[Study on the Calibration Transfer of Near Infrared Spectroscopy Model for Soil Organic Matter Content Prediction by Using FIR].

Calibration transfer of near infrared spectroscopy model is a key problem in the field of near infrared spectroscopy research. In this study, calibration transfer of near infrared spectroscopy model for soil organic matter prediction by using Finite Impulse Response (FIR) was analyzed. The specific research work and conclusions were as follows: Firstly, 59 soil samples were collected and detected by using ASD Fieldspec3 in different times. 50 soil samples called "master soil samples" were detected at the same time in 2012, and the other 9 soil samples called "target soil samples" were detected at the same time in 2013. Secondly, 41 soil samples as calibration samples were randomly selected from the "master soil samples", and soil organic matter prediction model was built by using partial least square (PLS) analysis. The other 9 "master soil samples" were predicted. The result shows that the prediction correlation coefficient is 0. 961, Root Mean Standard Error of Prediction(RMSEP) is 0.600%, and Standard Error of Prediction(SEP) is 0.597%. It indicates that it is feasible to predict "master soil samples" by using above PLS model. Then, 9 "target soil samples" were predicted by using above PLS model. The result shows that it is infeasible to predict "target soil samples" by using above PLS model. Finally, FIR was applied to realize calibration transfer. The result shows that, when the window size was 516, higher prediction accuracy was obtained. The prediction correlation coefficient is 0.706, RMSEP is 0.662%, and SEP is 0.430%. It indicates that it is feasible to realize calibration transfer by using FIR.