Calibration transfer can solve the problem that multivariate calibration models cannot be shared among different near-infrared spectrometers. Taking edible oil as the research object, transfer analysis of its acid value and peroxide value model was conducted. The partial least squares multivariate correction model was established on the master spectrometers, and the calibration transfer was realized by using the parameter-free and efficient calibration enhancement (PFCE) calibration transfer algorithm in NS-PFCE without standard sample transfer and FS-PFCE with standard sample transfer, and the dependence of calibration transfer on the number of standardization samples was explored. In addition, it was compared with three calibration transfer algorithms with standard sample, which were slope/bias (S/B), direct standardization (DS) and piecewise direct standardization (PDS), and two calibration transfer algorithms without standard sample, which were finite impulse response (FIR) and stability competitive adaptive reweighted sampling (SCARS). The results suggested that after the NS-PFCE without standard sample algorithm was transferred, the root mean square error of prediction (RMSEP) of the acid value and peroxide value was decreased from 0.613mg/g and 16.153mmol/kg to 0.275mg/g and 9.523mmol/kg,respectively. Furthermore, after the FS-PFCE with standard sample algorithm was transferred, the root mean square error of prediction (RMSEP) of the acid value and peroxide value was dropped to 0.274mg/g and 8.945mmol/kg, respectively. Specifically, the increase of the number of standardized samples, the root mean square error of prediction (RMSEP) was lower. The parameter-free and efficient calibration enhancement (PFCE) algorithm combined a single transfer method without a standard sample and a standard sample, which enhanced the adaptability and inclusiveness of the transfer model. And PFCE algorithm effectively reduced the difference between the master spectrum and the slave spectrum, and also realized the calibration model sharing between different spectrometers.