The selection of animals using molecular information is more reliable with increased accuracy of selection and higher genetic gain. Hence, there is need to use selection methods that are based on genomic studies. Genomic selection (GS) is a variant of marker-assisted selection method used for predicting genomic breeding values (GEBVs) of animals using high density genetic markers, such as single nucleotide polymorphisms (SNPs). The utility of genomic information in dairy cattle breeding schemes has now reached the level of accuracy that enables dramatic changes and improvements to breeding schemes. GS can increase the accuracy of selection, shorten the generation interval by selecting individuals at the early stage of life, and accelerate genetic progress. The application of GS in dairy cattle has been reported in many countries, including USA, Canada, Australia, Norway, New Zealand, Netherland, Denmark, Germany and Ireland with very promising results. Published results indicates that for dairy cattle approximately 1000 bulls are required in the reference population to obtain GEBVs with accuracies that compete with the accuracies of EBVs based on progeny testing for all traits. Use of genomically evaluated young bulls can accelerate the breeding cycle and increase genetic gain per unit time beyond what is possible with phenotypic selection. With denser marker panels, more sophisticated statistical tools and in the longer term, sequencing, it is expected that the accuracy of GEBVs will continue to improve and breeding schemes will utilize genomic information further at the expense of progeny testing. Current application of genomic selection is only the start of the genomic era in livestock production. To fully capitalize on the benefits provided by GS, breeding programmes may need to be redesigned substantially.

The multiparent advanced generation inter-cross (MAGIC) population is one of a new generation emerging mapping population for plant genetics study. They are generally created by intercrossing multiple founder lines over several generations. The MAGIC populations offer an alternative to traditional linkage or association mapping populations by increasing the precision of quantitative trait loci (QTL) mapping resolution and analysis of gene–trait association by taking the advantages of both historical and synthetic recombination. MAGIC offer great potential both for dissecting genomic structure and for improving breeding populations.

Twenty-one genotypes of rice were evaluated in Randomised block design with three replications during Kharif season of 2015. Observations recorded for characters like days to 50% flowering, Chl-a (mg/kg), Chl-b (mg/kg), Chl a/b, Plant Height (cm), No of tillers, No of effective tillers, 1000 seed weight, number of filled grains, floret Steriity (%), Dry weight (g) and Seed yield (g).Twenty-one genotypes were grouped into seven clusters, according to depicted distances among the genotypes based on D2 values. Among the all seven clusters, maximum genotypes present in Cluster-IV, possessing six genotypes followed by cluster-I, which had five genotypes and the remaining clusters had two genotypes each. According to D2 values, highest inter cluster distances were witnessed between cluster-III and cluster-V (18248.23), followed by cluster III and VII (11764.44), cluster V and VI (104.22.98). Lowest inter cluster distances were observed between cluster-II and cluster-VI (856.26), signifying close relationship among the genotypes of this group. During hybridization programmes, parents from distant clusters should be selected and maximum should be given to characters like number of grains per panicle, seed yield, 1000 grain weight, floret fertility and number of tillers per plant which together contributed more than 89% towards divergence.

In the present study we reported the physio-morphological characterization of fourteen mineral rich as well as high yielding rice genotypes. Genotypic and phenotypic coefficient of variation for various traits in fourteen rice varieties reported in this study. Phenotypic coefficient of variation (PCV) was higher than or equal to the genotypic coefficient of variation for all the parameters of all rice genotypes. Phenotypic correlation coefficient association between various traits in fourteen rice varieties was assessed, yield per plant showed a positive correlation with grains per panicle (0.250; p=0.01), number of panicles per plant (0.111; p=0.01), and effective number of tillers per plant (0.152; p=0.01). In addition to this path coefficient analysis was done to study direct and indirect effects of component traits on grain yield per plant. The data shows that grain weight had highest positive direct effect on grain yield per plant.

The present experiment was conducted with 15 groundnut genotypes to estimate the genetic variability and correlation for yield and its components. Analysis of variance clearly specified the existence of ample amount of variability in present experimental material for improvement. Variability studies indicated the higher scope of selection in desirable direction for number of pods per plant, shelling percentage, hundred kernel weight, hundred pod weight, dry pod yield per hectare and kernel yield as they recorded higher GCV and genetic advance values. These traits were found to be governed by additive genes as evident by recording higher values for both heritability and genetic advance. Correlation studies revealed the simultaneous improvement of hundred pod weight, sound mature kernels and hundred kernel weights for improvement of the yield.

Data on female adult body weight and egg production measurements were analysed to obtain their heritability estimates. The mean values for body weight and egg production at various ages showed good performance of indigenous Uttara chicken. The heritability estimates observed for body weight decrease with increasing age of birds. The heritability values for various egg production traits at 40 and 58 week were low to high in magnitude. Changes in heritability estimates across different ages indicated expression of different genes at different ages of the Uttara fowl and the reduction of environmental effects as the flock is maintained under quite uniform environmental conditions.

Potato (Solanum tuberosum L.) is an annual herbaceous, cross-pollinated species. Potato belongs to family solanaceae and the genus Solanum with a basic set of 12 chromosomes (x = 12). It is used as vegetable and in industries for manufacturing starch, alcoholic beverages and other processed products like French fries, chips etc. Afresh potato contains 16-20% carbohydrates 2.5-3.2% crude protein. Even though potato contains little amount of protein, nutritional quality of potato is better than cereals. Potato has potential to produce more calories and protein per unit land area with little time and water than most of the major food crops. Therefore, understanding its genetic diversity is important for the improvement of this crop and as well as for effective utilization of germplasm. Diversity analysis based on molecular characterization is better than morphological characterization as it is highly influenced by the environment. Hence, in-depth studies based on both morphological and molecular markers will help in better understanding the genetic diversity of potato germplasm.