Abstract:Discriminant analysis is an important method in multivariate statistic analysis to distinguish whatever type an individual should belong to. Based on the field actual photosynthetic data obtained from the research platform--Northeast China Transect (NECT), the concept and principle of discriminant analysis were used to distinguish the different plant photosynthetic types. A number of indices related to plant photosynthetic rate measured by a LCA4 photosynthesis system were selected to build the discriminant model. In this case study, 15 plant species from C4 plant functional groups and 51 from C3 plant functional groups were selected to build a discriminant model. The rate of accuracy, of returned classification using methods of squared Mahalanobis distances from group centroids and posterior probabilities, reached to 98.48 %. With the help of this model, any plants‘ photosynthetic types could be distinguished simply by using their four related parameters, viz., photosynthetic rate, transpiration, stomatal conductance and the temperature difference between leaf surface and atmosphere.