Available via license: CC BY
Content may be subject to copyright.
Academic Editor: Clive J. C. Phillips
Received: 19 October 2024
Revised: 13 January 2025
Accepted: 22 January 2025
Published: 23 January 2025
Citation: Processi, E.F.; Rocha, T.C.;
Bendia, L.C.R.; Silveira Filho, C.C.;
Berndt, A.; Souza Aniceto, E.; Oliveira,
T.S.d. Effects of Lipids from Soybean
Oil or Ground Soybeans on Energy
Efficiency and Methane Production in
Steers. Animals 2025,15, 321. https://
doi.org/10.3390/ani15030321
Copyright: © 2025 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license
(https://creativecommons.org/
licenses/by/4.0/).
Article
Effects of Lipids from Soybean Oil or Ground Soybeans
on Energy Efficiency and Methane Production in Steers
Elizabeth Fonsêca Processi 1, Tiago Cunha Rocha 2, Laila Cecília Ramos Bendia 3, Clóvis Carlos Silveira Filho 3,
Alexandre Berndt 4, Elon Souza Aniceto 3and Tadeu Silva de Oliveira 3,*
1Experimental Campus, Universidade Federal Rural do Rio de Janeiro, Av. Lourival Martins Beda, s/n,
Campos dos Goytacazes 28022-560, RJ, Brazil; elizabethufrrj@gmail.com
2Center for Agricultural Sciences, Universidade Estadual da Região Tocantina do Maranhão, R. Godofredo
Viana, 1300, Imperatriz 65900-000, MA, Brazil; tiagoticuro@yahoo.com.br
3Laboratory of Animal Science, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Av. Alberto
Lamego, Campos dos Goytacazes 28013-602, RJ, Brazil; lailabendia@gmail.com (L.C.R.B.);
cloviscsfilho@hotmail.com (C.C.S.F.); elon1995@hotmail.com (E.S.A.)
4EMBRAPA Sudeste, Rod. Washington Luiz, Km 234, Fazenda Canchim, São Carlos 13560-970, SP, Brazil;
alexandre.berndt@embrapa.br
*Correspondence: tsoliveira@uenf.br
Simple Summary: Incorporating fats into the diets of ruminants, like beef cattle, can play a
significant role in reducing methane emissions, which are a major contributor to climate
change. Ruminants naturally produce methane during digestion, mainly through a process
called enteric fermentation. In this study, we altered the fermentation process by adding
fats to the diet, resulting in reduced methane production. Adding dietary fats can alter
this fermentation process, lowering methane production. Moreover, a fat-enhanced diet
can boost animal health, reduce disease risks, and promote overall well-being. Lowering
methane emissions is crucial for climate action since methane is significantly more potent
than carbon dioxide in the short term. Farmers can achieve a practical solution that benefits
both livestock productivity and environmental sustainability by focusing on the inclusion
of fats in ruminant diets. This strategy helps to meet agricultural goals and contributes
positively to combating climate change, making it a beneficial approach for farmers and
the planet.
Abstract: Using lipids can correct energy deficiencies in pasture, boost weight gain in
ruminants, and enhance profitability in farming activities. The objective of this study was
to evaluate the energy losses in feedlot steers fed diets based on corn silage, with or without
the addition of lipids in the form of soybean oil or ground soybean seeds. Eight steers
were randomly assigned to two balanced 4
×
4 Latin squares. The experimental treatments
were as follows: corn silage; corn silage and concentrate feed without lipid addition;
corn silage and concentrate feed with 5% lipid (soybean oil) addition; corn silage and
concentrate feed with 5% lipid (ground soybean seeds) addition. The results showed that
steers fed only corn silage had (p< 0.001) lower dry matter intake (DMI) compared to
other treatments. Gross energy intake and gross energy in feces mirrored DMI trends
(
p< 0.05
). Diets with concentrate supplements resulted in higher digestible energy intake
(
p< 0.05
) and increased gross energy in urine. Notably, adding lipids decreased (p< 0.05)
methane energy losses, although the processing method did not (p> 0.05) impact these
outcomes. In conclusion, adding lipids to the diet reduced energy losses through methane
emissions, increasing steers’ energy efficiency. Therefore, the inclusion of lipids reduced
enteric methane production in steers. Additionally, the method of lipid processing (soybean
oil or ground soybean seeds) did not affect energy partitioning.
