Abstract

Within-plant spatial heterogeneity in the production of and demand for assimilates may have major implications for the formation of fruits. Spatial heterogeneity is related to organ age, but also to position on the plant. This study quantifies the variation in local carbohydrate availability for the phytomers in the same cohort using a cotton growth model that captures carbohydrate production in phytomers and carbohydrate movement between phytomers. Based on field observations, we developed a functional-structural plant model of cotton that simulates production and storage of carbohydrates in individual phytomers and transport of surplus to other phytomers. Simulated total leaf area, total above-ground dry mass, dry mass distribution along the stem, and dry mass allocation fractions to each organ at the plant level were compared with field observations for plants grown at different densities. The distribution of local carbohydrate availability throughout the plant was characterized and a sensitivity analysis was conducted regarding the value of the carbohydrate transport coefficient. The model reproduced cotton leaf expansion and dry mass allocation across plant densities adequately. Individual leaf area was underestimated at very high plant densities. Best correspondence with measured plant traits was obtained for a value of the transport coefficient of 0.1 d-1. The simulated translocation of carbohydrates agreed well with results from C-labelling studies. Moreover, simulation results revealed the heterogeneous pattern of local carbohydrate availability over the plant as an emergent model property. This modelling study shows how heterogeneity in local carbohydrate production within the plant structure in combination with limitations in transport result in heterogeneous satisfaction of demand over the plant. This model provides a tool to explore phenomena in cotton that are thought to be determined by local carbohydrate availability, such as branching pattern and fruit abortion in relation to climate and crop management.

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