NEW MULTIVARIATE EMPIRICAL PREDICTION EQUATION FOR RELATIVE FEED VALUE OF NATIVE GRASSES


Celiktas N., Can E., Kaya S., Atis I., Hatipoglu R., Ertekin I.

APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH, cilt.18, ss.5049-5063, 2020 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 18 Konu: 4
  • Basım Tarihi: 2020
  • Doi Numarası: 10.15666/aeer/1804_50495063
  • Dergi Adı: APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH
  • Sayfa Sayıları: ss.5049-5063

Özet

Relative feed value and structural mineral differentiation of native grasses and their relationships at different plant growth stages were studied to create a more informative multivariate model to predict relative feed value. The hierarchical clustering grouped the species and their growth stages under six distinct categories with their average relative feed values of 122.6, 108.6, 99.6, 90.3, 80.9 and 71.5. The principal component analyses for the relative feed value and the mineral composition of native grasses was efficient to classify the forages with the total explained variation of 63.69% with the first two principal components. The most important predictors for relative feed value were determined as nitrogen and potassium contents of the native grasses according to beta coefficients from the partial least square regression analyses. Three partial least square regression based new empirical equations for predicting the relative feed value were constructed by using the forage nitrogen content. The coefficients of determination (R-2) and the root mean square error of prediction (RMSEP) for the equations were 0.92, 0.35, 0.81 and 2.17, 11.29, 5.88, respectively. The Fisher's F test manifested that the actual and the predicted relative feed values were not different (P>0.05) for all three equations.