Future Prospects and Challenges

  • Roland SchafleitnerEmail author
  • Ramakrishnan M. Nair
Part of the Compendium of Plant Genomes book series (CPG)


Legume crops play a key role for producing proteins for human and animal nutrition. Sustainable increase of plant protein production is essential to satisfy the rising demand of a growing world population. Breeding varieties with high and stable yields and with optimized nutritional value, which at the same time require less input in terms of energy and labor is one of the pathways for sustainable rise of mungbean productivity. Mungbean is mainly used in rotation with cereals. Therefore, producing an economically viable harvest in the short time window between two main crops, often under stressful conditions of a hot and dry season, is an important breeding aim for this crop. Breeding improved varieties requires access to the genetic diversity of the crop and crop wild relatives to source new traits. As natural plant populations are endangered by loss of habitats and climate change, ex situ collections have gained increased importance to conserve biodiversity for crop improvement. Effective screening methods for desired agronomical traits, including biotic and abiotic stress tolerances and pre-breeding technologies to introgress new traits from non-adapted materials into elite lines are facilitating breeding efforts. Often new traits have to be sourced from wild relatives. Crossing barriers between different Vigna species and the need of technologies to restore fertility add additional complexity when traits have to be sourced from wild species. Genomics methods such as quantitative trait mapping or pangenomics studies elucidate the genetic basis of traits of interest, and marker assisted or genomic selection are guiding breeding efforts. Well-coordinated phenotyping efforts to collect and analyze crop performance data across multiple locations are essential for effective breeding of a more productive, nutritious and resilient mungbean crop.


Mungbean Crop biodiversity Wild relatives Stress tolerance Genomics-assisted breeding 


  1. Ahmad M, Zahir ZA, Asghar HN, Arshad M (2012) The combined application of rhizobial strains and plant growth promoting rhizobacteria improves growth and productivity of mung bean (Vigna radiata L.) under salt-stressed conditions. Ann Microbiol 62(3):1321–1330CrossRefGoogle Scholar
  2. Alexandratos N, Bruinsma J (2012) World agriculture towards 2030/2050: the 2012 revision. ESA working paper. FAO, RomeGoogle Scholar
  3. Barkley NA, Wang ML, Gillaspie AG, Dean RE, Pederson GA, Jenkins TM (2008) Discovering and verifying DNA polymorphisms in a mung bean [V. radiata (L.) R. Wilczek] collection by EcoTILLING and sequencing. BMC Res Notes 1:28. Scholar
  4. Bayer PE, Ruperao P, Mason AS, Stiller J, Chan CK, Hayashi S et al (2015) High-resolution skim genotyping by sequencing reveals the distribution of crossovers and gene conversions in Cicer arietinum and Brassica napus. Theor Appl Genet 128:1039–1048. Scholar
  5. Bisht IS, Mahajan RK, Patel DP (1998) The use of characterisation data to establish the Indian mungbean core collection and assessment of genetic diversity. Genet Resour Crop Ev 45:127–133CrossRefGoogle Scholar
  6. Bushby H, Lawn R (1992) Accumulation and partitioning of nitrogen and dry matter by contrasting genotypes of mungbean (Vigna radiata (L.) Wilczek). Aust J Agric Res 43:1609–1628CrossRefGoogle Scholar
  7. Carberry P, Muchow R, Williams R, Sturtz J, McCown R (1992) A simulation model of kenaf for assisting fibre industry planning in northern Australia. I. General introduction and phenological model. Aust J Agric Res 43:1501–1513CrossRefGoogle Scholar
  8. Chauhan Y, Williams R (2018) Physiological and agronomic strategies to increase mungbean yield in climatically variable environments of Northern Australia. Agronomy 8(6):83CrossRefGoogle Scholar
