Use of n-alkanes to estimate feed intake in ruminants: a meta-analysis

Influence of Cuticular Waxes from Triticale on Rumen Fermentation: A Metabolomic and Microbiome Profiling Study

Cuticular wax, a critical defense layer for plants, remains a relatively unexplored factor in rumen fermentation. We investigated the impact of cuticular wax on rumen fermentation using triticale as a model. In total, six wax classes were identified, including fatty acids, aldehydes, alkane, primary alcohol, alkyresorcinol, and β-diketone, with low-bloom lines predominated by 46.05% of primary alcohols and high-bloom lines by 35.64% of β-diketone. Low-wax addition (2.5 g/kg DM) increased the gas production by 19.25% (P < 0.05) and total volatile fatty acids by 6.34% (P > 0.05), and enriched key carbohydrate-fermenting rumen microbes like Saccharofermentans, Ruminococcus, and Prevotellaceae, when compared to non-wax groups. Metabolites linked to nucleotide metabolism, purine metabolism, and protein/fat digestion in the rumen showed a positive correlation with low-wax, benefiting rumen microbes. This study highlights the intricate interplay among cuticular wax, rumen microbiota, fermentation, and metabolomics in forage digestion, providing insights into livestock nutrition and forage utilization.

Correlation of Ruminal Fermentation Parameters and Rumen Bacterial Community by Comparing Those of the Goat, Sheep, and Cow In Vitro

In this study, we aimed to establish the correlation between ruminal fermentation parameters and the bacterial community by comparing those of the goat, sheep, and cow, thus illustrating the main bacteria causing the difference in rumen fermentation among goats, sheep, and cows and providing a new idea for improving the feed digestibility of ruminants. Rumen fluid from goats (Taihang White cashmere goat, n = 6), sheep (Hu sheep, n = 6), and cows (Holstein cow, n = 6) was collected using oral intubation and immediately brought back to the laboratory for a fermentation test with the same total mixed ration (TMR) feed in vitro. The rumen bacterial composition was measured by high-throughput sequencing of 16S rRNA genes in the MiSeq platform, the gas production (GP) was recorded after 2, 4, 6, 8, 10, 12, 24, 36, and 48 h of fermentation, and the feed nutrient digestibility and the rumen fluid parameters were determined after 48 h of fermentation. The results showed that the 48 h GP of the sheep group was higher than that of the cow group (p < 0.05), and the theoretical maximum GP was higher than that of the goat and cow groups (p < 0.05). The organic matter digestibility (OMD), dry matter digestibility (DMD), crude protein digestibility (CPD), and gross energy digestibility (GED) of the sheep group were higher than those of the goat and cow groups (p < 0.05). The ammonia nitrogen (NH3-N), microbial protein (MCP), and total volatile fatty acids (TVFA) concentrations of the sheep group were higher than those of the other groups (p < 0.05), and the pH of the sheep group was lower than those of the other groups (p < 0.05). The 16S rRNA gene sequencing revealed that bacterial composition also differed in the rumens of the sheep, goat, and cow groups (ANOSIM, p < 0.05). We then used a random forest machine learning algorithm to establish models to predict the fermentation parameters by rumen bacterial composition, and the results showed that rumen bacterial composition could explain most of the ruminal fermentation parameter variation (66.56%, 56.13%, 65.75%, 80.85%, 61.30%, 4.59%, 1.41%, −3.13%, 34.76%, −25.62%, 2.73%, 60.74%, 76.23%, 47.48%, −13.2%, 80.16%, 4.15%, 69.03%, 32.29%, and 89.96% for 48 h GP, a (GP of quickly degraded part), b (GP of slowly degraded part), c (GP rate), a + b (theoretical maximum GP), DMD, OMD, GED, CPD, NDFD, ANDF, pH, NH3-N, MCP, acetic acid, propionic acid, butyric acid, valeric acid, TVFA, and A:P (acetic acid–propionic acid ratio), respectively). A correlation analysis revealed that Lactobacillus, Prevotellaceae_UCG-003, Selenomonas, Peptostreptococcus, and Olsenella significantly correlated with most in vitro fermentation parameters (p < 0.05). A comprehensive analysis showed that rumen fermentation parameters and bacterial composition differed in goats, sheep, and cows. The ruminal fermentation parameters of GP, a, b, c, a + b, pH, NH3-N, propionic acid, valeric acid, and A:P could be accurately predicted by rumen bacteria (explanation > 55% of variation), and the Lactobacillus, Prevotellaceae_UCG-003, Olsenella, Selenomonas, and Peptostreptococcus were the main bacteria that affected the in vitro fermentation parameters of goats, sheep, and cows.

Near Infrared Reflectance Spectroscopy Analysis to Predict Diet Composition of a Mountain Ungulate Species

Simple Summary

Ungulates are characterized by their ability to modify or maintain habitats through their impact on plant species composition and the structure of vegetation. Assessing the diet composition of ungulates is therefore important to understand their role in the ecosystem integrity and to develop monitoring and population management plans. The diet composition of free-ranging ungulates has most often been assessed by time-consuming and cost-intensive approaches such as the direct observation of animals, chemical analysis, molecular approaches or microhistological analysis of fecal samples. Near infrared reflectance spectroscopy analysis would be a quick, economic and non-destructive alternative to assess diet composition using fecal samples. In this work, we evaluated the use of this spectroscopy method to assess the diet composition of the Pyrenean chamois (Rupicapra pyrenaica pyrenaica), a medium-size subalpine ungulate with a broad dietary niche. Our results support the reliability of the fecal spectroscopy analysis to monitor diet composition of free-ranging ungulates.

Abstract

The diet composition of ungulates is important to understand not only their impact on vegetation, but also to understand the consequences of natural and human-driven environmental changes on the foraging behavior of these mammals. In this work, we evaluated the use of near infrared reflectance spectroscopy analysis (NIRS), a quick, economic and non-destructive method, to assess the diet composition of the Pyrenean chamois Rupicapra pyrenaica pyrenaica. Fecal samples (n = 192) were collected from two chamois populations in the French and Spanish Pyrenees. Diet composition was initially assessed by fecal cuticle microhistological analysis (CMA) and categorized into four functional groups, namely: woody, herbaceous, graminoid and Fabaceae plants. Regressions of modified partial least squares and several combinations of scattering correction and derivative treatments were tested. The results showed that models based on the second derivative processing obtained the higher determination coefficient for woody, herbaceous and graminoid plants (R²_CAL, coefficient of determination in calibration, ranged from 0.86 to 0.91). The Fabaceae group, however, was predicted with lower accuracy (R²_CAL = 0.71). Even though an agreement between NIRS and CMA methods was confirmed by a Bland–Altman analysis, confidence limits of agreement differed by up to 25%. Our results support the viability of fecal NIRS analysis to study spatial and temporal variations of the Pyrenean chamois’ diets in summer and winter when differences in the consumption of woody and annual plants are the greatest. This new use for the NIRS technique would be useful to assess the consequences of global change on the feeding behavior of this mountain ungulate and also in other ungulate counterparts.