Animals 2025,15, 321 https://doi.org/10.3390/ani15030321
Animals 2025,15, 321 2 of 11
Keywords: beef cattle; energy partitioning; mitigation; oil
1. Introduction
Energy is the most limiting nutrient in meat production for weight gain and finishing
carcasses. This limitation is primarily observed in pasture-based production systems, where
intake is insufficient due to the low energy value of most forages [
1
]. Although energy is
vital, it is considered a secondary nutrient, with a greater emphasis on correcting protein
deficiencies in tropical forage. Using supplements can eliminate deficiencies caused by
forages, increase the animals’ weight gain, and maximize profits from the activity [1].
In this context, the success of beef cattle production (finishing carcasses) depends on
integrating various technologies and management practices to improve the animals’ ability
to produce meat more profitably. As the consumer market evolves and demands higher
meat quality, Brazilian beef farms are increasingly focusing on enhancing management
practices, reducing costs, and boosting production efficiency [2].
Given this, energy is essential to sustain all vital body processes, and its deficiency
is shown through a lack of growth, reproductive failure, and the loss of body reserves,
which reduces animal productivity [
3
]. Energy intake has the most significant influence on
the growth rate of meat animals. Diets that minimize energy losses during digestion and
increase energy retention lead to better feed utilization efficiency in cattle [4].
Thus, including lipids to replace part of the starch in the diets of high-performance
animals to meet their high energy needs is essential to avoid nutritional disorders caused
by changes in the fermentation pattern (lipids increase the concentrations of glycerol [via
lipolysis] and propionate, both of which are gluconeogenic precursors) [
5
]. Replacing
starch with lipid sources (soybean oil or ground soybean seeds) in ruminant diets can be an
effective strategy to improve energy efficiency due to the reduction in methane production
and the increase in energy concentration, as lipids provide 2.25 times more calories per
gram compared to starch [
6
]. Additionally, biohydrogenation acts as a hydrogen (H
2
) sink,
reducing the supply of H
2
to Methanogenic archaea, thus decreasing methane production [
7
].
However, lipid availability depends on how lipids are processed in the rumen. Soybean
oil is composed mainly of triglycerides and is a highly available and rapidly digestible
source of lipids, as triglycerides are quickly released in the rumen. Whole soybeans contain
lipids within plant cells, partially protected by cell walls. These walls need to be broken
down for the lipids to become available, affecting both the biohydrogenation and digestion
of the lipids [
5
]. However, excess lipids in the diets of ruminants have negative impacts
on ruminal fermentation. They can reduce microbial activity due to their toxic effects on
ruminal microorganisms, particularly cellulolytic bacteria, which are responsible for fiber
degradation. This can alter the production of volatile fatty acids (VFAs) and ruminal pH
and decrease VFA production, as well as affect the digestion of carbohydrates and fiber. To
ensure the health and productivity of ruminants, it is essential to balance the amount of
lipids in the diet to optimize ruminal fermentation and energy production [8].
We hypothesized that adding lipids from different processing forms (soybean oil or
ground soybean seeds) would affect the energy utilization efficiency of crossbred steers
on feedlot diets. Therefore, the objective of this study was to evaluate the energy losses
of feedlot steers fed diets based on corn silage with or without the addition of lipids from
different processing forms.
Animals 2025,15, 321 3 of 11
2. Materials and Methods
The experiment was conducted in Campos dos Goytacazes, RJ, Brazil (21
◦
45
′
45
′′
S,
41
◦
17
′
06
′′
W, and 13 m a.s.l.). The local climate is classified as Aw, indicating a humid
tropical climate with rainy summers and dry winters, according to the Köppen–Geiger
classification system [9].
2.1. Animals, Experimental Design, and Diets
The Ethics Committee on Animal Use of the Universidade Estadual do Norte Flumi-
nense approved the experiment (Protocol 207/2013).
Eight ruminally cannulated European–Zebu crossbred steers, with an average live
weight of 281.25 kg
±
28.74 kg and 401.06
±
20.48 kg at the beginning and end of the
experiment, respectively, were randomly assigned to two balanced 4
×
4 Latin squares.
The animals were dewormed and housed in individual pens with feeders and drinkers,
where they went through adaptation to the facilities, feeds, and experimental conditions
before the beginning of the trial. Each experimental period lasted 21 days, in which the
first 14 days were the adaptation of the animals to diets and the last 7 days for samplings,
totaling 84 days. Body weight was measured (without fasting) at 8:00 h at the beginning
(1 day) and end (21 days) of each period, and the two values were averaged for each period.
