M. Bagge and T. Lubberstedt, Functional markers in wheat: technical and economic aspects, Molecular Breeding, vol.47, issue.3, pp.319-328, 2008.
DOI : 10.1139/g05-040

J. Zhu, Y. Zhou, Y. Liu, Z. Wang, Z. Tang et al., Fine mapping of a major QTL controlling panicle number in rice, Molecular Breeding, vol.48, issue.2, pp.171-180, 2011.
DOI : 10.1111/j.1365-313X.2006.02916.x

Y. Xing and Q. Zhang, Genetic and Molecular Bases of Rice Yield, Annual Review of Plant Biology, vol.61, issue.1, pp.1-11, 2010.
DOI : 10.1146/annurev-arplant-042809-112209

T. Tanabata, T. Shibaya, . K. Hori, K. Ebana, and M. Yano, SmartGrain: High-Throughput Phenotyping Software for Measuring Seed Shape through Image Analysis, PLANT PHYSIOLOGY, vol.160, issue.4, pp.1871-1880, 2012.
DOI : 10.1104/pp.112.205120
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3510117

H. Liu, H. Zhang, G. Wang, and Z. Shen, Identification of Rice Varieties with High Tolerance or Sensitive to Copper, Journal of Plant Nutrition, vol.311, pp.121-136, 2007.

F. Liu, B. Yusuf, and J. Zhong, Variety Identification of Rice Vinegars using visible and near infrared spectroscopy and multivariate calibrations, International Journal of Food Properties, vol.146, pp.1264-1276, 2011.
DOI : 10.1080/10942911003647508

Q. Zhang, Strategies for developing Green Super Rice, Proceedings of the National Academy of Sciences, vol.101, issue.27, pp.16402-16409, 2007.
DOI : 10.1073/pnas.0403720101
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2034246

N. Attaviroj, S. Kasemsumran, and A. Noomhorm, Rapid Variety Identification of Pure Rough Rice by Fourier-Transform Near-Infrared Spectroscopy, Cereal Chemistry Journal, vol.88, issue.5, pp.490-496, 2011.
DOI : 10.1094/CCHEM-03-11-0025

C. Huang, Rice panicle length measuring system based on dual-camera imaging, Computers and Electronics in Agriculture, vol.98, pp.158-165, 2013.
DOI : 10.1016/j.compag.2013.08.006

L. Duan, A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice, Plant Methods, vol.7, issue.1, p.44, 2011.
DOI : 10.1126/science.325_380

H. Feng, A hyperspectral imaging system for an accurate prediction of the above-ground biomass of individual rice plants, Review of Scientific Instruments, vol.14, issue.9, p.95107, 2013.
DOI : 10.1063/1.3531980

. L. Duan, Fast discrimination and counting of filled/unfilled rice spikelets based on bi-modal imaging, Computers and Electronics in Agriculture, vol.75, issue.1, pp.196-203, 2011.
DOI : 10.1016/j.compag.2010.11.004

W. Yang, X. Xu, L. Duan, Q. Luo, S. Chen et al., High-throughput measurement of rice tillers using a conveyor equipped with x-ray computed tomography, Review of Scientific Instruments, vol.11, issue.2, pp.25102-25103, 2011.
DOI : 10.1126/science.325_380

V. Vapnik, An overview of statistical learning theory, IEEE Transactions on Neural Networks, vol.10, issue.5, pp.988-999
DOI : 10.1109/72.788640

M. Kumar and M. Gopal, Reduced one-against-all method for multiclass SVM classification, Exp. Syst. Appl, vol.38, pp.14238-14248, 2011.

C. Hsu, C. Chang, L. , and C. , A Practical Guide to Support Vector Classification, 2003.