Short communication: Development of an equation for estimating methane emissions of dairy cows from milk Fourier transform mid-infrared spectra by using reference data obtained exclusively from respiration chambers

Vanlierde, Amélie; Soyeurt, Hélène; Gengler, Nicolas; Colinet, Frédéric; Froidmont, Éric; Kreuzer, Michael; Grandl, Florian; Bell, Matthew; Lund, Peter; Olijhoek, D.W.; Eugène, Maguy; Martin, Cécile; Kuhla, Björn; Dehareng, Frédéric

doi:10.3168/jds.2018-14472

Cited by 46 publications

(58 citation statements)

References 16 publications

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“…For dairy cows, use of milk mid-IR spectroscopy to detect fatty acid composition and predict CH 4 emissions is based on the principle that the precursors for CH 4 and de novo synthesis of milk fatty acids both arise in the rumen. Mid-IR spectroscopy analysis of milk fatty acids has good potential to predict CH 4 production of individual cows on commercial dairy farms (van Gastelen and Dijkstra, 2016;Vanlierde et al, 2018), especially when combined with additional information such as feed intake, nutrient composition of the feed, parity and lactation stage. This approach could allow CH 4 production to be incorporated in dairy cow breeding programs.…”

Section: Unresolved Issues and Future Directionmentioning

confidence: 99%

Review: Fifty years of research on rumen methanogenesis: lessons learned and future challenges for mitigation

Beauchemin

Ungerfeld

Eckard

et al. 2020

Animal

369

241

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Meat and milk from ruminants provide an important source of protein and other nutrients for human consumption. Although ruminants have a unique advantage of being able to consume forages and graze lands not suitable for arable cropping, 2% to 12% of the gross energy consumed is converted to enteric CH4 during ruminal digestion, which contributes approximately 6% of global anthropogenic greenhouse gas emissions. Thus, ruminant producers need to find cost-effective ways to reduce emissions while meeting consumer demand for food. This paper provides a critical review of the substantial amount of ruminant CH4-related research published in past decades, highlighting hydrogen flow in the rumen, the microbiome associated with methanogenesis, current and future prospects for CH4 mitigation and insights into future challenges for science, governments, farmers and associated industries. Methane emission intensity, measured as emissions per unit of meat and milk, has continuously declined over the past decades due to improvements in production efficiency and animal performance, and this trend is expected to continue. However, continued decline in emission intensity will likely be insufficient to offset the rising emissions from increasing demand for animal protein. Thus, decreases in both emission intensity (g CH4/animal product) and absolute emissions (g CH4/day) are needed if the ruminant industries continue to grow. Providing producers with cost-effective options for decreasing CH4 emissions is therefore imperative, yet few cost-effective approaches are currently available. Future abatement may be achieved through animal genetics, vaccine development, early life programming, diet formulation, use of alternative hydrogen sinks, chemical inhibitors and fermentation modifiers. Individually, these strategies are expected to have moderate effects (<20% decrease), with the exception of the experimental inhibitor 3-nitrooxypropanol for which decreases in CH4 have consistently been greater (20% to 40% decrease). Therefore, it will be necessary to combine strategies to attain the sizable reduction in CH4 needed, but further research is required to determine whether combining anti-methanogenic strategies will have consistent additive effects. It is also not clear whether a decrease in CH4 production leads to consistent improved animal performance, information that will be necessary for adoption by producers. Major constraints for decreasing global enteric CH4 emissions from ruminants are continued expansion of the industry, the cost of mitigation, the difficulty of applying mitigation strategies to grazing ruminants, the inconsistent effects on animal performance and the paucity of information on animal health, reproduction, product quality, cost-benefit, safety and consumer acceptance.

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Section: Unresolved Issues and Future Directionmentioning

confidence: 99%

Review: Fifty years of research on rumen methanogenesis: lessons learned and future challenges for mitigation

Beauchemin

Ungerfeld

Eckard

et al. 2020

Animal

369

241

View full text Add to dashboard Cite

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“…Other notable FT-MIR research includes studies of individual fatty acids and milk proteins [8,9], and studies of milk properties related to manufacturing, especially coagulation and other cheese-making properties [10][11][12]. Further studies have focussed on traits not directly measurable in milk, including those related to pregnancy [13,14], energy status [15,16], nitrogen outputs [17] and methane emissions [18][19][20]. Such applications demonstrate that FT-MIR spectra can be used to predict a wide range of traits, including highly topical traits that are important to animal welfare and the environment.…”

Section: Phenotyping Applications Of Ft-mir Spectramentioning

confidence: 99%

“…There is, therefore, some potential for the future incorporation of FT-MIR predicted methane traits into breeding programs. However, there are still issues to be resolved to address uncertainties and discrepancies in methane datasets and measurement methods, and to improve the accuracy and robustness of prediction equations to make them applicable across a broader range of production systems and environments [19,20,71,72]. Milk urea nitrogen (MUN) concentrations are routinely predicted using FT-MIR spectroscopy [4], however, there are few studies of the genetic parameters of FT-MIR predicted MUN and its relationship with other production traits.…”

Section: Environment Traitsmentioning

confidence: 99%

The evolving role of Fourier-transform mid-infrared spectroscopy in genetic improvement of dairy cattle