The steers were assigned to their dietary treatments within each Latin square so that each
treatment followed every other treatment only once during the experiment to balance any
residual effects.
Four experimental diets were formulated according to the proportions of ingredients
shown in Table 1. Corn silage (CS), corn silage and concentrate feed without lipid addition
(W/O), corn silage and concentrate feed with 5% lipid addition (soybean oil [SO]), and
corn silage and concentrate feed with 5% lipid addition (ground soybean seeds [SS]) were
used. The chemical composition of the diets is presented in Table 2.
Table 1. The proportions of ingredients in the experimental diets, expressed as % of DM.
Ingredients
Lipid Sources
CS W/O SO SS
Corn silage 100.00 70.00 70.00 70.00
Soybean seeds - - - 16.43
Corn - 16.88 13.12 13.02
Soybean oil - - 3.10 -
Limestone - 0.59 0.57 0.55
Soybean meal - 12.53 13.21 -
DM: Dry matter; CS: corn silage diet; W/O: corn silage and concentrate without lipid addition; SO: corn silage
and concentrate with 5% lipid addition, supplemented with soybean oil; SS: corn silage and concentrate with 5%
lipid addition, supplemented with ground soybean seeds.
Table 2. Chemical compositions of experimental diets.
Composition Treatments (g/kg DM)
CS W/O SO SS
DM (g/kg of
as-fed) 316.5 390.4 389.6 385.0
OM 917.4 930.5 927.2 930.0
CP 54.0 116.5 114.0 113.0
EE 15.2 18.4 47.8 48.4
Ashes 82.6 69.5 72.94 70.0
NDF 521.1 390.4 404.4 383.9
CS: corn silage diet; W/O: corn silage and concentrate without lipid addition; SO: corn silage and concentrate
with 5% lipid addition, supplemented with soybean oil; SS: corn silage and concentrate with 5% lipid addition,
supplemented with ground soybean seeds; DM: dry matter; OM: organic matter; CP: crude protein; EE: ether
extract; and NDF: neutral detergent fiber; all were expressed as g/kg, except DM, which was expressed as-fed.
Animals 2025,15, 321 4 of 11
2.2. Feeding and Feed Intake
Feed was offered twice daily, at 8:00 and 16:00 h, in an amount to allow ad libitum
intake (minimum of 5% orts). Intake was measured daily (8:00 h) by the difference between
offered feed and orts. The feed supply was sampled, and orts were weighed before the
morning feeding. Samples corresponding to 10% ort weights were taken and composited
per animal per period.
Samples of corn silage, concentrates, and orts were partially dried in a forced air oven
at 55
◦
C for 72 h, processed in a knife mill to 1 mm, and evaluated for dry matter (DM)
(AOAC 967.03; [
10
]) and gross energy content (GE) using an adiabatic bomb calorimeter
(Parr 1266, Parr Instruments Co., Moline, IL, USA).
2.3. Feces and Urine Collection
Feces was collected and packed in plastic bags. During five consecutive days
(
15th to 20th experimental day
), the feces was collected every two hours, and the total
amount of excreted feces was weighed and sampled, making up samples per animal per
day and per experimental period. Feces samples were partially dried in a forced air oven
at 55
◦
C for 72 h, processed in a knife mill to 1 mm, and evaluated for dry matter (DM)
(AOAC 967.03; [
9
]) and crude energy content (CE) using an adiabatic bomb calorimeter
(Parr 1266, Parr Instruments Co., Moline, IL, USA).
Urine samples were obtained using funnel collectors attached to the animals. Rubber
hoses coupled to the hoppers led the urine into plastic containers containing 200 mL of sul-
furic acid (H
2
SO
4
) at a 20% concentration. The excreted urine was measured, homogenized,
and filtered through filter paper, and 50 mL samples were collected for five consecutive
days simultaneously with the feces. These samples were stored at
−
15
◦
C for subsequent
analysis, composing samples per day, animal, and experimental period. The gross energy
content was determined using an adiabatic bomb calorimeter in the urine previously dried
in an oven at 55 ◦C.
