Meta-Analysis of Methane Mitigation Strategies: Improved Predictions of Mitigation Potentials and Production Implications

Iranian Journal of Applied Animal Science

مقاله 2، دوره 8، شماره 4، اسفند 2018، صفحه 567-573   

نوع مقاله: Research Articles

نویسندگان

A. Chijioke Ogbonna¹؛ E. Rudinow Saetnan^{* 2}

¹Department of Animal Production and Livestock Management, Michael Okpara University of Agriculture, Umudike, Nigeria

²Institute of Biological Environmental and Rural Science, Aberystwyth University, Aberystwyth, United Kingdom

چکیده

The aim of this study was to use meta-analysis to identify the enteric methane (CH₄) mitigation strategy that reduced CH₄ emission without lowering production. To this end, a database initially developed was updated, compiling data from 61 publications (233 experiments) for various observations in dairy cattle on effects of hydrogen sink (H-sink), ionophore, lipid and concentrate feeds inclusion on enteric CH₄ production, milk production and milk composition from dairy cattle. There was no significant effect (P>0.05) of H-sink and ionophore feeds inclusion on CH₄ production while supplementation of lipid and concentrate considerably suppressed CH₄ production (P<0.05). CH₄ production per kg milk produced was not depressed with H-sink treatment (P<0.05). Lipids lightly increased CH₄ production per kg milk from 26.19 g kg⁻¹ for control to 29.12 g kg⁻¹ for treatment (P>0.05), while concentrate and ionophore feeds inclusion decreased CH₄ production per kg milk with no significant effect (P>0.05). There was a significant effect of concentrate on milk protein and milk yield, which increased from 23.27 kg d⁻¹ for control to 26.52 kg d⁻¹ for concentrate treated diet (P<0.05). Milk yield and milk protein was not significantly affected with H-sink, ionophore and lipid feeds inclusion (P>0.05). This meta-analysis demonstrates that lipid and concentrate feeds inclusion reduced CH₄ emissions from dairy cattle without lowering their production.

کلیدواژه‌ها

dairy cattle؛ meta-analysis؛ methane؛ methane abatement strategies

اصل مقاله

INTRODUCTION

Ruminant farming plays a great role in ensuring global food security and it is able to sustain the livelihood of millions of people in both developed and less developed worlds (Thornton et al. 2006). It is economically important with the world’s population of about 12% mainly depending on it for their livelihood (Herrero et al. 2013; Steinfeld et al. 2006). Ruminants utilize poor quality forages as energy source for various life purposes as maintenance, growth and production (Kingston-Smith et al. 2010). Unfortunately, ruminants meat and milk production are associated with greenhouse gas (GHG) emissions when compared with the production of other food types (Williams et al. 2009) with great effect on the environment. CH₄, carbon dioxide (CO₂) and nitrous oxide (N₂O) are the major GHG that promote the effects of solar radiation on the earth surface (Lassey, 2008). It was estimated that up to 18% of anthropogenic GHG emissions globally are mainly from animal agriculture (Steinfeld et al. 2006) with enteric CH₄ from ruminant farming systems representing by far the most numerically important source being responsible for circa 60-65% of the CH₄ emissions (USEPA, 2012). Evidently, if the ruminant livestock production is to remain a significant sector in agriculture, effective strategies that minimize CH₄ emission must be devised and implemented which increase their production efficiency, while at the same time reduce the environmental impact. An important area of focus is therefore to tackle the GHG emissions from livestock production, and to reduce the enteric CH₄ emission from dairy ruminants. Methanemitigationapproaches have been found to be economically and environmentally profitable and advantageous (Gerber et al. 2013; Shafer et al. 2011). Reduction of CH₄ substantially decreased the amount of GHG associated with milk production (Van Zijderveld et al. 2011) with dietary strategies (Martin et al. 2010). The policy makers need clear and objective information to get a worldwide picture for recommendations (Veneman et al. 2016) which make the qualification of mitigation strategy using meta-analysis of CH₄ emission strategy in dairy sector an important step to identifying the mitigation opportunity and review of new published studies to update data (FAO, 2010). To this end, this meta-analysis study was aimed to identifying the CH₄ mitigation strategy that reduced CH₄ emission without lowering production.

