Skip to main content
Log in

Development of Indian mustard [Brassica juncea (L.) Czern.] core collection based on agro-morphological traits

  • Research Article
  • Published:
Genetic Resources and Crop Evolution Aims and scope Submit manuscript

Abstract

Indian mustard [Brassica juncea (L.) Czern.] is a major edible oil crop of India. The Indian Council of Agricultural Research—National Bureau of Plant Genetic Resources (ICAR-NBPGR) and ICAR—Directorate of Rapeseed Mustard Research (DRMR) together conserve one of the largest global collection of Indian mustard germplasm comprising 5950 accessions which includes indigenously collected landraces, exotic accessions, breeding lines, Improved/released cultivars, registered genetic stocks and other type of material of unknown origin. However, only a small fraction of this huge collection has been deployed in the breeding programme due to lack of information on majority of accessions. The objective of this study was to develop a core collection of Indian mustard to enhance utilization of conserved germplasm in crop improvement programme. For this purpose, the accessions were characterized at one ideal site (Bharatpur) using 14 agro-morphological traits and the resultant data was analysed using three state-of-the-art core collection construction tools—MSTRAT, Power Core and Core Hunter 3 (CH3), to obtain three core sets each with 595 accessions. The quality of these core sets was evaluated and compared using two genetic distance based metrices (E-NE & A-NE), several summary statistics, Shannon diversity index, phenotypic correlations etc. The core collection generated using CH3 which optimized simultaneously for both representativeness and diversity was found the best in capturing the genetic variation existed in the base collection for all the 14 traits. The diversity represented in the core collection will therefore, be a guideline to breeders for a wider use of the Indian mustard genetic resources available in the genebank for identification and introgression of new useful traits, as well as for delineation of their genetic basis particularly through marker-trait association.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • An XH, Chen BY, Fu TD, Liu HL (1999) Genetic diversity of Chinese landraces in Brassica juncea was analysed by RAPD markers. J HuazhongAgric U 18:524–527

    CAS  Google Scholar 

  • Aravind J, Mukesh Sankar S, Wankhede DP, Kaur V (2018) AugmentedRCBD: analysis of augmented randomised complete block designs. R packageversion 0.1.0. https://aravind-j.github.io/augmentedRCBD. https://cran.r-project.org/package=augmentedRCBD

  • Aravind J, Kaur V, Wankhede DP, Nanjundan J (2020) EvaluateCore: quality evaluation of core collections. R package version 0.1. https://aravind-j.github.io/EvaluateCore; https://cran.r-project.org/package=EvaluateCore

  • Arora RK (1998) The Indian gene center: priorities and prospects for collection. In: Paroda RS, Arora RK, Chandel KPS (eds) Plant genetic resources: Indian perspective. Indian Society of Plant Genetic Resources, National Bureau of Plant Genetic Resources, New Delhi, pp 66–75

    Google Scholar 

  • Basigalup DH, Barnes DK, Stucker RE (1995) Development of a core collection for perennial Medicago plant introductions. Crop Sci 35:1163–1168

    Article  Google Scholar 

  • Bhattacharjee R, Khairwal IS, Bramel PJ, Reddy KN (2007) Establishment of a pearl millet [Pennisetum glaucum (L.) R. Br.] core collection based on geographical distribution and quantitative traits. Euphytica 155:35–45

    Article  Google Scholar 

  • Bisht IS, Mahajan RK, Patel DP (1998) The use of characterisation data to establish the Indian mung bean core collection and assessment of genetic diversity. Genet Resour Crop Evol 45:127–133

    Article  Google Scholar 

  • Carpio DPD, Basnet RK, Vos RCHD, Maliepaard C, Visser R, Bonnema G (2011) The patterns of population differentiation in a Brassica rapa core collection. Theor Appl Genet 122:1105–1118

    Article  Google Scholar 

  • Chauhan JS, Singh KH, Singh VV, Satyanshu K (2011) Hundred years of rapeseed-mustard breeding in India: accomplishments and future strategies. Indian J Agric Sci 81(12):1093–1109

    Google Scholar 

  • Chen S, Wan Z, Nelson MN, Chauhan JS, Redden R, Burton WA, Lin P, Salisbury PA, Fu T, Cowling WA (2013) Evidence from Genome-wide simple sequence repeat markers for a polyphyletic origin and secondary centers of genetic diversity of Brassica juncea in China and India. J Hered 104(3):416–427

