Prediction Model Of Pine Nut Yield For Korean Pine Plantation

The Logistic and non-linear models were developed for predicting nut yields of tree for Korean pine (Pinus koraiensis) plantation based on579Korean pines measured in12sample plots and Korean pines of21diferent sample plots in Mengjiagang forest farm, Jiamusi, Heilongjiang Province. First, the statistical analysis system (SAS9.22) was employed using data of pine nut yield to establish Logistic model for predicting whether individual pine could seed or not. Second, a non-linear regression was set up for predicting nut yields of individual seeded pines using tree variables. Last, stepwise linear regression was applied to make models for predicting nut yields of stand pines using stand variables.The results showed that the predicting accuracy of chance, whether individual pine could seed or not, was above65%for Logistic model. The optimal model of predicting nut yields was y=α(D2cw)b due to the best fitting performance, which included the prediction accuracy of77%and evenly distributed model residuals. The accuracy assessment was92.78%for the two models using the observed pine nut yield data of Plot2, which indicated a good prediction performance. The prediction accuracy of the models for predicting stand nut yields was above85%, and the accuracy assessments were above85%for models using the observed pine nut yield data of3plots established in2012. This paper has been provided suitable method for predicting pine nut yield for Korean pine plantation.