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Morpho-physiological traits and SSR markers-based analysis of relationships and genetic diversity among fodder maize landraces in India

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Abstract

Background

Maize is an excellent fodder crop due to its high biomass, better palatability, succulency, and nutrition. Studies on morpho-physiological and biochemical characterization of fodder maize are limited. The present study aimed to explore the genetic variation in fodder maize landraces for various morpho-physiological traits and estimation of genetic relationship and population structure.

Methods and results

The study on 47 fodder maize landraces revealed significant variation for all morpho-physiological traits except leaf-stem ratio. Plant height, stem girth, leaf-width and number of leaves showed positive correlation with green fodder yield. Morpho-physiological traits-based clustering grouped the landraces into three major clusters, whereas neighbour joining cluster and population structure analysis using 40 SSR markers revealed four and five major groups, respectively. Most landraces of Northern Himalaya-Kashmir and Ludhiana fall into a single group, whereas rest groups mainly had landraces from North-Eastern Himalaya. A total of 101 alleles were generated with mean polymorphic information content value of 0.36 and major allele frequency of 0.68. The pair wise genetic dissimilarity between genotypes ranged from 0.21 to 0.67. Mantel test revealed weak but significant correlation between morphological and molecular distance. Biochemical characterisation of superior landraces revealed significant variation for neutral detergent fibre, acid detergent fibre, cellulose and lignin content.

Conclusion

Interestingly, significant, and positive correlation of SPAD with lignin content can be explored to bypass the costly affair of invitro quality assessment for digestibility parameters. The study identified superior landraces and demonstrated the use of molecular markers in genetic diversity assessment and grouping of genotypes for fodder maize improvement.

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Data Availability

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.

References

  1. Food and Agriculture Organization of the United Nations. FAOSTAT Database. Crops and Livestock Products (2022) Available online: https://www.fao.org/faostat/en/#data/QCL (accessed on 12 Sept 2022)

  2. Choudhary M, Singh A, Gupta M, Rakshit S (2020a) Enabling technologies for utilization of maize as a bioenergy feedstock. Biofuels Bioprod Biorefin 14(2):402–416

    CAS  Google Scholar 

  3. Choudhary M, Kumar P, Kaswan S, Jat SL (2020b) Harnessing the tillering ability of Zea mays ssp. parviglumis in fodder maize breeding. Indian J Agric Sci 90(12):2317–2312

    CAS  Google Scholar 

  4. Chaudhary DP, Jat SL, Kumar R, Kumar A, Kumar B (2014) Fodder quality of maize: its preservation. Maize: Nutrition Dynamics and Novel uses. Springer, New Delhi, pp 153–160

    Google Scholar 

  5. Erenstein O, Blu¨mmel M, Grings E (2013) Potential for dual-purpose maize varieties to meet changing maize demands: overview. Field Crops Res 153:1–4

    Google Scholar 

  6. Sharma L, Prasanna BM, Ramesh B (2010) Phenotypic and microsatellite-based diversity and population genetic structure of maize landraces in India, especially from the North-East Himalayan region. Genetica 138:619–631

    CAS  PubMed  Google Scholar 

  7. Choudhary M, Singh V, Muthusamy V, Wani S (2017) Harnessing crop wild relatives for crop improvement. Int J Life Sci 6:73

    Google Scholar 

  8. Ertiro BT, Twumasi-Afriyie S, Blu¨mmel M, Friesen D, Negera D, Worku M, Abakemal D, Kitenge K (2013) Genetic variability of maize stover quality and the potential for genetic improvement of fodder value. Field Crops Res 153:79–85

    Google Scholar 

  9. Anil L, Park J, Phipps RH (2000) The potential of forage–maize intercrops in ruminant nutrition. Anim Feed Sci Technol 86(3–4):157–164

    Google Scholar 

  10. Saiyad MM, Kumar S (2018) Evaluation of maize genotypes for fodder quality traits and SSR diversity. J Plant Biochem Biotechnol 27(1):78–89

    Google Scholar 

  11. Hartings H, Berardo N, Mazzinelli GF, Valoti P, Verderio A, MottoM (2008) Assessment of genetic diversity and relationships among maize italian landraces by morphological traits and AFLP profiling. Theor Appl Genet 117(2):831–842

    CAS  PubMed  Google Scholar 

  12. Choudhary, M., Hossain, F., Muthusamy, V., Thirunavukkarasu, N., Saha, S., Pandey,N., … Gupta, H. S. (2016). Microsatellite marker-based genetic diversity analyses of novel maize inbreds possessing rare allele of β-carotene hydroxylase (crtRB1) for their utilization in β-carotene enrichment. Journal of Plant Biochemistry and Biotechnology 25(1): 12–20

