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Correlation between dynamic tomato fruit-set and source-sink ratio: a common relationship for different plant densities and seasons?
- Kang, MengZhen, Yang, LiLi, Zhang, BaoGui, de Reffye, Philippe
- Annals of botany 2011 v.107 no.5 pp. 805-815
- autumn, biomass production, buds, crop models, crop production, fruit set, fruits, greenhouses, inflorescences, internodes, petioles, plant density, plant organs, prediction, probability, spring, tomatoes, vegetative growth
- BACKGROUND AND AIMS: It is widely accepted that fruit-set in plants is related to source-sink ratio. Despite its critical importance to yield, prediction of fruit-set remains an ongoing problem in crop models. Functional-structural plant models are potentially able to simulate organ-level plasticity of plants. To predict fruit-set, the quantitative link between source-sink ratio and fruit-set probability is analysed here via a functional-structural plant model, GreenLab. METHODS: Two experiments, each with four plant densities, were carried out in a solar greenhouse during two growth seasons (started in spring and autumn). Dynamic fruit-set probability was estimated by frequent observation on inflorescences. Source and sink parameter values were obtained by fitting GreenLab outputs for the biomass of plant parts (lamina, petiole, internode, fruit), at both organ and plant level, to corresponding destructive measurements at six dates from real plants. The dynamic source-sink ratio was calculated as the ratio between biomass production and plant demand (sum of all organ sink strength) per growth cycle, both being outputs of the model. KEY RESULTS AND CONCLUSIONS: Most sink parameters were stable over multiple planting densities and seasons. From planting, source-sink ratio increased in the vegetative stage and reached a peak after fruit-set commenced, followed by a decrease of leaf appearance rate. Fruit-set probability was correlated with the source-sink ratio after the appearance of flower buds. The relationship between fruit-set probability and the most correlated source-sink ratio could be quantified by a single regression line for both experiments. The current work paves the way to predicting dynamic fruit-set using a functional structure model.