Discover Agriculture (Jun 2024)

Performance evaluation and multivariate analysis of maize accessions against drought stress in Lamjung district, Nepal

  • Rashmi Poudel,
  • Bishnu Prasad Kandel,
  • Ankur Poudel,
  • Anubhav Tripathi,
  • Reema Gurung,
  • Unisha Ghimire

DOI
https://doi.org/10.1007/s44279-024-00046-x
Journal volume & issue
Vol. 2, no. 1
pp. 1 – 19

Abstract

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Abstract The selection of drought-tolerant genotypes from the existing gene pool is a preliminary step for breeding for drought tolerance. Research efforts aimed at exploring the ability of crops to withstand drought stress have not yet touched the realm of reproductive drought performance of local genotypes. To examine how local crop accessions demonstrate varying reproductive performance under drought conditions, twenty accessions of maize (Zea mays L.) were evaluated for six quantitative traits in a two-factor factorial completely randomized design with two replications between February to June of 2023. All the traits under study showed significant differences among the genotypes (p < 0.05). Owing to their grain yield, ear weight, and hundred grain weight, accessions NGRC05592, NGRC05582, NGRC05564, NGRC05565, NGRC05571, and NGRC05569 performed better under drought condition than other tested accessions. Accession NGRC05592 showed the highest yield under drought condition, whereas, NGRC05573 and NGRC05576 showed poor performance. GGE Biplot analysis for grain yield revealed that NGRC05571 and NGRC05592 had the highest mean yield, with the accession NGRC05592 standing out as the stable variety under changing soil moisture levels and performing best among all the tested accessions under drought condition. The possibility of accession NGRC05592 being used as a potential genetic resource for drought breeding programs has been observed, but further studies aiming at its stability under field conditions in diverse agro-climatic regions across different years are encouraged to assure its prospect for developing cultivars suited to drought-affected regions.

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