QTLs Analysis Of Processing Quality And Appearance Quality Of Rice

Rice is the most important cereal crop, and provides staple food for more than 60% of the population in our country. Rice quality improvement has become one of the most important goals in rice breeding programs, since the global economic integration and increasing people's living standards. Many high-quality rice varieties crushed into our country, such as Koshihikari from Japan and Jasmine from Thailand.There are also very small part of the main cultivated rice varieties in China meet the national standard of quality rice, resulting in rice export or domestic sales are sluggish, and some rice in main producing areas suffering from a structural surplus. The main aspects of rice grain quality include appearance, eating, cooking, milling and nutritional qualities. Rice milling quality is determined mainly by brown rice ratio (BR), milled rice ratio (MR) and head rice ratio(HR), and appearance quality is determined mainly by grain shape, chalkiness and translucence.Long, slender and translucent grain varieties are preferred by consumers in most Asian areas. Rice grain quality traits are multi-genes inheritence. The identification of quantitative trait loci (QTLs) for grain quality and elucidation of their genetic control are necessary for the improvement of rice quality on theoretical and applied value. However, there are fewer studies on milling and appearance quality of high-quality variety Koshihikari. In the present study, a recombinant inbred lines (RIL) population derived from the cross of Koshihikari, a top elite japonica variety with superior grain quality, and Guichao2,a high-yield indica variety with poor grain quality, were used to detect stable QTL for grain quality. The results are as follows:1.Continuous distributions observed in all the traits in the RIL population, most of them were transgressive segregation, when planted in xinxiang, henna province,2008 and 2009.2.A total of 35 QTLs for nine traits were identified using software IciMapping v2.1 of the mixed-model-based composite interval mapping (MCIM) model.Six of them can be detected in consective two years, such as qGW2-1 for grain width,qLWR2 for length-width ratio,qCGRl and qCGR8 for chalky grain rate,qCD6-1 and qCD6-2 for chalkiness severity.3.The qGW2-1 for grain width is consistent with He YQ et al.(2003) and Wang MQ et al.(2007); the qCD6-1 and qCD6-2 for chalkiness severity have large additive effect and occupied 28.10% and 27.6% of phenotypic variation, respectively. The positive effect of these two loci is contributed either by Koshihikari or by Guichao2.