Tiplady

Lopdell

Littlejohn

et al. 2020

J Animal Sci Biotechnol

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Over the last 100 years, significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs. Technological progress has enabled a shift from labour intensive, on-farm collection and processing of samples that assess yield and fat levels in milk, to large-scale processing of samples through centralised laboratories, with the scope extended to include quantification of other traits. Fourier-transform midinfrared (FT-MIR) spectroscopy has had a significant role in the transformation of milk composition phenotyping, with spectral-based predictions of major milk components already being widely used in milk payment and animal evaluation systems globally. Increasingly, there is interest in analysing the individual FT-MIR wavenumbers, and in utilising the FT-MIR data to predict other novel traits of importance to breeding programs. This includes traits related to the nutritional value of milk, the processability of milk into products such as cheese, and traits relevant to animal health and the environment. The ability to successfully incorporate these traits into breeding programs is dependent on the heritability of the FT-MIR predicted traits, and the genetic correlations between the FT-MIR predicted and actual trait values. Linking FT-MIR predicted traits to the underlying mutations responsible for their variation can be difficult because the phenotypic expression of these traits are a function of a diverse range of molecular and biological mechanisms that can obscure their genetic basis. The individual FT-MIR wavenumbers give insights into the chemical composition of milk and provide an additional layer of granularity that may assist with establishing causal links between the genome and observed phenotypes. Additionally, there are other molecular phenotypes such as those related to the metabolome, chromatin accessibility, and RNA editing that could improve our understanding of the underlying biological systems controlling traits of interest. Here we review topics of importance to phenotyping and genetic applications of FT-MIR spectra datasets, and discuss opportunities for consolidating FT-MIR datasets with other genomic and molecular data sources to improve future dairy cattle breeding programs.

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“…The reported random cross validation R 2 val ranged from 0.13 (Shetty et al, 2017) to 0.77 (Vanlierde et al, 2015). These large differences between studies can be partly explained by differences in methods used to quantify CH4 emission: some studies used climate respiration chambers (Van Gastelen et al, 2018;Vanlierde et al, 2018) whereas others used sulfur hexafluoride (SF6) tracer Vanlierde et al, 2015) or the sniffer method (Shetty et al, 2017). Similar like the current study Shetty et al (2017) used the sniffer method and reported a R 2 val based on random cross validation of 0.13.…”

Section: Literaturementioning

confidence: 47%

“…Several methods have been suggested to quantify CH4 emission from individual dairy cows (Hammond et al, 2016;Negussie et al, 2017). Some studies investigated the possibility of predicting CH4 emission based on milk infrared (IR) spectroscopy Vanlierde et al,2015;Shetty et al, 2017;Van Gastelen et al, 2018;Vanlierde et al, 2018). Milk IR spectroscopy is a method to analyse milk composition and widely used to routinely quantify milk fat-, protein-and lactose content.…”

Section: Introductionmentioning

confidence: 99%

The genetic background of bovine milk infrared spectra

Wang¹

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1-General introduction 2-Genetic and environmental variation in bovine milk infrared spectra 3-Genome wide association study for milk infrared wavenumbers 4-Validation strategy can result in overoptimistic view on the ability of milk infrared spectra to predict methane emission of dairy cattle 5-Combined use of milk infrared spectra and genotypes improves prediction of milk fat composition 6-General discussion Summary Curriculum Vitae Acknowledgements Colophon 14 selenium, and zinc, which are especially important for pregnant women and children (Black et al., 2002). 1.1.2 Milk composition and manufacturing properties of dairy products Milk composition is also related to manufacturing properties of milk. Milk fat composition has an influence on melting properties of fat and therefore on the texture of dairy products such as butter, ice cream, yogurt (e.g., Chen et al., 2004). A softer texture is related to a lower melting point, which is associated with an increased unsaturated fatty acid content (e.g., Couvreur et al., 2006). Milk protein composition plays an important role in cheese production. Casein proteins are positively correlated with cheese yield (Wedholm et al., 2006; Heck et al., 2009). Milk protein composition affects milk coagulation properties which is a crucial parameter in cheese making (Auldist et al., 2004; Bonfatti et al., 2010; Penasa et al., 2010). 1.1.3 Milk composition and farm management Milk composition can serve as an indicator which can be used by farmers to assist in dairy farm management (Hamann and Krömker, 1997). Major milk components e.g. milk fat and protein, are routinely recorded and their changes may indicate changes in the farm management or health status of dairy cows. Bastin et al. (2012) suggested the use of milk fat composition as an indicator for body reserve mobilization and fertility of dairy cows. Schukken et al. (2003) suggested the use of somatic cell counts in milk to monitor milk quality and udder health of dairy cows, since a high somatic cell count is associated with risk of mastitis. Clinical mastitis has also been related to lactoferrin content in milk (Kawai et al., 1999). Changes in β-hydroxybutyrate, milk fatty acids, and fat to protein ratio are related to energy balance of dairy cows which is related to metabolic disorders like ketosis (

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Short communication: Development of an equation for estimating methane emissions of dairy cows from milk Fourier transform mid-infrared spectra by using reference data obtained exclusively from respiration chambers

Cited by 46 publications

References 16 publications

Review: Fifty years of research on rumen methanogenesis: lessons learned and future challenges for mitigation

Review: Fifty years of research on rumen methanogenesis: lessons learned and future challenges for mitigation

The evolving role of Fourier-transform mid-infrared spectroscopy in genetic improvement of dairy cattle

The genetic background of bovine milk infrared spectra

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