 

MATERIALS AND METHODS

Data collection/source

The MITIGATE database (Veneman et al. 2016) was initially built and developed in excel compiling data of various treatment details used in enteric CH₄ mitigation strategies from relevant experiments. Data from experiments in dairy cattle were downloaded from this existing database, papers were located and further data on production outcomes were extracted and filled in the database base. The production outcomes data that were investigated and added to the database included quantitative factors as animal body weight, feed details as nutrient composition and chemical composition; milk yield, milk fat, milk protein; rumen fermentation factors, ammonia, nitrogen in urine and faeces. Not all variables were available across all observations in the database. When any of the variables in the study were not reported and it was impossible to calculate the missing data from the reported data, these variables were considered as missing data of the study and were reported as not available (na) in the database.

 

Updating database

Several literature searches were made using Web of Science, Google Scholar and Aber-Primo (University of Aberystwyth Library Database) to further identify relevant papers on mitigation of CH₄ from dairy cattle from October, 2013 untill August, 2015. Certain keywords as “mitigate”, “lipids”, “ionophores”, “monensin”, “tannins”, “fatty acids”, “saponins” and methane were used. The searches resulted in six publications with 22 experiments and were all in vivo studies.

 

 

Meta-analysis

The meta-data were subjected to random effects model analysis due to reduced variance of experimental procedure or circumstances which may have been brought about by the vast nature and diversity in animal studies (Hooijmans et al. 2014; Vesterinen et al. 2014). The response of CH₄ production, milk production and milk protein to H-sink, ionophore, concentrate and lipid supplementation in dairy cattle for all studies included in the database were evaluated using SPSS package application. The data were analyzed using the following linear model:

Y_ij= B₀ + B₁X_ij + B₂X_ij² + S_i + b_iX_ij + e_ij

Where:

Y_ij: expected outcome i.e. the dependent variable Y observed in the j level of the variable X in the ith study.

B₀: overall intercept across all studies equivalent to µ in the random effects model above.

B₁ and B₂: overall linear models and quadratic coefficient of Y on X across all studies.

X_ij: average value j of the X variable in the ith study.

S_i: random error effect of the ith study.

b_i: random error effect of the ith study on the coefficient Y on X in the ith study, e_ij, S_i and b_i= independent random variables.

e_ij: residual error.

Results were reported at least square means and standard error of the mean for control and H-sink, ionophore, concentrates and lipid as treatment strategies. It was considered significantly different when P ≤ 0.05.

 