    Article  CAS  Google Scholar 

  • Chen R, Hara T, Ohsawa R, Yoshioka Y (2017) Analysis of genetic diversity of rapeseed genetic resources in Japan and core collection construction. Breed Sci 67:239–247

    Article  Google Scholar 

  • De Beukelaer H, Davenport GF (2018) Corehunter: multi-purpose core subset selection. R package version 3.2.1. https://CRAN.R-project.org/package=corehunter

  • De Beukelaer H, Davenport GF, Fack V (2018) Core Hunter 3: flexible core subset Selection. BMC Bioinform 19:203. https://doi.org/10.1186/s12859-018-2209-z

    Article  Google Scholar 

  • Diwan N, McIntosh MS, Bauchan GR (1995) Methods of developing a core collection of annual Medicago species. Theor Appl Genet 90:755–761

    Article  CAS  Google Scholar 

  • Dutta M, Phogat BS, Kumar S, Kumar N, Kumari J, Pandey AC, Singh TP, Tyagi RK, Jacob SR, Srinivasan K, Bisht IS, Karale M, Yadav M, Sharma P, Kumari G, Aftab T, Rathi YS, Singh AK, Archak S, Bhat KV, Bhandari DC, Solanki YPS, Singh D, Bansal KC (2015) Development of core set of wheat (Triticum spp) germplasm conserved in the National Genebank in India. In: Ogihara Y, Takumi S, Handa H (eds) Advances in wheat genetics: from genome to field. Springer, Tokyo

    Google Scholar 

  • Federer WT (1956) Augmented (or hoonuiaku) designs Hawaiian Planters Record. Honolulu 55:191–208

    Google Scholar 

  • Frankel OH (1984) Genetic perspectives of germplasm conservation. In: Arber W, Illmensee K, Peacock JW, Starlinger P (eds) Genetic manipulation: impact on man and society. Cambridge: University Press, Cambridge, pp 161–170. http://hdl.handle.net/102.100/281332?index=1

  • Gouesnard B, Bataillon TM, Decoux G, Rozale C, Schoen DJ, David JL (2001) MSTRAT: an algorithm for building germplasm core collections by maximizing allelic or phenotypic richness. J Hered 92:93–94

    Article  CAS  Google Scholar 

  • Gower JC (1971) A general coefficient of similarity and some of its properties. J C Gower Biometrics 27(4):857–871

    Article  Google Scholar 

  • Hu J, Zhu J, Xu H (2000) Methods of constructing core collections by stepwise clustering with three sampling strategies based on the genotypic values of crops. Theor Appl Genet 101:264–268. https://doi.org/10.1007/s001220051478

    Article  CAS  Google Scholar 

  • Jain A, Bhatia S, Banga SS, Prakash S, Lakshmikumaran M (1994) Potential use of Random Amplified Polymorphic DNA (RAPD) technique to study the genetic diversity in Indian mustard (Brassica juncea) and its relationship to heterosis. Theor Appl Genet 88:116–122

    Article  CAS  Google Scholar 

  • Jeong S, Kim JY, Jeong SC, Kang ST, Moon JK, Kim N (2017) Geno Core: a simple and fast algorithm for core subset selection from large genotype datasets. PLoS ONE 12(7):e0181420. https://doi.org/10.1371/journal.pone.0181420

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Keuls M (1952) The use of the ‘“Studentized range”’ in connection with an analysis of variance. Euphytica 1:112–122

    Article  Google Scholar 

  • Kim KW, Chung HK, Cho GT, Ma KH, Chandrabalan D, Gwag JG, Kim TS, Cho EG, Park YJ (2007) PowerCore: a program applying the advanced M strategy with a heuristic search for establishing core sets. Bioinformatics 23(16):515–526

    Article  Google Scholar 

  • Krishnan RR, Sumathy R, Ramesh S, Bindroo B, Naik GV (2014) SimEli: similarity elimination method for sampling distant entries in development of core collections. Crop Sci 54(3):1070–1078

    Article  Google Scholar 

  • Kumar S, Ambreen H, Variath MT, Rao AR, Agarwal M, Kumar A, Goel S, Jagannath A (2016) Utilization of molecular, phenotypic, and geographical diversity to develop compact composite core collection in the oilseed crop, safflower (Carthamus tinctorius L.) through maximization strategy. Front Plant Sci 7:1554. https://doi.org/10.3389/fpls.2016.01554

