Seasonal changes in the metabolic fingerprint of 21 grass and legume cultivars studied by nuclear magnetic resonance-based metabolomics.

A nuclear magnetic resonance (NMR)-based approach was introduced for metabolic fingerprinting of 21 grass and legume cultivars in the present study. Applying principal component analysis (PCA) on the fingerprints obtained on water extracts, it was possible to elucidate the variation between cultivars and the magnitude of changes in the metabolic fingerprint between the spring growth and the second regrowth. Consequently, the potential of the method for tracking differences and changes related to cultivar and season was demonstrated. In addition, partial least-squares (PLS) regressions revealed correlations between the NMR fingerprints and the value of the grasses as animal feed evaluated as concentration of sugars, neutral detergent fibres (NDF) (R = 0.82), indigestible neutral detergent fibres (iNDF) (R = 0.90), and in vitro organic matter digestibility (IVOMD) (R = 0.75). The correlations between these parameters and the NMR fingerprint could mainly be ascribed to differences in spectral intensities from signals assigned to malic acid (2.40 and 4.70 ppm), choline (3.27 ppm), and glucose (5.24 ppm), and the biochemical rationale for this relation is discussed.