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

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