Background: Groundnut (Arachis hypogaea L.) is one of the most nutritious crops having versatile use. Its yield is mostly exaggerated by two foliar fungal diseases i.e., early and late leaf spot. In present investigation 96 germplasm lines were screened for early and late leaf spot diseases along with diverse biochemical parameters including protein, oil, fatty acids, proline and sugar contents. Methods: Early and late leaf spot diseases have been screened under field condition as well as employing SSR molecular markers. Nutritional profiling has also been done for protein, oil, fatty acids viz., oleic acid, linoleic acid, stearic acid and palmitic acid, proline and sugar contents. Result: In correlation analysis, oleic acid is negatively correlated with linoleic acid (r= -0.911) and palmitic acid (r= -0.688) at 1% level of significance, whereas stearic acid is positively and highly significantly correlated with oil percentage (r=0.381) at 1% significance level. The gene diversity value varied between 0.1866 to 0.4837 for markers ipahm103 and GM1536 with an average of 0.4014 and polymorphic information content (PIC) values ranged between 0.1692 to 0.3855 for the markers pahm103 to GM1536 respectively with a mean value of 0.3183.

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Plant breeding systems have a extensive antiquity and they had been employed meanwhile the commencement of subjugation of the initial agricultural crop plants. Subsequently, innumerable novel procedures have and are being advanced to added upsurge the profitable worth and harvest of plants. The newest crop enhancement method recognized as genome editing is a method which empowers accurate alteration of the crop genome via bashing out unwanted genes or permitting genes to advance novel occupation. Genome sequencing of many plants and advancement in genome editing methodologies has unlocked prospects to breed advantageous traits. Innovations in genome editing machineries for instance have created it feasible for biotechnologists to mark a specific gene of consideration more proficiently. The first-generation CRISPR/Cas9 genome editing entails modest conniving and cloning approaches, which can be accessible and applicable for various guide RNAs to edit various positions in the genome of targeted organism. It is more willingly recognized in the marketplace economically. The tradition of genome editing has verified to be reimbursements and theatres an encouraging part in upcoming crop development endeavors. So, in presented review article, it is intended to emphasize the advancement and usage of genome editing procedures, in regard, the CRISPR/Cas9 for crop improvement.

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The primary goal of every plant breeder is to identify gene alleles and then use them in crop improvement programmes. If there is no population variation, there cannot be a breeding programme. Breeders need a lot of labour and money to screen germplasm for a desired gene. Additionally, these screenings are compliant with environmental effects. The method of "allele mining" is employed to identify suitable alleles of a candidate gene affecting important agronomic properties or naturally occurring allelic variations. TILLING and Eco-TILLING are the ideal solutions to this issue for allele mining. A technique known as "tilling" uses mutagens to introduce new diversity in a specific allele. Then, different sequencers are used to screen the diversity in a gene to identify different mutations. The best mutant among them can then be directly used in breeding programmes. In a modified version, alleles of a gene that are present in the population are identified by screening natural populations. Eco-TILLING is the name of this fresh iteration of the technology. The generation of novel haplotypes, the use of molecular markers to characterize genetic diversity and the syntenic links across crop genotypes, as well as marker-assisted selection are just a few of the many applications of allele mining in agriculture and crop improvement. Many genes may be found and used in the breeding of many crop species using these reverse genetics techniques.Allele mining