




































In ternationa l
Scholars
Journa ls

 

African Journal of Pig Farming ISSN 2375-0731 Vol. 7 (3), pp. 001-007, March, 2019. Available online at 
www.internationalscholarsjournals.org © International Scholars Journals 

 

Author(s) retain the copyright of this article. 

 
 

 

Full Length Research Paper 

 

Diversity of methanogens in the hindgut of grower 
and finisher pigs 

 
Zhen Cao1, Xin Di Liao1*, Juan Boo Liang2, Yin Bao Wu1 and Bin Yu3

 
 

1
College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China. 

2
Institute of Tropical Agriculture, Universiti Putra Malaysia, Serdang, 43400, Malaysia. 

3
Agro-Animal Husbandry Co., Ltd. of Shenzhen City, Shenzhen, Guangdong, 518023, China. 

 
Accepted 07 January, 20119 

 
This study examined the diversity of the methanogens in the hindgut of two different weight groups of pigs and 
correlated it with the amount of digested organic carbon (OC) and various components of dietary fiber. Five 
grower (58.9 ± 1.15 kg) and five finisher (89.4 ± 0.85 kg) Duroc × Landrace × Large Yorkshire female pigs were 
allocated into two groups and individually housed in cages. During the experiment, feed intake and fecal output 
were recorded for determination of apparent digestibility of OC, crude fiber (CF), neutral detergent fiber (NDF) and 
acid detergent fiber (ADF). At the end of the digestibility trial, pigs were sacrificed, and the contents of five 
segments of hindgut were sterilely collected to determine diversity of methanogens. Total microbial DNA of the 
hindgut contents was used as template for amplification of the methanogen16S rRNA gene, and the PCR products 
were further subjected to denaturing gradient gel electrophoresis (DGGE) analysis. Results show that the number 
of DGGE bands and Shannon diversity index for the 90 kg pigs were higher (P<0.05) than those for the 60 kg pigs. 
Methanogen communities did not alter along the different segments of the hindgut for the two weight groups. In 
addition, the amount of OC, CF, NDF and ADF digested (g/d) for the 90 kg pigs (1018.77, 23.11, 268.86 and 99.16, 
respectively) was higher (P<0.05) than the respective values for the 60 kg pigs (669.27, 13.77, 222.31 and 69.07), 
indicating that the higher diversity of methanogens in the former group was related to the higher quantity of fiber 
materials fermented in the hindgut. The positive correlation (p<0.05) between number of DGGE bands and 
Shannon diversity index with quantity of digested OC and ADF further reaffirmed the above suggestion. 

 
Key words: Methanogen, pig, Shannon diversity index, polymerase chain reaction-denaturing gradient gel 
electrophoresis (PCR-DGGE). 

 
INTRODUCTION 

 
There has been an intense interest in rumen metha-
nogenic archaea because hydrogen is used by 

methanogen to reduce carbon dioxide (CO2) to methane 

(CH4) gas. It is well documented that diet influenced 
diversity and population of a wide range of bacterial  
 
 
 
*Corresponding author. E-mail: xdliao2002@yahoo.com.cn. Tel: 
+86-20-85280279. Fax: +86-20-85280740. 
 
Abbreviations: OC, Organic carbon; CF, crude fiber; NDF, 
neutral detergent fiber; ADF, acid detergent fiber; PCR, 
polymerase chain reaction; DGGE, denaturing gradient gel 
electrophoresis. 

 
 
 

 
species (Tajima et al., 1999, 2000; Kocherginskaya, et 
al., 2001) and methanogen (Zhou et al., 2007; Zhou et 
al., 2010) in the rumen. Due to its contribution as a 
greenhouse gas and loss of dietary energy for the host 

animals, enteric CH4 production from ruminant livestock 
has been extensively studied (Johnson and Johnson, 
1995; Lassey et al., 1997; Moss et al., 2000; Lassey, 
2007; Andy Thorpe, 2009). On the other hand, studies on 

enteric CH4 emission from pigs are scarce (Jørgensen, 
2007; Ji et al., 2011). However, due to the large popu-

lation of pigs, particularly in China, enteric CH4 emission, 
which has been estimated to represent a 1.2% loss of the 
ingested energy (Monteny et al., 2001) from hindgut 
fermentation in pigs, cannot be ignored. In addition, pigs 

mailto:xdliao2002@yahoo.com.cn


 
 
 

 

are an appropriate animal model for gastrointestinal 
micro-ecological studies of monogastric animals including 
humans.  

