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Population-based threshold models describe weed germination and emergence patterns across varying temperature, moisture and oxygen conditions

机译:基于阈值模型描述杂草发芽和跨不同的模式出现温度、湿度和氧气条件

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摘要

Opportunities for diversifying the management of weedy populations may be enhanced through accurate predictions of seedling emergence, because the timing and success of control measures often hinges on the timing of weed emergence. We used population-based threshold models to establish the temperature, moisture and oxygen conditions for optimum germination of herbicide-resistant and -susceptible Echinochloa phyllopogon, a weed of temperate paddy rice, and applied them to predict emergence from field soil. We combined hydrothermal time for germination, accounting for within-population variation in base water potentials (Ψ_b), with thermal time for early seedling growth to predict the quantity and proportional size of the emergence flushes that constitute final recruitment. Emergence in field soils was reduced by moisture stress and flooding, especially for the resistant population. In all populations, germination rates increased between 9·5 and 31 °C, Ψ_b was <-1·0 MPa, and there was no sensitivity to oxygen supply. Synthesis and applications. Population-based threshold models produced physiologically meaningful germination parameters, which are useful in defining the environmental constraints to germination, and predicting Echinochloa phyllopogon germination and emergence in field soils. By exploring the effects of temperature, water stress and flooding on germination and emergence, we predict irrigation regimes for optimising recruitment and the timing of weed control. Population-based threshold models produced physiologically meaningful germination parameters, which are useful in defining the environmental constraints to germination, and predicting Echinochloa phyllopogon germination and emergence in field soils. By exploring the effects of temperature, water stress and flooding on germination and emergence, we predict irrigation regimes for optimising recruitment and the timing of weed control.
机译:多元化管理的机会杂草丛生的人群可能会增强准确的预测的出苗率,因为时间和成功控制措施往往取决于杂草的时机出现。模型建立温度、水分和为最佳萌发氧条件抗杂草和易感Echinochloaphyllopogon、温带水稻的杂草他们适用于预测脱离现场土壤。发芽,占群体内基础水潜力的变化(Ψ_b)热时间早期幼苗生长预测的数量和比例的大小将构成最终出现招聘。通过水分压力和洪水,尤其是对耐药的人口。萌发率增加9·5 - 31所示°C,Ψ_b < 1·0 MPa,并没有灵敏度的氧气供应。应用程序。生理上产生有意义的发芽在定义参数,这是有用的环境约束发芽,预测Echinochloa phyllopogon发芽并在现场土壤出现。温度的影响、水压力和洪水在萌发和出现,我们预测为优化招聘和灌溉制度除草的时机。阈值模型产生生理上有意义的萌发参数,这是用于定义环境约束发芽,预测Echinochloaphyllopogon发芽,在现场出现的土壤。水压力和萌发和洪水出现,我们预测灌溉制度优化招聘和杂草的时机控制。

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