P. Martre, N. Bertin, C. Salon, and . Gé, Modelling the size and composition of fruit, grain and seed by process-based simulation models, New phytol, vol.191, p.21649661, 2011.

K. J. Boote, M. J. Kropff, and P. S. Bindraban, Physiology and modelling of traits in crop plants: implications for genetic improvement, Agric Syst, vol.70, pp.395-420, 2001.

F. Tardieu, Virtual plants: modelling as a tool for the genomics of tolerance to water deficit. Trend plant sci, vol.8, pp.9-14, 2003.

X. Yin, S. Chasalow, C. J. Dourleijn, P. Stam, and M. J. Kropff, Coupling estimated effects of QTLs for physiological traits to a crop growth model: predicting yield variation among recombinant inbred lines in barley, Heredity, vol.85, pp.539-549, 2000.

N. Bertin, P. Martre, M. Génard, B. Quilot, and C. Salon, Under what circumstances can process-based simulation models link genotype to phenotype for complex traits? case-study of fruit and grain quality traits, J Exp Bot, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01189446

X. Yin, M. J. Kropff, and P. Stam, The role of ecophysiological models in QTL analysis: The example of specific leaf area in barley, Heredity, 1999.

X. Yin, P. Stam, M. J. Kropff, and A. Schapendonk, Crop modeling, QTL mapping, and their complementary role in plant breeding, Agron J, vol.95, pp.90-98, 2003.

D. Constantinescu, M. M. Memmah, G. Vercambre, M. Génard, V. Baldazzi et al., Model-Assisted Estimation of the Genetic Variability in Physiological Parameters Related to Tomato Fruit Growth under Contrasted Water Conditions. Front Plant Sci, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01475599

X. Yin, P. C. Struik, J. Gu, and H. Wang, Modelling QTL-Trait-Crop Relationships: Past Experiences and Future Prospects, Crop Systems Biology, pp.193-213, 2016.

K. Wei, J. Wang, M. Sang, S. Zhang, H. Zhou et al., An ecophysiologically based mapping model identifies a major pleiotropic QTL for leaf growth trajectories of Phaseolus vulgaris, Plant Journal, 2018.

R. Wu and M. Lin, Opinion: Functional mapping-How to map and study the genetic architecture of dynamic complex traits, Nature Reviews Genetics, 2006.

Y. Li and R. Wu, Functional mapping of growth and development, Biological Reviews, 2010.

Q. Li, Z. Huang, M. Xu, C. Wang, J. Gai et al., Functional mapping of genotype environment interactions for soybean growth by a semiparametric approach, Plant Methods, 2010.

Z. Huang, C. Tong, W. Bo, X. Pang, Z. Wang et al., An allometric model for mapping seed development in plants, Briefings in Bioinformatics, 2014.

W. Hou, H. Li, B. Zhang, M. Huang, and R. Wu, A non linear mixed-effect mixture model for functional mapping of dynamic traits, Heredity, 2008.

M. Chang-xing, G. Casella, and R. Wu, Functional mapping of quantitative trait loci underlying the character process: A theoretical framework, Genetics, vol.161, issue.4, pp.1751-1762, 2002.

J. Xing, J. Li, R. Yang, X. Zhou, and S. Xu, Bayesian B-spline mapping for dynamic quantitative traits, Genetics Research, 2012.

W. Wu, Y. Zhou, W. Li, D. Mao, and Q. Chen, Mapping of quantitative trait loci based on growth models. Theoretical and Applied Genetics, 2002.

B. Quilot-turion, O. Sidi, M. Kadrani, A. Hilgert, N. Gé-nard et al., Optimization of genetic parameters of the 'Virtual Fruit' model to design peach ideotypes for sustainable production systems, European Journal of Agronomy, vol.42, pp.34-48, 2012.

B. K. Podisi, S. A. Knott, D. W. Burt, and P. M. Hocking, Comparative analysis of quantitative trait loci for body weight, growth rate and growth curve parameters from 3 to 72 weeks of age in female chickens of a broiler-layer cross, BMC Genetics, 2013.

M. Ashyraliyev, Y. Fomekong-nanfack, J. A. Kaandorp, and J. G. Blom, Systems biology: parameter estimation for biochemical models, FEBS J, 2009.

I. C. Chou and E. O. Voit, Recent developments in parameter estimation and structure identification of biochemical and genomic systems, Math Biosci, vol.219, pp.57-83, 2009.

P. Li and Q. D. Vu, Identification of parameter correlations for parameter estimation in dynamic biological models, analysis in Prunus: a breeding perspective and beyond, vol.7, pp.1-18, 2013.

M. Cirilli, D. Bassi, and A. Ciacciulli, Sugars in peach fruit: a breeding perspective, Horticulture Research, vol.3, 2016.

J. Ioannidis, T. A. Trikalinos, and E. E. Ntzani, Contopoulos-Ioannidis DG. Genetic associations in large versus small studies: an empirical assessment, Lancet, vol.361, issue.03, pp.12516-12516, 2003.

Y. Jian-bing, J. -. Hua, T. , Y. , M. Xi-qing et al., Improving QTL Mapping Resolution Based on Genotypic Samplying-a Case using a RIL Population. Acta Genetica Sinica, vol.33, pp.617-624, 2006.

M. Wang and S. Xu, Statistical power in genome-wide association studies and quantitative trait locus mapping, Heredity, p.30858595, 2019.

S. Chen, J. Montgomery, and A. Bolufé-rö-hler, Measuring the curse of dimensionality and its effects on particle swarm optimization and differential evolution, Artif Intell, 2015.

Y. Mei, M. N. Omidvar, X. Li, and X. Yao, A Competitive Divide-and-Conquer Algorithm for Unconstrained Large-Scale Black-Box Optimization. ACM t math software, 2016.

S. Mahdavi, M. E. Shiri, and S. Rahnamayan, Metaheuristics in large-scale global continues optimization: A survey. Inform sciences, 2015.