Butine and Leedle, (1989) quantified methanogens in 
cecal and colonic contents of pigs using ruminal fluid-
based broth medium and reported that the quantity of 
methanogens in colonic sample was 30 folds higher than 
those in the cecum without determining their diversity. 
Although methanogenic archaea community in pig feces 
and in anaerobic bioreactors fed with pig feces were 
studied using different molecular techniques (Ufnar et al., 
2007; Liu et al., 2009; Zhu et al., 2011; Mao et al., 2011), 
we do not know of any published data on diversity of 
methanogens in different segments of larger intestine (the 
major site of feed fermentation in pigs) of pig using 
polymerase chain reaction-denaturing gradient gel 
electrophoresis (PCR-DGGE).  

Methanogens are phylogenetically placed exclusively 
as members of the domain archaea (Woese, 1987). Due 
to the fact that methanogens are strictly anaerobes and 
difficult to isolate and culture, phenotypic characters are 
often insufficient for their identification (Woese et al., 
1990) and thus molecular ecology techniques, such as 
16S rRNA gene clone libraries, 16S rRNA gene 
fingerprinting including PCR-DGGE, quantitative real-time 
PCR, fluorescent in situ hybridization (FISH) and DNA 
microarray have been used in studies of gastrointestinal 
microbial communities (Amann et al., 1992).  

PCR-DGGE technology was used for the first time to 
analyze microbial diversity in soil by Muyzer, et al. (1993), 
and then applied in micro-ecological studies of animal 
gastrointestinal tract (Tannock et al., 2000; McCracken et 
al., 2001; Donskey et al., 2003). The advantage of PCR-
DGGE is its simplicity, that is, it can rapidly monitor the 
spatial-temporal variability of microbial populations by 
analyzing bands that migrates separately on DGGE gel to 
study the structure and composition of intestinal microbes 
without using the conventional cultivation procedures.  

This study was designed to achieve three objectives: (i) 
To determine and compare the diversity of methanogens 
in hindgut between two different weight groups of pigs 
using PCR-DGGE technique; (ii) to examine whether 
methanogen communities alter along the different 
segments of the hindgut, and (iii) to correlate the amount 
of digested dietary fiber with methanogenic diversity in 
hindgut of pigs. 
 
 
MATERIALS AND METHODS 
 
Animals and feeding 
 
Five grower (mean body weight of 58.9 ± 1.15 kg) and five finisher 
(89.4 ± 0.85 kg) Duroc × Landrace × Large Yorkshire female pigs, 
purchased from a commercial farm near Guangzhou, south China, 
were used for this study. The pigs were randomly assigned into 
individual cages (2.0 m long × 1.0 wide) with five animals as 
replicates per weight group. The experimental pigs were fed ad 
libitum with the same commercial diet as pigs in the respective 
weight groups in the farm, twice daily at 07.00 and 19.00 h. The 

 
 
 
 

 
composition and nutrient content of the experimental diets are 
shown in Table 1. The study, carried out during winter with mean 
outdoor temperature of 20.3°C and the indoor temperature of 
23.7°C, consisted of 11 days of adaptation and three days 
measurement of diet digestibility. Pigs were weighed on day one 
and seven of the experimental period. Fresh drinking water was 
available at all time. 

 

Digestibility and sampling of intestinal content and feces 
 
During the digestibility trial, daily fecal output of each pig was 
collected, weighed and sampled (200 g) and stored at -20°C. Fecal 
samples were separately dried at 60°C for 72 h and ground through 
1 mm and followed by 0.45 mm sieve and the three days fecal 
samples were pooled for individual pig for determination of their 
nutrient contents, that is, organic carbon (OC), crude fiber (CF), 
acid detergent fiber (ADF) and neutral detergent fiber (NDF). 
Nutrient apparent digestibility was calculated as: 
 
Apparent digestibility (%) = (nutrient intake – nutrient excretion) / 
nutrient intake ×100% 
 
and 
 
The amount of digested nutrient (g/d) = (nutrient intake – nutrient 
excretion). 
 