RESULTS AND DISCUSSION

Description of the MitiGate database

At the time of this study, the MitiGate database (www.mitigate.ibers.aber.ac.uk) was made up of 233 experiments with 61 publications comprising data and significant results of research studies on enteric CH₄ mitigation strategies from all regions of the world in dairy cattle. Ninety-three percent of the research studies were from the year 2000 untill August, 2015 with the largest number of publications from Europe (29 publications), North America (14 publications) and Australasia (14 publications). Nothing was reported for Africa, one publication for South America and three publications were reported for Asia. There was great variation among data on different enteric CH₄ mitigation strategies from dairy cattle from different locations and continents of the world. Table 1 reports the average values of the sample size, animal weight, dietary compositions, dry matter intake (DMI), CH₄ emissions, milk yield and composition, rumen volatile fatty acids, pH, ammonia concentration, nitrogen excreted in urine and faeces of dairy cattle for the construction of the database used for meta-analysis. The mean concentrations of crude protein (CP) and neutral detergent fiber (NDF) were 184.1 and 408 g kg⁻¹ DM. There was wide range of dietary and animal characteristics evaluated in this study. The DMI varied from 5.5 to 25.7 kg d⁻¹. Methane emissions expressed in g d⁻¹, g kg⁻¹ DMI, GEI MJ MJ⁻¹ also varied greatly in the database. Table 2 reports the effects of H-sink, ionophores, concentrates and lipids on CH₄ production, milk production and composition. There was no significant difference between the control and the H-sink treated diets (p=0.641) on CH₄ production expressed as (g kg⁻¹ DMI) from dairy cows. H-sink diets did not reduce CH₄ production from dairy cows but significantly increased CH₄ production relative to milk (P<0.05). There was no effect of H-sink supplementation on milk yield and milk protein. Milk yield of 24.35 kg d⁻¹ was reported for cows fed control diet and 25.44 kg d⁻¹ for those fed H-sink supplemented diet while milk protein of 3.07 vs. 2.47 was reported for cows fed control diet and those fed H-sink supplemented diet respectively. CH₄ production was slightly lower (20.59 vs. 19.89±1.26 g kg⁻¹ DMI, respectively) for cows fed ionophore supplemented diets than those fed control diets but there was no significant difference (P>0.05). CH₄ production per unit product decreased from 29.63 for cows fed control diets to 25.68 for ionophore supplemented dairy cow diets with no significant effect at (SEM=7.51; p=0.600). There was no effect of ionophore supplementation on milk yield and milk protein (P>0.05). It was reported that 25.23 vs. 24.57 ± 2.15 g d⁻¹; 3.02 vs. 2.52 ± 1.05% were for cows fed control diet and those fed ionophore supplemented diet for milk yield and milk protein respectively (Table 2). CH₄ production was significantly lower for cows fed concentrate diets than for those fed control diets (18.26 vs. 22.22±0.83 g kg⁻¹ DMI, respectively (P<0.05). CH₄ production per unit product was lower (23.09 vs. 32.22±4.99 g kg⁻¹, respectively) for cows fed concentrate diets than for those fed control diets but there was no significant difference (p=0.067). There was a significant effect of concentrate inclusion on milk yield which increased from 23.27 for control to 26.52 for treatment ± 1.23 kg d⁻¹ (P<0.05) and no effect on milk protein (p=0.337) which decreased from 3.02 for cows fed control diets to 2.53 those fed concentrate diet (Table 2). CH₄ production was significantly lower for cows fed control diets than for those fed lipid-supplemented diets (18.64 vs. 21.84±1.23 g kg⁻¹ DMI, respectively, p=0.009). CH₄ production per unit product increased from 26.19 for control diets to 29.12 for lipid-supplemented diets with no significant difference at (SEM=7.61; p=0.700) (Table 2). There was no effect of lipid supplementation on milk yield and protein between dairy cows fed control diets and lipid-supplemented diets (P>0.05). Meta-analysis of CH₄ mitigation strategies in this study shows the possibility to reduce CH₄ emissions from dairy cattle while not lowering their production if the energy lost as CH₄ by the ruminant can be used for growth and production purposes (Martin et al. 2010). Certain regions as Africa, South America and Asia are underrepresented which reflect the state of research and the intensity of livestock systems in these regions. Differences in the experimental procedure, specific production system where research was carried out and high level of missing data (St-Pierre, 2007) explain the wide variations and diversity of data. These factors made it unbalanced thus prevent the identification of the relationship that exists between treatments and factors of interest. Data was summarized to obtain a qualitative estimation and arrive at a general conclusion for recommendation (Sauvant et al. 2008; Hooijmans et al. 2014). Hydrogen sinks (organic acids as nitrates and sulphates) are feed additives used to improve the quality and palatability of ruminants feeds (Shingfield et al. 2002). They provide energy, act as an alternate sink for H₂ in the rumen and inhibit methanogenesis by causing a drop in pH which affects the fermentation of feed (Ungerfeld et al. 2007). Nitrates are reduced to ammonia during metabolism in the rumen and make up for shortage of nutrients in the diet (Ungerfeld and Kohn, 2006; Dijkstra et al. 2007). Nitrates (NO₃⁻) and sulfates (SO₄⁻²) accept electrons (alternate hydrogen-sink) and thus reduce methanogenesis. Addition of NO₃⁻ and SO₄⁻² reduced CH₄ production in sheep, lactating dairy cows and bulls at a very high dose which may be due to the lower electron available to methanogens. The results obtained agrees with those obtained by van Zijderveld et al. (2010) who reported that nitrate and sulfate supplementation reduced enteric CH₄ production due their ability to favorably utilize H₂ during metabolism of nitrate to ammonia than methanogens. Also, agrees with Veneman et al. (2016) who reported decrease in CH₄ production with H-sink supplementation. Though, H-sink slightly increased CH₄ production but was not significant. Ionophores as monensin are antimicrobials used as feed additive in ruminant production to improve feed utilization efficiency and animal performance (Moss et al. 2000). Experiments with monensin on mitigation of CH₄ in different animal production systems have been studied and reviewed (Grainger et al. 2010; Sauer et al. 1998; Beauchemin et al. 2008).

