In the present study, the fruit flesh firmness of apple was analyzed by near infrared (NIR) spectroscopy using an FTNIR spectrometer. The sensitive spectral regions that provide the lowest prediction error were analyzed by different well-known variable selection methods, including dynamic backward interval partial least-squares (dynamic biPLS), sequential application of backward interval partial least-squares and genetic algorithm(dynamic biPLS ＆ GA-PLS), and iterative genetic algorithm partial least-squares (iterative GA-PLS). Iterative GA-PLS, dynamic biPLS ＆ GA-PLS led to a distinct reduction in the number of spectral data points with better predictive quality. Furthermore, the majority of selected wavelengths were content with the characteristic of the sorption bands of fruit flesh firmness. Pectin constituents, complex non-starch polysaceharides, which are related to texture change in apple, play an important role in their harvest maturity, ripening and storage. Comparing NIR characteristic wavelengths of apple flesh firmness and typical absorption bands for pectin, it was found that characteristic wavelengths of apple flesh firmness were consistent with the pectins relevant spectral regions. Therefore, the NIR characteristic wavelengths of apple firmness based on GA and iPLS reflected the chemical component of apple and the results were reasonable.