    Article  PubMed  PubMed Central  Google Scholar 

  • Levene H (1960) Robust tests for equality of variances. In: Olkin I (ed) Contributions to probability and statistics: essays in honor of Harold Hotelling. Stanford University Press, Stanford, pp 278–292

    Google Scholar 

  • Li RG, Zhu L, Wu NF, Fan YL, Wu XM, Qian XZ (1997) Genetic diversity among oilseed cultivars of B. juncea (L.) Czern. & Coss in China. J Biotechnol 5:26–31

    CAS  Google Scholar 

  • Nanjundan J, Singh K, Singh KH, Singh D (2014) Catalogue on rapeseed-mustard germplasm. ICAR-Directorate of Rapeseed- Mustard Research, Bharatpur, Rajasthan, India, p180

    Google Scholar 

  • Newman D (1939) The distribution of range in samples from a normal population expressed in terms of an independent estimate of standard deviation. Biometrika 31:20–30

    Article  Google Scholar 

  • Odong TL, van Heerwaarden J, Jansen J, van Hintum TJL, van Eeuwijk FA (2011) Statistical techniques for defining reference sets of accessions and microsatellite markers. Crop Sci 51(6):2401–2411

    Article  Google Scholar 

  • Odong TL, Jansen J, van Eeuwijk FA, van Hintum TJL (2013) Quality of core collections for effective utilisation of genetic resources review, discussion and interpretation. Theor Appl Genet 126(2):289–305

    Article  CAS  Google Scholar 

  • Ortiz R, Ruia-Tapia E, Mijica-Sanchez A (1998) Sampling strategy for a core collection of Peruvian Quinoa germplasm. Theor Appl Genet 96:475–483

    Article  CAS  Google Scholar 

  • Park JH, Suresh S, Raveendar S, Baek HJ, Kim CK, Lee S, Cho GT, Ma KH, Lee CW, Chung JW (2015) Development and evaluation of core collection using qualitative and quantitative trait descriptor in sesame (Sesamum indicum L.) germplasm. Korean J Crop Sci. https://doi.org/10.7740/kjcs.2014.60.1

    Article  Google Scholar 

  • Perseguini JMKC, Silva GMB, Rosa JRBF, Gazaffi R, Marçal JF, Carbonell SAM, Chiorato AF, Zucchi MI, Garcia AAF, Benchimol-Reis LL (2015) Developing a common bean core collection suitable for association mapping studies. Genet Mol Biol 38(1):67–78

    Article  Google Scholar 

  • PPV&FRA (2009) Guidelines for the conduct of test for distinctiveness, uniformity and stability on Indian mustard and Karan rai. Plant Variety J India 3(10): 191–202

  • R Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/

  • Radhamani J, Singh R, Kalyani S, Tyagi RK (2013) Conservation of triat-specific germplasm of Brassica in Natonal Genebank. National Bureau of Plant Genetic Resources, New Delhi, India, p 114

    Google Scholar 

  • Reddy LJ, Upadhyaya HD, Gowda CLL, Singh S (2005) Development of core collection in pigeonpea [Cajanus cajan (L.) Millspaugh] using geographic and qualitative descriptors. Genet Resour Crop Evol 52:1049–1056

    Article  Google Scholar 

  • Reeves PA, Panella LW, Richards CM (2012) Retention of agronomically important variation in germplasm core collections: implications for allele mining. Theor Appl Genet 124(6):1155–71

    Article  Google Scholar 

  • Rodiño AP, Santalla M, de Ron AM, Singh SP (2003) A core collection of common bean from the Iberian peninsula. Euphytica 131:165–175

    Article  Google Scholar 

  • Schafleitner R, Nair RM, Rathore A, Wang YW, Lin CY, Chu SH, Lin PY, Chang JC, Ebert AW (2015) The AVRDC: The World Vegetable Center mung bean (Vigna radiata) core and mini core collections. BMC Genomics 16:344. https://doi.org/10.1186/s12864-015-1556-7

    Article  PubMed  PubMed Central  Google Scholar 

  • Schoen DJ, Brown AHD (1993) Conservation of allelic richness in wild crop relatives is aided by assessment of genetic markers. Proc Natl Acad Sci USA 38:10623–10627

    Article  Google Scholar 

  • Shannon CE (1948) A mathematical theory of communication. Bell Sys Tech J 27(3):379–423

    Article  Google Scholar 

  • Sharma D, Nanjundan J, Singh Lal, Singh SP, Parmar Nehanjali, Sujith Kumar MS, Singh KH, Mishra AK, Singh R, Verma KS, Thakur AK (2020) Genetic diversity in leafy mustard (Brassica juncea var. rugosa) as revealed by agro-morphological traits and SSR markers. Physiol Mol Biol Plants. https://doi.org/10.1007/s12298-020-00883-2

