Groundnut (Arachis hypogaea L.) is an important oilseed crop cultivated in 96 countries of world. World crop productivity (1.30 t per hectar) is low. The available large variability contained in the germplasm accessions has not been adequately utilized in the crop improvement programs and most groundnut cultivars stand on a very narrow genetic base. This is due to lack of information on agronomic and other economic traits, which require extensive evaluation. The development of a core collection could facilitate easier access to groundnut genetic resources, enhance their use in crop improvement programs, and simplify the genebank management.
This paper describes the development of a core collection from 14310 accessions of groundnut available from ICRISAT genebank. Germplasm accessions were stratified by country of origin within each of six botanical varieties. Data on 14 morphological descriptor traits were used for clustering by Ward’s method. From each cluster ≈10 percent accessions were randomly selected to constitute a core collection consisting of 1704 accessions. Mean comparisons using ‘t’ test and distribution using chi-square test and Wilcoxon’s rank-sum non-parametric test on different descriptors indicated that the genetic variation available for these traits in the entire collection has been preserved in the core collection. The Shannon-Weaver diversity index for different traits was also similar in the entire collection and core collection. The important phenotypic correlations between different traits, which may be under the control of co-adapted gene complexes, were preserved in the core collection. This core collection provides an effective mechanism for the proper exploitation of groundnut germplasm resources for the genetic improvement of this crop.
MCPD passport data
MCPD - 1edd3efd-b967-40d0-bdf5-c150a0661ca0.xlsx
Apply custom filters to accessions in this subset
Explore subset accessions on the map
List of accessions included in the subset
IND002
• DOI: 10.18730/RHVE5IND002
• DOI: 10.18730/RHVH8IND002
• DOI: 10.18730/RHVJ9IND002
• DOI: 10.18730/RHVNCIND002
• DOI: 10.18730/RHVQEIND002
• DOI: 10.18730/RHW0QIND002
• DOI: 10.18730/RHW4VIND002
• DOI: 10.18730/RHW7YIND002
• DOI: 10.18730/RHWA~IND002
• DOI: 10.18730/RHWG2IND002
• DOI: 10.18730/RHWH3IND002
• DOI: 10.18730/RHX5QIND002
• DOI: 10.18730/RHX9VIND002
• DOI: 10.18730/RHXN2IND002
• DOI: 10.18730/RHXS6IND002
• DOI: 10.18730/RHXYBIND002
• DOI: 10.18730/RHY2FIND002
• DOI: 10.18730/RHY3GIND002
• DOI: 10.18730/RHYGXIND002
• DOI: 10.18730/RHYK*IND002
• DOI: 10.18730/RHYR0IND002
• DOI: 10.18730/RHYW4IND002
• DOI: 10.18730/RHYZ7IND002
• DOI: 10.18730/RHZ08IND002
• DOI: 10.18730/RHZ3BIND002
• DOI: 10.18730/RHZCMIND002
• DOI: 10.18730/RHZGRIND002
• DOI: 10.18730/RHZR*IND002
• DOI: 10.18730/RHZT$IND002
• DOI: 10.18730/RJ047IND002
• DOI: 10.18730/RJ069IND002
• DOI: 10.18730/RJ0ADIND002
• DOI: 10.18730/RJ0GKIND002
• DOI: 10.18730/RJ0RVIND002
• DOI: 10.18730/RJ0SWIND002
• DOI: 10.18730/RJ0Y~IND002
• DOI: 10.18730/RJ164IND002
• DOI: 10.18730/RJ197IND002
• DOI: 10.18730/RJ1A8IND002
• DOI: 10.18730/RJ1NKIND002
• DOI: 10.18730/RJ2A3IND002
• DOI: 10.18730/RJ2E7IND002
• DOI: 10.18730/RJ2KCIND002
• DOI: 10.18730/RJ2XPIND002
• DOI: 10.18730/RJ33WIND002
• DOI: 10.18730/RJ3J6IND002
• DOI: 10.18730/RJ3K7IND002
• DOI: 10.18730/RJ3RCIND002
• DOI: 10.18730/RJ41NIND002
• DOI: 10.18730/RJ47V