The changes of measurement environment and spectral signals of spectroscopy instruments could lead to big errors in the transferring process of the NIR（near infrared） spectra model to slave instruments.The influences of baseline drift and light scattering on NIR spectra were eliminated by standard normal variate transformation（SNV） plus derivative pretreatment in this paper.And then the wavelengths in which spectral signals are consistent and the spectral differences among samples are great were selected by screening wavelengths based on spectrum ratio analysis（SWSRA） among instruments.The partial least squares regression（PLS） models for predicting quality to be measured were built on the basis of the selected wavelength variables.Two data sets were utilized to validate the SWSRA method,in which one set was consisted of 72 Scutellaria baicalensis samples whose NIR spectra were measured on two types of NIR spectroscopy instruments,another one was composed of 80 corn samples whose contents of moisture,protein and oils,and NIR spectra measured on three NIR instruments were available online.The results showed that the average errors of slave instruments for samples predicted by SWSRA models built on master instrument were all below 43%.Root mean square error of prediction（RMSEP） of the method was much lower than that of the full-wavelength PLS model transferred to slaves,which was equivalent or superior to those of the other model transfer methods reported in literatures.With the advantages of few parameters,stability and simplicity,the SWSRA method could keep a good prediction performance during the transmission of spectral signals between the master and salve instruments.Similar near-infrared instruments could share the SWSRA models without standards.