2.4. Ruminal Methane Emission: Collection of Gases
The daily methane emission was estimated using the tracer gas SF
6
technique [
11
],
following the methodology described by [
12
]. Before the experiment, the animals under-
went adaptation for gas collection (methane and SF
6
). They were equipped with imitation
halters and PVC tanks (yokes) similar in weight and shape to authentic ones but made
of inferior material and without devices for gas collection and storage. The animals were
evaluated with authentic halters and yokes during the gas collection periods.
Ruminal methane emissions were estimated for five consecutive days. Forty-eight
hours before the first evaluation, each animal received an intra-ruminal SF
6
delivery device,
previously standardized for the gas release rate [
12
]. In the morning (8:00 h) of the first
day of each collection period, the animals were individually equipped with the halter and
the yoke containing the devices for collecting and storing the gases. Each day (8:00 h), the
animals were restrained for the following four days, and the yokes were changed since the
devices were calibrated to collect the gases during the 24 h. A baseline yoke was set (1 m
high) in the common area of animals in the feedlot to quantify potential methane emissions
not coming from the experimental animals. This baseline yoke was also changed daily.
After a collection period of five days, the yokes were sent to the Chemical Ecology
Laboratory of Embrapa Meio Ambiente (Jaguariúna-SP) for chromatographic analysis and
the determination of the gases sulfur hexafluoride (SF
6
) and methane (CH
4
). The concen-
trations of the gases CH
4
and SF
6
were determined on a gas chromatograph equipped
with two injectors coupled to two automated valves. One valve was the flame ionization
detector (FID) for reading methane, and the other was the electron capture detector (
µ
ECD)
Animals 2025,15, 321 5 of 11
for reading SF
6
. The capillary columns Plot HP-Al/M (for methane) and HP-MolSiv (for
SF6) were between the injector and the detector.
It was assumed that the emission pattern of SF6 simulated that of CH
4
and that the
quantification of methane gas in the sample was a function of SF
6
flow emitted by the
capsules in the animal [
12
]. The calculation of the emission rate of CH
4
(QCH
4
) was based
on the concentrations of CH
4
and SF
6
measured in the samples and the known rate of
release of SF6(QSF6) according to Equation (1):
QCH4 =QSF6 ×[CH4]/[SF6](1)
Basal concentrations of CH
4
and SF
6
were subtracted from their concentrations in
the baseline yokes. The basal concentrations of SF
6
were typically very low and could
be neglected. However, the CH
4
(approximately 2 mg/L (ppm); [CH
4
]
b
) needed to be
subtracted from the measured concentrations in the yokes of experimental animals ([CH
4
]
y
),
and for that, we used a baseline yoke collecting ambient air, according to Equation (2):
QCH4 =QSF6 ×[CH4]y−[CH4]b/[SF6](2)
2.5. Energy Calculations
The intakes of dry matter (DMI), gross energy (GEI), digestible energy (DEI), and
metabolizable energy (MEI) were calculated by the following equations proposed by [
13
,
14
]:
DMI(kg)=DM of diet (kg)−DM of orts (kg)(3)
GEI(Mcal)=GE of diet (Mcal)−GE of orts (Mcal)(4)
DEI(Mcal/day)=GEI −GEF (5)
MEI(Mcal/day)=DEI −(GEU +GEM)(6)
where GEF is the gross energy of feces, GEU is the gross energy of urine, and GEM is
the gross energy of methane. The energy loss of 0.0133 Mcal/g of CH4 was assumed to
quantify the energy lost in the form of methane [15].
The concentrations of gross energy [GE], digestible energy [DE], and metabolizable en-
ergy [ME] in the diet, expressed as Mcal/kg DM, were obtained according
to Equation (7):
Concentration of energy in diet (Mcal/kg)=energy intake(Mcal)/DMI(kg)(7)
The contents of net energy for maintenance (NEm) and net energy for gain (NEg) in
diets were estimated according to the equations adopted by [13]:
NEm(Mcal/day)=1.37 ME −0.138 ME2+0.0105 ME3−1.12 (8)
NEg(Mcal/day)=1.42 ME −0.174 ME2+0.0122 ME3−1.65 (9)
2.6. Statistical Analysis
In the statistical analysis of data, the following model was used:
yijkl =µ+αi+βj+γk+τl+eijkl
where Y
ijkl
is the observation of Latin Square lon animal kin period junder treatment i;
α1
is the fixed effect of the i-th treatment, i= 1, 2, 3, and 4;
βj
is the random effect of the j-th
period, j= 1, 2, 3 and 4;
γk
is the random effect of the k-th animal, k= 1, 2, 3, 4, 5, 6, 7, and
Animals 2025,15, 321 6 of 11
8;
τl
is the random effect of the l-th Latin square l= 1 and 2; and e
ijkl
is the random error
associated with each observation, assumed to be normal and independently distributed
with mean zero and variance σ2.
