To allow more efficient exploitation of germplasm collections, core subsets are typically assembled by various criteria, e.g. [11], [12], and eventually characterized with presumably neutral molecular markers.
In the past 20 years, there has been a steady increase in the rate of release of cultivars containing genes from CWR, and their contribution should only increase as the development of molecular technologies makes identification and utilization of diverse germplasm more efficient [2] [5].
The challenge in wheat breeding is to accelerate the adaptation of germplasm for more efficient and rapid results, if possible, to increase yield, and to adapt to future climate change.
This will lead to deeper understanding of breeding germplasm, as well as more efficient QTL mapping, association mapping and marker-assisted selection, collectively resulting in more predictable and directed breeding.
Thus, the public availability of introgression libraries enhances the value of the genetic resources available in our in situ and ex situ germplasm collections and leads to more efficient development of improved rice varieties for agricultural producers and consumers around the world.
The mungbean whole genome sequence became available recently [ 7], paving the path for molecular breeding approaches that will make trait introgression into elite material more efficient, provided breeders have sufficient access to diverse mungbean germplasm to source these traits.
The rich phenotypic and genotypic diversity data generated from this initiative will greatly expand our understanding of natural variation in crop plants and will open the door to more efficient utilization of the enormous wealth of diversity available in rice germplasm repositories around the world.
The SNPs identified in this study will enable high-throughput genotyping of germplasm and populations, which in turn will enable more efficient marker-assisted breeding efforts in potato.
In particular, linkage analysis has the advantage over AM of being more efficient in detecting alleles that are present in rare frequencies in the target germplasm, as could be the case for the QTLs detected in the Kofa × Svevo durum mapping population, and alleles whose distribution correlates to the genetic population structure.
So, leaf wilting, turfgrass quality, growth rate, evorpotranspiration rate, and chlorophyll content provided convenient and more efficient measurements for studying turfgrass responding mechanism under unfavorable conditions, which have been intensively applied for screening heat-tolerant germplasm of turfgrass [ 29- 31].
