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PCA In Horticulture.pdf

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Preview of PCA in Horticulture
🔗 Source: journals.ashs.org
📊 Size: 168 KB
👤 Author: "Amy F. Iezzoni and Marvin P. Pritts"
⬇️ Downloads: 104

Summary

Horticultural researchers often measure complex traits, which are composites of individual traits that vary together in response to treatments or evolutionary pressures. Principal Component (PC) analysis is a method that identifies patterns in a data set, eliminates redundancy in univariate analyses, and restructures data sets into smaller sets of components. PC analysis transforms data to create new variables and axes that account for more variation in the original data, reducing dimensionality and making patterns easy to visualize and interpret. The analysis involves selecting variables, transforming data, and extracting orthogonal axes that account for variation in the data set. The resulting components may suggest biological meaning and can replace original correlated variables in univariate statistical procedures.

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Horticultural researchers often measure complex traits, which are composites of individual traits that vary together in response to treatments or evolutionary...

Technical Information

  • File Format: PDF
  • File Size: 168 KB
  • Pages: 5
  • Language: EN
  • Author: "Amy F. Iezzoni and Marvin P. Pritts"
  • Total Downloads: 104
  • Last Updated: 1 week ago

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