Exploring Grain Trait Diversity and Yield Stability in Bread Wheat through Multi Environment Evaluation and Multivariate Statistical Tools
Meda Alekya
Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, India.
Abhijeet Mudhale *
Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, India.
D SiriNandini
Division of Seed Science and Technology, ICAR- Indian Agricultural Research Institute, New Delhi, India.
Kagita Navya
Division of Seed Science and Technology, ICAR- Indian Agricultural Research Institute, New Delhi, India.
Poonam Sharma
Department of Genetics and Plant Breeding, Chaudhary Sarwan Kumar Himachal Pradesh Krishi Vishvavidyalaya, HP, India.
Uma Bharati
Department of Genetics and Plant Breeding, Chaudhary Sarwan Kumar Himachal Pradesh Krishi Vishvavidyalaya, HP, India.
R Vishal
Division of Vegetable Science, ICAR- Indian Agricultural Research Institute, New Delhi, India.
Jyoti Mishra
Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, India.
*Author to whom correspondence should be addressed.
Abstract
Bread wheat (Triticum aestivum L.) underpins global food security, yet its productivity is challenged by variable sowing environments. To identify stable, high-yielding genotypes with desirable grain morphology, 49 advanced breeding lines were evaluated under early and timely sowing across two years at ICAR-IARI, New Delhi. Digital imaging quantified grain morphometric traits, and yield was recorded across environments. Combined ANOVA revealed significant genotype, environment, and genotype × environment effects for all traits, confirming substantial variability. Correlation analysis showed that grain area, perimeter, breadth, equivalent diameter, and median width were positively associated with yield, while roundness was negatively correlated. Principal component analysis (PCA) explained 69.8% of total variation, with yield clustering with grain size traits. Hierarchical clustering grouped genotypes into three clusters, with Cluster II combining bold grain morphology and superior yield. Trait wise rankings highlighted elite lines such as G12, G6, G25, G28, and G29, while unique contributors like G43, G17, and G40 added diversity for extreme morphology and grain colour. These findings demonstrate the potential of advanced breeding lines as donors for both productivity and quality improvement, offering valuable resources for wheat breeding under climate-challenged production systems.
Keywords: Bread wheat, grain morphology, genotype × environment interaction, principal component analysis, hierarchical clustering