  13. Litt M, Luty JA (1989) A hypervariable microsatellite revealed by in vitro amplification of a dinucleotide repeat within the cardiac muscle actin gene. Am J Hum Genet 44(3):397

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Kumar B, Choudhary M, Kumar P, Kumar K, Kumar S, Singh BK, Lahkar C, Meenakshi, Kumar P, Dar ZA, Devlash R, Hooda KS, Guleria SK, Rakshit S (2022) Population structure analysis and Association Mapping for Turcicum Leaf Blight Resistance in Tropical Maize using SSR markers. Genes (Basel) 13(4):618

    CAS  PubMed  Google Scholar 

  15. Kumar A, Kumari J, Rana JC, Chaudhary DP, Kumar R, Singh H, Singh TP, Dutta M (2015) Diversity among maize landraces in NorthWest Himalayan region of India assessed by agro-morphological and quality traits. Indian J Genet 75(2):188–195

    Google Scholar 

  16. McKee GW (1964) A coefficient for computing leaf area in hybrid corn. Agron J 56:240–241

    Google Scholar 

  17. AOAC (2005) Official methods of analysis, 18th edn. Association of Official Analytical Chemists, Virginia, USA

    Google Scholar 

  18. Van Soest PJ, Robertson JB, Lewis BA (1991) Method for dietary fibre, neutral detergent fibre and non-starch polysaccharides in relation to animal nutrition. J Dairy Sci 74:3588–3597

    Google Scholar 

  19. Rebourg C, Gouesnard B, Charcosset A (2001) Large scale molecular analysis of traditional european maize populations. Relationships with morphological variation. Heredity 86(5):574–587

    CAS  PubMed  Google Scholar 

  20. Doyle JJ, Doyle JL (1990) A rapid total DNA preparation procedure for fresh plant tissue. Focus 12:13–15

    Google Scholar 

  21. Liu K, Muse SV (2005) Power marker: integrated analysis environment for genetic marker data. Bioinformatics 21:2128–2129

    CAS  PubMed  Google Scholar 

  22. Rohlf FJ (2000) NTSYS-pc: Numerical Taxonomy and Multivariate Analysis System, Version 2.2. Exeter Software. Setauket, New York

    Google Scholar 

  23. Peakall ROD, Smouse PE (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes 6(1):288–295

    Google Scholar 

  24. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155(2):945–959

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Suwarno WB, Pixley KV, Palacios-Rojas N, Kaeppler SM, Babu R (2014) Formation of heterotic groups and understanding genetic effects in a provitamin a biofortified maize breeding program. Crop Sci 54(1):14–24

    Google Scholar 

  26. Arau´jo KG, Villela SDJ, Leone FP, Costa MP, Fernandes LO, Tamy WP, Andrade VR (2012) Yield and quality of silage of maize hybrids. R Bras Zootec 41:1539–1544

    Google Scholar 

  27. Zampaligré N, Yoda G, Delma J, Sanfo A, Balehegn M, Rios E, Dubeux JC, Boote K, Adesogan AT (2022) Fodder biomass, nutritive value, and grain yield of dual-purpose improved cereal crops in Burkina Faso. Agron J 114(1):115–125

    Google Scholar 

  28. Ali Q, Saeed MA, Qasrani A, Ramzan I, Malook S, Sher A, ShakoorA, Mubarik MK (2015) Genetic variability and correlation analysis for various morpho-physiological traits in maize (Zea mays L.) for green fodder yield. Am Eur J Agric Environ Sci 15:1298–1303

    Google Scholar 

  29. Kapoor R, Batra C (2015) Genetic variability and association studies in maize for green fodder yield and quality traits. Elect J Plant Breed 6:233–240

    Google Scholar 

  30. Zaidi PH, Vinayan MT, Blu¨mmel M (2013) Genetic variability of tropical maize stover quality and the potential for genetic improvement of food-feed value in India. Field Crops Res 153:94–101

    Google Scholar 

  31. Reddy YR, Ravi D, Reddy CR, Prasad KVSV, Zaidi PH, Vinayan MT, Blu¨mmel M (2013) A note on the correlations between maize grain and maize stover quantitative and qualitative traits and the implications for whole maize plant optimization. Field Crops Res 153:63–69

    Google Scholar 

  32. Kara SM, Deveci M, Dede O, Sekeroglu N (1999) The effects of different plant densities and nitrogen levels on forage yield and some attributes in silage corn III. In Field Crops Congress in Turkey, Adana, vol. 3, pp. 172–177

  33. Parmathama M, Balasubhramania M (1986) Correlation and path analysis in forage maize (Zea mays L). Madras Agric J 73:6–10