At the end of the digestibility trial, 10 pigs were sacrificed, 
approximately 3 h after feeding. The whole gastrointestinal tract 
was immediately excised; cecum, colon (proximal, medium and 
distal) and rectum were ligated and their contents sterilely collected 
separately into 50 ml sterile centrifuge tubes, and immediately 
stored at -20°C for later determination of diversity of methanogens 
using DGGE procedure. 

 

Chemical analysis 
 
CF, ADF and NDF were determined according to Van Soest et al. 
(1991) using F57 filter bag in an Ankom Fiber analyzer (Ankom220 
Fiber Analyzer, ANKOM Technology, USA). OC of diet and feces 
was analyzed following the method of Bao (2000). 

 

DNA extraction and PCR amplification 
 
The total microbial DNA isolation from large intestinal contents 
were extracted using the E.Z.N.A. stool DNA kit (Omega Corp, 
USA) following the procedure provided by the manufacturer. Total 
DNA obtained was used as a template for PCR amplification of 
small subunit rRNA gene sequences from the large intestinal 
contents for domain archaea community.  

The universal primer pair (Wu et al., 2001) A934F (5’-  
AGGAATTGGCGGGGGAGCA-3’) and 1390R-gc(5’-  
CGCCCGGGGCGCGCCCCGGGCGGGGCGGGGGCACGGGCG 
GTGTGTGCAA-3’, with the underlined sequences are the GC-
clamp region) were used for PCR to amplify 16S rRNA gene from 

members of the domain archaea with a PCR C1000
TM

 thermal 
cycler (Bio-Rad Laboratories, Inc., USA), using the following 
program: Initial denaturation for 5 min at 94°C; 30 cycles of 94°C 
for 30 s, 56°C for 30 s, and 72°C for 2 min; and final extension for 
10 min at 72°C. 

 

DGGE analysis of methanogens 
 
The aforementioned PCR products were subjected to DGGE using 
Bio-Rad D-Code system. PCR products were separated using a 



  
 
 

 
Table 1. Ingredient (%) and chemical composition of the diets for two weight groups of pigs.  

 
 The composition and nutrient content of diet Diet 1 (60 kg grower pigs) Diet 2 (90 kg finisher pigs) 

 Composition   

 Corn (%) 66 69 

 Bean meal (%) 23 20 

 Rapeseed meal (%) 4 4 

 DDGS
a
 (%) 3 3 

 Premix
b
 (%) 4 4 

 Nutrient content   
 Gross energy (MJ/kg) 13.81 13.39 

 Organic carbon (%) 47.04 46.40 

 Crude protein (%) 17.00 16.10 

 Lysine (%) 0.87 0.84 

 Met+Cys (%) 0.54 0.51 

 Calcium (%) 0.60 0.53 

 Phosphorus (%) 0.50 0.45 

 Available phosphorus (%) 0.24 0.19 

 Crude fiber (%) 3.90 3.77 

 Neutral detergent fiber ((%) 17.97 16.23 

 Acid detergent fiber (%) 7.99 7.04 
 

a
DDGS, soluble distiller’s dried grains. 

b
Commercial premix consists of trace elements (Fe, Cu, Zn, Mn, I and Se), vitamin (A, D, 

K, E, B1, B2, B6, B12, C, folic acid and biotin), amino acids (lysine, methionine), Ca, P and salts. 
 

 
6.5% polyacrylamide gel in one Tris-base, acetic acid and EDTA 
(TAE) buffer (40 mM Tris base, 20 mM glacial acetic acid, 1 mM 
EDTA) with a 40 to 65% linear denaturing gradient. The gels were 
initiated by pre-running for 10 min at 200 V and subsequently ran at 
80 V for 21 h at 60°C. Then the gels were stained for 10 to 15 min 
with SYBR Green and photographed using UV transillumination.  

