Invited review: Phenotypes to genetically reduce greenhouse gas emissions in dairying

Haas, Y. de; Pszczoła, Marcin; Soyeurt, Hélène; Wall, E.; Lassen, Jan

doi:10.3168/jds.2016-11246

Cited by 84 publications

(63 citation statements)

References 113 publications

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“…There is an ongoing research effort towards CH4 mitigation. Apart from the available set of efficient dietary interventions (Hristov et al, 2013), targeted animal breeding has emerged as a promising and, if successful, sustainable mitigation strategy (de Haas et al, 2017). Breeding progress is possible if a trait is sufficiently heritable and if phenotypic data are available from populations relevant for genetic selection purposes.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of methane emissions predicted from milk mid-infrared spectra and measured by laser methane detectors in Brown Swiss dairy cows

Denninger

Schwarm

Dohme‐Meier

et al. 2020

Journal of Dairy Science

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Characteristics of low methane emitting cows as categorized by midinfrared spectra and respiration chamber measurements. Denninger et al. Mid-infrared spectra (MIR) were used to identify low and high methane emitting dairy cows within the Swiss, Brown Swiss population. Thirty individuals were selected for methane measurements using respiration chambers and laser methane detectors. The MIR predictions were fairly persistent across different environments and differently developed equations. However, correlations with methane measurements were too weak to use MIR as a tool to select low emitting cows. Cows categorized as low emitters by respiration chamber data expressed distinct characteristics in digestion and efficiency.

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Section: Introductionmentioning

confidence: 99%

Accuracy of methane emissions predicted from milk mid-infrared spectra and measured by laser methane detectors in Brown Swiss dairy cows

Denninger

Schwarm

Dohme‐Meier

et al. 2020

Journal of Dairy Science

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“…Because enteric methane (CH 4 ) emissions of ruminants compose a large proportion of greenhouse gas (GHG) from the agricultural sector, various mitigation strategies (Steinfeld et al, 2006;Hammond et al, 2016a) and phenotypes for identifying and selecting cattle with lower emissions have been proposed (de Haas et al, 2017). Mitigation of enteric CH 4 emissions from ruminants may be achieved by the intensification of production, improved efficiency of feed conversion, feed additives, improved genetics, better manure management, and biogas production (Steinfeld et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Enteric methane emission from Jersey cows during the spring transition from indoor feeding to grazing

Szalanski

Kristensen

Difford

et al. 2019

Journal of Dairy Science

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Organic dairy cows in Denmark are often kept indoors during the winter and outside at least part time in the summer. Consequently, their diet changes by the season. We hypothesized that grazing might affect enteric CH 4 emissions due to changes in the nutrition, maintenance, and activity of the cows, and they might differentially respond to these factors. This study assessed the repeatability of enteric CH 4 emission measurements for Jersey cattle in a commercial organic dairy herd in Denmark. It also evaluated the effects of a gradual transition from indoor winter feeding to outdoor spring grazing. Further, it assessed the individual-level correlations between measurements during the consecutive feeding periods (phenotype × environment, P × E) as neither pedigrees nor genotypes were available to estimate a genotype by environment effect. Ninety-six mixed-parity lactating Jersey cows were monitored for 30 d before grazing and for 24 d while grazing. The cows spent 8 to 11 h grazing each day and had free access to an in-barn automatic milking system (AMS). For each visit to the AMS, milk yield was recorded and logged along with date and time. Monitoring equipment installed in the AMS feed bins continuously measured enteric CH 4 and CO 2 concentrations (ppm) using a noninvasive "sniffer" method. Raw enteric CH 4 and CO 2 concentrations and their ratio (CH 4 : CO 2 ) were derived from average concentrations measured during milking and per day for each cow. We used mixed models equations to estimate variance components and adjust for the fixed and random effects influencing the analyzed gas concentrations. Univariate models were used to precorrect the gas measurements for diurnal variation and to estimate the direct effect of grazing on the ana-lyzed concentrations. A bivariate model was used to assess the correlation between the 2 periods (in-barn vs. grazing) for each gas concentration. Grazing had a weak P × E interaction for daily average CH 4 and CO 2 gas concentrations. Bivariate repeatability estimates for average CH 4 and CO 2 concentrations and CH 4 : CO 2 were 0.77 to 0.78, 0.73 to 0.80, and 0.26, respectively. Repeatability for CH 4 : CO 2 was low (0.26) but indicated some between-animal variation. In conclusion, grazing does not create significant shifts compared with indoor feeding in how animals rank for average CH 4 and CO 2 concentrations and CH 4 : CO 2 . We found no evidence that separate evaluation is needed to quantify enteric CH 4 and CO 2 emissions from Jersey cows during inbarn and grazing periods.

