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Evaluation of Shea nut meal potential to mitigate enteric methane in vitro

C Amerit1,2, J O Ondiek1, M K Ambula1 and N Kibitok1

1 Department of Animal Sciences, Egerton University, P.O Box 536-20115 Egerton, Kenya
2 Grainpulse Limited, PO Box 6217, Kampala – Uganda


The worry of unmitigated global warming causing irreversible climate change is on the rise. Sustainable solutions to mitigate methane production from ruminant farming should thus be sought. Shea nut meal (SNM) contains numerous plant compounds proved to reduce enteric methane production in ruminants and its adoption in ruminant feed could become a game changer. This experiment examined total gas production, metabolizable energy, organic matter digestibility and methane mitigation properties of shea nut meal when included at varying levels of SNM0 (0%), SNM5 (5%), SNM10 (10%), SNM15 (15%) and SNM20 (20%) in a basal diet containing Rhodes grass hay and maize bran in an in vitro experiment set in a completely randomized design. Results showed total gas production (ml) was improved at 5% (49.8) compared to 0% (46.7) but declined with further SNM inclusions at 10% (40.6), 15% (29.5) and 20% (24.8), Organic matter digestibility (% OMD) was reduced (p<0.05) with SNM inclusion of 5% (42.8), 10% (40.5), 15% (35.51), 20% (34.0) compared to 0% (43.3). Metabolizable energy was improved (p<0.05) for 5% (4.95) and 10% (4.82) but also declined (p<0.05) with SNM further inclusion of 15% (4.27) and 20% (4.25). Methane from the 0.2g of the truly digested substrate was (p<0.05) reduced with increasing inclusion by 28.7%, 31.9%, 42.8% and 56.9% in 5%, 10%, 15% and 20% respectively. It was concluded that SNM reduced methanogenesis and low inclusion of 5% can safely be fed without detrimental effects on fermentation.

Key words: gas production, metabolizable energy, methane reduction, organic matter digestibility


The fundamentally shared consent by scientists and National Aeronautics and Space Administration (NASA) that the unmitigated global warming could result to irreversible climate change (Sarkwa et al 2016 ; Darkwah et al 2018) is increasingly worrying. Should this change happen, it might cause a strong negative impact on biodiversity, hence affecting the ecosystem balance which in turn might negatively affect the feed and food resources, impacting life on earth (Migwi et al 2013). Even though the economic importance of ruminants agriculture are inevitable, the effects of Greenhouse gases (GHG) from their activities are substantial as justified by the 17% ruminal methane produced globally, and an averagely 7% gross energy loss caused from each feed taken (Beauchemin et al 2009). Enteric methane results from an inevitable physiology that maintains a virtuous rumen fermentation equilibrium. High fiber diets have been reported to increase the amount of methane produced (Dijkstra et al 2011), and also to favor the production of acetate and butyrate (Knapp et al 2014). Acetate and butyrate are hydrogen production pathways (Janssen 2010), they effect the build-up of hydrogen through oxidation of NADH, NADPH and FADH (Dijkstra et al 2011), releasing (2H) (Janssen 2010) which are then used in the formation of methane (Knapp et al 2014). Manipulating diets through varying compositions and supplementing with concentrates reduces methane production by 2.5 to 15% (Knapp et al 2014). The use of concentrates and plant metabolites like plant fat, tannins, flavonoids and saponins as alternative feed additives in ruminant diets is constantly growing and proving more acceptable and also efficient in mitigating enteric methane production (Wanapat et al 2015). Shea nut (Vitellaria paradoxa) meal contains considerable amounts of these metabolites that range from fats of essential oil with an excellent fatty acid profile, tannins, flavonoids and saponins (Abdul-Mumeen 2013). The fatty acid profile of shea butter nut fat is presented in (Table 1).

