Principal Component Analysis (PCA) is a multivariate analysis that reduces the complexity of datasets while preserving data covariance. The outcome can be visualized on colorful scatterplots, ideally ...
Finger millet productivity is strongly influenced by genotype × environment interaction (GEI), which complicates the identification of high-yielding and stable genotypes. This study evaluated 35 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results