Water limitation affects weed competitive ability for light. A demonstration using a model‐based approach combined with an automated watering platform - Archive ouverte HAL Access content directly
Journal Articles Weed Research Year : 2022

Water limitation affects weed competitive ability for light. A demonstration using a model‐based approach combined with an automated watering platform

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Delphine Moreau
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Marion Prudent
Nathalie Colbach

Abstract

Climate change is driving the need to investigate responses to water limitation of morphological traits involved in competition for light, the main resource for which crops and weeds compete in conventional temperature and tropical cropping systems, to better understand field crop-weed dynamics. Our objective was to develop an innovative approach to quantify weed species responses to water limitation, using three species. This approach combined (1) key morphological traits involved in competition for light (taken from a mechanistic crop-weed model) as criteria to analyse responses to water limitation and (2) a pot/greenhouse platform allowing automated precision-watering and daily quantification of soil water availability in each pot. For all species and growth stages, increased plant height per unit of aboveground biomass and production of smaller/thicker leaves were the most noteable responses. Plants with a strong increase in plant height per unit of aboveground biomass in response to water limitation maintained high levels of specific leaf area, even at low soil water availability. Increases in biomass allocation to roots (vs. aboveground parts) and leaves (vs. stems and reproductive organs) were also observed, but not for all species and growth stages. Overall, these effects of water limitation on morphological traits indicate strong interactions between competition for light and water.
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Dates and versions

hal-03910768 , version 1 (22-12-2022)

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Delphine Moreau, Hugues Busset, Annick Matejicek, Marion Prudent, Nathalie Colbach. Water limitation affects weed competitive ability for light. A demonstration using a model‐based approach combined with an automated watering platform. Weed Research, 2022, 62 (6), pp.381-392. ⟨10.1111/wre.12554⟩. ⟨hal-03910768⟩
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