Gel images were analyzed using Labwork 4.0 image analysis 
software. Bands in DGGE fingerprints were automatically identified. 
Lanes were individually converted to filled plots by the program. 
After a background correction was made, the intensity of each band 
was measured by integrating the area under the peak and 
expressing the total area in the lane in percentage, and then the 
Shannon diversity index of different lanes were calculated. The 
formula of Shannon diversity index is as follow: 
 

S  

H 
'   

    pi  ln pi 
i 1 

 
where, S = numbers of band per lane, and Pi = ratio of intensity of 
each band / total bands. 

 

Statistical analysis 
 
Data were analyzed using SPSS 15.0 (2005). T-test was used to 
compare treatment means. Pearson correlation was adopted to 
analyze correlation of parameters, and 0.05 level of probability was 
used to identify differences. 
 

 

RESULTS 

 

16S rRNA gene fragments of methanogens were 

 
 

 

amplified by A934f/1390r primer using total microbial 
DNA as template, and all PCR products were 500 bp. 
PCR products were then used for DGGE analysis. PCR-
DGGE profiles obtained from the large intestinal content 
samples of 60 and 90 kg pigs are presented in Figures 1 
and 2 and Table 2.  

There were 5 DGGE bands for the 60 kg pigs and the 

average Shannon diversity index ranged from 1.33 to 1.38 

between cecum to rectum. The higher Shannon diversity 

index indicated higher diversity. The Shannon diversity 

index of distal colon was lowest (1.33), followed by rectum 

(1.34), proximal colon (1.35), cecum (1.36) and medium 

colon (1.38) the highest. However, no differences (p>0.05) 

were observed in the number of band and Shannon diversity 

index among the five segments, indicating no differences in 

diversity of methanogens throughout in the length of hindgut 

for the 60 kg pigs.  
For the 90 kg pigs, the averaged number of DGGE 

bands in hindgut was 7.48 and Shannon diversity index 
ranged from 1.45 to 1.69 for cecum to rectum. The mean 
number of DGGE bands and Shannon diversity index for 
rectum (6.47 and 1.45) were significantly lower (p<0.05) 
than the other four segments of hindgut, which were not 
statistically different (P>0.05). Results of T-test (Table 2) 
show that the number of DGGE bands and Shannon 
diversity index of 90 kg pigs were higher (p<0.05) than 60 
kg pigs in four segments except rectum.  

Only apparent digestibility of OC was higher (p<0.05) 
for the 90 kg pigs compared to the 60 kg pigs (92.05% 
vs. 89.01%), while no differences were detected in the 



  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
Figure 1. DGGE profiles of 60 kg pig. DGGE, Denaturing gradient  
gel electrophoresis.  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

Figure 2. DGGE profiles of 90 kg pig. DGGE, Denaturing gradient  
gel electrophoresis. 

 

 

apparent digestibility of the other nutrient between the 
two age groups. As expected (due to the heavier weight) 
the amount of digested OC, CF, NDF and ADF (g/d) for 
90 kg pigs was significantly higher (p<0.05) than those for 
60 kg pigs (Table 3). Results of correlation studies show 
that the quantity of digested OC (p<0.01) and ADF 
(p<0.05) significantly correlated with number of DGGE 
bands and Shannon diversity index (Table 4). However, 
digested NDF only correlated (p<0.05) to number of 
DGGE bands but not with Shannon diversity index for the 
two weight groups (Table 4). 
 

 

DISCUSSION 

 

The number of  methanogenic PCR-DGGE  profiles from 

 
 

 

steer fed with different diets were reported to range from 
22 to 28 (Zhou et al., 2010) and 13 for swamp buffaloes 

fed CH4 mitigating agents, such as coconut oil and garlic 

powder (Kongmun et al., 2011) while the present results 
recorded only between four to eight bands for pigs. Mao 
et al. (2011) assessed the diversity of methanogens in 
feces of pig by constructing the 16S rRNA gene clone 
libraries using primers Met86F and Met1340R and 
reported clones consisting of 10 phylotypes which 
belonged to three monophyletic groups. The lower value 
recorded for pigs could be because, being monogastric 
animals, most of the ingested feed are digested in the 
small intestine leaving only the undigested feed to 
undergo fermentation in the hindgut. This is in 

accordance with the much lower CH4 production in pigs 

(Ji et al., 2011) compared to ruminants (Yamaji et al., 



  
 
 

 
Table 2. Number of band and Shannon diversity index between five segments of 60 and 90 kg pigs.  