    Google Scholar 

  34. Richards RA (2000) Selectable traits to increase crop photosynthesis and yield of grain crops. J Exp Bot 51:447–458

    CAS  PubMed  Google Scholar 

  35. Thakur N, Prakash J, Thakur K, Sharma JK, Kumari R, Rana M, Lata S (2017) Genetic diversity and structure of maize accessions of north-western Himalayas based on morphological and molecular markers. Proc Natl Acad Sci India Sect B: Biol Sci 87(4):1385–1398

    Google Scholar 

  36. Lynch M, Walsh B (1998) Genetics and Analysis of quantitative traits. Sinauer Associates, Sunderland, MA

    Google Scholar 

  37. Yu¨cel C, Hizli H, Firincioglu HK, Cil A, Anlarsal AE (2009) Forage yield stability of common vetch (Vicia sativa L.) genotypes in the Cukurova and GAP regions of Turkey. Turk J Agric For 33:119–125

    Google Scholar 

  38. Iptas S, Acar AA (2006) Effects of hybrid and row spacing on maize forage yield and quality. Plant Soil and Environment 52(11):515

    Google Scholar 

  39. Vinayan MT, Babu T, Jyothsna T, Zaidi PH, Blu¨mmel M (2013) A note on potential candidate genomic regions with implications for maize stover fodder quality. Field Crops Res 153:102–106

    Google Scholar 

  40. Simili, F. F., Barbosa, K. R. S., Augusto, J. G., Menegatto, L. S., Mendonça, G. G.,Bonacim, P. M., … Savegnago, R. P. (2019). Study of the chemical composition of Urochloa brizantha using the SPAD index, neural networks, multiple linear models, principal components and cluster analysis. Animal Feed Science and Technology 258:114307

  41. Hoxha S, Shariflou MR, Sharp P (2004) Evaluation of genetic diversity in albanian maize using SSR marker. Maydica 49:97–103

    Google Scholar 

  42. Wasala SK, Prasanna BM (2013) Microsatellite marker-based diversity and population genetic analysis of selected lowland and mid-altitude maize landrace accessions of India. J Plant Biochem Biotechnol 22(4):392–400

    CAS  Google Scholar 

  43. Legesse BW, Myburg AA, Pixley KV, Twumasi S, Botha AM (2007) Genetic diversity of african maize inbred lines revealed by SSR markers. Hereditas 144:7–10

    Google Scholar 

  44. Frankham R, Ballou JD, Briscoe DA (2002) Introduction to Conservation Genetics. Cambridge University Press, Cambridge

    Google Scholar 

  45. Luo, Z., Brock, J., Dyer, J. M., Kutchan, T., Schachtman, D., Augustin, M., … Abdel-Haleem,H. (2019). Genetic diversity and population structure of a Camelina sativa spring panel. Frontiers in Plant Science 10:184

  46. Wright S (1965) The interpretation of population structure by F-statistics with special regard to systems of mating. Evolution 19(3):395–420

    Google Scholar 

  47. Eltaher S, Sallam A, Belamkar V, Emara HA, Nower AA, Salem KFM et al (2018) Genetic diversity and population structure of F3:6 Nebraska winter wheat genotypes using genotyping-by-sequencing. Front Genet 9:76

    PubMed  PubMed Central  Google Scholar 

  48. Akinwale RO, Badu-Apraku B, Fakorede MAB, Vroh I (2014) Heterotic grouping of tropical early-maturing maize inbred lines based on combining ability in Striga-infested and Striga-free environments and the use of SSR markers for genotyping. Field Crops Res 156:48–62

    Google Scholar 

  49. Cömertpay G, Baloch FS, Kilian B, Ülger AC, Özkan H (2012) Diversity assessment of turkish maize landraces based on fluorescent labelled SSR markers. Plant Mol Biology Report 30(2):261–274

    Google Scholar 

  50. Gunjaca, J., Buhinicek, I., Jukic, M., Sarcevic, H., Vragolovic, A., Kozic, Z., …Pejic, I. (2008). Discriminating maize inbred lines using molecular and DUS data.Euphytica 161(1), 165–172

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Acknowledgements

The authors are most grateful to ICAR for financial support. The contribution of Dr. JP Tyagi and Dr. Zahoor Ahmad Dar for shared maize landraces is sincerely acknowledged.

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MC and PK designed the experiments. MC, AS, MMD and PK performed the experiments. RN, BK, and VS performed a part of experiments. MC and PK analyzed the data. MC, PK, AS, VS, BK and SR wrote the manuscript. All authors contributed to the article and approved the submitted version.

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Correspondence to Pardeep Kumar.

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The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. None of the authors have any non-financial conflict of interest, as well as no financial conflict.

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Choudhary, M., Singh, A., Das, M. et al. Morpho-physiological traits and SSR markers-based analysis of relationships and genetic diversity among fodder maize landraces in India. Mol Biol Rep 50, 6829–6841 (2023). https://doi.org/10.1007/s11033-023-08602-2

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