Abstract: Logistic and non-linear models were developed for predicting nut yields for Korean pine (Pinus koraiensis) plantation based on 579 Korean pines measured in 12 sample plots in Mengjiagang forest farm, Jiamusi, Heilongjiang Province. First, the statistical analysis system (SAS 9.22) was employed using data of pine nut yields 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. The results showed that the predicting accuracy of whether individual pine could seed or not, was above 65% for Logistic model. The optimal model of predicting nut yields was y=a(D²CW)^b due to the best fitting performance, which included the prediction accuracy of 77% and evenly distributed model residuals. The accuracy assessment was 92.78% for the two models using the observed pine nut yield data of Plot 2, which indicated a good prediction performance. This paper has been provided suitable method for predicting pine nut yields for Korean pine plantation.

Key words: korean pine plantation, nut yields, Logistic regression, nonlinear regression