Author(s): Cici SZ, Adkins S, Hanan J
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Abstract BACKGROUND AND AIMS: Improving the competitive ability of crops is a sustainable method of weed management. This paper shows how a virtual plant model of competition between chickpea (Cicer arietinum) and sowthistle (Sonchus oleraceus) can be used as a framework for discovering and/or developing more competitive chickpea cultivars. METHODS: The virtual plant models were developed using the L-systems formalism, parameterized according to measurements taken on plants at intervals during their development. A quasi-Monte Carlo light-environment model was used to model the effect of chickpea canopy on the development of sowthistle. The chickpea-light environment-sowthistle model (CLES model) captured the hypothesis that the architecture of chickpea plants modifies the light environment inside the canopy and determines sowthistle growth and development pattern. The resulting CLES model was parameterized for different chickpea cultivars (viz. 'Macarena', 'Bumper', 'Jimbour' and '99071-1001') to compare their competitive ability with sowthistle. To validate the CLES model, an experiment was conducted using the same four chickpea cultivars as different treatments with a sowthistle growing under their canopy. RESULTS AND CONCLUSIONS: The growth of sowthistle, both in silico and in glasshouse experiments, was reduced most by '99071-1001', a cultivar with a short phyllochron. The second rank of competitive ability belonged to 'Macarena' and 'Bumper', while 'Jimbour' was the least competitive cultivar. The architecture of virtual chickpea plants modified the light inside the canopy, which influenced the growth and development of the sowthistle plants in response to different cultivars. This is the first time that a virtual plant model of a crop-weed interaction has been developed. This virtual plant model can serve as a platform for a broad range of applications in the study of chickpea-weed interactions and their environment.
This article was published in Ann Bot
and referenced in Agrotechnology