 
 Segment / index Cecum Pro-colon Med-colon Dis-colon Rectum 

 Number of DGGE band for 60 kg 4.33±0.33
B

 5.13±0.13
B

 5.26±0.18
B

 5.07±0.27
B

 5.33±0.38 

 Number of DGGE band for 90 kg 8.00±0.28
aA

 7.67±0.61
aA

 7.88±0.48
aA

 7.40±0.60
aA

 6.47±0.26
b
 

 Shannon diversity index for 60 kg 1.36±0.01
B

 1.35±0.05
B

 1.38±0.04
B

 1.33±0.05
B

 1.34±0.04 

 Shannon diversity index for 90 kg 1.69±0.07
aA

 1.67±0.01
aA

 1.67±0.05
aA

 1.59±0.04
aA

 1.45±0.11
b
 

 
a,b

, Different superscripts within the same row differed significantly (P<0.05) . 
A, B

, Different superscripts within the same column differed 
significantly (P<0.05). 

 

 

Table 3. Digestibility and daily quantity of OC, CF, NDF and ADF digested for 60 and 90 kg pigs.  
 

 Parameter (kg) Organic carbon Crude fiber Neutral detergent fiber Acid detergent fiber 

 Digestibility (%)     

 60 89.01±0.85
a
 22.09±2.45 77.36±3.32 54.10±3.31 

 90 92.05±0.60
b
 25.71±2.99 69.46±2.66 59.06±2.88 

 Digested nutrients (g/d)     
 60 669.27±5.94

a
 13.77±1.54

a
 222.31±9.97

a
 69.07±4.08

a
 

 90 1018.77±6.66
b
 23.11±2.67

b
 268.86±9.98

b
 99.16±4.77

b
 

 
a, b

Different superscripts within the same column for the same parameter differed significantly (P<0.05). 
 

 
Table 4. The correlation of number of band and Shannon diversity index with amount of digested OC, CF, NDF and ADF (g/d).  

 

 
Parameter 

Digested OC Digested Digested Digested Number of Shannon 
 

 
(g/d) CF (g/d) NDF (g/d) ADF (g/d) band diversity index  

  
 

         

 Digested OC (g/d) 1.000      
 

 Digested CF (g/d) 0.740* 1.000     
 

 Digested NDF (g/d) 0.757* 0.796** 1.000    
 

 Digested ADF (g/d) 0.882** 0.648* 0.696* 1.000   
 

 Number of band 0.910** 0.603 0.740* 0.814* 1.000  
 

 Shannon diversity index 0.868** 0.652* 0.582 0.669* 0.878** 1.000 
 

 
*p<0.05; **p<0.01. OC, Organic carbon; CF, crude fiber; NDF, neutral detergent fiber; ADF, acid detergent fiber. 

 

 

2003; IPCC, 2007; Zhou et al., 2007). Liu et al. (2009) 
studied structure of the bacterial and archaeal community 
in a biogas digester using pig manure as substrate 
obtained from nine archaeal bands in DGGE profile. The 
aforementioned finding further reaffirmed the lower 
diversity of methanogens in pigs compared to ruminants.  

We must emphasize that this study did not carry out 
gene sequence analysis of the DGGE bands to identify 
the species of methanogens in the large intestinal content 
of pigs, thus the diversity of methanogens could have 
been over-or underestimated. However, we believe that 
the simultaneous use of DGGE band and Shannon 
diversity index procedures is sufficient for the primary 
objectives of this study; that is, to compare the diversity of 
methanogens in the hindgut between two different weight 
groups of pigs as well as whether methanogen 
communities alter along the different segments of their 

 
 

 

hindguts.Fermentation of dietary fiber leads predo-
minantly to the production of volatile fatty acids (VFA), 

gases (CO2, H2, and CH4), ammonia and heat. 

