Literature DB >> 21649661

Modelling the size and composition of fruit, grain and seed by process-based simulation models.

Pierre Martre1,2, Nadia Bertin3, Christophe Salon4,5, Michel Génard3.   

Abstract

Understanding what determines the size and composition of fruit, grain and seed in response to the environment and genotype is challenging, as these traits result from several linked processes controlled at different levels of organization, from the subcellular to the crop level, with subtle interactions occurring at or between the levels of organization. Process-based simulation models (PBSMs) implement algorithms to simulate metabolic and biophysical aspects of cell, tissue and organ behaviour. In this review, fruit, grain and seed PBSMs describing the main phases of growth, development and storage metabolism are discussed. From this concurrent work, it is possible to identify generic storage organ processes which can be modelled similarly for fruit, grain and seed. Spatial heterogeneity at the tissue and whole-plant level is found to be a key consideration in modelling the effects of the environment and genotype on fruit, grain and seed end-use value. In the future, PBSMs may well become the main link between studies at the molecular and whole-plant levels. To bridge this phenotype-to-genotype gap, future models need to remain plastic without becoming overparameterized.
© 2011 INRA. New Phytologist © 2011 New Phytologist Trust.

Mesh:

Year:  2011        PMID: 21649661     DOI: 10.1111/j.1469-8137.2011.03747.x

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.151


  10 in total

1.  Simulation of carbon allocation and organ growth variability in apple tree by connecting architectural and source-sink models.

Authors:  Benoît Pallas; David Da Silva; Pierre Valsesia; Weiwei Yang; Olivier Guillaume; Pierre-Eric Lauri; Gilles Vercambre; Michel Génard; Evelyne Costes
Journal:  Ann Bot       Date:  2016-06-08       Impact factor: 4.357

Review 2.  Putting primary metabolism into perspective to obtain better fruits.

Authors:  Bertrand Beauvoit; Isma Belouah; Nadia Bertin; Coffi Belmys Cakpo; Sophie Colombié; Zhanwu Dai; Hélène Gautier; Michel Génard; Annick Moing; Léa Roch; Gilles Vercambre; Yves Gibon
Journal:  Ann Bot       Date:  2018-06-28       Impact factor: 4.357

3.  A Process-Based Model of TCA Cycle Functioning to Analyze Citrate Accumulation in Pre- and Post-Harvest Fruits.

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4.  Kinetic Modeling of Sunflower Grain Filling and Fatty Acid Biosynthesis.

Authors:  Ignacio Durruty; Luis A N Aguirrezábal; María M Echarte
Journal:  Front Plant Sci       Date:  2016-05-06       Impact factor: 5.753

5.  Integrating Physiology and Architecture in Models of Fruit Expansion.

Authors:  Mikolaj Cieslak; Ibrahim Cheddadi; Frédéric Boudon; Valentina Baldazzi; Michel Génard; Christophe Godin; Nadia Bertin
Journal:  Front Plant Sci       Date:  2016-11-21       Impact factor: 5.753

6.  Modeling Allometric Relationships in Leaves of Young Rapeseed (Brassica napus L.) Grown at Different Temperature Treatments.

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Journal:  Front Plant Sci       Date:  2017-03-21       Impact factor: 5.753

7.  Incorporating genome-wide association into eco-physiological simulation to identify markers for improving rice yields.

Authors:  Niteen N Kadam; S V Krishna Jagadish; Paul C Struik; C Gerard van der Linden; Xinyou Yin
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8.  Carbon supply and water status regulate fatty acid and triacylglycerol biosynthesis at transcriptional level in the olive mesocarp.

Authors:  Adrián Perez-Arcoiza; M Luisa Hernández; M Dolores Sicardo; Virginia Hernandez-Santana; Antonio Diaz-Espejo; José M Martinez-Rivas
Journal:  Plant Cell Environ       Date:  2022-05-25       Impact factor: 7.947

9.  Disentangling the Effects of Water Stress on Carbon Acquisition, Vegetative Growth, and Fruit Quality of Peach Trees by Means of the QualiTree Model.

Authors:  Mitra Rahmati; José M Mirás-Avalos; Pierre Valsesia; Françoise Lescourret; Michel Génard; Gholam H Davarynejad; Mohammad Bannayan; Majid Azizi; Gilles Vercambre
Journal:  Front Plant Sci       Date:  2018-01-24       Impact factor: 5.753

10.  Model-based QTL detection is sensitive to slight modifications in model formulation.

Authors:  Caterina Barrasso; Mohamed-Mahmoud Memah; Michel Génard; Bénédicte Quilot-Turion
Journal:  PLoS One       Date:  2019-10-03       Impact factor: 3.240

  10 in total

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