China is a big country of apple producers and exporters，so it is essential to control the quality of exported apples. The soluble solids content （SSC） in apples is an essential factor affecting the quality of apples. Non-destructive inspection of SSC in apples can be realized by near-infrared spectroscopy （NIR）. The model update method combined with the variable screening method was used to perform nondestructive inspection on the SSC in five apple varieties including Red Fuji，Green apple，Golden Delicious，Rose and Lokit to obtain a general robust multi-variety apple model. The results showed that the updated new model achieved high-precision prediction of the SSC in five varieties of apples. At this time，the root mean square error of prediction （RMSEP） of the model was 0.698%，the correlation coefficient of prediction （R_p） was 0.904，the prediction deviation was 0.074%，and the ratio of performance to standard deviate （RPD） reached 2.340. The model was optimized with three waveband selection methods including competitive adaptive reweighted sampling （CARS），successive projections algorithm （SPA） and uninformative variable elimination （UVE） to identify and extract important information bands of the spectrum. The results showed that CARS selected effective wavebands more effectively. The established model significantly improved the analytical performance in new apple varieties，with RMSEP of 0.587%，R_p of 0.928，and prediction bias reduced to -0.052%，with RPD of 2.684. Therefore，the strategy of combining model updating with waveband selection has great application potential in studying and developing the general model of portable near-infrared detector for multi-variety fruits.