Loading...

Genetic Diversity Analysis in Maize Landraces under Temperate Ecology

DOI: 10.18805/ag.D-5490    | Article Id: D-5490 | Page : 541-547
Citation :- Genetic Diversity Analysis in Maize Landraces under Temperate Ecology.Agricultural Science Digest.2022.(42):541-547
Latif Ahmad Peer, Zahoor A. Dar, Aijaz A. Lone, Mohd. Yaqub Bhat peerlatif@gmail.com
Address : Department of Botany, University of Kashmir, Srinagar-190 006, Jammu and Kashmir, India.
Submitted Date : 20-09-2021
Accepted Date : 1-02-2022

Abstract

Background: Though modern high yielding and synthetics developed through maize heterosis are replacing low-yielding maize populations worldwide, it has shown little impact in Kashmir due to poor adaptability and expensive seed cost. Nevertheless, retaining popularity due to adaptability, more resistance to natural factors, early maturity, good grain quality, great food and fodder value and ability to thrive best under low input conditions, landraces are going out of farmer’s domain and becoming extinct owing to low yielding potential, low resilience to some biotic stresses and lower sensitivity to inputs. For developing high yielding, climate-resilient cultivars and broadening of the genetic base, efficient and rapid identification and introgression of novel and favourable alleles dispersed among the landraces are necessary. 
Methods: Seventy maize landraces from different parts of Kashmir valley designated as K-L1 to K-L70 were subjected to genetic analysis for thirteen important agronomic traits viz. days to 50% tasselling, days to 50% silking, anthesis-silking interval, plant height, ear height, days to maturity, ear diameter, kernel rows per ear, kernels per row, prolificacy, shelling percentage, yield per hectare and 100-grain weight. The least significance increase was calculated to evaluate best performing landraces and clustering of landraces was done using Mahalanobis D2 analysis through Tocher’s method. The experimentation was carried out at Dryland Agriculture Research Station Budgam during the years 2019 and 2020.
Result: Significant differences for all agronomic traits except anthesis-silking interval and prolificacy depicted the presence of significant genetic variability. The least significant increase calculations allowed the evaluation of best-performing landraces for specific traits and  Mahalanobis D2 analysis through Tocher’s method led to clustering landraces into 14 clusters with cluster I having the highest 23, followed by cluster VI with 14, cluster II and cluster III each with 9, cluster VIII with 6 genotypes and rest 9 clusters being mono-genotypic. Intra and inter-clustering distance and cluster means suggest utilizing genotypes belonging to clusters with wider statistical distances for crossing in hybridization programme to produce segregates with extensive variation resulting in higher heterosis.

Keywords

Agronomic traits Cluster analysis Genetic diversity Zea mays L.

References

  1. Azad, M.A.K., Biswas, B.K., Alam, N. and Alam, S.S. (2012). Genetic diversity in maize (Zea mays L.) inbred lines. The Agriculturists. 10(1): 64-70.
  2. Federer, W.T. (1956). Augmented (or hoonuiaku) designs. Hawaiian Planters’ Record. 55: 191-208.
  3. Hemavathy, T.A., Balaji, K., Ibrahim, S.M., Anand, G. and Deepa, S. (2008). Genetic variability and correlation studies in maize (Zea mays L.). Agriculture Science Digest. 28(2): 112-114. 
  4. Iqbal, J., Shinwari, Z.K. and Rabbani, M.A. (2015). Maize (Zea mays L.) germplasm agro-morphological characterization based on descriptive, cluster and principal component analysis. Pakistan Journal of Botany. 47: 255-264.
  5. Kumar, V., Singh, P.K. and Gupta, A. (2011). Studies of genetic diversity in quality protein maize (Zea mays L.) inbreds. Current Advances in Agricultural Sciences. 3(2): 96-99.
  6. Kumari, A., Sweta, S., Kumari, R., Mandal, S. and Sanjay, S. (2018). Genetic diversity analysis in maize (Zea mays L.) using SSR markers. Journal of Pharmacognosy and Phytochemistry. 1116-1120.
  7. Kumari, J., Kumar, A., Singh, T. P., Bhatt, K. C., Mishra, A.K., Semwal, D. P., et al., (2017). Collection, evaluation and phenotypic diversity assessment of maize (Zea mays) germplasm from North Eastern Himalayan region. Indian Journal of Agricultural Sciences. 87(6): 727-733.
  8. Magar, B. T., Acharya, S., Gyawali, B., Timilsena, K., Upadhayaya, J. and Shrestha, J. (2021). Genetic variability and traits association in maize (Zea mays L.) varieties for growth and yield traits. Heliyon. e07939.
  9. Marker, S. and Krupakar, A. (2009). Genetic divergence in exotic maize germplasm (Zea mays L.). Journal of Agricultural and Biological Science. 4(4): 44-47.
  10. McLean-Rodríguez, F.D., Costich, D.E., Camacho-Villa, T.C., Pè, M.E. and Dell’Acqua, M. (2021). Genetic diversity and selection signatures in maize landraces compared across 50 years of in situ and ex situ conservation. Heredity. 126(6): 913-928. 
  11. McLean-Rodríguez, F.D., Camacho-Villa, T.C., Almekinders, C.J.M., Pè, M.E., Dell’Acqua, M. and Costich, D.E. (2019). The abandonment of maize landraces over the last 50 years in Morelos, Mexico: a tracing study using a multi-level perspective. Agriculture and Human Values. 36(4): 651- 668.
  12. Oppong, O., Bedoya, C.A., Ewool, M.B., Asante, M.D., Thompson, R.N., Dapaah, H.A., Lamptey, J.N. L., Ofori, K., Offei, S.K. and Warburton, M.L. (2014). Bulk genetic characterization of Ghanaian maize landraces using microsatellite markers. Maydica. 59: 1-8.
  13. Panwar, V.S. and Ram, J. (1970). Interspecific divergence in rice (Oriza sativa L.). Indian Journal of Genetics. 30: 1-2. 
  14. Prasanna, B.M. and Sharma, L. (2005). The landraces of maize (Zea mays L): diversity and utility. Indian Journal of Plant Genetic Resources. 18: 155-168.
  15. Ranawat, A., Singh, S.K., R., Bhati, P.K. and Sharma, A. (2013). Morphological diversity analysis in QPM and non-QPM maize (Zea mays L.) genotypes. Journal of Crop and Weed. 9(2): 32-35. 
  16. Ranatunga, M., Meenakshisundaram, P., Arumugachamy, S. and Maheswaran, M. (2009). Genetic diversity analysis of maize (Zea mays L.) inbreds determined with morphometric traits and simple sequence repeat markers. Maydica. 54(1): 113.
  17. Rao, C.R. (1952). Advanced Statistical Methods in Biometrical Research. John Wiley and Sons, New York. pp 390.
  18. Sachan, K.S. and Sharma, J.R. (1971). Multivariate analysis of divergence in tomato. Indian Journal of Genetics. 31: 86-93. 
  19. Sharma, L., Prasanna, B. and Ramesh, B. (2010). Analysis of phenotypic and microsatellite-based diversity of maize landraces in India, especially from the North East Himalayan region. Genetica. 138: 619-631. 
  20. Shiferaw, B., Prasanna, B.M., Hellin, J. and Banziger, M. (2011). Crops that feed the world 6, past successes and future challenges to the role played by maize in global food security. Food Security. 3:307-327.
  21. Shrestha, J. (2016). Cluster analysis of maize inbred lines. Journal of Nepal Agricultural Research Council. 2: 33-36.

Global Footprints