Application of Fourier transform infrared spectroscopy (FTIR) techniques in the mid-IR (MIR) and near-IR (NIR) spectroscopy to determine n-alkane and long-chain alcohol contents in plant species and faecal samples

n-Alkanes and long-chain alcohols (LCOH) have been used as faecal markers to assess the feeding behaviour of both wild and domestic herbivore species. However, their chemical analysis is time-consuming and expensive, making it necessary to develop more expeditious methodologies to evaluate concentrations of these markers. This work aimed to evaluate the use of Fourier Transform Infrared Spectroscopy (FTIR) technology in the near infrared (NIR) and mid infrared (MIR) intervals, for the determination of n-alkane and LCOH concentrations of different plant species and faecal samples of domestic herbivores. Spectra of 33 feed samples, namely L. perenne, T. repens, U. gallii, short heathers (mixture of Erica spp. and Calluna vulgaris), improved pasture grasses (mixture of L. perenne and A. capillaris), heath grasses (mixture of P. longifolium and A. curtissii), improved pasture species (mixture of L. perenne, T. repens and A. capillaris) and herbaceous species (mixture of all herbaceous species found in the plot)) and 181 faecal samples (cattle and horses) were recorded. In order to develop calibrations for the prediction of n-alkanes and LCOH concentrations, partial least squares (PLS) regression was used. Regarding the models developed for plant species, the best results were observed for the calibrations using NIR. The best external validation coefficients of determination (R²v) obtained were 0.90 and 0.79 for LCOH and n-alkanes, respectively. For faecal samples, in the NIR interval, results indicate similar external validation predictions (R²v) for both animal species (0.64). On the contrary, in the MIR interval, differences between cattle (0.70) and horses (0.57) faecal samples in R²v were observed. Regarding the models created for both animal species faeces, LCOH (C₂₆-OH and C₃₀-OH concentrations ranging from 713.3 to 4451.9 mg/kg DM, respectively; R²v values ranging from 0.72 to 0.95) and n-alkanes (C31 and C33 concentrations ranging from 112.8 to 643.2 mg/kg DM, respectively; R²v values ranging from 0.19 to 0.90) present in higher concentrations tended to be those with better estimates. Results obtained suggest that the selection of the technique to be used may depend on the type of matrix, being the homogeneity of the matrices one of the most important factors for its success. In order to improve the accuracy and robustness of the models created for the estimation of the concentrations of these markers using these methodologies, the database (greater variability) used for the calibrations of these models must be increased.

Prediction of Lignin Content in Ruminant Diets and Fecal Samples Using Rapid Analytical Techniques

The measurement of lignin content in ruminant diet and fecal samples is important for digestibility studies, but it is typically time-consuming and costly. The work reported involves correlation of traditional wet chemistry data with those from three rapid instrumental techniques, Fourier transform infrared spectroscopy (FTIR), conventional thermogravimteric analysis (TGA), and high-resolution TGA (MaxRes TGA) to predict the lignin content of diets and feces from digestibility trials. Calibration and performance data indicate that the FTIR model is acceptable for screening, while the conventional and MaxRes TGA predictions are high accuracy for quantitative analysis. Cross validation and model performance data reveal that MaxRes TGA provides the best-performing predictive model. This work shows that MaxRes TGA can accurately predict lignin content in ruminant diet and fecal samples with distinct advantages over traditional wet chemistry: namely, the requirement of small sample size, ease of sample preparation, speed of analysis, and high sample throughput at considerably lower cost.