The statistical model was fit using the PROC MIXED procedure of SAS (SAS OnDe-
mand for academics), as estimated by the maximum likelihood method and the matrices
of variance–covariance arranged as composite symmetry, auto-regressive correlation, and
random auto-regressive correlation [
16
]. The choice of covariance structure was made
using the Akaike criterion (A ICc) [17,18].
After conducting the analysis of variance, the treatment sum of squares was partitioned
into three orthogonal contrasts: C1—comparing animals that did not receive a concentrate
supplement (CS) with those that received a concentrate supplement (W/O, SO, and SS);
C2—comparing animals that received a supplement without lipids (W/O) with those that
received a supplement with lipids (SO and SS); C3—comparing animals supplemented
with soybean oil (SO) with those supplemented with soybean grains (SS).
3. Results
We observed that treatment had a significant effect (p< 0.05) on all variables except
for gross energy in feces (GEF). Animals that were fed only corn silage (CS) exhibited
lower (p< 0.001) dry matter intake (DMI) compared to those on diets with concentrate
supplements (Table 3). The gross energy intake (GEI) also showed significant differences
(p = 0.003), as did the gross energy in feces (GEF) (p= 0.016), reflecting similar trends to
DMI. Additionally, the digestible energy intake (DEI) was higher (p= 0.002) in animals
fed diets with concentrate supplements (Table 3). However, the gross energy in urine
(GEU), as well as GEU expressed as a percentage of GEI and DEI, was also higher (p< 0.05)
in those same animals. In our analysis of methane, we found that the addition of lipids
significantly reduced (p< 0.05) gross energy in methane (MGE), as well as MGE expressed
as a percentage of both GEI and DEI (Table 3). Furthermore, animals on concentrate
supplement diets showed increases (p< 0.05) in metabolizable energy intake (MEI) and
MEI as a percentage of GEI. MEI as a percentage of DEI increased even more significantly
(p< 0.001) with the inclusion of lipids (Table 3).
Table 3. Energy intake and losses in steers supplemented or not with lipids from different sources
(means ±standard error).
Variable Treatments p-Values
CS W/O SO SS C1 C2 C3
DMI 7.29 ±0.33 8.54 ±0.33 8.44 ±0.33 8.62 ±0.33 <0.001 0.958 0.331
GEI 28.58 ±1.34 32.98 ±1.34 32.99 ±1.34 33.89 ±1.34 0.003 0.753 0.600
GEF 9.78 ±0.51 9.65 ±0.51 9.19 ±0.51 9.93 ±0.51 0.504 0.850 0.169
GEF (%GEI) 34.15 ±1.78 29.56 ±1.78 28.12 ±1.78 29.39 ±1.78 0.016 0.665 0.559
DEI 18.78 ±1.13 23.33 ±1.13 23.80 ±1.13 23.96 ±1.13 0.002 0.705 0.924
UGE 0.40 ±0.06 0.67 ±0.06 0.65 ±0.06 0.56 ±0.06 0.008 0.460 0.323
UGE (%GEI) 1.39 ±0.18 2.04 ±0.18 1.97 ±0.18 1.66 ±0.18 0.003 0.892 0.074
UGE (%DEI) 2.03 ±0.25 2.68 ±0.25 2.84 ±0.25 2.40 ±0.25 0.022 0.807 0.156
MGE 1.81 ±0.18 2.38 ±0.18 1.87 ±0.18 1.86 ±0.18 0.261 0.025 0.985
MGE (%GEI) 6.37 ±0.67 7.08 ±0.67 5.71 ±0.67 5.67 ±0.67 0.487 0.001 0.922
MGE (%DEI) 9.69 ±1.0 10.07 ±1.0 7.95 ±1.0 8.12 ±1.0 0.317 0.027 0.935
MEI 16.57 ±1.07 20.27 ±1.07 21.27 ±1.07 21.54 ±1.07 0.003 0.422 0.871
MEI (%GEI) 58.02 ±2.07 6136 ±2.07 64.21 ±2.07 63.26 ±2.07 0.002 0.122 0.580
MEI (%DEI) 88.25 ±0.97 86.86 ±0.97 89.12 ±0.97 89.78 ±0.97 0.587 <0.001 0.395
