Abstract:

Using near-infrared spectroscopy,64 leaves of P.bournei in the P.bournei Seed Garden of Guanshan Forest Farm in Yongfeng,Jiangxi Province were used as materials,and the nitrogen content of P.bournei leaf samples was determined by the traditional chemical analysis method as a reference value.At the same time,the near-infrared spectrum of the P.bournei leaf powder samples was collected.Using the chemometric software NIRCal,the optimal determination model was established by selecting the modeling method,modeling band,and pre-treatment method.In addition,10 unknown samples were randomly selected to test the model,and the paired sample T test was used to evaluate the model.The results showed that the model established by the Principal Component Regression (PCR) method had the best effect;its related coefficient of calibration (Rc) was 0.912;the Root Mean Square Error (RMSEC) of calibration was 1.098;the related coefficient of validation (Rv) was 0.897;and the Root Mean Square Error of validation(RMSEV) was 1.192.The external verification results showed that the relative deviation between the predicted value and the measured value ranged from 0.070 to 0.705,and the paired sample T-test results showed that the P value was 0.116,greater than 0.05,and there was no significant difference.It can be used for large-scale rapid detection of the nutrient level and high-quality seed selection of P.bournei.

Key words: P.bournei, nitrogen content, leaf powder, near infrared reflectance spectroscopy