Table 1. Fatty acid profile of shea nut butter fat

Fatty acid

Percentage profile

Palmitic acid (C16:0)


Stearic acid (C18:0)


Oleic acid (C18:1n9)


Linoleic acid (C18:2n6)


Arachidic acid (C20:00)


Source:(Okullo et al 2010)

Shea nut inflorescenceShea nut fruitsShea nut unshelled seeds
Shea nut kernelsShea nut mealShea nut butter fat
Photo 1. Shea nut products (Source Choungo et al 2021 ; Global Shea alliance)

This study therefore sought to examine the effect of varying SNM inclusion levels on in-vitrogas production, organic matter digestibility, metabolizable energy and methane reduction properties when included in basal diet of Rhodes grass hay (Chloris gayana) and maize bran. The hypothesis was that supplementation with varying shea nut meal levels would not have a significant effect on in vitro digestibility test and methane reduction.

Materials and methods

Study Location and diet of donor animals

This research was done at Egerton University, Kenya, at the department of Animal Science Laboratory. Rumen liquor was collected from donor sheep that were fed 70% Rhodes grass hay and 30% maize bran basal diet for a period of five weeks.

Ingredient collection and preparation of diets

Shea nut kernels were procured from Katakwi district in the North Eastern Uganda and were processed through mechanical ram pressing to obtain the shea butter and the shea nut meal which the later was used for diet preparations. Diets were formulated to include Rhodes grass hay, maize bran which were all locally sourced from Njoro agro-input shop, and shea nut meal included at five levels of (SNM0) 0% control, (SNM5) 5%, (SNM10) 10%, (SNM15)15% and (SNM20) 20%. Individual ingredients were first ground in a willey mill to pass through a 1 mm sieve then measured according to their inclusion in the different diets. The ingredient inclusion rates are presented in Table 2.

Table 2. Ingredient inclusion levels (g) of formulated diets

Ingredient (g)

Shea nut meal, %






Rhodes grass hay






Maize bran






Shea nut meal






Chemical analysis of diets

Diets were analyzed for proximate, where dry matter was determined by drying samples in an oven at 105oC overnight, ether extract was determined by solvent extraction using standard procedures of AOAC described in (Weende, 2000), nitrogen was analyzed using the Kjeldahl method and protein calculated as N x 6.25 and crude fibre determined as per method of (Van Soest et al 1991). Total tannins were analyzed by total extraction process using 70% aqueous acetone (Makkar 2003).

In vitro
Gas production technique

The rumen liquor was collected in the morning before feed offer using an oral stomach tube (Wang et al 2016). The first approximately 2ml was discarded to elude saliva contamination. The rumen liquor was then directed into a pre-warmed thermal flask and then taken to the laboratory within 20 minutes time. Liquor was filtered using a four layered cheese cloth and mixed with artificial saliva buffer prepared 45 minutes earlier before rumen liquor collection. The artificial buffer was made from 150ml water, 75ml of macro element made from 5.7g (1N NaOH), 6.2g (NH 4 HCO3), 0.6g (Na2HPO4) in a liter of distilled water, 75ml micro element made from 13.2g (CaCl2X 6H2O), 10.0g (MnCl2X 4H2O), 1.0g (CoCl2X 6H2O), 0.8g (Fe3Cl2X 6H2O) in a 100ml distilled water, 0.375ml buffer solution made from 35g (KH2PO4), 4g (MgSO4X 7H2O) in a litter of distilled water, 0.375ml resazurin solution made from 100mg resazurin in 100ml distilled water and 15ml reducing solution made from 2ml of 1 N NaOH and 285mg (Na2S x7 H2O) in 47.5ml distilled water. The solutions were flushed and kept under 39oC water bath in a continuous stirrer. Approximately 0.2g of substrate diets were measured and placed into pre-warmed calibrated glass syringes of 100ml capacity fitted with Vaseline lubricated pistons in triplicate including blanks and 30ml mixture of rumen liquor and buffer medium were added. The syringes were then gently shaken and the clips opened to rid gas, they were then properly closed and syringes placed in a controlled rotor-incubator set at 39oC (Menke and Steingass, 1988).

The readings of gas production were then taken 0, 3, 6, 12, 24, 48, 72 and 96 hours after incubation. Total gas values were corrected from readings for blanks (syringes with no substrate).