CS: corn silage diet; W/O: corn silage and concentrate without lipid addition; SO: corn silage and concentrate
with 5% lipid addition, supplemented with soybean oil; SS: corn silage and concentrate with 5% lipid addition,
supplemented with ground soybean seeds; DMI: dry matter intake in kg/day; GEI: gross energy intake in
Mcal/day; GEF: gross energy in feces in Mcal/day; DEI: digestible energy intake in Mcal/day; UGE: urine gross
energy in Mcal/day; MGE: methane gross energy in Mcal/day; MEI, metabolizable energy intake in Mcal/day;
C1: comparison between animals that did not receive a concentrate supplement (CS) and those that received a
concentrate supplement (W/O, SO, and SS); C2: comparison between animals that received a supplement without
lipids (W/O) and those that received a supplement with lipids (SO and SS); C3: comparison between animals that
received a supplement containing soybean oil (SO) and those that received a supplement containing soybean
grain (SS).
Animals 2025,15, 321 7 of 11
Methane production (CH
4
) was not significantly affected by the lipid processing form
in the diet (p> 0.05) (Table 4). However, the inclusion of lipids in the diet led to a reduction
in methane production (p< 0.05) (Table 4). The concentrate supplements had impacts only
on CH4/MR (p= 0.027) and CH4/DMI (p= 0.016) (Table 4).
Table 4. Methane production by steers supplemented or not with lipids from different sources
(means ±standard error).
Variable
Treatments p-Values
CS W/O SO SS C1 C2 C3
CH4/day 139.3 ±8.65 160.2 ±8.74 131.8 ±8.64 143.3 ±8.54 0.472 0.016 0.289
CH4/year 50.9 ±3.16 59.3 ±3.19 48.0 ±3.15 52.3 ±3.12 0.461 0.014 0.274
CH4/MR 1.6 ±0.25 2.2 ±0.25 1.8 ±0.25 1.7 ±0.24 0.027 0.001 0.925
CH4/DMI 20.3 ±2.52 19.7 ±2.52 16.2 ±2.52 16.2 ±2.52 0.016 0.008 0.893
CS: corn silage diet; W/O: corn silage and concentrate without lipid addition; SO: corn silage and concentrate
with 5% lipid addition, supplemented with soybean oil; SS: corn silage and concentrate with 5% lipid addition,
supplemented with ground soybean seeds; CH
4
/day: methane production in g/kg; CH
4
/year: methane pro-
duction in kg/year; CH
4
/MR: methane production by metabolic rate (BW
0.75
); CH
4
/DMI: methane production
by dry matter intake in g/kg; C1: comparison between animals that did not receive a concentrate supplement
(CS) and those that received a concentrate supplement (W/O, SO, and SS); C2: comparison between animals that
received a supplement without lipids (W/O) and those that received a supplement with lipids (SO and SS); C3:
comparison between animals that received a supplement containing soybean oil (SO) and those that received a
supplement containing soybean grain (SS).
Regarding energy partitioning, the form of lipid processing did not show a significant
effect (p> 0.05) (Table 5). However, animals that were fed lipids in their diet exhibited
increased GE (p< 0.001), DE (p= 0.017), and ME (p= 0.013). In contrast, animals fed diets
containing concentrate supplements displayed higher energy efficiency (p< 0.05) compared
to those that received only corn silage (Table 5).
Table 5. Energy partitioning in steers fed different lipid sources (means ±standard error).
