Classification Of Main Corn Inbred Lines In Heilongjiang Province

The main problems which hinder continues development in corn breeding in Heilongjiang province are lack of elite germplasm, relatively little knowledge about heterotic pattern because of later breeding program. Hence, in hybrid breeding program, one of the most important things is to classify elite germplasm into different heterotic groups and to divide inbred lines into these heterotic groups. In this study, we classified 22 inbred lines in Heilongjiang province into different heterotic groups, and discussed the effect of each classification methods. This study was meaningful both in breeding new hybrid with strong heterosis and helpful for corn breeding and production. The results indicated that:1. These 22 inbred lines in Heilongjiang province can be divided into seven heterotic groups by means of pedigree, agronomical traits analyses, heterosis and combining ability analysis combining with breeding practice: Reid population (B73), Ludahonggu population (Lii 9), Tangsipingtou population (Dong6002 and 81162), Lancaster population (Mo 17, Zc546, He344 and Ken44), Dong237 population (Dong237, DonglO, 169, Dong91 and Chang3), Dianll population (Dong46, HaiOH, Ji8l8, Dong96, Dongl7, 7010, Dianll and 434) ; Xiongzhang population (Xiongzhang).2. The dominant heterotic pattern of corn germplasm in Heilongjiang province are: Lancaster population X Dianll population, representative hybrid Baidan9 (Zc546XJi818) ; Reid population X Lancaster population, representative hybrid Benyu9 ( 7884-7 X Mol 7) ; Tangsipingtou population X Lancaster population, representative hybrid Sidanl9 (444 X Mo 17); Dianll population X Dong237 population, representative hybrid Dongnong248 (Dong46X Dong237); Lancaster population X Ludahonggu population, representative hybrid Jidanl59(Ji846XDan340) .3. The cluster results based on agronomic traits of inbred lines differed significantly when compared to final result. It should be used only when combining with other methods in cluster analysis. Combining ability analysis based on NC2 design was an effective and economical classification method, especially, the results based on total combining ability analysis are better than those based on special combining ability and general combining ability analysis.4. In cluster analysis, we should select independent agronomic traits set according to breeding objective and calculated genetic distance on principle component scores.