Abstract Species delimitation methods based on macromorphology are often limited by phenotypic plasticity in plants. Fourier Transform near-infrared spectroscopy (FT-NIR) provides a promising alternative as a non-destructive technique that measures molecular vibrations (overtone and combination bands of C–H, N–H, and O–H bonds) from plant tissue exposed to near-infrared light (780–2,500 nm). We applied FT-NIR to the taxonomically challenging Scaly clade of Microgramma ferns (94 samples, eight species), including dimorphic and monomorphic taxa, to evaluate its diagnostic potential. Using multivariate models and cross-validation, we achieved 81–100% average identification accuracy. Well-defined species (e.g., M. percussa ) reached 100% accuracy, while morphologically overlapping taxa showed lower accuracy, likely due to hybridization, introgression, or cryptic variation. Dimorphic species exhibited higher intraspecific spectral variability and lower accuracy linked to differences between fertile/sterile fronds than monomorphic species. FT-NIR proves effective as a complementary tool for fern systematics, elucidating species limits and diversity patterns. Further studies should address how hybridization, introgression, and indumentum affect spectral data.
Mendonça et al. (Mon,) studied this question.