Methanogens obtained their energy by reducing CO2 to 

CH4 using H2 (produced by catalyzing the terminal step in 
this anaerobic digestion) as the electron donor. Results 
from our study suggest that the diversity of methanogens 
in hindgut of 90 kg pigs was higher (P<0.05) than that of 
60 kg pigs. Based on the higher quantities of CF, NDF 
and ADF digested (g/d) in the heavier pigs (Table 3), the 
present results seem to suggest that the higher 
methanogens diversity in the 90 kg pigs was related to 
the larger quantity of fermented fiber materials in their 
hindgut. This is further supported by the fact that the 
number of DGGE bands and Shannon diversity index 
were significantly correlated (p<0.05) with the amount of 
digested ADF and OC (Table 4) for the two weight 



 
 
 

 

groups. The aforementioed assumption is in agreement 
with previous study (Noblet and Goff, 2001) which 
reported that the ability of the pig to digest dietary fiber 
improved with the age and live weight and mainly due to 
changes in the composition of microbial population 
(without any reference to methanogens) of its hindgut. 
Similarly, Zhu et al. (1993) and Jensen and Jørgensen 

(1994) reported that the amount of CH4 production 
increased with increasing fiber content in the diet. Recent 
study from our laboratory (Ji et al., 2011) showed that 

daily enteric CH4 production from 90 kg (2.01 g/pig) was 
higher (P<0.05) than that from 60 kg (1.13 g/pig). 
Available information from the literature seems to support 
our view that diversity of methanogenic archaea 
increased with body weight and/or quantity of fermented 
materials in the high gut of pigs.  

No regular pattern of change in the number of DGGE 
bands and Shannon diversity index among the different 
segments of the hindgut in the two weight groups was 
detected, thus indicating no differences in the diversity of 
methanogens along the hindgut of the two weight groups. 
It has been reported that the gastrointestinal tract 
bacterial community structure is susceptible to changes 
by the diet of the host animal (Durmic et al., 1998; Moore 
et al., 1987). For instance, bacterial community can adapt 
to the introduction of high levels of dietary fiber by 
increased growth of bacteria with cellulolytic and 
xylanolytic activities (Varel et al., 1987). However, Jensen 
and Jørgensen (1994) found that the density of 
microorganisms was quite constant throughout the cecum 
and hindgut for pigs received high and low fiber diets, and 

they suggested that CH4 production from pig increased 

with increasing amounts of feed intake and dietary fiber in 
the diet because greater amount of undigested material 
would reached the hindgut and provided more substrates 
for the microorganisms to utilize. None of the afore-
mentioned studies specifically referred to methanogens 
and thus could not be used for direct comparison with the 
present study.  

In conclusion, the number of DGGE band and Shannon 
diversity index for 90 kg pigs were higher (P<0.05) than 
those for 60 kg pigs, thus suggesting higher diversity of 
methanogen in the hindgut of the heavier finisher pigs 
compared to the lighter grower pigs. However, no 
differences in the diversity of methanogen among the 
different sections of the hindgut were detected in both 
weight groups of pigs. The amount of digested OC, CF, 
NDF and ADF of the 90 kg pigs were higher (P<0.05) 
than those of the 60 kg group, indicating that the higher 
diversity of methanogen in the former group was due to 
the higher quantity of fiber materials fermented in the 
hindgut. The significant correlations (p<0.05) between 
number of DGGE band and Shannon diversity index with 
quantity of digested OC and ADF further reaffirmed the 
above suggestion. We do not know of any published data 
on diversity of methanogenic archaea in the different 
segments of large intestine of pigs for direct comparison 

 
 
 
 

 

with the results of the present study. 

 
REFERENCES 
 
Amann RI, Stromley J, Devereux R, Key R, Stahl DA (1992). Molecular 

and microscopic identification of sulfate-reducing bacteria in 
multispecies biofilms. Appl. Environ. Microbiol. 58: 614-623.  

