*2.4. Statistical Analysis*

All the quantitative comparations between the different soluble sugars of the examined apple flesh were subjected to Variance analysis, which were tested for *p* < 0.05 using the SPSS Statistics 20 package (IBM). The correlation between the contents of soluble sugars and soluble solids was investigated using the Pearson method of analysis with significant *p* < 0.05 in IBM SPSS 20. The partial least square regression (PLS) models of SSC, TSS and soluble sugars contents were built based on μ*<sup>a</sup>* and μ- *<sup>s</sup>* separately using MATLAB R2010b® in order to choose the most important soluble sugar parameter that determined optical properties of apple flesh. Finally, the model performance was evaluated by the determination coefficient of prediction (*Rp* 2) with the root mean square error of prediction (*RMSEP*), and the determination coefficient of calibration (*Rc* 2) with the root mean square error of calibration (*RMSEC*).