  9. Chauhan Y, Rachaputi RC (2014) Defining agro-ecological regions for field crops in variable target production environments: a case study on mungbean in the northern grains region of Australia. Agric Forest Meteorol 194:207–217CrossRefGoogle Scholar
  10. Chen J, Somta P, Chen X, Cui X, Yuan X, Srinives P (2016) Gene mapping of a mutant mungbean (Vigna radiata L.) using new molecular markers suggests a gene encoding a yuc4-like protein regulates the chasmogamous flower trait. Front plant Sci 7:830PubMedPubMedCentralGoogle Scholar
  11. Chhabra KS, Kooner BS (1985) Problem of flower shedding caused by thrips, Megalurothrips distalis (Karny), on summer mungbean, Vigna radiata (L.) Wilczek, and its control. Int J Pest Manag 31(3):186–188Google Scholar
  12. Cook DE, Lee TG, Guo X, Melito S, Wang K, Bayless AM, Wang J et al (2012) Copy number variation of multiple genes at Rhg1 mediates nematode resistance in soybean. Science 338:1206–1209PubMedCrossRefGoogle Scholar
  13. Crossa J, Pérez-Rodríguez P, Cuevas J, Montesinos-López O, Jarquín D, de los Campos G, Burgueño J, González-Camacho JM, Pérez-Elizalde S, Beyene Y, Dreisigacker S (2017) Genomic selection in plant breeding: methods, models, and perspectives. Trends Plant Sci 22(11):961–975PubMedCrossRefGoogle Scholar
  14. Dıaz A, Zikhali M, Turner AS, Isaac P, Laurie DA (2012) Copy number variation affecting the photoperiod-B1 and vernalization-A1 genes is associated with altered flowering time in wheat (Triticum aestivum). PLoS ONE 7:e33234PubMedPubMedCentralCrossRefGoogle Scholar
  15. Eshed Y, Zamir D (1995) An introgression line population of Lycopersicon pennellii in the cultivated tomato enables the identification and fine mapping of yield-associated QTL. Genetics 141(3):1147–1162PubMedPubMedCentralGoogle Scholar
  16. Golicz AA, Bayer PE, Edwards D (2015) Skim-based genotyping by sequencing. InPlant genotyping. Humana Press, New York, NY, pp 257–270Google Scholar
  17. Hamid A, Agata W, Kawamitsu Y (1990) Photosynthesis, transpiration and water use efficiency in four cultivars of mungbean, Vigna radiata (L.) Wilczek. Photosynthetica 24(1):96–101Google Scholar
  18. Hanumantha Rao B, Nair RM, Nayyar H (2016) Salinity and high temperature tolerance in mungbean [Vigna radiata (L.) Wilczek] from a physiological perspective. Front Plant Sci 7:957Google Scholar
  19. Heffner EL, Sorrells ME, Jannink JL (2009) Genomic selection for crop improvement. Crop Sci 49(1):1–2CrossRefGoogle Scholar
  20. Hirsch CN, Foerster JM, Johnson JM, Sekhon RS, Muttoni G, Vaillancourt B, Peñagaricano F, Lindquist E, Pedraza MA, Barry K, de Leon N (2014) Insights into the maize pan-genome and pan-transcriptome. Plant Cell 26:121–135PubMedPubMedCentralCrossRefGoogle Scholar
  21. Kang YJ, Kim SK, Kim MY, Lestari P, Kim KH, Ha BK, Jun TH, Hwang WJ, Lee T, Lee J, Shim S (2014) Genome sequence of mungbean and insights into evolution within Vigna species. Nat Commun 5(5443):6443Google Scholar
  22. Kayani AK, Qureshi S, Kayani WK, Qureshi R, Waheed A, Arshad M, Gulfraz M, Laghai MK (2010) Assessment of wheat yield potential after cropping mungbean (Vigna radiata (L.) Wilczek). Pak J Bot 42(3):1535–1541Google Scholar
  23. Khan S, Goyal S (2009) Mutation genetic studies in mungbean IV. Selection of early maturing mutants. Thai J Agri Sci 42(2):109–113Google Scholar
  24. Khattak GS, Ashraf M, Elahi T, Abbas G (2003) Selection for large seed size at the seedling stage in mungbean (Vigna radiata (L.) Wilczek). Breed Sci 53(2):141–143CrossRefGoogle Scholar
  25. Kitamura K, Ishimoto M, Sawa M (1988) Inheritance of resistance to infestation with azuki bean weevil in Vigna sublobata and successful incorporation to V. radiata. Japanese J Breed 38(4):459–464CrossRefGoogle Scholar
  26. Lam HM, Xu X, Liu X, Chen WB, Yang GH, Wong FL, Li MW et al (2010) Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic diversity and selection. Nat Genet 42:1053–1059PubMedCrossRefGoogle Scholar
