Fiber is essential for rumen health, microbial fermentation, and the energy supply of herbivores. Even though the study of fecal fiber contents (neutral detergent fiber NDF, acid detergent fiber ADF, and acid detergent lignin ADL) using near-infrared reflectance spectroscopy (NIRS) has allowed investigating nutritional ecology of different herbivore species, NIRS calibrations are species-specific and require a large number of samples for predictions. A multispecies calibration would be an advantage since samples from different herbivores could be used to calibrate a model capable of predicting the fecal fiber content of other herbivores. To date, however, multispecies models have not been developed to predict fiber contents in the feces of herbivores. Here, we fill this gap by calibrating three fiber multispecies models (NDF, ADF and ADL) using fecal samples from domestic and wild herbivore species. We also evaluated the effect of incorporating sodium sulfite in fiber determination protocol. The initial dataset consisting of 445 samples of six herbivore species was used to calibrate (80% of the samples) and validate (20% of the samples) the models. Subsequently, 63 samples of five herbivores not included in the calibration set were used for the external validation of the model. Since sodium sulfite did not significantly improve fecal fiber prediction, our model was developed without this compound. The multispecies models obtained were highly accurate determining NDF, ADF and ADL (R2CAL, coefficient of determination in calibration, ≥ 0.93, R2VAL, coefficient of determination in validation, ≥ 0.91) and independent of external confounders. For external validation, the accuracy in predicting fecal samples in other herbivore species was also satisfactory, with consistently better values for NDF (R2VAL, 0.86-0.94) and ADF (R2VAL, 0.80-0.95) than for ADL (R2VAL, 0.66-0.89). We show that multispecies NIRS calibrations can be used with high accuracy to assess fecal fiber contents across diverse herbivore species. This finding represents a significant advance in the study of the nutritional ecology of herbivores with contrasting foraging patterns. In the future, widening the data range (e.g., species and locations) of the initial dataset could further improve the accuracy of these models.
Copyright: © 2025 Rossa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.