ArticleJournal of experimental botany2011
Combining ecophysiological modelling and quantitative trait locus analysis to identify key elementary processes underlying tomato fruit sugar concentration.
Article in Journal of experimental botany, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 65 citations in OpenAlex.
- Nutritional Supply vs. Flavor Quality: Characterizing the Physicochemical Properties and Amino Acid Profiles of Tomatoes from Beijing and Shandong.Foods (Basel, Switzerland) · 2026Article
- Allele-based modeling to predict phenological stages of grapevine hybrids under future climatic conditions.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Model-assisted analysis for tuning anthocyanin composition in grape berries.Annals of botany · 2023Article
- Integration of Crop Growth Models and Genomic Prediction.Methods in molecular biology (Clifton, N.J.) · 2022Article
- The Associated With Carbon Conversion Rate and Source-Sink Enzyme Activity in Tomato Fruit Subjected to Water Stress and Potassium Application.Frontiers in plant science · 2021Article
- Molecular Tools for Adapting Viticulture to Climate Change.Frontiers in plant science · 2021Review
- Model-assisted comparison of sugar accumulation patterns in ten fleshy fruits highlights differences between herbaceous and woody species.Annals of botany · 2020Article
- Fruit water content as an indication of sugar metabolism improves simulation of carbohydrate accumulation in tomato fruit.Journal of experimental botany · 2020Article
- Heterologous expression of the apple hexose transporter MdHT2.2 altered sugar concentration with increasing cell wall invertase activity in tomato fruit.Plant biotechnology journal · 2020Article
- SUGAR Model-Assisted Analysis of Carbon Allocation and Transformation in Tomato Fruit Under Different Water Along With Potassium Conditions.Frontiers in plant science · 2020Article
- Combining Crop Growth Modeling With Trait-Assisted Prediction Improved the Prediction of Genotype by Environment Interactions.Frontiers in plant science · 2020Article
- Optimization of multi-environment trials for genomic selection based on crop models.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2017Article
- Inter-Species Comparative Analysis of Components of Soluble Sugar Concentration in Fleshy Fruits.Frontiers in plant science · 2016Article
- Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress.Annals of botany · 2014Article
- The Malus domestica sugar transporter gene family: identifications based on genome and expression profiling related to the accumulation of fruit sugars.Frontiers in plant science · 2014Article
- An update on source-to-sink carbon partitioning in tomato.Frontiers in plant science · 2014Review
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A mechanistic model predicting the accumulation of tomato fruit sugars was developed in order (i) to dissect the relative influence of three underlying processes: assimilate supply (S), metabolic transformation of sugars into other compounds (M), and dilution by water uptake (D); and (ii) to estimate the genetic variability of S, M, and D. The latter was estimated in a population of 20 introgression lines derived from the introgression of a wild tomato species (Solanum chmielewskii) into S. lycopersicum, grown under two contrasted fruit load conditions. Low load systematically decreased D in the whole population, while S and M were targets of genotype × fruit load interactions. The sugar concentration positively correlated to S and D when the variation was due to genetic introgressions, while it positively correlated to S and M when the variation was due to changes in fruit load. Co-localizations between quantitative trait loci (QTLs) for sugar concentration and QTLs for S, M, and D allowed hypotheses to be proposed on the processes putatively involved at the QTLs. Among the five QTLs for sugar concentration, four co-localized with QTLs for S, M, and D with similar allele effects. Moreover, the processes underlying QTLs for sugar accumulation changed according to the fruit load condition. Finally, for some genotypes, the processes underlying sugar concentration compensated in such a way that they did not modify the sugar concentration. By uncoupling genetic from physiological relationships between processes, these results provide new insights into further understanding of tomato fruit sugar accumulation.
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