Notice of RetractionEvaluation of component factors of maize yield based on PPC model under different film-mulching methods and drip irrigation

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

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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.