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“…">IntroductionEnteric methane (EME) emitted by lactating cows [1] makes the greatest contribution to greenhouse gas (GHG) emissions out of the entire animal sector, and therefore has the greatest impact on climate change [2].The direct quantification of GHG using respiration chambers requires facilities, tools, resources, and knowledge that are available in only a few research centers [3] and make it impossible to test GHG emissions in the field with a large number of farms and cows. Among the different proxies that have been proposed for indirectly measuring EME in dairy cattle [4], the analysis of fatty acid (FA) profiles of milk and a proper combination of FAs constitute an easy-to-use method for use in the field [5][6][7], as it requires only the collection of milk samples and analysis of them in the laboratory [8]. This method exploits the complex relationships between feed characteristics, rumen microbial activity, methane production, the production and metabolism of volatile and non-volatile fatty acids, and their absorption and transportation to the udder, de novo synthesis of fatty acids in the mammary gland, and, lastly, fat globule excretion in milk [5,9,10].Van Lingen et al[11] undertook a meta-analysis of the relationships between EME and milk FA profiles using the combined data from eight experiments covering 30 different diets, from which they derived two equations, one for predicting methane yield per kg of dry matter (DM) intake (CH 4 /DMI) and one for methane intensity (CH 4 /CM) per kg of fat-protein corrected milk (CM).…”

mentioning

confidence: 99%

Enteric Methane Emissions of Dairy Cows Predicted from Fatty Acid Profiles of Milk, Cream, Cheese, Ricotta, Whey, and Scotta

Bittante

Bergamaschi

2019

Animals

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Simple Summary: Six main fatty acids measured by gas-chromatography of four types of milk samples, fresh products, by-products, and ripened cheeses were used for predicting enteric methane yield per kg of feed consumed and intensity per kg of milk produced. Methane yield and intensity can be predicted from single milk samples with good accuracy. Cream, ricotta, and ripened cheese could be used only taking into account the possible overestimation of emissions and increasing the number of samples analyzed to improve the precision. Among by-products, whey could be a possible alternative source of information for predicting methane emission, whereas scotta showed low precision. Ripened cheeses were found to be less valuable sources of information to predict methane emission. This method could be used for monitoring the ecological footprint of different farms, dairy and feeding systems, and processing units. Abstract:Enteric methane emissions (EME) of ruminants contribute to global climate change, but any attempt to reduce it will need an easy, inexpensive, and accurate method of quantification. We used a promising indirect method for estimating EMEs of lactating dairy cows based on the analysis of the fatty acid (FA) profile of their milk. The aim of this preliminary study was to assess milk from four single samplings (morning whole, evening whole, evening partially skimmed, and vat milks) as alternatives to reference whole milk samples from two milkings. Three fresh products (cream, cheese, and ricotta), two by-products (whey and scotta), and two long-ripened cheeses (6 and 12 months) were also assessed as alternative sources of information to reference milk. The 11 alternative matrices were obtained from seven experimental cheese-and ricotta-making sessions carried out every two weeks following the artisanal Malga cheese-making procedure using milk from 148 dairy cows kept on summer highland pastures. A total of 131 samples of milk, dairy products, and by-products were analyzed to determine the milk composition and to obtain detailed FA profiles using bi-dimensional gas-chromatography. Two equations taken from a published meta-analysis of methane emissions measured in the respiration chambers of cows on 30 different diets were applied to the proportions of butyric, iso-palmitic, iso-oleic, vaccenic, oleic, and linoleic acids out of total FAs to predict methane yield per kg of dry matter ingested and methane intensity per kg of fat and protein corrected milk produced by the cows. Methane yield and intensity could be predicted from single milk samples with good accuracy (trueness and precision) with respect to those predicted from reference milk. The fresh products (cream, cheese and ricotta) generally showed good levels of trueness but low precision for predicting both EME traits, which means that a greater number of samples needs to be analyzed. Among by-products, whey could be a viable alternative source of information for predicting both EME traits, whereas scotta overestimated both traits and showed low precisio...

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Invited review: Phenotypes to genetically reduce greenhouse gas emissions in dairying

Cited by 84 publications

References 113 publications

Accuracy of methane emissions predicted from milk mid-infrared spectra and measured by laser methane detectors in Brown Swiss dairy cows

Accuracy of methane emissions predicted from milk mid-infrared spectra and measured by laser methane detectors in Brown Swiss dairy cows

Enteric methane emission from Jersey cows during the spring transition from indoor feeding to grazing

Enteric Methane Emissions of Dairy Cows Predicted from Fatty Acid Profiles of Milk, Cream, Cheese, Ricotta, Whey, and Scotta

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