Dormancy, a critical trait for weed success in crop production systems
Agricultural practices exert selective forces on weed populations. As these practices change over time, weed adaptive traits also evolve, allowing weeds to persist in the new environment. However, only weeds having individuals showing the trait with adaptive significance will be able to cope with th...
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Veröffentlicht in: | Pest management science 2020-04, Vol.76 (4), p.1189-1194 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Agricultural practices exert selective forces on weed populations. As these practices change over time, weed adaptive traits also evolve, allowing weeds to persist in the new environment. However, only weeds having individuals showing the trait with adaptive significance will be able to cope with these changes, thus allowing a sub‐population to be selected for persistence. In addition, changes in agricultural practices can select new weed species showing functional traits with characteristics adaptive to the modified system. Seed dormancy has long been recognized as a trait with enormous adaptive value to adjust weed biology to cropping systems. In this paper, we illustrate with examples of success and failure, the value of seed dormancy as a functional trait to cope with long‐term changes in crop production systems. We show that successful outcomes are mostly related to the existence of sufficient variability for the functioning of physiological mechanisms that control dormancy characteristics as influenced by the agricultural environment. Presented examples illustrate how knowledge about the relationship that exists between agricultural practices and their selective pressure on seed dormancy can be instrumental in predicting changes in weed biotype dormancy characteristics or foreseeing the appearance of new weed species in future agricultural scenarios. © 2019 Society of Chemical Industry
We illustrate how knowledge about agricultural practices' selective pressure on seed dormancy strategies can be instrumental in predicting changes in weed species in forthcoming agricultural scenarios. |
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ISSN: | 1526-498X 1526-4998 |
DOI: | 10.1002/ps.5707 |