Four nondestructive technologies (i.e., acoustic firmness, bioyield firmness, visible and shortwave near infrared (Vis-SWNIR) spectroscopy, and spectral scattering) have been developed in recent years for assessing the firmness and/or soluble solids content (SSC) of apples. Each of these technologies has its merits and limitations in predicting the two quality parameters. With the concept of multi-sensor data fusion, different sensors would work synergistically and complementarily to improve the quality prediction of apples. In this research, the four sensing systems were evaluated and combined for nondestructive prediction of the firmness and SSC of 'Jonagold' (JG), 'Golden Delicious' (GD), and 'Delicious' (RD) apples. A total of 6535 apples harvested in 2009 and 2010 were used for analysis. Better predictions of the firmness and, in most cases, of the SSC were obtained using sensors fusion than using individual sensors, as measured by correlation coefficient and standard error of prediction (SEP). The SEPs for the firmness of JG, GD and RD using the best combination of two-sensor data were reduced by 13.5%, 20.0% and 7.3% for the 2009 data and 14.6%, 14.2% and 6.2% for the 2010 data; and using the best three or four fused sensor data by 19.1%, 24.9% and 13.9% in 2009, and 15.7%, 23.6%, and 8.9% in 2010, respectively. The combination of Vis-SWNIR and scattering data improved SSC predictions for RD apples, with the SEP values being reduced by 5.8% and 6.0% for 2009 and 2010, respectively. This research demonstrated that the fused systems provided more complete and complementary information and, thus, were more effective than individual sensors in prediction of apple quality. © 2012.