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<p>Identifying physiological traits that respond to stress is a challenge in plant biotechnology, given the complexity of salinity and water-deficit effects. This study evaluated the usefulness of Principal Component Analysis (PCA) to highlight the most relevant indicators in sugarcane and pineapple cultured in temporary immersion bioreactors (TIBs). Secondary data from previous experiments were used, including shoot multiplication rate, fresh biomass, and biochemical profiles (aldehydes, chlorophylls, carotenoids, and phenolics). PCA reduced dataset dimensionality and emphasized the variables with the greatest contribution to experimental variance, namely soluble phenolics, malondialdehyde, other aldehydes, and cell wall-linked phenolics. These findings confirmed that PCA is a valuable tool to guide breeding programs toward the selection of stress-resilient genotypes.</p>

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Phenolic and aldehyde responses of sugarcane and pineapple to sodium chloride and mannitol stress revealed by Principal Component Analysis

  • 期刊论文

  • 发表日期：

    2026年3月31日

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  • Julio César Quintana-Zaez,
  • Alberto Lozada,
  • Daviel Gómez,
  • Yanier Acosta,
  • María de Lourdes Tapia y Figueroa,
  • Sershen,
  • José Carlos Lorenzo

摘要

Identifying physiological traits that respond to stress is a challenge in plant biotechnology, given the complexity of salinity and water-deficit effects. This study evaluated the usefulness of Principal Component Analysis (PCA) to highlight the most relevant indicators in sugarcane and pineapple cultured in temporary immersion bioreactors (TIBs). Secondary data from previous experiments were used, including shoot multiplication rate, fresh biomass, and biochemical profiles (aldehydes, chlorophylls, carotenoids, and phenolics). PCA reduced dataset dimensionality and emphasized the variables with the greatest contribution to experimental variance, namely soluble phenolics, malondialdehyde, other aldehydes, and cell wall-linked phenolics. These findings confirmed that PCA is a valuable tool to guide breeding programs toward the selection of stress-resilient genotypes.