequent canola crops and other crops. Timely and more accurate control could be developed if there is a better understanding of its temporal emergence patterns. The objectives of this study were to develop and validate a predictive model of emergence for B. napus under semi-arid conditions based on thermal time (TT). Experiments were conducted during 3 years to obtain cumulative seedling emergence data and used to develop and validate the model. A Weibull function was fitted to cumulative seedling emergence and TT. The model closely fitted the observed emergence patterns, accounting for 99% of the variation observed. According to this model, seedling emergence of B. napus started at 56.1 TT and increased to 50 and 95% of maximum seedling emergence at 86.3 and 105.4 TT, respectively. Validation was performed with the Weibull model and two logistics models (taken from the literature) developed under different climate conditions. The validation indicated that the Weibull model performed better than the logistic models. The Weibull model proposed is robust enough and could be useful as a predictive tool for effective control of B. napus under semi-arid climate.
Keywords
Weibull model Logistic model Base temperature Soil depth Thermal time Degree days Weed emergenceNotes
Acknowledgements
JLG-A was partially supported by FEDER (European Regional Development Fund) and the Spanish Ministry of Economy and Competitiveness Grant (AGL2015-64130-R).
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