Variables
Treatments p-Values
CS W/O SO SS C1 C2 C3
GE 4.19 ±0.03 4.19 ±0.03 4.31 ±0.03 4.39 ±0.03 0.006 <0.001 0.080
DE 2.76 ±0.09 2.96 ±0.09 3.01 ±0.09 3.01 ±0.06 <0.001 0.017 0.992
ME 2.43 ±0.06 2.58 ±0.06 2.78 ±0.06 2.78 ±0.05 <0.001 0.013 0.954
NEm 1.42 ±0.04 1.59 ±0.04 1.65 ±0.04 1.64 ±0.04 <0.001 0.253 0.927
NEg 0.84 ±0.04 0.98 ±0.04 1.04 ±0.04 1.03 ±0.04 <0.001 0.259 0.891
CS: corn silage diet; W/O: corn silage and concentrate without lipid addition; SO: corn silage and concentrate
with 5% lipid addition, supplemented with soybean oil; SS: corn silage and concentrate with 5% lipid addition,
supplemented with ground soybean seeds; GE: gross energy in Mcal/kg DM; DE: digestible energy in Mcal/kg
DM; ME: metabolizable energy in Mcal/kg DM; NEm: estimated net energy for maintenance in Mcal/kg DM;
NEg: estimated net energy for production in Mcal/kg DM. C1: comparison between animals that did not
receive a concentrate supplement (CS) and those that received a concentrate supplement (W/O, SO, and SS);
C2: comparison between animals that received a supplement without lipids (W/O) and those that received a
supplement with lipids (SO and SS); C3: comparison between animals that received a supplement containing
soybean oil (SO) and those that received a supplement containing soybean grain (SS).
4. Discussion
The increased DMI resulting from using concentrate supplements occurs because
ruminants can adjust their consumption according to their energy requirements. When
they consume a diet rich in concentrates, they can intake more energy without increasing
the volume of feed consumed [
19
]. However, as noted in previous studies [
20
,
21
], multiple
signals are integrated into the brain’s feeding centers to regulate eating behavior. The
liver is a key sensor of the body’s energy status, integrating both short-term and long-term
regulatory mechanisms. It is uniquely positioned to detect available energy and balance
it with nutrient demands. According to [
20
,
21
], increased lipid intake raises the levels of
Animals 2025,15, 321 8 of 11
free fatty acids in the blood, which act as peripheral signals influencing the feed intake
control centers in the hypothalamus. This phenomenon, however, was not observed in this
study. Although not directly measured, it is essential to highlight the role of glucagon in
regulating feed intake. With the inclusion of lipids in the diet, glucagon can modulate food
intake, as the body interprets this condition as a state of high energy availability, thereby
reducing the need for additional feed intake. [
21
]. The reduction in DM of CS can also be
explained by the low CP content of the diet (54 g/kg).
Including concentrate supplements, such as grains rich in starch and protein, which
are more energy-dense than roughage feeds like silage, increases dietary energy intake (GEI,
DEI, and MEI). However, the decreased fecal energy loss as a proportion of GE intake (GEF
[% GEI]) may be due to increased DM digestibility, as concentrates are more digestible than
forages, which also corroborates with the findings of [
22
,
23
]. Our study observed lower
urinary energy loss in animals that received exclusively corn silage compared to those that
received concentrate supplements, whether or not lipid was added. According to [
24
], GEU
primarily results from nitrogenous constituents in urine, including urea, purine derivatives,
creatine and creatinine, and hippuric acid. The formation of hippuric acid in the liver
is driven by the dietary concentration of degradable phenolic acids, typically higher in
forages than in concentrates [
23
,
25
]. The heat of combustion of hippuric acid is higher than
that of urea [
26
]. Although these changes may be quantitatively small, GEU accounts for
approximately one-third to one-half of the energy losses when transitioning from DE to
ME [
21
]. The urinary energy losses, expressed as a percentage of gross energy intake (UGE
[% GEI]) and digestible energy intake (UGE [% DEI]), were higher in animals that received
concentrate supplements, with or without lipid addition, compared to those fed exclusively
corn silage. This difference is likely attributed to the higher nitrogen contents of the
supplemented diets. Interestingly, the addition of lipids to the concentrate and the method
of lipid processing did not influence urinary energy losses. This may be because the lipid
inclusion did not impact DMI or alter the protein contents of the diets. It is important to
note that the availability and processing of lipids in the rumen differ significantly. Soybean
oil contains more rapidly digestible lipids, providing immediate availability, while whole
soybeans release lipids more gradually and require more processing for complete digestion.
The decision to use soybean oil or whole soybeans should be based on the specific needs of
the feeding system.