    Article  PubMed  PubMed Central  Google Scholar 

  • Srivastava A, Gupta V, Pental D, Pradhan AK (2001) AFLP-based genetic diversity assessment amongst agronomically important natural and some newly synthesized lines of Brassica juncea. Theor Appl Genet 102:193–199

    Article  CAS  Google Scholar 

  • Tai P, Miller JD (2000) A core collection for Saccharum spontaneum L. from the world collection of sugarcane. Crop Sci 41(3):879–885

    Article  Google Scholar 

  • Thachuk C, Crossa J, Franco J, Dreisigacker S, Warburton M, Davenport GF (2009) Core Hunter: an algorithm for sampling genetic resources based on multiple genetic measures. BMC Bioinform. https://doi.org/10.1186/1471-2105-10-243

    Article  Google Scholar 

  • Upadhyaya HD (2003) Development of a groundnut core collection using taxonomical, geographical and morphological descriptors. Genet Resour Crop Evol 50:139–148

    Article  CAS  Google Scholar 

  • Upadhyaya HD, Gowda CLL, Pundir RPS, Reddy VP, Singh S (2006) Development of core subset of finger millet germplasm using geographical origin and data on 14 quantitative traits. Genet Resour Crop Evol 53:679–685

    Article  Google Scholar 

  • Upadhyaya HD, Dwivedi SL, Singh SK, Singh S, Vetriventhan M, Sharma S (2014) Forming core collections in Barnyard, Kodo, and Little Millets using morpho-agronomic descriptors. Crop Sci 54:2673–2682

    Article  Google Scholar 

  • Upadhyaya HD, Reddy KN, Ahmed MI, Gowda CLL, Reddy TM, Ramachandran S (2015) Identification of Gaps in Pigeon pea Germplasm from East and Southern Africa Conserved at the ICRISAT Genebank. Indian J Plant Genetic Res 28(2):180–188

    Article  Google Scholar 

  • USDA (2021) World agriculture production. Foreign Agriculture Service, Office of Global analysis, IPA division, United States Department of Agriculture, Circular series, WAP 5-21, p 39

  • Vavilov NI (1951) The origin, variation, immunity and breeding of cultivated plants (Translated by Chestitee SK). Chronica Bot 13:1–366. https://doi.org/10.2134/agronj1952.00021962004400020016x

    Article  Google Scholar 

  • Villegas JR, Khoury C, Jarvis A, Debouck DG, Guarino L (2010) A gap analysis methodology for collecting crop gene pools: a case study with phaseolus beans. PLoS ONE 5(10):e13497. https://doi.org/10.1371/journal.pone.0013497

    Article  CAS  Google Scholar 

  • Wang JC, Hu J, Xu HM, Zhang S (2007) A strategy on constructing core collections by least distance stepwise sampling. Theor Appl Genet 115:1–8

    Article  CAS  Google Scholar 

  • Wilcoxon F (1945) Individual comparisons by ranking methods. Biom Bull 1:80–83

    Article  Google Scholar 

  • Zhang H, Bai R, Wu F, Guo W, Yan Z, Yan Q, Zhang Y, Ma J, Zhang J (2019) Genetic diversity, phylogenetic structure and development of core collections in Melilotus accessions from a Chinese gene bank. Sci Rep 9:13017. https://doi.org/10.1038/s41598-019-49355-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The first and corresponding author highly thankful to all the three Directors of ICAR-DRMR, Bharatpur, Rajasthan-321 303, India, at the helm during the study period, for resource facilitation; all the 12 Project Assistants for data curation; and ICAR, New Delhi, India, for funding under Consortia Research Project on Agro-biodiversity (CRP-AB).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joghee Nanjundan.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

10722_2021_1211_MOESM1_ESM.xlsx

The list of Indian mustard entries included in the core set along with the detailed passport data (country and state of origin, biological status etc.) are included in this manuscript as a supplementary information file. (XLSX 47 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nanjundan, J., Aravind, J., Radhamani, J. et al. Development of Indian mustard [Brassica juncea (L.) Czern.] core collection based on agro-morphological traits. Genet Resour Crop Evol 69, 145–162 (2022). https://doi.org/10.1007/s10722-021-01211-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10722-021-01211-7

Keywords

Navigation