Bao SD (2002). Chemical analysis method of agricultural soil. China 
Agriculture Press, Beijing, China.  

Butine TJ, Leedle JAZ (1989). Enumeration of selected anaerobic 
bacterial groups in caecal and colonic contents of growing-finishing 
pigs. Appl. Environ. Microbiol. 55: 1112-1116.  

Donskey CJ, Hujer AM, Das SM, Pultz NJ, Bonomo RA, Rice LB 
(2003).Use of denaturing gradient gel electrophoresis for analysis of 
the stool microbiota of hospitalized patients. J. Microbiol. Method, 
39(2): 249-256.  

Durmic Z, Pethick DW, Pluske JR, Hampson DJ (1998). Changes in 
bacterial populations in the colon of pigs fed different sources of 
dietary fibre, and the development of swine dietary after experimental 
infection. J. Appl. Microbiol. 85: 574-582.  

IPCC (2007). Climate Change 2007: Synthesis Report: The forth 
assessment report of the intergovernental panel on climate change. 
IPCC, Geneva, Swizerland.  

Jensen BB, Jørgensen H (1994). Effect of dietary fiber on microbial 
activity and microbial gas production in various regions of the 
gastrointestinal tract of pigs. Appl. Environ. Microbiol. 6: 1897-1904.  

Ji ZY, Cao Z, Liao XD, Wu YB, Liang JB, Yu B (2011). Methane 
production of growing and finishing pigs in southern China. Anim. 
Feed. Sci. Technol. 166-167: 430-435.  

Johnson KA, Johnson DE (1995). Methane emissions from cattle. Anim. 
Sci. 73: 2483-2492.  

Jørgensen H (2007). Methane emission by growing pigs and adult sows 
as influenced by fermentation. Livest. Sci.109: 216-219.  

Kocherginskaya SA, Aminov RI, White BA (2001). Analysis of the 
rumen bacterial diversity under two different diet conditions using 
denaturing gradient gel electrophoresis, random sequencing, and 
statistical ecology approaches. Ana```erobe. 7: 119-134.  

Kongmun P, Wanapat M, Pakdee P, Navanukraw C, Yu Z (2011). 
Manipulation of rumen fermentation and ecology of swamp buffalo by 
coconut oil and garlic powder supplementation. Livest. Sci. 1: 84-92.  

Lassey KR (2007). Livestock methane emission: from the individual 
grazing animal through national inventories to the global methane 
cycle. Agr. Forest. Meteorol. 142:120-132.  

Lassey KR, Ulyatt MJ, Martin RJ, Walker CF, Shelton ID (1997). 
Methane emissions measured directly from grazing livestock in New 
Zealand. Atmos. Environ. 31: 2905-2914.  

Liu FH, Wang SB, Zhang JS, Zhang J, Yan X, Zhou HK, Zhao GP, 
Zhou ZH (2009). The structure of the bacterial and archaeal 
community in a biogas digester as revealed by denaturing gradient 
gel electrophoresis and 16S rDNA sequencing analysis. J. Appl. 
Microbiol. 106: 952-966.  

Mao SY, Yang CF, Zhu WY (2011). Phylogenetic analysis of 
methanogens in the pig feces. Curr. Microbiol. 62: 1386-1389.  

McCracken VJ, Simpson JM, Mackie RI, Gaskins HR (2001). Molecular 
ecological analysis of dietary and antibiotic induced alterations of the 
mouse inIestinal microbiota. J. Nutr. 131: 1862-1870.  

Monteny GJ, Groenestein CM, Hilhorst MA (2001). Interactions and 
coupling between emissions of methane and nitrous oxide from 
animal husbandry. Nutr. Cycl. Agroecosyst. 60: 123-132.  

Moore WEC, Moore LVH, Cato EP, Wilkins TD, Kornegay ET (1987). 
Effect of high fiber and high-oil diets on the fecal flora of swine. Appl. 
Environ. Microbiol. 53: 1638-1644.  

Moss AR, Jouany JP, Newbold J (2000). Methane production by 
ruminants: its contribution to global warming. Ann. Zootechnol. 49: 
231-253. 

