The objective of this study was to investigate the effects of chitosan (CHI) on ruminal and cecal fermentation and on apparent digestibility in sheep. In a first trial, 4 ruminally fistulated sheep fed an alfalfa hay and concentrate diet formulated to meet 1.2 times their maintenance energy requirements were assigned to 2 treatments [no-additive control (CTR), or 136 mg/kg of BW of CHI] for 19 d in a 2 × 2 crossover design. Samples of ruminal fluid and feces were taken for VFA and NH₃-N concentrations. At the end of each period of the crossover, ruminal fluid was used as inoculum for batch cultures (24 and 96 h), and the effects on rate and extent of gas production and on fermentation variables for starch, cellulose, and the same diet fed to the animals were calculated. In a second trial, 4 sheep fed the alfalfa hay and concentrate diet were assigned to 2 treatments (CTR and CHI), as for the first trial, but this time for 14 d in a 2 × 2 crossover design. Apparent digestibility was studied. In the first trial, in terms of ruminal fermentation, CHI did not affect (P = 0.12) total VFA concentration or acetate proportion, but increased propionate proportion (P = 0.004) and propionate-to-acetate ratio (C3:C2; P = 0.007) and decreased branched-chain VFA (BCVFA) proportion (P = 0.003) and NH₃-N concentration (P = 0.045). In feces, CHI decreased total VFA concentration (P = 0.01) and acetate (P = 0.045) and butyrate (P = 0.025) proportions, and increased propionate (P = 0.04), valerate (P = 0.01), and BCVFA (P = 0.032) proportions and C3:C2 ratio (P = 0.045). In batch cultures, when starch was used as substrate, CHI decreased acetate proportion (P = 0.016) and methane production (P = 0.03) and increased propionate and valerate proportions and C3:C2 ratio (P < 0.001). When cellulose was used as substrate, CHI decreased in vitro OM digestibility (P = 0.033), total VFA concentration, propionate proportion (P < 0.001), C3:C2 ratio (P = 0.006), methane production (P < 0.001), NH₃-N concentration (P = 0.019), and gas production rate (P = 0.002), and increased butyrate (P = 0.029) and BCVFA (P = 0.004) proportions and pH (P < 0.001). When the alfalfa hay and concentrate diet was used as substrate, CHI decreased butyrate (P < 0.001) and BCVFA (P = 0.008) proportions, methane (P = 0.005) and asymptotic gas production (P = 0.02), and gas production rate (P = 0.05). In the second trial, CHI decreased NDF apparent digestibility (P = 0.09). In conclusion, CHI shifted ruminal fermentation toward energetically more efficient routes, without reducing OM apparent digestibility. Copyright © 2010. American Society of Animal Science .

The aim of this trial was to study the agreement between the non-dispersive infrared methane analyzer (NDIR) method and the hand held laser methane detector (LMD). Methane (CH₄) was measured simultaneously with the two devices totaling 164 paired measurements. The repeatability of the CH₄ concentration was greater with the NDIR (0.42) than for the LMD (0.23). However, for the number of peaks, repeatability of the LMD was greater (0.20 vs. 0.14, respectively). Correlation was moderately high and positive for CH₄ concentration (0.73 and 0.74, respectively) and number of peaks (0.72 and 0.72, respectively), and the repeated measures correlation and the individual-level correlation were high (0.98 and 0.94, respectively). A moderate concordance correlation coefficient was observed for the CH₄ concentration (0.62) and for the number of peaks (0.66). A moderate-high coefficient of individual agreement for the CH₄ concentration (0.83) and the number of peaks (0.77) were observed. However, CH₄ concentrations population means and all variance components differed between instruments. In conclusion, methane concentration measurements obtained by means of NDIR and LMD cannot be used interchangeably. The joint use of both methods could be considered for genetic selection purposes or for mitigation strategies only if sources of disagreement, which result in different between-subject and within-subject variabilities, are identified and corrected for.

Records of methane emissions from 1,501 cows on 14 commercial farms in 4 regions of Spain were collected from May 2018 to June 2019. Methane concentrations (MeC) were measured using a nondispersive infrared methane detector installed within the feed bin of the automatic milking system during 14- to 21-d periods. Rumination time (RT; min/d) was collected using collars with a tag that registered time (minutes) spent eating and ruminating. The means of MeC and methane production (MeP) were 1,254.28 ppm and 182.49 g/d, respectively; mean RT was 473.38 min/d. Variance components for MeC, MeP, and RT were estimated with REML using pedigree and genomic information in a single-step model. Heritabilities for MeC and MeP were 0.11 and 0.12, respectively. Rumination time showed a slightly larger heritability estimate (0.17). The genetic correlation between MeP and MeC was high (>0.95), suggesting that selection on either trait would lead to a positive correlated response on the other. Negative correlations were estimated between RT and MeC (-0.24 ± 0.38) and MeP (-0.43 ± 0.35). Methane concentration and MeP had slightly positive correlations with milk yield (0.17 ± 0.39 and 0.21 ± 0.36), protein percentage (0.08 ± 0.32 and 0.30 ± 0.45), protein yield (0.22 ± 0.41 and 0.31 ± 0.35), fat percentage (0.02 ± 0.40 and 0.27 ± 0.36), and fat yield (0.27 ± 0.28 and 0.29 ± 0.28) from bivariate analyses. Rumination time had positive correlations with milk yield (0.41 ± 0.75) and protein yield (0.26 ± 0.57) and negative correlations with fat yield (-0.45 ± 0.32), protein percentage (-0.15 ± 0.38), and fat percentage (-0.40 ± 0.47). A positive approximated genetic correlation was estimated between fertility and MeC (0.10 ± 0.05) and MeP (0.18 ± 0.05), resulting in slightly higher CH4 production when selecting for better fertility [days open estimated breeding values (EBV) are expressed with mean 100 and SD 10, inversely related to days from calving to conception; that is, greater days open EBV implies better fertility]. Positive correlations were also estimated for stature with MeC and MeP (0.30 ± 0.04 and 0.43 ± 0.04, respectively). Other type traits (chest width, udder depth, angularity, and capacity) were positively correlated with methane traits, possibly because of higher milk yield and higher feed intake from these animals. Rumination time showed positive EBV correlations with production traits and type traits, and negative correlations with somatic cell count and body condition score. Based on the genetic correlations and heritabilities estimated in this study, methane is measurable and heritable, and estimates of genetic correlations suggest no strong opposition to current breeding objectives in Spanish Holsteins.

Mitigating the effects of global warming has become the main challenge for humanity in recent decades. Livestock farming contributes to greenhouse gas emissions, with an important output of methane from enteric fermentation processes, mostly in ruminants. Because ruminal microbiota is directly involved in digestive fermentation processes and methane biosynthesis, understanding the ecological relationships between rumen microorganisms and their active metabolic pathways is essential for reducing emissions. This study analysed whole rumen metagenome using long reads and considering its compositional nature in order to disentangle the role of rumen microbes in methane emissions. The β-diversity analyses suggested a subtle association between methane production and overall microbiota composition (0.01 < R² < 0.02). Differential abundance analysis identified 36 genera and 279 KEGGs as significantly associated with methane production (P_adj < 0.05). Those genera associated with high methane production were Eukaryota from Alveolata and Fungi clades, while Bacteria were associated with low methane emissions. The genus-level association network showed 2 clusters grouping Eukaryota and Bacteria, respectively. Regarding microbial gene functions, 41 KEGGs were found to be differentially abundant between low- and high-emission animals and were mainly involved in metabolic pathways. No KEGGs included in the methane metabolism pathway (ko00680) were detected as associated with high methane emissions. The KEGG network showed 3 clusters grouping KEGGs associated with high emissions, low emissions, and not differentially abundant in either. A deeper analysis of the differentially abundant KEGGs revealed that genes related with anaerobic respiration through nitrate degradation were more abundant in low-emission animals. Methane emissions are largely associated with the relative abundance of ciliates and fungi. The role of nitrate electron acceptors can be particularly important because this respiration mechanism directly competes with methanogenesis. Whole metagenome sequencing is necessary to jointly consider the relative abundance of Bacteria, Archaea, and Eukaryota in the statistical analyses. Nutritional and genetic strategies to reduce CH₄ emissions should focus on reducing the relative abundance of Alveolata and Fungi in the rumen. This experiment has generated the largest ONT ruminal metagenomic dataset currently available.