 

Table 1 Average values of the sample size, animal weight, dietary compositions, dry matter intake, CH₄ emissions, milk yield and composition, rumen volatile fatty acids, pH, ammonia concentration, nitrogen excreted in urine and faeces of dairy cattle for the construction of the database used for meta-analysis

 

SD: standard deviation; N: number; Min: minimum; Max: maximum; OM: organic matter; ADF: acid detergent fibre; NDF: neutral detergent fibre; CP: crude protein; DMI: dry matter intake; GEI: gross energy intake; TVFAs: total volatile fatty acids and NH₃: ammonia.

 

The results obtained here for ionophore supplementation is in line with the results obtained by Beauchemin et al. (2008) who reported that ionophore supplementation of lactating dairy cows diets did not mitigate CH₄ emission. There was no effect of ionophore supplementation on milk yield and protein. This is in disagreement with results obtained by Grainger et al. (2010) and Duffield et al. (2008) who reported improved milk production with ionophore supplementation. The long term persistency and inhibitory effects of ionophores on CH₄ production did not consistently reduce CH₄ production (Odongo et al. 2007) which may be due to the development of resistance by certain varieties of rumen methanogens and adaptations to antimicrobial treatment (Boadi et al. 2004). The public health authority concern over the use of monensin in animal production limits its use which makes it an unviable option for CH₄ mitigation (Martin et al. 2010). It is well known and established (Firkins et al. 2001) that feeding concentrates or more energy-dense diets as sugars and starches that are digested in the small intestine provide more energy necessary for production purposes (milk). This, also, reduce enteric CH₄ emission due to the change in rumen pH (<5.5) which reduce the methanogenic populations with increased intake levels (Hegarty, 1999) and decline the ratio of acetate to propionate. The results obtained for concentrate inclusion is in line with those reported by Beauchemin et al. (2008). Though concentrates reduced CH₄ emissions and increased milk yield, it reduced milk quality (protein). High level of concentrate inclusion in diet is needed to achieve positive results but have economic constraints especially in the less developed worlds. High quality forage improvement with high starch levels as cereal forages through breeding and conservation can be used to increase the nutrient use efficiency, productivity of the animal and overall farm profitability thus reduce CH₄ emissions per unit animal product (Beauchemin et al. 2008). Lipids (fats and oils) are supplemented to ruminant diet to increase the energy density of diet for increased production (Shingfield et al. 2010). Lipid supplementation reduces CH₄ emissions by reducing the numbers and activities of methanogens and protozoa during metabolism in the rumen (Brask et al. 2013).

 

Table 2 Effects of of hydrogen sink (H-sink), ionophores, concentrates and lipids on CH₄ production, milk production and composition

 

N: number of data and DMI: dry matter intake.

SEM: standard error of the means.

