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Modelling Weed Seedbank Dormancy and Germination

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Decision Support Systems for Weed Management

Abstract

Weeds are usually more vulnerable to control practices at the seedling stage or at early stages of their growth. Therefore, developing models to predict the timing and extent of weed emergence is useful to assist farmers and agronomist to time pre- and post-emergence control practices to increase their efficacy. However, many important weeds forming persistence seedbanks in agricultural fields present dormancy. In those species, the number of established seedlings is strongly related to the dormancy level of the seedbank, and the timing of seedling emergence depends on the seasonal variation in seedbank dormancy level. Therefore, if we pretend to predict timing and extent of seedling emergence, we should include the regulation of the seedbank dormancy level in our predictive models. In this chapter, we present a conceptual framework to understand how dormancy and germination of weed seedbanks are regulated by the environment. This framework is based on the distinction between those factors that regulate seasonal changes in the seedbank dormancy level (i.e. temperature in interaction with seed moisture content) and those factors that terminate dormancy (i.e. light and alternating temperatures). Changes in the seedbank dormancy level are related to changes in the range of environmental conditions permissive for seed germination, as, for example, the thermal range permissive for germination which is defined by the lower and the higher limit temperatures. Seeds germinate when environmental conditions are within the permissive range, for example, seeds begging to accumulate thermal time towards germination once soil temperature overlaps the permissive thermal range. We present examples of how these concepts can be used to establish functional relationships between dormancy and germination regulating factors (i.e. temperature) and changes in seedbank population dormancy level and germination dynamics in order to develop mechanistic models to predict the timing and extent of weed seedling emergence in the field.

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Authors and Affiliations

  1. Facultad de Agronomía, Cátedra de Cerealicultura, IFEVA (UBA/CONICET), Buenos Aires, Argentina

    Diego Batlla

  2. Facultad de Agronomía, Cátedra de Cultivos Industriales, IFEVA (UBA/CONICET), Buenos Aires, Argentina

    Cristian Malavert, Rocío Belén Fernández Farnocchia & Roberto Benech-Arnold

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  1. Diego Batlla
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  2. Cristian Malavert
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  3. Rocío Belén Fernández Farnocchia
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  4. Roberto Benech-Arnold
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Correspondence to Diego Batlla .

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Editors and Affiliations

  1. Departamento de Agronomía, Universidad Nacional del Sur - CERZOS/CONICET, Bahía Blanca, Buenos Aires, Argentina

    Guillermo R. Chantre

  2. Department of Crop Protection, Institute for Sustainable Agriculture, Córdoba, Córdoba, Spain

    José L. González-Andújar

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Batlla, D., Malavert, C., Farnocchia, R.B.F., Benech-Arnold, R. (2020). Modelling Weed Seedbank Dormancy and Germination. In: Chantre, G., González-Andújar, J. (eds) Decision Support Systems for Weed Management. Springer, Cham. https://doi.org/10.1007/978-3-030-44402-0_4

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