Discriminant Analysis as a Tool to Classify Grasslands Based on Near-Infrared Spectra.

ABSTRACT: This study aims to classify plant communities by applying discriminant analysis based on principal components (DAPC) on near-infrared spectra (FT-NIRS) starting from fresh herbage samples. Grassland samples (n~156) belonged to (i) recent alfalfa pure crops (CAA), (ii) recent grass-legume mixtures (GLM), (iii) permanent meadows derived from old alfalfa stands that were re-colonized (PMA), and iv) permanent meadows originated from old grass-legume mixtures (PLM). Samples were scanned using FT-NIRS, and a multivariate exploration of the original spectra was performed using DAPC. The following two scenarios were proposed: (i) cross-validation, where all data were used for model training, and (ii) semi-external validation, where the group assignment was performed without samples of the t

SUBMITTER: Parrini S 

PROVIDER: S-EPMC11429457 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature