Ranking cows’ methane emissions under commercial conditions with sniffers versus respiration chambers

Host genetics associated with gut microbiota and methane emission in cattle

In livestock sector, dairy animals alone produce 18% of the total greenhouse gas emissions globally as methane (CH₄). This Enteric methane is the largest component of total carbon footprints produced by livestock production system and its reduction is today's new challenge to make livestock farming sustainable for earth's environment. The production of enteric methane in ruminants is a complex phenomena involving different host factors like host genotype, rumen microbiome, host physiology along with dietary factors. Efforts have been made to reduce methane emissions largely through nutritional interventions and dietary supplements, but permanent reductions can be obtained through genetic means by selecting and breeding of low methane emitting animals. From genome-wide association studies, many important genomic QTL regions and single nucleotide polymorphisms involved in shaping the composition of the ruminal microbiome and thus their carbon footprints have been recognised, implying that methane emission traits are quantitative traits. The major bottleneck in implementation of reduced methane emission traits in the breeding programs is wide variation at phenotypic level, lack of precise methane measurements at individual level. Overall, the heritability for CH₄ production traits is moderate, and it can be used in breeding programmes to target changes in microbial composition to reduce CH₄ emission in the dairy industry for far-reaching environmental benefits at the cost of a minor reduction in genetic gain in production traits.

Genetic Variability of Methane Production and Concentration Measured in the Breath of Polish Holstein-Friesian Cattle

The genetic architecture of methane (CH₄) production remains largely unknown. We aimed to estimate its heritability and to perform genome-wide association studies (GWAS) for the identification of candidate genes associated with two phenotypes: CH₄ in parts per million/day (CH₄ ppm/d) and CH₄ in grams/day (CH₄ g/d). We studied 483 Polish Holstein-Friesian cows kept on two commercial farms in Poland. Measurements of CH₄ and carbon dioxide (CO₂) concentrations exhaled by cows during milking were obtained using gas analyzers installed in the automated milking system on the farms. Genomic analyses were performed using a single-step BLUP approach. The percentage of genetic variance explained by SNPs was calculated for each SNP separately and then for the windows of neighbouring SNPs. The heritability of CH₄ ppm/d ranged from 0 to 0.14, with an average of 0.085. The heritability of CH₄ g/d ranged from 0.13 to 0.26, with an average of 0.22. The GWAS detected potential candidate SNPs on BTA 14 which explained ~0.9% of genetic variance for CH₄ ppm/d and ~1% of genetic variance for CH₄ g/d. All identified SNPs were located in the TRPS1 gene. We showed that methane traits are partially controlled by genes; however, the detected SNPs explained only a small part of genetic variation-implying that both CH₄ ppm/d and CH₄ g/d are highly polygenic traits.

Genomic and Phenotypic Agreement Defines the Use of Microwave Dielectric Spectroscopy for Recording Muscle Lipid Content in European Seabass (Dicentrarchus labrax)

Recording the fillet lipid percentage in European seabass is crucial to control lipid deposition as a means toward improving production efficiency and product quality. The reference method for recording lipid content is solvent lipid extraction and is the most accurate and precise method available. However, it is costly, requires sacrificing the fish and grinding the fillet sample which limits the scope of applications, for example grading of fillets, recording live fish or selective breeding of fish with own phenotypes are all limited. We tested a rapid, cost effective and non-destructive handheld microwave dielectric spectrometer (namely the Distell fat meter) against the reference method by recording both methods on 313 European seabass (Dicentrarchus labrax). The total method agreement between the dielectric spectrometer and the reference method was assessed by Lin’s concordance correlation coefficient (CCC), which was low to moderate CCC = 0.36–0.63. We detected a significant underestimation in accuracy of lipid percentage 22–26% by the dielectric spectrometer and increased imprecision resulting in the coefficient of variation (CV) doubling for dielectric spectrometer CV = 40.7–46% as compared to the reference method 27–31%. Substantial genetic variation for fillet lipid percentage was found for both the reference method (h² = 0.59) and dielectric spectroscopy (h² = 0.38–0.58), demonstrating that selective breeding is a promising method for controlling fillet lipid content. Importantly, the genetic correlation (r_g) between the dielectric spectrometer and the reference method was positive and close to unity (r_g = 0.96), demonstrating the dielectric spectrometer captures practically all the genetic variation in the reference method. These findings form the basis of defining the scope of applications and experimental design for using dielectric spectroscopy for recording fillet lipid content in European seabass and validate its use for selective breeding.

Selective breeding as a mitigation tool for methane emissions from dairy cattle

The global livestock sector, particularly ruminants, contributes substantially to the total anthropogenic greenhouse gases. Management and dietary solutions to reduce enteric methane (CH₄) emissions are extensively researched. Animal breeding that exploits natural variation in CH₄ emissions is an additional mitigation solution that is cost-effective, permanent, and cumulative. We quantified the effect of including CH₄ production in the Dutch breeding goal using selection index theory. The current Dutch national index contains 15 traits, related to milk yield, longevity, health, fertility, conformation and feed efficiency. From the literature, we obtained a heritability of 0.21 for enteric CH₄ production, and genetic correlations of 0.4 with milk lactose, protein, fat and DM intake. Correlations between enteric CH₄ production and other traits in the breeding goal were set to zero. When including CH₄ production in the current breeding goal with a zero economic value, CH₄ production increases each year by 1.5 g/d as a correlated response. When extrapolating this, the average daily CH₄ production of 392 g/d in 2018 will increase to 442 g/d in 2050 (+13%). However, expressing the CH₄ production as CH₄ intensity in the same period shows a reduction of 13%. By putting economic weight on CH₄ production in the breeding goal, selective breeding can reduce the CH₄ intensity even by 24% in 2050. This shows that breeding is a valuable contribution to the whole set of mitigation strategies that could be applied in order to achieve the goals for 2050 set by the EU. If the decision is made to implement animal breeding strategies to reduce enteric CH₄ production, and to achieve the expected breeding impact, there needs to be a sufficient reliability of prediction. The only way to achieve that is to have enough animals phenotyped and genotyped. The power calculations offer insights into the difficulties that will be faced in trying to record enough data. Recording CH₄ data on 100 farms (with on average 150 cows each) for at least 2 years is required to achieve the desired reliability of 0.40 for the genomic prediction.

Individual-level correlations of rumen volatile fatty acids with enteric methane emissions for ranking methane yield in sheep fed fresh pasture

Context Total ruminal volatile fatty acids (VFA) or acetate concentrations were previously found to be moderate correlated proxies to select sheep that are genetically low methane (CH4) emitters. However, this was based on trials, with sheep fed lucerne pellets at a fixed feeding level, which is different from pastoral farming conditions in New Zealand, where the correlated proxy would be applied. Aim To determine repeatability and individual-level correlation of rumen VFAs with CH4 emissions in sheep fed ad libitum cut pasture in three and four repeated periods in Experiments 1 and 2 respectively. Sheep in Experiment 1 were also fed lucerne pellets at 2.0 × maintenance-energy requirements in two periods. Methods Methane emissions were measured from 96 and 72 animals, in Experiments 1 and 2 respectively, in respiration chambers and rumen samples were collected via oral stomach tubing before morning feeding. Repeatability estimates between periods within feed and experiment serve as an upper threshold for the estimate of heritability and ri estimates are a proxy for genetic correlation. Key results Methane (g/day) production and yield (g/kg dry-matter intake) were low to moderately repeatable traits on pasture across periods (0.58 and 0.39 for CH4 production and 0.43 and 0.32 for yield in Experiments 1 and 2 respectively). On pasture, repeatability was generally greater for VFA proportions (0.13–0.32) than for VFA concentrations (0.02–0.24), while the opposite was the case on lucerne pellets. Rumen propionate as a proportion of total VFA had strong negative ri (−0.82 and −0.87) and acetate:propionate ratio (A:P; 0.82 and 0.78) and (acetate + butyrate):(propionate + valerate) ratio (AB:PV; 0.84 and 0.82) had a strong positive ri with CH4 yield in sheep fed cut pasture, while the ri of total ruminal VFA (−0.13 and 0.35) and acetate (−0.08 and 0.38) concentrations with CH4 yield were only moderate and non-significant. Conclusion The VFA traits propionate proportion and A:P and AB:PV ratios had strong individual-level correlations with CH4 yield in sheep fed pasture ad libitum, suggesting that they would be useful correlated proxies to rank sheep CH4 yields.

Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle

Partners in Expert Working Group WG2 of the COST Action METHAGENE have used several methods for measuring methane output by individual dairy cattle under various environmental conditions. Methods included respiration chambers, the sulphur hexafluoride (SF6) tracer technique, breath sampling during milking or feeding, the GreenFeed system, and the laser methane detector. The aim of the current study was to review and compare the suitability of methods for large-scale measurements of methane output by individual animals, which may be combined with other databases for genetic evaluations. Accuracy, precision and correlation between methods were assessed. Accuracy and precision are important, but data from different sources can be weighted or adjusted when combined if they are suitably correlated with the 'true' value. All methods showed high correlations with respiration chambers. Comparisons among alternative methods generally had lower correlations than comparisons with respiration chambers, despite higher numbers of animals and in most cases simultaneous repeated measures per cow per method. Lower correlations could be due to increased variability and imprecision of alternative methods, or maybe different aspects of methane emission are captured using different methods. Results confirm that there is sufficient correlation between methods for measurements from all methods to be combined for international genetic studies and provide a much-needed framework for comparing genetic correlations between methods should these become available.