Application of RAGA-PPC model on the optimal harvest time of Puccinellia tenuiflora

In order to ascertain the optimal harvest time of Puccinellia tenuiflora in practical production scientifically, PPC (Projection Pursuit Classification) model based on RAGA (Real coding based Accelerating Genetic Algorithm) was applied. Projection direction was optimized and high-dimension data were converted into low-dimension space with PPC, value of projection indexes could be obtained. Based on these projection function values, the sequence of samples from the big to the small was gained, at the same time, subjective impact on weight matrix farthest could be avoided with PPC model. The results showed that the initial biloom stage have the biggest value of projection indexes, which was 2.2572, and its comprehensive evaluation was the best based on the data from 2007 to 2008. Puccinellia tenuiflora harvested in the initial bloom stage had higher nutritive value, higher output and lower coarse fibre content. This model offered a new method to solve the evaluating problem of the optimal harvest time of Puccinellia tenuiflora.