Cumulative gas production data was fitted in the exponential equation

Y= a+b (1-exp (-ct)

where; Y = volume of gas produced at time‘t’ (ml), a = gas produced from the immediately soluble fraction (ml), b = gas production from the insoluble fraction, (a+b) = the potential gas production (ml), c = the gas production rate constant for insoluble fraction (b), (ml/hr), t is incubation time (h) model of (Řrskov & McDonald 1979).

A 24hr gas production was corrected by a standard for estimation of organic matter digestibility (OMD) and metabolizable energy (ME).

OMD (%) was calculated using the formula: OMD % = 14.88 + 0,899GP + 0.45CP + XA

where, GP = 24hr net gas production (ml/200g), CP = crude protein (%), XA = ash content (%) method by (Getachew et al 2002)

Metabolizable energy (ME) was calculated using equation;

ME (MJ/Kg/DM) = 2.20 + 0.136 GP + 0.0057 CP + 0.00929 CP2

where; GP = 24 net gas production (ml/200mg), CP = crude protein, ME = metabolizable energy (MJ= mega joules, kg = kilogram DM = dry matter) ( Menke et al 1979 & Menke and Steingass 1988).

Methane analysis

The gas from individual treatments from the in vitrogas production technique procedure after 96hr incubation were sampled and collected into gas vials. They were immediately taken for identification and quantification of methane in the total gas. Methane analysis was performed by GC- flame ionization detection (FID) using gas chromatograph (trace GC ultra, thermo scientific) which was equipped with the methanator and a flame ionization detector using argon as a gas carrier at a flow rate of 25 ml min-1at an oven temperature of 70oC. Samples were then run for 45 minutes and peak areas and retentions of methane were reported by the digital processor. The retention time for the methane gas were then compared to those of known methane and the percentage of methane gas was calculated by expressing each peak area as a percentage of the total area which excludes the area of the solvent peak.

Data was fitted in the statistical model;

Y ij = µ + τi + εij


Yijk= observation of methane emitted associated with effect of i th treatment diet,

µ = the overall mean,

τi = effect of i th treatment diets,

ε ijk = the random error associated with the Yijk

Statistical analysis

A completely randomized design was used to compare gas production and gas production kinetics of diets, organic matter digestibility, metabolizable energy and methane reduction properties of SNM subjected in one way ANOVA using SAS (2002) software package. significantly different means were separated using least significance difference level considered at (p<0.05).

Results and discussion

Effect of SNM inclusion on chemical composition of diets

The chemical composition for diets is as presented in Table 3. CP, EE and total tannins increased with SNM increased inclusion (p<0.05). This findings concurs with (Venkateswarlu et al 2018, Obioha 2018, Konlan et al 2012) who also reported that SNM improved the nutrient composition of diets and could potentially be a good nutrient source for livestock diets.

Table 3. Chemical composition of experimental diets (g/kg DM)



















































Means within the same column with different latter superscripts are different at (p<0.05) DM=Dry matter, ADF= Acid detergent fiber, NDF Neutral detergent fiber, CP= Crude protein, EE= Ether extract, TT= total tannins, ME= Metabolizable energy, CF= Crude protein.

Effect of Shea nut meal varying inclusion levels on in vitro fermentation characteristics

