Pesquisa Agropecuária Brasileira (Feb 2022)

Sample size for principal component analysis in corn

  • Alberto Cargnelutti Filho,
  • Marcos Toebe

DOI
https://doi.org/10.1590/s1678-3921.pab2021.v56.02510
Journal volume & issue
Vol. 56

Abstract

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Abstract The objective of this work was to determine the number of plants required to estimate the eigenvalues of the principal components analysis in corn (Zea mays) traits. Twelve traits were measured in 361, 373, and 416 plants of single-, three-way, and double-cross hybrids, respectively, in the 2008/2009 crop year; and in 1,777, 1,693, and 1,720 plants of single-, three-way, and double-cross hybrids, respectively, in the 2009/2010 crop year (six cases), totaling 6,340 plants. Principal component analysis was performed for the six cases. Sample size (number of plants) for the eigenvalue estimations of the principal components was determined by resampling with replacement and application of the model linear response and plateau model. The measurement of 267 plants is sufficient to estimate the eigenvalues of the principal components in corn traits.

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