Muyzer G, Waal EC, Uttrlinden AG (1993). Profiling of complex 
microbial populations by denaturing gradient gel electrophoresis 
analysis of polymerase chain reaction amplified genes coding for 16S 
rRNA. Appl. Environ. Microbiol. 59(3): 695-700.  

Noblet J, Goff GL (2001). Effect of dietary fiber on the energy value of 
feeds for pigs. Anim. Feed. Sci. Technol. 90: 35-52. 



 
 
 

 
SPSS Inc (2005). SPSS Software, Release 11.5. SPSS Inc., Chicago, 

IL. http://www.spss.com/spss/.  
Tajima K, Aminov RI, Nagamine T, Ogata K, Nakamura M, Matsui H, 

Benno Y (1999). Rumen bacterial diversity as determined by 
sequence analysis of 16S rDNA libraries. FEMS. Microbiol. Ecol. 29: 
159-169.  

Tajima K, Arai S, Ogata K, Nagamine T, Matsui H, Nakamura M, 
Aminov RI, Benno Y (2000). Rumen bacterial community transition 
during adaptation to high-grain diet. Anaerobe, 6: 273-284.  

Tannock GW, Munro K, Harmsen H JM, Welling GW, Smart J, Gopal 
PK (2000). Analysis of the fecal microflora of human subjects 
consuming a probiotic product containing Lactobacillus rhamnosus 
DR20. Appl. Environ. Microbiol. 66(6): 2578-2588.  

Thorpe A (2009). Enteric fermentation and ruminant eructation: the role 
(and control?) of methane in the climate change debate. Climatic 
Change, 93: 407-431.  

Ufnar JA, David F, Ufnar S, Wang Y, Ellender RD (2007). Development 
of a swine-specific fecal pollution marker based on host differences in 
methanogen mcrA genes. Appl. Environ. Microbiol. 16: 5209-5217.  

Van Soest PJ, Robertson JB, Lewis BA (1991). Methods for dietary 
fiber, neutral detergent fiber, and nonstarch polysaccharides in 
relation to animal nutrition. Dairy Sci. 74: 3583-3597.  

Varel VH, Robinson IM, Jung HJG (1987). Influence of dietary fiber on 
xylanolytic and cellulytic bacteria of adult pigs. Appl. Environ. 
Microbiol. 53: 22-26.  

Woese CR (1987). Bacterial evolution. Microbiol. Rev. 51: 221-271. Woese 

CR, Kandler O, Wheelis ML (1990). Towards a natural system of 
organisms: proposal for the domains Archaea, Bacteria and Eucarya. 
Proc. Natl. Acad. Sci. 87: 4576-4579. 

  
  

 
 

 
Wu JH, Liu WT, Tseng IC, Cheng SS (2001). Characterization of 

microbial consortia in a terephthalat- degrading anaerobic granular 
sludge system. Microbiology, 147: 373-382. 

Yamaji K, Ohara T, Akimoto H (2003). A country-specific, high 
resolution emission inventory for methane from livestock in Asia in 
2000. Atmos. Environ. 37: 4393-4406.  

Zhou JB, Jiang MM, Chen GQ (2007). Estimation of methane and 
nitrous oxide emission from livestock and poultry in China during 
1949-2003. Energy Policy, 35: 3759-3767.  

Zhou M, Sanabria EH, Guan LL (2010). Characterization of variation in 
rumen methanogenic communities under different dietary and host 
feed efficiency conditions, as determined by PCR denaturing gradient 
gel electrophoresis analysis. Appl. Environ. Microbiol. 12: 3776-3786.  

Zhu CG, Zhang JY, Tang YP, Xu ZK, Song RT (2011). Diversity of 
methanogenic archaea in a biogas reactor fed with swine feces as 
the mono-substrate by mcrA analysis. Microbiol. Res. 1: 27-35.  

Zhu JQ, Fowler VR, Fuller ME (1993). Assessment of fermentation in 
growing pigs given unmolassed sugar beet pulp: a stoichiometic 
approach. Br. J. Nutr. 69: 511-525. 


