Near-infrared spectroscopy (NIRS) was used to predict the nutritive value of
forage species available to the critically endangered northern hairy-nosed
wombat (Lasiorhinus krefftii). Nutritive attributes of
the forage successfully estimated included total nitrogen concentration, fibre
(including neutral detergent fibre, acid detergent fibre and acid lignin),
organic matter, water soluble carbohydrates and in vitro
dry matter digestibility. The reported results demonstrate the seasonal
variability of the forage resource available to
L. krefftii in its tropical savanna habitat.
Multivariate modelling of the spectra enabled the nutritive value of forage
samples to be estimated with coefficients of determination
(r2) of 0.770–0.995 and
standard errors of the cross-validation of 0.070–2.850 using a modified
partial least-squares analysis technique. The standard error of the laboratory
was 0.02–1.42. This study demonstrates that broad-based NIRS predictive
equations can be used to predict the nutritive value of a number of plant
types available to a herbivore over time. By using NIRS the analyst can
rapidly analyse large numbers of samples with limited reduction of precision,
thereby enabling large-scale ecological applications that may have previously
been impeded by time and costs.
Retraction: Water-soluble multidentate polymers compactly coating Ag2S quantum dots with minimized hydrodynamic size and bright emission tunable from red to second near-infrared region
