Key message Groundnut has entered now in post-genome era enriched with optimum genomic and genetic resources to facilitate faster trait dissection, gene discovery and accelerated genetic improvement for developing climate-smart varieties. Abstract Cultivated groundnut or peanut (Arachis hypogaea), an allopolyploid oilseed crop with a large and complex genome, is one of the most nutritious food. This crop is grown in more than 100 countries, and the low productivity has remained the biggest challenge in the semiarid tropics. Recently, the groundnut research community has witnessed fast progress and achieved several key milestones in genomics research including genome sequence assemblies of wild diploid progenitors, wild tetraploid and both the subspecies of cultivated tetraploids, resequencing of diverse germplasm lines, genome-wide transcriptome atlas and cost-effective high and low-density genotyping assays. These genomic resources have enabled high-resolution trait mapping by using germplasm diversity panels and multi-parent genetic populations leading to precise gene discovery and diagnostic marker development. Furthermore, development and deployment of diagnostic markers have facilitated screening early generation populations as well as marker-assisted backcrossing breeding leading to development and commercialization of some molecular breeding products in groundnut. Several new genomics applications/technologies such as genomic selection, speed breeding, mid-density genotyping assay and genome editing are in pipeline. The integration of these new technologies hold great promise for developing climate-smart, high yielding and more nutritious groundnut varieties in the post-genome era.

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Peanut plays a key role to the livelihood of millions in the world especially in Arid and Semi-Arid regions. Peanut with high oleic acid content aids to increase shelf-life of peanut oil as well as food products and extends major health benefits to the consumers. In peanut, ahFAD2 gene controls quantity of two major fatty acids viz, oleic and linoleic acids. These two fatty acids together with palmitic acid constitute 90% fat composition in peanut and regulate the quality of peanut oil. Here, two ahfad2 alleles from SunOleic 95R were introgressed into ICGV 05141 using marker-assisted selection. Marker-assisted breeding effectively increased oleic acid and oleic to linoleic acid ratio in recombinant lines up to 44% and 30%, respectively as compared to ICGV 05141. In addition to improved oil quality, the recombinant lines also had superiority in pod yield together with desired pod/seed attributes. Realizing the health benefits and ever increasing demand in domestic and international market, the high oleic peanut recombinant lines will certainly boost the economical benefits to the Indian farmers in addition to ensuring availability of high oleic peanuts to the traders and industry.

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has shown potential for achieving >75% oleic acid as demonstrated among introgression lines. Significant advances have been made in seed systems research to bridge the gap between trait discovery, deployment, and delivery through innovative partnerships and action learning.

Peanut (Arachis hypogaea L.) is an important nutrient-rich food legume and valued for its good quality cooking oil. The fatty acid content is the major determinant of the quality of the edible oil. The oils containing higher monounsaturated fatty acid are preferred for improved shelf life and potential health benefits. Therefore, a high oleic/linoleic fatty acid ratio is the target trait in an advanced breeding program. The two mutant alleles, ahFAD2A (on linkage group a09) and ahFAD2B (on linkage group b09) control fatty acid composition for higher oleic/linoleic ratio in peanut. In the present study, marker-assisted backcrossing was employed for the introgression of two FAD2 mutant alleles from SunOleic95R into the chromosome of ICGV06100, a high oil content peanut breeding line. In the marker-assisted backcrossing-introgression lines, a 97% increase in oleic acid, and a 92% reduction in linoleic acid content was observed in comparison to the recurrent parent. Besides, the oleic/linoleic ratio was increased to 25 with respect to the recurrent parent, which was only 1.2. The most significant outcome was the stable expression of oil-content, oleic acid, linoleic acid, and palmitic acid in the marker-assisted backcrossing-introgression lines over the locations. No significant difference was observed between high oleic and normal oleic in peanuts for seedling traits except germination percentage. In addition, marker-assisted backcrossing-introgression lines exhibited higher yield and resistance to foliar fungal diseases, i.e., late leaf spot and rust.

Additive main effects and multiplicative interaction (AMMI) analysis is widely used for analyzing data of multi-environment trials (METs) to model the genotype-by-environment interactions (GEIs). However, AMMI model do not rank genotypes which is required for aiding selection. In order to overcome these lacunae a stability index titled AMMI stability value (ASV) was proposed by Purchase et al. (1997) using first two interaction principal components (IPCA) from the results of AMMI analysis. Later, Zali et al. (2012) modified it and proposed Modified ASV (MASV) which used all significant IPCAs. However, Zali et al. (2012) read the original formula of ASV incorrectly while proposing MASV thus rendering it erroneous. Use of this erroneous MASV impacted genotype ranking significantly. Corrected version of MASV, i.e. MASV2 showed significant correlation with other stability models. Hence, we propose MASV2 as a correct formula for modified AMMI stability Value (MASV) and this correct version of MASV may be used instead of earlier formula proposed by Zali et al. (2012).

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