Evaluation of Component Factors of Maize Yield Based on PPC Model under Different Film-Mulching Methods and Drip Irrigation
In order to find the factors with prominent contribution to the maize yield, an evaluation model which is based on the combination of projection pursuit classification model (PPC) and real coding based accelerating genetic algorithm (RAGA) was established, took the component factors as the evaluation indexes, and the data observed in the experimental base which located in Dumeng county Heilongjiang province in 2009 was analyzed by means of the model. The results showed that the main factors with prominent contribution to the maize yield were grain number per spike and spikes per hm2 for double line film-mulching treatment and 100-seed weight and spikes per hm2 for film-mulching between furrows treatment.
drip irrigation film-mulching maize yield PPC RAGA evaluation
Lv Guo-liang Wei Yong-xia
Water and Civil Engineering College Northeast Agricultural University Harbin Heilongjiang, P.R.China
国际会议
太原
英文
630-633
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）