Identification of high-performing wheat landraces using morphological characterization and multi-trait genotype-ideotype distance index

Anjali Sha; Mukunda Bhattarai; Babu Ram Khanal

doi:10.26832/24566632.2026.1103018

Authors

Anjali Sha
Agriculture and Forestry University, Rampur, Chitwan, Nepal
Mukunda Bhattarai
National Agriculture Genetic Resources Centre, Khumaltar, Lalitpur, Nepal
Babu Ram Khanal
Department of Soil and Agricultural Engineering, Agriculture and Forestry University, Rampur, Chitwan, Nepal

DOI:

https://doi.org/10.26832/24566632.2026.1103018

Keywords:

FAI-BLUP index, MGIDI, Multi-trait selection, Smith Hazel index, Wheat landraces

Abstract

Wheat landraces are an invaluable source of germplasm for developing climate-resilient and high-yielding cultivars. To characterize morphological diversity and select superior wheat landraces using the Multi-Trait Genotype-Ideotype Distance Index (MGIDI) to maximize genetic gain and productivity, 58 wheat landraces from across Nepal were studied in a randomized complete block design for 12 qualitative and 19 quantitative traits at Khumaltar, Nepal. We analyzed quantitative traits using linear mixed models to estimate broad-sense heritability and Best Linear Unbiased Predictors (BLUPs). MGIDI at 15% selection intensity was computed based on the Euclidean distance of each landrace from an ideal ideotype for multi-trait selection, and the results were compared with FAI-BLUP and two Smith-Hazel indices. Significantly high Shannon-Weaver diversity was observed in qualitative traits, guiding selection. Pronounced genotypic differences and high broad-sense heritability (h2 = 0.89-1.00; p<0.001) were observed for most quantitative traits. Factor analysis revealed six factors explaining 80.34% of the total variation. MGIDI successfully identified nine elite landraces with desirable gains, with maximum selection gains obtained for spike length (30.12%) and grain yield (15.57%). MGIDI showed a perfect coincidence index (CI=100%) with FAI-BLUP but substantially lower coincidences with Smith Hazel indices. Four genotypes, G41 (NGRC-7819), G34 (NGRC-7615), G22 (NGRC-6554), and G31 (NGRC-7586), were selected concurrently in the study across all four indices and are recommended for further study. Overall, the findings highlight MGIDI as an effective, reliable, and data-driven approach for selecting and leveraging wheat germplasm to develop climate-resilient varieties to ensure food security.

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