13 research outputs found
Predicting herbivore faecal nitrogen using a multispecies near-infrared reflectance spectroscopy calibration
Optimal management of free-ranging herbivores requires the accurate assessment of an animal's nutritional status. For this purpose 'near-infrared reflectance spectroscopy' (NIRS) is very useful, especially when nutritional assessment is done through faecal indicators such as faecal nitrogen (FN). In order to perform an NIRS calibration, the default protocol recommends starting by generating an initial equation based on at least 50-75 samples from the given species. Although this protocol optimises prediction accuracy, it limits the use of NIRS with rare or endangered species where sample sizes are often small. To overcome this limitation we tested a single NIRS equation (i.e., multispecies calibration) to predict FN in herbivores. Firstly, we used five herbivore species with highly contrasting digestive physiologies to build monospecies and multispecies calibrations, namely horse, sheep, Pyrenean chamois, red deer and European rabbit. Secondly, the equation accuracy was evaluated by two procedures using: (1) an external validation with samples from the same species, which were not used in the calibration process; and (2) samples from different ungulate species, specifically Alpine ibex, domestic goat, European mouflon, roe deer and cattle. The multispecies equation was highly accurate in terms of the coefficient of determination for calibration R = 0.98, standard error of validation SECV = 0.10, standard error of external validation SEP = 0.12, ratio of performance to deviation RPD = 5.3, and range error of prediction RER = 28.4. The accuracy of the multispecies equation to predict other herbivore species was also satisfactory (R > 0.86, SEP 2.6, and RER > 8.1). Lastly, the agreement between multi- and monospecies calibrations was also confirmed by the Bland-Altman method. In conclusion, our single multispecies equation can be used as a reliable, cost-effective, easy and powerful analytical method to assess FN in a wide range of herbivore species
Relationships between faecal nitrogen (FN) predicted by NIRS and FN estimated by the Dumas dry combustion method in five herbivorous mammal species.
<p>Relationships between faecal nitrogen (FN) predicted by NIRS and FN estimated by the Dumas dry combustion method in five herbivorous mammal species.</p
Species and sources of faecal samples used in NIRS calibration equations to predict faecal nitrogen.
<p>Species and sources of faecal samples used in NIRS calibration equations to predict faecal nitrogen.</p
NIRS predicted faecal nitrogen contents (% of dry matter) in faecal samples and validation statistics using the multispecies equation.
<p>NIRS predicted faecal nitrogen contents (% of dry matter) in faecal samples and validation statistics using the multispecies equation.</p
Calibration and validation statistics of monospecies and multispecies calibrations used to determine the faecal nitrogen content (%) in faecal samples by NIRS analysis.
<p>Calibration and validation statistics of monospecies and multispecies calibrations used to determine the faecal nitrogen content (%) in faecal samples by NIRS analysis.</p
Bland and Altman plot of the difference between mono- and multispecies NIRS calibrations to predict the faecal nitrogen (FN expressed on a % dry matter basis) in five herbivorous mammal species.
<p>The mean of differences (<i>d</i>) between mono- and multispecies calibration equations are represented by a dotted dark-blue line, whereas limits of agreement (<i>d</i> ± 1.96sd) are represented by dashed lines. Confidence intervals at 95% are shown by shaded areas.</p
Model selection to explore whether the relationships between faecal nitrogen (FN) predicted by NIRS and faecal nitrogen estimated by the Dumas dry combustion method (reference method) varied among species.
<p>Model selection to explore whether the relationships between faecal nitrogen (FN) predicted by NIRS and faecal nitrogen estimated by the Dumas dry combustion method (reference method) varied among species.</p