Literature DB >> 17283376

Towards a virtual fruit focusing on quality: modelling features and potential uses.

M Génard1, N Bertin, C Borel, P Bussières, H Gautier, R Habib, M Léchaudel, A Lecomte, F Lescourret, P Lobit, B Quilot.   

Abstract

The fruit is a hierarchically organized organ composed of cells from different tissues. Its quality, defined by traits such as fruit size and composition, is the result of a complex chain of biological processes. These processes involve exchanges (transpiration, respiration, photosynthesis, phloem and xylem fluxes, and ethylene emission) between the fruit and its environment (atmosphere or plant), tissue differentiation, and cell functioning (division, endoreduplication, expansion, metabolic transformations, and vacuolar storage). In order to progress in our understanding of quality development, it is necessary to analyse the fruit as a system, in which processes interact. In this case, a process-based modelling approach is particularly powerful. Such a modelling approach is proposed to develop a future 'virtual fruit' model. The value of a virtual fruit for agronomists and geneticists is also discussed.

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Year:  2007        PMID: 17283376     DOI: 10.1093/jxb/erl287

Source DB:  PubMed          Journal:  J Exp Bot        ISSN: 0022-0957            Impact factor:   6.992


  13 in total

1.  Modelling fruit-temperature dynamics within apple tree crowns using virtual plants.

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Journal:  Ann Bot       Date:  2011-04-07       Impact factor: 4.357

2.  Variability of polyteny of giant chromosomes in Drosophila melanogaster salivary glands.

Authors:  Volodymyr Yu Strashnyuk; Lyubov A Shakina; Daria A Skorobagatko
Journal:  Genetica       Date:  2022-09-26       Impact factor: 1.633

3.  Changes in the distribution of cell wall polysaccharides in early fruit pericarp and ovule, from fruit set to early fruit development, in tomato (Solanum lycopersicum).

Authors:  Azusa Terao; Hiromi Hyodo; Shinobu Satoh; Hiroaki Iwai
Journal:  J Plant Res       Date:  2013-03-02       Impact factor: 2.629

4.  When parameters in dynamic models become phenotypes: a case study on flesh pigmentation in the chinook salmon (Oncorhynchus tshawytscha).

Authors:  Hannah Rajasingh; Arne B Gjuvsland; Dag Inge Våge; Stig W Omholt
Journal:  Genetics       Date:  2008-05-27       Impact factor: 4.562

5.  Model-assisted comparison of sugar accumulation patterns in ten fleshy fruits highlights differences between herbaceous and woody species.

Authors:  Coffi Belmys Cakpo; Gilles Vercambre; Valentina Baldazzi; Léa Roch; Zhanwu Dai; Pierre Valsesia; Mohamed-Mahmoud Memah; Sophie Colombié; Annick Moing; Yves Gibon; Michel Génard
Journal:  Ann Bot       Date:  2020-08-13       Impact factor: 4.357

6.  Understanding the effect of carbon status on stem diameter variations.

Authors:  Tom De Swaef; Steven M Driever; Lieven Van Meulebroek; Lynn Vanhaecke; Leo F M Marcelis; Kathy Steppe
Journal:  Ann Bot       Date:  2012-11-27       Impact factor: 4.357

7.  Meeting present and future challenges in sustainable horticulture using virtual plants.

Authors:  Gerhard Buck-Sorlin; Mickaël Delaire
Journal:  Front Plant Sci       Date:  2013-11-05       Impact factor: 5.753

8.  Inter-Species Comparative Analysis of Components of Soluble Sugar Concentration in Fleshy Fruits.

Authors:  Zhanwu Dai; Huan Wu; Valentina Baldazzi; Cornelis van Leeuwen; Nadia Bertin; Hélène Gautier; Benhong Wu; Eric Duchêne; Eric Gomès; Serge Delrot; Françoise Lescourret; Michel Génard
Journal:  Front Plant Sci       Date:  2016-05-19       Impact factor: 5.753

9.  Optimization of Allelic Combinations Controlling Parameters of a Peach Quality Model.

Authors:  Bénédicte Quilot-Turion; Michel Génard; Pierre Valsesia; Mohamed-Mahmoud Memmah
Journal:  Front Plant Sci       Date:  2016-12-20       Impact factor: 5.753

10.  Statistical mapping of maize bundle intensity at the stem scale using spatial normalisation of replicated images.

Authors:  David Legland; Marie-Françoise Devaux; Fabienne Guillon
Journal:  PLoS One       Date:  2014-03-12       Impact factor: 3.240

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