  27. Latati M, Bargaz A, Belarbi B, Lazali M, Benlahrech S, Tellah S (2016) The intercropping common bean with maize improves the rhizobial efficiency, resource use and grain yield under low phosphorus availability. Eur J Agron 72:80–90CrossRefGoogle Scholar
  28. Lee YS, Lee JY, Kim DK, Yoon CY, Bak GC, Park IJ, Bang GP, Moon JK, Oh YJ, Min KS (2004) A new high-yielding mungbean cultivar, “Samgang” with lobed leaflet. Kor Breed J 36:183–184Google Scholar
  29. Li Y-H, Zhou G, Ma J, Jiang W, Jin L-G, Zhang Z et al (2014) De novo assembly of soybean wild relatives for pan-genome analysis of diversity and agronomic traits. Nat Biotech 32:1045–1052CrossRefGoogle Scholar
  30. Liu C, Wang S, Wang L, Sun L, Mei L, Xu N, Cheng X (2008) Establishment of candidate core collection in Chinese mungbean germplasm resources. Acta Agron Sin 34:700CrossRefGoogle Scholar
  31. Liu MS, Kuo TC, Ko CY, Wu DC, Li KY, Lin WJ, Lin CP, Wang YW, Schafleitner R, Lo HF, Chen CY (2016) Genomic and transcriptomic comparison of nucleotide variations for insights into bruchid resistance of mungbean (Vigna radiata [L.] R. Wilczek). BMC Plant Biol 16(1):46PubMedPubMedCentralCrossRefGoogle Scholar
  32. Lorenc MT, Hayashi S, Stiller J, Lee H, Manoli S, Ruperao P, Visendi P, Berkman PJ, Lai K, Batley J, Edwards D (2012) Discovery of single nucleotide polymorphisms in complex genomes using SGSautoSNP. Biology 1(2):370–382PubMedPubMedCentralCrossRefGoogle Scholar
  33. Mariyammal I, Seram D, Samyuktha SM, Karthikeyan A, Dhasarathan M, Murukarthick J, Kennedy JS, Malarvizhi D, Yang TJ, Pandiyan M, Senthil N (2019) QTL mapping in Vigna radiata × Vigna umbellata population uncovers major genomic regions associated with bruchid resistance. Mol Breed 39:110CrossRefGoogle Scholar
  34. McMullen MD, Kresovich S, Villeda HS, Bradbury P, Li H, Sun Q, Flint-Garcia S, Thornsberry J, Acharya C, Bottoms C, Brown P (2009) Genetic properties of the maize nested association mapping population. Science 325(5941):737–740PubMedCrossRefGoogle Scholar
  35. Michelmore RW, Paran I, Kesseli RV (1991) Identification of markers linked to disease-resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions by using segregating populations. Proc Natl Acad Sci USA 88(21):9828–9832PubMedCrossRefGoogle Scholar
  36. Moe KT, Gwag JG, Park YJ (2012) Efficiency of PowerCore in core set development using amplified fragment length polymorphic markers in mungbean. Plant Breed 131:110–117CrossRefGoogle Scholar
  37. Nair RM, Yang RY, Easdown WJ, Thavarajah D, Thavarajah P, Hughes JD, Keatinge JD (2013) Biofortification of mungbean (Vigna radiata) as a whole food to enhance human health. J Sci Food Agri 93(8):1805–1813CrossRefGoogle Scholar
  38. Nakhlawy FS, Ismail SM, Basahi JM (2018) Optimizing mungbean productivity and irrigation water use efficiency through the use of low water-consumption during plant growth stages. Legume Res. Scholar
  39. Noble TJ, Tao Y, Mace ES, Williams B, Jordan DR, Douglas CA, Mundree SG (2018) Characterization of linkage disequilibrium and population structure in a mungbean diversity panel. Front Plant Sci 8:2102PubMedPubMedCentralCrossRefGoogle Scholar
  40. Pandiyan M, Senthil N, Ramamoorthi N, Muthiah AR, Tomooka N, Duncan V, Jayaraj T (2010) Interspecific hybridization of Vigna radiata x 13 wild Vigna species for developing MYMV donor. Elect J Plant Breed 1(4):600–610Google Scholar
  41. Pannu RK, Singh DP (1993) Effect of irrigation on water use, water-use efficiency, growth and yield of mungbean. Field Crops Res 31(1–2):87–100CrossRefGoogle Scholar
  42. Pascual L, Desplat N, Huang BE, Desgroux A, Bruguier L, Bouchet JP, Le QH, Chauchard B, Verschave P, Causse M (2015) Potential of a tomato MAGIC population to decipher the genetic control of quantitative traits and detect causal variants in the resequencing era. Plant Biotech J 13(4):565–577CrossRefGoogle Scholar
  43. Pestsova EG, Börner A, Röder MS (2001) Development of a set of Triticum aestivum-Aegilops tauschii introgression lines. Hereditas 135(2–3):139–143PubMedPubMedCentralGoogle Scholar
