6533b7d4fe1ef96bd1261b94

RESEARCH PRODUCT

Modélisation de la répartition des assimilats au sein du système racinaire chez le pois de printemps (Pisum sativum)

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leguminous plant, can fix atmospheric nitrogen through symbiosis with symbiotic bacteria of the genus Rhizobium. Yet the sensitivity of symbiotic N fixation to biotics and abiotics stresses leads to a significant yield and protein rate variability compared with cereals. A better understanding of C and N partitioning between roots and shoots according to the mode of N nutrition seems necessary to identify levers of yield stabilisation. In this context, the model PeaNod developed within INRA Dijon Ecophysiology team combines an architectural model of pea with an source-sink approach. The main objective of this work was to study the impact of competition between nodules and roots on roots architecture. The major hypotheses are : (1) competition between nodules and roots via rate of C satisfaction (2) nodules are initiated on apical meristems according to plant N status. To thid end, the model was simplified then parametrized according to several stages: (1) study of architectural distribution of root biomass (2) study of biomass repartition between roots and nodules (3) study of nodule initiation according to N status. Then, results of simulations were compared with experimental data obtained under greenhouse and in hydroponic conditions with pea genotype Baccara. Our results showed that formulated hypotheses allow to simulate biomass repartition between nodules and roots and in particular oscillations of laterals density and length along taproot. These phenomena had been observed but never compared to experimental data. These oscillations translate impact of carbon competition on speed growth modification of roots meristems and thus on elongation and initiation of new roots meristems. However, the model doesn’t allow us to simulate suitably kinetics of nodules initiation and thus their position on roots system. The model requires more adjustments of formalisms and parameters. Eventually, PeaNod model will allow us to test scenarios of nodulation by varying speed of nodules growth and fixation specific activity. It will be also interesting to confront the model with other sets data like hypernodulating mutants.