QTL Mapping For High Starch Content And Other Important Economic Traits In Cassava (Manihot Esculenta Crantz)

The starchy root crop cassava (Manihot esculenta Crantz) is ranking fourth of the most important tropical food crop globally, and was known as one of the potential bio-energy crop presently. There are more than 600 million people living with cassava a dietary staple. Cassava is characteristed for its high biomass output, tolerance to biotic & abiotic stresses and excellent starch quality that possessed storage root contains 40% to 50% dry matter with 65% to 80% of starch. Generally, cassava was grown in barren field with less manage and the output is lower. There is huge potential to increase the yield. However, because of heavy heterozygosity of cassava genome caused by stack propagation and outcross pollination in longtime, cassava conventional breeding is constrained by less selective effect, deleterious'genetic load'and lower propagation index etc. How to set up a fruitful cassava breed program based on biotechnology would be very important.Development of molecular marker can help us find out the hereditary principle of the complicate traits, and practice genotyping of them avoid influence of the environment. For example, we can earth out the important QTLs related to yield and increase the selective efficiency by MAS,that depends a trend of cassava breeding in the future.In this work, A cassava mapping population comprised of 211 F1 lines crossed from two no inbred parents'SC6'and'Mianbao'have been set up. All individuals in the population were evaluated in 2003 to 2005 for starch content (SC), fresh root yield (FRY), harvest index (HI), leaf retention (LR) and branching height (BH) in the field test, and screened by SSR markers in lab. Combining the above data, where and what QTLs of these traits have been detected by software that will benefit to MAS in breeding of them. The main results shown as followings:Phenotypes of starch content, fresh root yield and harvest index of individuals during three years shown rich diversity in the population, took on normal distribution with bias distance that fit the request of QTL analysis. Meanwhile, it was discovered...