3-Nitrooxypropanol decreases methane emissions and increases hydrogen emissions of early lactation dairy cows, with associated changes in nutrient digestibility and energy metabolism
Gastelen, Sanne van; Dijkstra, Jan ; Binnendijk, Gisabeth ; Duval, Stéphane M. ; Heck, Jeroen M.L. ; Kindermann, Maik ; Zandstra, Tamme ; Bannink, André - \ 2020
Journal of Dairy Science (2020). - ISSN 0022-0302
3-nitrooxypropanol - dairy cow - enteric methane production - lactation stage
The aim of this study was to determine the methane (CH4) mitigation potential of 3-nitrooxypropanol and the persistency of its effect when fed to dairy cows in early lactation. Sixteen Holstein-Friesian cows (all multiparous; 11 cows in their second parity and 5 cows in their third parity) were blocked in pairs, based on actual calving date, parity, and previous lactation milk yield, and randomly allocated to 1 of 2 dietary treatments: a diet including 51 mg of 3-nitrooxypropanol/kg of dry matter (3-NOP) and a diet including a placebo at the same concentration (CON). Cows were fed a 35% grass silage, 25% corn silage, and 40% concentrate (on dry matter basis) diet from 3 d after calving up to 115 d in milk (DIM). Every 4 weeks, the cows were housed in climate respiration chambers for 5 d to measure lactation performance, feed and nutrient intake, apparent total-tract digestibility of nutrients, energy and N metabolism, and gaseous exchange (4 chamber visits per cow in total, representing 27, 55, 83, and 111 DIM). Feeding 3-NOP did not affect dry matter intake (DMI), milk yield, milk component yield, or feed efficiency. These variables were affected by stage of lactation, following the expected pattern of advanced lactation. Feeding 3-NOP did not affect CH4 production (g/d) at 27 and 83 DIM, but decreased CH4 production at 55 and 111 DIM by an average of 18.5%. This response in CH4 production is most likely due to the differences observed in feed intake across the different stages of lactation because CH4 yield (g/kg of DMI) was lower (on average 16%) at each stage of lactation upon feeding 3-NOP. On average, feeding 3-NOP increased H2 production and intensity 12-fold; with the control diet, H2 yield did not differ between the different stages of lactation, whereas with the 3-NOP treatment H2 yield decreased from 0.429 g/kg of DMI at 27 DIM to 0.387 g/kg of DMI at 111 DIM. The apparent total-tract digestibility of dry matter, organic matter, neutral detergent fiber, and gross energy was greater for the 3-NOP treatment. In comparison to the control treatment, 3-NOP did not affect energy and N balance, except for a greater metabolizable energy intake to gross energy intake ratio (65.4 and 63.7%, respectively) and a greater body weight gain (average 0.90 and 0.01% body weight change, respectively). In conclusion, feeding 3-NOP is an effective strategy to decrease CH4 emissions (while increasing H2 emission) in early lactation Holstein-Friesian cows with positive effects on apparent total-tract digestibility of nutrients.
Short communication: The effect of linseed oil and DGAT1 K232A polymorphism on the methane emission prediction potential of milk fatty acids
Gastelen, S. van; Antunes-Fernandes, E.C. ; Hettinga, K.A. ; Dijkstra, J. - \ 2018
Journal of Dairy Science 101 (2018)6. - ISSN 0022-0302 - p. 5599 - 5604.
DGAT1 K232 polymorphism - enteric methane production - linseed oil - milk fatty acid
Several in vivo CH4 measurement techniques have been developed but are not suitable for precise and accurate large-scale measurements; hence, proxies for CH4 emissions in dairy cattle have been proposed, including the milk fatty acid (MFA) profile. The aim of the present study was to determine whether recently developed MFA-based prediction equations for CH4 emission are applicable to dairy cows with different diacylglycerol o-acyltransferase 1 (DGAT1) K232A polymorphism and fed diets with and without linseed oil. Data from a crossover design experiment were used, encompassing 2 dietary treatments (i.e., a control diet and a linseed oil diet, with a difference in dietary fat content of 22 g/kg of dry matter) and 24 lactating Holstein-Friesian cows (i.e., 12 cows with DGAT1 KK genotype and 12 cows with DGAT1 AA genotype). Enteric CH4 production was measured in climate respiration chambers and the MFA profile was analyzed using gas chromatography. Observed CH4 emissions were compared with CH4 emissions predicted by previously developed MFA-based CH4 prediction equations. The results indicate that different types of diets (i.e., with or without linseed oil), but not the DGAT1 K232A polymorphism, affect the ability of previously derived prediction equations to predict CH4 emission. However, the concordance correlation coefficient was smaller than or equal to 0.30 for both dietary treatments separately, both DGAT1 genotypes separately, and the complete data set. We therefore concluded that previously derived MFA-based CH4 prediction equations can neither accurately nor precisely predict CH4 emissions of dairy cows managed under strategies differing from those under which the original prediction equations were developed.
