Deciphering the Multidimensional Trait Space of Yield and Quality Attributes in Oat (Avena sativa L.) Using Multivariate Analysis

This dataset contains phenotypic observations and statistical analyses of 54 oat (Avena sativa L.) germplasm lines including three check varieties evaluated during the 2021–22 and 2022–23 growing seasons at the Experimental Dairy Farm, Nagala, G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India. The experiment was conducted using an augmented block design, where test genotypes were unreplicated and check varieties were replicated six times. Observations were recorded from five randomly selected plants per plot for sixteen quantitative traits including plant height, number of tillers, days to heading, panicle length, green fodder yield, dry matter, grain yield, crude protein, neutral detergent fiber (NDF) and acid detergent fiber (ADF). The dataset also includes pooled data over two years and R scripts used for statistical analyses such as genetic variability estimation, correlation analysis, principal component analysis, and hierarchical clustering. These data support multivariate analysis of yield and quality traits in oat germplasm and can be used for further genetic and breeding research.