Total gas production (ml) of a 24-hour incubation period was improved at 5% (10.32) but was not (p>0.05) different from 0% (9.86). The 24-hour gas production then declined (p<0.05) with further SNM inclusions of 10% (9.11), 15% (4.28) and 20% (3.98). This result is in agreement with (Kumar et al 2015 ; Venkateswarlu et al 2018) who similarly reported a decline in gas production with increasing SNM inclusion. Metabolizable energy was improved at 5% (4.95) and 10% (4.82), but declined at high SNM inclusions of 15% (4.27) and 20% (4.25) compared to 0% (4.65). This result however contradicts (Kumar et al 2015; Venkateswarlu et al 2018) who reported a linear decline in ME with SNM increasing inclusion as the decline in this study was observed only at higher inclusions of (SNM15) and (SNM20). The variation can be attributed to a very low inclusion rate of 5% and 10% in this study compared to 15% low inclusion in Kumar et al (2015) ; Venkateswarlu et al (2018), as results were comparable when SNM inclusion increased. Also to note is ME results obtained in this study were far low compared to (7.4 & 12) reported in Kumar et al (2015); Venkateswarlu et al (2018) respectively. The variation is possible due to difference in diets used. Organic matter digestibility (OMD) on the other hand decreased with SNM increased inclusion and the result agreed with (Kumar et al 2015; Venkateswarlu et al 2018) who also reported a decline in OMD with increasing SNM inclusion. Plant phenolics such as tannins, saponins and oils are alleged to insert a negative biological effect on microbial growth and activity and therefore negatively impacting nutrient digestibility which directly corelates with gas production (Getachew et al 2004). Tannins even form affinities with feed and microbial proteins therefore diminishing nutrient digestibility (Naumann et al 2017 ; Huang et al 2018) and oils, especially those in the form of free fatty acids, become readily available to microbes thus, becoming harmful (Getachew et al 2004; Martínez Marín et al 2013). It is thus concluded that high SNM inclusions of above10% had negative impact on in vitro fermentation characteristics. The results of in vitro fermentation characteristics (24hr total gas production, OMD and ME) are presented in Table 4

Table 4. Effect of Shea nut meal varying inclusion levels on in vitro gas production, Organic matter digestibility and Metabolizable energy


Shea nut meal (%)

Sig Level







Gas 24 production (ml)
















ME (MJkg-1DM)








SEM= Standard error of the means, abMeans within the row with different letter superscripts are different at (p<0.05)

Effect of Shea nut meal increasing inclusion on 96hr total gas production, methane proportion and %methane reduction

Shea nut meal inclusion improved total gas production of 96-hour incubation at 5% inclusion but was declined (p<0.05) with further inclusions of 10%, 15% and 20%. When the methane in the total gas was quantified, the %methane from 0.200g of truly digested substrate was (p<0.05) reduced with SNM increasing inclusion by 28.7% (5%), 31.9% (10%), 42.8% (15%) and 56.9% (20%). A higher reduction was observed at 20% which was (p<0.05) different from low inclusions of 5%, 10% and 15%. Methane reduction could have been from the action of metabolite compounds in the diets, like ether extract and tannins which directly reduced the total gas produced and hence the proportion of methane gas in the total gas. These findings are consistent with (Venkateswarlu et al 2018; Kumar et al 2015) who too reported that shea nut cake reduced gas and methane production with increasing SNM inclusion. Phenolics from shea nut by products are reported to rid entodinia protozoa that are related with methane production thus exerting antimethanogenic properties that eventually reduce methane (Bhatta et al 2012). The effect of shea nut meal increasing levels on 96hr total gas production, methane proportion and %methane reduction are presented in Table 5.

Table 5. Effect of SNM inclusion on total gas production and methane reduction (ml).


Shea nut meal, %

Sig Level







Total gas production (ml)








CH4 (ml)








% Methane in total gas








CH4 (ml) for 0.02g of truly digested substrate








% Methane reduction








SEM= Standard error of the means, abMeans within the row with different letter superscripts are different at (p<0.05)

Figure 1. Gas production reduced with SNM increasing inclusion in diets Figure 2.  Methane % reduced with SNM increasing inclusion in diets


At high inclusions of 10%, 15% and 20%, SNM had negative effects on fermentation characteristics. However, at a low inclusion of 5%, fermentation was improved. it can be assumed that the meal can safely be fed to ruminants at low inclusion of 5% to improve fermentation, and to reduce methanogenesis. In vivo studies should be done to confirm these findings.


Financial support for this work was provided by Egerton Centre of Excellency in Sustainable Agriculture and Agribusiness Management (CESAAM) for which the authors are grateful to.

Conflict of interest

The authors declare that there is no conflict of interest and agree that the manuscript be submitted for publication.


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