Predicting enteric methane emission of dairy cows with milk Fourier-transform infrared spectra and gas chromatography–based milk fatty acid profiles
Gastelen, S. van; Mollenhorst, H. ; Antunes-Fernandes, E.C. ; Hettinga, K.A. ; Burgsteden, G.G. van; Dijkstra, J. ; Rademaker, J.L.W. - \ 2018
Journal of Dairy Science 101 (2018)6. - ISSN 0022-0302 - p. 5582 - 5598.
dairy cow - enteric methane production - milk fatty acid concentration - milk Fourier-transform infrared spectroscopy
The objective of the present study was to compare the prediction potential of milk Fourier-transform infrared spectroscopy (FTIR) for CH4 emissions of dairy cows with that of gas chromatography (GC)–based milk fatty acids (MFA). Data from 9 experiments with lactating Holstein-Friesian cows, with a total of 30 dietary treatments and 218 observations, were used. Methane emissions were measured for 3 consecutive days in climate respiration chambers and expressed as production (g/d), yield (g/kg of dry matter intake; DMI), and intensity (g/kg of fat- and protein-corrected milk; FPCM). Dry matter intake was 16.3 ± 2.18 kg/d (mean ± standard deviation), FPCM yield was 25.9 ± 5.06 kg/d, CH4 production was 366 ± 53.9 g/d, CH4 yield was 22.5 ± 2.10 g/kg of DMI, and CH4 intensity was 14.4 ± 2.58 g/kg of FPCM. Milk was sampled during the same days and analyzed by GC and by FTIR. Multivariate GC-determined MFA–based and FTIR-based CH4 prediction models were developed, and subsequently, the final CH4 prediction models were evaluated with root mean squared error of prediction and concordance correlation coefficient analysis. Further, we performed a random 10-fold cross validation to calculate the performance parameters of the models (e.g., the coefficient of determination of cross validation). The final GC-determined MFA–based CH4 prediction models estimate CH4 production, yield, and intensity with a root mean squared error of prediction of 35.7 g/d, 1.6 g/kg of DMI, and 1.6 g/kg of FPCM and with a concordance correlation coefficient of 0.72, 0.59, and 0.77, respectively. The final FTIR-based CH4 prediction models estimate CH4 production, yield, and intensity with a root mean squared error of prediction of 43.2 g/d, 1.9 g/kg of DMI, and 1.7 g/kg of FPCM and with a concordance correlation coefficient of 0.52, 0.40, and 0.72, respectively. The GC-determined MFA–based prediction models described a greater part of the observed variation in CH4 emission than did the FTIR-based models. The cross validation results indicate that all CH4 prediction models (both GC-determined MFA–based and FTIR-based models) are robust; the difference between the coefficient of determination and the coefficient of determination of cross validation ranged from 0.01 to 0.07. The results indicate that GC-determined MFA have a greater potential than FTIR spectra to estimate CH4 production, yield, and intensity. Both techniques hold potential but may not yet be ready to predict CH4 emission of dairy cows in practice. Additional CH4 measurements are needed to improve the accuracy and robustness of GC-determined MFA and FTIR spectra for CH4 prediction.
The relationship between milk metabolome and methane emission of Holstein Friesian dairy cows: Metabolic interpretation and prediction potential
Gastelen, S. van; Antunes Fernandes, E.C. ; Hettinga, K.A. ; Dijkstra, J. - \ 2018
Journal of Dairy Science 101 (2018)3. - ISSN 0022-0302 - p. 2110 - 2126.
