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The present research proposed to use Principal Components & Classification Analysis (PC&CA) as tool for the polyphenols content monitoring of perennial forages, at the end of May 2008, from a Romanian grassland fertilized since 2003. The grassland soil was Calcic Luvisol. StatSoft – STATISTICA Version 10 performed the matrix correlation of PC&CA. The ten trials unfertilized or with different fertilization were the PC&CA cases. The active variables of PC&CA were the floristic composition components: Poaceae (GMay08%), Fabaceae (FMay08%), others botanical families group (OMay08%), Calamagrostis epigejos (Ce%), Festuca rupicola (Fr%), Lathyrus nissolia (Ln%), Lathyrus pratensis (Lp%), Filipendula vulgaris (Fv%) and Rosa canina (Rc%). Perennial forages polyphenols content at the end of May 2008 and mineral nitrogen fertilization data were supplementary variables. The correlation coefficient for total polyphenols content (PMay08) and others botanical families group (OMay08%) was positive: 0.704. In addition, the correlation coefficients of PMay08 and Fv% or Rc% were positively and higher than 0.700. Mineral nitrogen application influenced positively the Poaceae component (correlation coefficient 0.915). The PC&CA can represent a helpful tool for polyphenols content monitoring of grassland perennial forages at the end of spring, depending on fertilization.

PC&CA - Tool for Polyphenols Content Monitoring at the End of Spring Depending on Organic and/or Mineral Fertilization of Perennial Grassland