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# Summary
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SUNFLO1 is a process-based model for the sunflower crop which
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was developped to simulate the grain yield and oil concentration as
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a function of time (t), environment (E) which includes soil, climate
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and management practice and genetic diversity (G) (Debaeke et al.,
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2010; Casadebaig et al., 2011; Lecoeur et al., 2011).
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This model is based on a conceptual framework initially pro-
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posed by Monteith (1977) and now shared by a large familly of
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crop models (Jones et al., 2016). In this framework, the daily crop
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dry biomass (DMt ) is calculated as a difference equation function
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of incident photosynthetically active radiation (PAR, $`MJ.m^{-2}`$),
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light interception efficiency (RIE) and radiation use efficiency
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(RUE, $`g.MJ^{-1}`$).
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```math
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DM_{t} = DM_{t-1} + PAR*RIE*RUE
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```
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The light interception efficiency is based on Beer-Lambert’s law3 as a function of leaf area index (LAI) and light
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extinction coefficient (k). The radiation use efficiency concept (Mon-
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teith, 1994) is used to represent photosynthesis at the crop scale.
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Broad scale processes of this framework, the dynamics of LAI =
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f (t, G, E), photosynthesis (RUE = f ( t, G, E) ) and biomass allocation
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to grains were split into finer processes (e.g leaf expansion and
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senescence, response functions to environmental stresses) to reveal
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genotypic specificity and to allow the emergence of genotype-by-
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environment interactions. Globally, the SUNFLO crop model has
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about 50 equations and 64 parameters (43 plant-related traits and 21
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environment-related).
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# References
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[1] Casadebaig, P.; Guilioni, L.; Lecoeur, J.; Christophe, A.; Champolivier, L. & Debaeke, P. (2011), 'SUNFLO, a model to simulate genotype-specific performance of the sunflower crop in contrasting environments', Agricultural and Forest Meteorology 151, 163-178.
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[2] Lecoeur, J.; Poiré-Lassus, R.; Christophe, A.; Pallas, B.; Casadebaig, P.; Debaeke, P.; Vear, F. & Guilioni, L. (2011), 'Quantifying physiological determinants of genetic variation for yield potential in sunflower. SUNFLO: a model-based analysis', Functional Plant Biology 38(3), 246--259. |
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