dairy cow - enteric methane production - Milk metabolome
This study aimed to quantify the relationship between CH4 emission and fatty acids, volatile metabolites, and nonvolatile metabolites in milk of dairy cows fed forage-based diets. Data from 6 studies were used, including 27 dietary treatments and 123 individual observations from lactating Holstein-Friesian cows. These dietary treatments covered a large range of forage-based diets, with different qualities and proportions of grass silage and corn silage. Methane emission was measured in climate respiration chambers and expressed as production (g per day), yield (g per kg of dry matter intake; DMI), and intensity (g per kg of fat- and protein-corrected milk; FPCM). Milk samples were analyzed for fatty acids by gas chromatography, for volatile metabolites by gas chromatography-mass spectrometry, and for nonvolatile metabolites by nuclear magnetic resonance. Dry matter intake was 15.9 ± 1.90 kg/d (mean ± SD), FPCM yield was 25.2 ± 4.57 kg/d, CH4 production was 359 ± 51.1 g/d, CH4 yield was 22.6 ± 2.31 g/kg of DMI, and CH4 intensity was 14.5 ± 2.59 g/kg of FPCM. The results show that changes in individual milk metabolite concentrations can be related to the ruminal CH4 production pathways. Several of these relationships were diet driven, whereas some were partly dependent on FPCM yield. Next, prediction models were developed and subsequently evaluated based on root mean square error of prediction (RMSEP), concordance correlation coefficient (CCC) analysis, and random 10-fold cross-validation. The best models with milk fatty acids (in g/100 g of fatty acids; MFA) alone predicted CH4 production, yield, and intensity with a RMSEP of 34 g/d, 2.0 g/kg of DMI, and 1.7 g/kg of FPCM, and with a CCC of 0.67, 0.44, and 0.75, respectively. The CH4 prediction potential of both volatile metabolites alone and nonvolatile metabolites alone was low, regardless of the unit of CH4 emission, as evidenced by the low CCC values (<0.35). The best models combining the 3 types of metabolites as selection variables resulted in the inclusion of only MFA for CH4 production and CH4 yield. For CH4 intensity, MFA, volatile metabolites, and nonvolatile metabolites were included in the prediction model. This resulted in a small improvement in prediction potential (CCC of 0.80; RMSEP of 1.5 g/kg of FPCM) relative to MFA alone. These results indicate that volatile and nonvolatile metabolites in milk contain some information to increase our understanding of enteric CH4 production of dairy cows, but that it is not worthwhile to determine the volatile and nonvolatile metabolites in milk to estimate CH4 emission of dairy cows. We conclude that MFA have moderate potential to predict CH4 emission of dairy cattle fed forage-based diets, and that the models can aid in the effort to understand and mitigate CH4 emissions of dairy cows.
Linseed oil and DGAT1 K232A polymorphism: Effects on methane emission, energy and nitrogen metabolism, lactation performance, ruminal fermentation, and rumen microbial composition of Holstein-Friesian cows
Gastelen, S. van; Visker, M.H.P.W. ; Edwards, J.E. ; Antunes Fernandes, E.C. ; Hettinga, K.A. ; Alferink, S.J.J. ; Hendriks, W.H. ; Bovenhuis, H. ; Smidt, H. ; Dijkstra, J. - \ 2017
Journal of Dairy Science 100 (2017)11. - ISSN 0022-0302 - p. 8939 - 8957.
diary cow - enteric methane production - Linseed oil - DGAT1 K232A polymorphism
Complex interactions between rumen microbiota, cow genetics, and diet composition may exist. Therefore, the effect of linseed oil, DGAT1 K232A polymorphism (DGAT1), and the interaction between linseed oil and DGAT1 on CH4 and H2 emission, energy and N metabolism, lactation performance, ruminal fermentation, and rumen bacterial and archaeal composition was investigated. Twenty-four lactating Holstein-Friesian cows (i.e., 12 with DGAT1 KK genotype and 12 with DGAT1 AA genotype) were fed 2 diets in a crossover design: a control diet and a linseed oil diet (LSO) with a difference of 22 g/kg of dry matter (DM) in fat content between the 2 diets. Both diets consisted of 40% corn silage, 30% grass silage, and 30% concentrates (DM basis). Apparent digestibility, lactation performance, N and energy balance, and CH4 emission were measured in climate respiration chambers, and rumen fluid samples were collected using the oral stomach tube technique. No linseed oil by DGAT1 interactions were observed for digestibility, milk production and composition, energy and N balance, CH4 and H2 emissions, and rumen volatile fatty acid concentrations. The DGAT1 KK genotype was associated with a lower proportion of polyunsaturated fatty acids in milk fat, and with a higher milk fat and protein content, and proportion of saturated fatty acids in milk fat compared with the DGAT1 AA genotype, whereas the fat- and protein-corrected milk yield was unaffected by DGAT1. Also, DGAT1 did not affect nutrient digestibility, CH4 or H2 emission, ruminal fermentation or ruminal archaeal and bacterial concentrations. Rumen bacterial and archaeal composition was also unaffected in terms of the whole community, whereas at the genus level the relative abundances of some bacterial genera were found to be affected by DGAT1. The DGAT1 KK genotype was associated with a lower metabolizability (i.e., ratio of metabolizable to gross energy intake), and with a tendency for a lower milk N efficiency compared with the DGAT1 AA genotype. The LSO diet tended to decrease CH4 production (g/d) by 8%, and significantly decreased CH4 yield (g/kg of DM intake) by 6% and CH4 intensity (g/kg of fat- and protein-corrected milk) by 11%, but did not affect H2 emission. The LSO diet also decreased ruminal acetate molar proportion, the acetate to propionate ratio, and the archaea to bacteria ratio, whereas ruminal propionate molar proportion and milk N efficiency increased. Ruminal bacterial and archaeal composition tended to be affected by diet in terms of the whole community, with several bacterial genera found to be significantly affected by diet. These results indicate that DGAT1 does not affect enteric CH4 emission and production pathways, but that it does affect traits other than lactation characteristics, including metabolizability, N efficiency, and the relative abundance of Bifidobacterium. Additionally, linseed oil reduces CH4 emission independent of DGAT1 and affects the rumen microbiota and its fermentative activity.