Abstract: Orthogonal signal correction (OSC) was used as a method to preprocess the near infrared (NIR) spectra of apples ranging from 1300nm to 2100nm, to estahlish the calibration model of sugar content against apple spectra before and after OSC pretreatment by partial least square (PLS). Compared with those just being centered, apple spectra after OSC followed by centered pretreatment were smoother and in a closer and more orderly array, but their shape showed not much difference. This indicated that the major information in apple spectra could be reserved while part noise was removed by OSC method. The number of optimal factors of PLS model used to predict sugar content against apple spectra would be reduced in accordance with OSC factors reduction, even up to 1 finally (the precision of model also will have a little variation). In this study, the optimum PLS calibration model was obtained when 10 OSC factors were filtered, to have obtained the correlation coefficient (r 2 ) of 0.92644, with the standard error of calibration (SEC) of 0.40250 and the standard error of prediction (SEP) of 0.50229. Although this model could not improve precision to a great extent, but in comparison on with the model before OSC pretreatment, less reduction factors would be necessary and the model would be simpler.

Key words: orthogonal signal correction, partial least square, sugar content of apples, near infrared spectra