Principal Component Analysis is a statistical technique that reduces the dimensionality of complex datasets by transforming multiple correlated variables into a smaller set of uncorrelated components while retaining most of the original information. Research published in this journal applies this method across diver…
Principal Component Analysis is a statistical technique that reduces the dimensionality of complex datasets by transforming multiple correlated variables into a smaller set of uncorrelated components while retaining most of the original information. Research published in this journal applies this method across diverse fields to identify patterns and relationships within large, multivariable datasets. Studies have employed Principal Component Analysis to assess genetic diversity and morphological traits in agricultural species including chili peppers, cocoyam, sugar beet, and sorghum, enabling researchers to classify genotypes and evaluate stress resistance. The technique has been used to characterize land use dynamics in urban-rural transitions, monitor vineyard clusters through spectroscopic data, and analyze water quality parameters in rivers affected by industrial activity. Applications extend to public health research, where Principal Component Analysis has helped classify disease severity using insurance claims data, examine associations between environmental noise and depression at the municipal level, validate psychological assessment tools in clinical populations, and profile metabolic responses to toxicological exposures. This analytical approach proves valuable when researchers need to simplify complex datasets, reveal underlying structure, and support decision-making across agricultural, environmental, and health sciences.
12 peer-reviewed articles, ranked by relevance. Each links to its DOI.
The 12 articles above have been cited 69 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
A sample of recent works citing this journal's research on Principal Component Analysis, linking to each citing work.