Genetic diversity estimation among different species is an important tool for genetic improvement to maximize the yield, desirable quality, wider adaptation, pest and insect resistance that ultimately boosting traditional plant breeding methods. The most efficient way of diversity estimation is application of molecular markers. In this study, twenty random amplified polymorphic DNA (RAPD) primers were utilized to estimate the genetic diversity between ten sunflower genotypes. Overall 227 bands were amplified by 20 primers with an average of 11.35 bands per primer. RAPD data showed 86.34% polymorophic bands and 13.65% of monomorophic bands. Genetic similarity was ranged from 50.22% to 87.22%. The lowest similarity (50.22%) was observed between FH-352 and FH-359 and the maximum similarity 87.22% was observed between A-23 and G-46. Polymorphic information content (PIC) values were varying from 0.05 to 0.12 with a mean of 0.09. Cluster analysis based on RAPD results displayed two major distinct groups 1 and 2. Group-2 contains FH-352 which was the most diverse genotype, while group-1 consists of few sub groups with all other genotypes. Ample diversity was found in all the genotypes. Present study reveals novel information about sunflower genome which can be used in future studies for sunflower improvement.

Nonrenewable energy resources deplete with the passage of time due to rapid increase in industrialization and population. Hence, countries worldwide are investing dearly in substitute energy resources like biofuel from miscellaneous set of feedstocks. Among the energy crops, sorghum serves as a model crop due to its drought tolerance, small genome size (730 Mb), high biomass, dry matter contents, quick growth, wide adaptability to diverse climatic and soil conditions and C4 photosynthesis. Sweet sorghum with high sugar content in stalk is an efficient feedstock for advanced biofuels and other bio-based products from sugars.However, high biomass sorghum has the utility as a feedstock for cellulosic biofuels. The enhanced yield of monomeric carbohydrates is a key to cheap and efficient biofuel production. The efficiency of lignocellulosic biofuels is compromised by recalcitrance to cell wall digestion, a trait that cannot be efficiently improved by traditional breeding. Therefore, scientists are looking for solutions to such problems in biomass crop genomes. Sorghum genome has been completely sequenced and hence this crop qualifies for functional genomics analysis by fast forward genetic approaches. This chapter documents the latest efforts on advancement of sorghum for biomass potential at morphological and molecular level by exploiting genomics approaches.