 

Furthermore, lipid supplementation can influence the palatability, intake of feed, animal productivity and product quality (Odongo et al. 2007) which has great implications on the farm. The depressing effect of lipid-supplementation to dairy cow diet on enteric CH₄ production has been reported with variations in the extent of inhibition (Patra, 2013; Beauchemin et al. 2008). Here, lipid feeds inclusion slightly increased CH₄ production but was not significant. The effect of lipid supplementation on CH₄ production agree with the result obtained by Eugene et al. (2008) who reported that lipid-supplementation of lactating dairy cow diet could mitigate CH₄ emission by dairy cows. Certain factors as dose or concentration of lipid-supplementation, duration of feeding, source of lipids (seed vs. oil), fat type and diet composition influence the depressing effect of lipid supplementation of dairy cow diet on CH₄ production and productivity (milk production/protein) (Patra, 2013). Long-term experiment to investigate the effectiveness of lipid supplementation as a mitigation strategy is needed. The physiological stage of animal (lactating vs. dry) (NRC, 2001), morphological differences of rumen anatomy and differences in basal diet (feed factors as dose of supplementation, type and source) (Newbold et al. 1996) might have influenced the results. The period of the physiological stage (early vs. late lactation) of the animal can also influence the response of CH₄ abatement strategy to CH₄ production. During late lactation, decreased milk yield is associated with increased CH₄ yield per unit of product (milk). This is seen with lipid supplementation while during negative energy balance, when cows are producing at a high level in early lactation, CH₄ production per unit product is reduced (Johnson et al. 1996; Chilliard et al. 2009) which may explain the decrease in CH₄ milkwith concentrate feeds supplementation. The composition of feed as starch or cell wall carbohydrates, increasing level of feed intake and increasing passage of feed can influence the mitigation strategy and hence affect CH₄ production by strategy per unit of fermentable feed intake (Boadi et al. 2004). In addition, the duration of study influences the effectiveness of the mitigation strategies to reduce CH₄ emission. Short duration of study reduces the effectiveness and persistency of the mitigation strategy under consideration which makes longer-term studies important for better estimation of the efficacy and persistency of abatement strategy (Hristov et al. 2013). The research studies included in the database do not provide a true representation of the real practical farm livestock systems as some studies were carried out under controlled environment, housed, grazed or experimental; some used small number or large number of animals quite different from typical livestock production systems. Some data for incorporation into the database for meta-analysis were missing. Some animals were fed ad libitum, restricted and given different feeds as test ingredients which do not represent the true picture of what can be obtained from the different geographical locations of the world (Eckard et al. 2010). Meta-analysis is limited as data from various research studies for analysis are based on or weighted from outcome of previous and similar studies and error that occur due to inability to identify and differentiate between the effects of factors of interest especially when the studies involved are wide (St-Pierre, 2007). Due to differences in study characteristics, environmental and climatic conditions; experimental procedures, species, breed, physiological stage, diet composition, dose of supplementation and specific conditions where research was carried out. In addition, such studies may have considered few factor of importance, which may be small and diverse (Sauvant et al. 2008; St-Pierre, 2007). Thus, the current meta-analysis might not be used to make conclusive reports on the efficacy of CH₄ abatement strategy on animal productivity and product quality or used to make general recommendations as it might not reflect the farming system under consideration. Carrying out research for comparisons between animal species (dairy vs. beef), type (cow vs. heifer), weight, age, duration of study, physiological stage (lactation vs. dry or growth), estimation techniques and the production systems for different geographical regions of the world will increase the effectiveness of mitigation strategies for CH₄ abatement from dairy cows when implemented in specific regions (Sauvant et al. 2008). Finally, measurement and quantification of CH₄ emissions from different herd under different farm conditions will help in the establishment and improvement on the overall estimates and also, properly identify the mitigation strategy that reduce enteric CH₄ productions from dairy cattle under location of interest without lowering their production.

 

CONCLUSION

There are currently several potential effective strategies to mitigate CH₄ emissions from dairy cattle. The result of this meta-analysis showed that H-sinks, lipid and concentrates are potential and effective strategies resulting in reduced CH₄ emissions from dairy cattle without lowering their production. Many studies used in this meta-analysis only measured CH₄ emissions over a short time frame, which makes longer-term studies important.

 

ACKNOWLEDGEMENT

This study was supported by the Tertiary Education Trust-Fund (TETFUND) via Michael Okpara University of Agriculture, Umudike, Nigeria.

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