A. H. Gómez, Y. He, and A. G. Pereira, Non-destructive measurement of acidity, soluble solids and firmness of Satsuma mandarin using Vis/NIR-spectroscopy techniques, Journal of Food Engineering, vol.77, issue.2, pp.313-319, 2006.
DOI : 10.1016/j.jfoodeng.2005.06.036

S. Liu-yande, Z. Xudong, and . Hailiang, Nondestructive measurement of internal quality of Nanfeng mandarin fruit by charge coupled device near infrared spectroscopy, Agriculture, vol.71, pp.10-14, 2010.

F. Guoqiang, Z. Jianwen, and . Du-ran, Determination of soluble solids and firmness of apples by Vis/NIR transmittance, Journal of Food Engineering, vol.93, issue.4, pp.416-420, 2009.

E. Bertone, A. Venturello, and R. Leardi, Prediction of the optimum harvest time of ???Scarlet??? apples using DR-UV???Vis and NIR spectroscopy, Postharvest Biology and Technology, vol.69, pp.15-23, 2012.
DOI : 10.1016/j.postharvbio.2012.02.009

S. Tong, L. Hongjian, and X. Huirong, Effect of fruit moving speed on predicting soluble solids content of 'Cuiguan' pears (Pomaceae pyrifolia Nakai cv. Cuiguan) using PLS and LS-SVM regression, Postharvest Biology and Technology, issue.1, pp.51-86, 2009.

X. Huirong, Q. Bing, and S. Tong, Variable selection in visible and near-infrared spectra: Application to on-line determination of sugar content in pears, Journal of Food Engineering, vol.109, issue.1, pp.142-147, 2012.

V. A. Mcglone, C. J. Clark, and R. B. Jordan, Comparing density and VNIR methods for predicting quality parameters of yellow-fleshed kiwifruit (Actinidia chinensis), Postharvest Biology and Technology, vol.46, issue.1, pp.46-47, 2007.
DOI : 10.1016/j.postharvbio.2007.04.003

A. Moghimi, M. H. Aghkhani, and A. Sazgarnia, Vis/NIR spectroscopy and chemometrics for the prediction of soluble solids content and acidity (pH) of kiwifruit, Biosystems Engineering, vol.106, issue.3, pp.106-295, 2010.
DOI : 10.1016/j.biosystemseng.2010.04.002

K. Flores, M. T. Sanchez, and D. C. Perez-marin, Prediction of total soluble solid content in intact and cut melons and watermelons using near infrared spectroscopy, Journal of Near Infrared Spectroscopy, vol.16, issue.1, pp.16-91, 2008.
DOI : 10.1255/jnirs.771

T. Haiqing, W. Chunguang, and . Zhang-haijun, Measurement of soluble solids content in melon by transmittance spectroscopy, Sensor Letters, vol.2012, issue.1012, pp.570-573

Y. Yibin and L. Yande, Nondestructive measurement of internal quality in pear using genetic algorithms and FT-NIR spectroscopy, Journal of Food Engineering, vol.84, pp.206-213, 2008.

L. Fei and H. Yong, Application of successive projections algorithm for variable selection to determine organic acids of plum vinegar, pp.1430-1436, 2009.

N. Sorol, E. Arancibia, and S. A. Bortolato, Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice, Chemometrics and Intelligent Laboratory Systems, vol.102, issue.2, pp.100-109, 2010.
DOI : 10.1016/j.chemolab.2010.04.009

W. Di, C. Xiaojing, and Z. Xiangou, Uninformative variable elimination for improvement of successive projections algorithm on spectral multivariable selection with different calibration algorithms for the rapid and non-destructive determination of protein content in dried laver, Analytical Methods, vol.3, pp.1790-1796, 2011.

H. Lingxia, W. Di, and J. Hangfeng, Internal quality determination of fruit with bumpy surface using visible and near infrared spectroscopy and chemometrics: A case study with mulberry fruit, Biosystems Engineering, vol.109, pp.377-384, 2011.

S. Tong, X. Wenli, and L. Jinlong, Determination of Soluble Solids Content in Navel Oranges by Vis/NIR Semi-transmission Spectra Combined with CARS Method, Spectroscopy and Spectral Analysis, issue.12, pp.32-3229, 2012.

C. Bin, M. Xianglong, and W. Hao, Application of successive projections algorithm in optimising near infrared spectroscopic calibration model, Journal of Instrumental Analysis, vol.26, issue.1, pp.66-69, 2007.

Z. Xiaobo, Z. Jiewen, and H. Xingyi, Use of FT-NIR spectrometry in noninvasive measurements of soluble solid contents (SSC) of " Fuji " apple based on different PLS models, pp.43-51, 2007.

M. Arakawa, Y. Yamashita, and K. Funatsu, Genetic algorithm-based wavelength selection method for spectral calibration, Journal of Chemometrics, vol.40, issue.3, pp.10-19, 2011.
DOI : 10.1002/cem.1339

V. Centner, D. L. Massart, and O. E. Denoord, Elimination of Uninformative Variables for Multivariate Calibration, Analytical Chemistry, vol.68, issue.21, pp.68-3851, 1996.
DOI : 10.1021/ac960321m

R. Leardi, Application of genetic algorithm-PLS for feature selection in spectral data sets, Journal of Chemometrics, vol.40, issue.5-6, pp.643-655, 2000.
DOI : 10.1002/1099-128X(200009/12)14:5/6<643::AID-CEM621>3.0.CO;2-E

R. Leardi and A. L. Gonzalez, Genetic algorithms applied to feature selection in PLS regression: how and when to use them, Chemometrics and Intelligent Laboratory Systems, vol.41, issue.2, pp.195-207, 1998.
DOI : 10.1016/S0169-7439(98)00051-3

M. C. Araújo, T. C. Saldanha, and R. K. Galvã-o, The successive projections algorithm for variable selection in spectroscopic multicomponent analysis, Chemometrics and Intelligent Laboratory Systems, vol.57, issue.2, pp.57-65, 2001.
DOI : 10.1016/S0169-7439(01)00119-8

R. K. Galvã-o, M. C. Araújo, and W. D. Fragoso, A variable elimination method to improve the parsimony of MLR models using the successive projections algorithm, Chemometrics and Intelligent Laboratory Systems, vol.92, issue.1, pp.92-83, 2008.
DOI : 10.1016/j.chemolab.2007.12.004

L. Hongdong, L. Yizeng, and X. Qingsong, Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration, Analytica Chimica Acta, vol.648, issue.1, pp.77-84, 2009.

B. Shao-yongni, H. Yidan, and . Yong, Visible/near-infrared spectra for linear and nonlinear calibrations: a case to predict soluble solids contents and pH value in peach, Bioprocess Technology, issue.48, pp.1376-1383, 2011.

P. C. Williams and D. C. Sobering, Comparison of commercial near infrared transmittance and reflectance instruments for analysis of whole grains and seeds, Journal of Near Infrared Spectroscopy, vol.1, issue.1, pp.25-32, 1993.
DOI : 10.1255/jnirs.3