  44. Ramanujam S, Tiwari AS, Mehra RB (1974) Genetic divergence and hybrid performance in mung bean. Theor App Genet 45(5):211–214CrossRefGoogle Scholar
  45. Rang FJ, Kloosterman WP, de Ridder J (2018) From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy. Genome Biol 19(1):90PubMedPubMedCentralCrossRefGoogle Scholar
  46. Rashid A, Harris D, Hollington PA, Rafiq M (2004) Improving the yield of mungbean (Vigna radiata) in the North West Frontier Province of Pakistan using on-farm seed priming. Exp Agri 40(2):233–244CrossRefGoogle Scholar
  47. Robertson MJ, Fukai S, Peoples MB (2004) The effect of timing and severity of water deficit on growth, development, yield accumulation and nitrogen fixation of mungbean. Field Crops Res 86:67–80CrossRefGoogle Scholar
  48. Salunkhe DK, Kadam SS, Chavan JK (1985) Post-harvest biotechnology of food legumes. CRC Press, Boca Raton, FL, p 160Google Scholar
  49. Saxena KB, Sameer Kumar CV, Saxena RK, Vijay Kumar R, Singh IP, Hingane AJ, Mula MG, Patil SB, Varshney RK (2016) Hybrid pigeonpea: accomplishments and challenges for the next decade. Legume Persp 11:30–32Google Scholar
  50. 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 mungbean (Vigna radiata) core and mini core collections. BMC Genom 16(1):344CrossRefGoogle Scholar
  51. Singh VK, Khan AW, Jaganathan D, Thudi M, Roorkiwal M, Takagi H, Garg V, Kumar V, Chitikineni A, Gaur PM, Sutton T (2016) QTL-seq for rapid identification of candidate genes for 100-seed weight and root/total plant dry weight ratio under rainfed conditions in chickpea. Plant Biotech J14(11):2110–2119CrossRefGoogle Scholar
  52. Singh D, Singh B (2011) Breeding for tolerance to abiotic stresses in mungbean. J Food Legumes 24:83–90Google Scholar
  53. Sorajjapinun W, Srinives P (2011) Chasmogamous mutant, a novel character enabling commercial hybrid seed production in mungbean. Euphytica 181:217–222CrossRefGoogle Scholar
  54. Srivastava AC, Pal M, Das M, Sengupta UK (2001) Growth, CO2 exchange rate and dry matter partitioning in mungbean (Vigna radiata L.) grown under elevated CO2. Indian J Exp Bio 39:572–577Google Scholar
  55. Stagnari F, Maggio A, Galieni A, Pisante M (2017) Multiple benefits of legumes for agriculture sustainability: an overview. Chem Biol Tech Agri 4(1):2CrossRefGoogle Scholar
  56. Summerfield R, Lawn R (1987) Environmental modulation of flowering in mung bean (Vigna radiata): a reappraisal. Exp Agric 23:461–470CrossRefGoogle Scholar
  57. Takagi H, Abe A, Yoshida K, Kosugi S, Natsume S, Mitsuoka C, Uemura A, Utsushi H, Tamiru M, Takuno S, Innan H, Cano LM, Kamoun S, Terauchi R (2013) QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations. Plant J 74:174–183PubMedCrossRefGoogle Scholar
  58. Varshney RK, Pandey MK, Bohra A, Singh VK, Thudi M, Saxena RK (2018) Toward the sequence-based breeding in legumes in the post-genome sequencing era. Theor App Genet. Scholar
  59. Vinuesa P, Ochoa-Sánchez LE, Contreras-Moreira B (2018) GET_PHYLOMARKERS, a software package to select optimal orthologous clusters for phylogenomics and inferring pan-genome phylogenies, used for a critical geno-taxonomic revision of the genus Stenotrophomonas. Front Microbiol 9:771. Scholar
  60. Yang HL, Le DO, Hui WA, Liu CL, Fang LI, Xie CX (2018) A simple way to visualize detailed phylogenetic tree of huge genome-wide SNP data constructed by SNPhylo. J Integ Agri 17(9):1972–1978CrossRefGoogle Scholar
  61. Zekic T, Holley G, Stoye J (2018) Pan-genome storage and analysis techniques. Comparative genomics. Humana Press, New York, NY, pp 29–53CrossRefGoogle Scholar
  62. Zhao Q, Feng Q, Lu H, Li Y, Wang A, Tian Q, Zhan Q, Lu Y, Zhang L, Huang T, Wang Y (2018) Pan-genome analysis highlights the extent of genomic variation in cultivated and wild rice. Nat Genet 50(2):278PubMedCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.The World Vegetable CenterShanhua, TainanTaiwan
  2. 2.World Vegetable Center, South Asia, ICRISAT CampusPatancheru, HyderabadIndia

Personalised recommendations