Methane is a byproduct of ruminal fermentation, produced autotrophically by
methanogenic archaea from carbon dioxide (CO2) and hydrogen (H2) generated during
the fermentation of carbon sources. This methane production represents a loss of gross
energy from the diet. In ruminants, the production of enteric gas is influenced by various
dietary factors, including the type of carbohydrate, forage processing methods, fat supple-
mentation, and the addition of ionophores, among others [
27
,
28
]. Including dietary fat in
the diet can reduce methane production in the rumen by decreasing hydrogen accumu-
lation. This reduction occurs through the biohydrogenation of fatty acids, which lowers
the intake of fermentable organic matter, reduces fiber digestion, and inhibits the activity
of ruminal methanogens and protozoa [
7
,
11
]. The inhibitory effect of fats on methane
production depends on factors such as their concentration, type, and fatty acid composition
and the overall nutrient composition of the diet [
7
]. In the current study, we observed
that adding lipids reduced methane production, decreasing energy losses associated with
methane production. It is worth pointing out that incorporating lipids into ruminant diets
can reduce feed intake, potentially impacting animal productivity [
5
]. However, in this
study, supplemental lipids in concentrate feed did not diminish feed intake compared
to animals fed the concentrate without added lipids. This finding suggests that lipids
directly contribute to the reduction in methane emissions. Specifically, adding lipids to
Animals 2025,15, 321 9 of 11
the concentrate led to a 17.8% decrease in energy lost as methane compared to animals
receiving the concentrate without any added lipids.
Smaller concentrations of GE, DE, and ME were found in the diet consisting only of
corn silage (CS) compared to diets with concentrate supplements (W/O, SO, and SS). The
higher GE contents in diets that included concentrate supplements can be attributed to their
greater amounts of protein and fat, which have caloric equivalents of 5.6 and 9.4 Mcal/kg,
respectively, higher than those of carbohydrates [
29
]. The increased DE in diets with lipid
additions compared to those without can be explained by the superior digestibility of lipids,
which exceeds that of carbohydrates. Additionally, the higher ME concentration in diets
with added lipids (SO and SS) compared to those without lipid addition (W/O) could be
related to reduced energy losses in the form of methane.
The ME provides more valuable information about a diet’s energy content and animals’
energy requirements than DE. This is because ME considers energy losses through urine
and methane in addition to fecal losses. Therefore, ME offers a better estimate of the
dietary energy available to the animal. A factor of 0.82 was established in studies primarily
conducted at maintenance levels of DMI for cattle on high-forage diets. This value has been
used by the Nutrient Requirements of Beef Cattle (NRC 1976, 1984, and 2000). According
to [
30
], this ratio can vary significantly based on factors such as intake, animal age, and feed
source. Similarly, Ref. [
14
] indicates that recent data show a variable relationship between
ME and DE, ranging from 0.82 to over 0.95, depending on cattle age, intake level, and diet
composition [
22
]. In a recent study, we observed that with the inclusion of lipids, this ratio
was 0.92.
5. Conclusions
Adding lipids to the diet (5%) reduces energy losses through methane emissions,
increasing steers’ energy efficiency. This addition decreases enteric methane production
in these animals. Additionally, the way in which the lipids are processed does not impact
energy partitioning.
Author Contributions: Conceptualization, E.F.P. and T.S.d.O.; methodology, T.C.R., L.C.R.B., C.C.S.F.
and A.B.; formal analysis, E.F.P.; investigation, E.F.P., T.C.R., L.C.R.B. and C.C.S.F.; data curation, E.F.P.
and T.S.d.O.; writing—original draft preparation, E.F.P.; writing—review and editing, T.S.d.O. and E.S.A.;
supervision, E.F.P. All authors have read and agreed to the published version of the manuscript.
Funding: Tadeu Silva de Oliveira thanks the Conselho Nacional de Desenvolvimento Científico e
Tecnológico (CNPq) for the grant.
Institutional Review Board Statement: The Ethics Committee on Animal Use of the Universidade
Estadual do Norte Fluminense approved the experiment (Protocol No. 207/2013).
Informed Consent Statement: Not applicable.
Data Availability Statement: The data that support this study will be shared upon request to the
corresponding author.
Acknowledgments: We would like to dedicate this work to the memory of Carlos Augusto de Alencar
Fontes, whose passion for knowledge and commitment to teaching and research inspired countless
generations of students.
Conflicts of Interest: The authors declare no conflicts of interest.
Animals 2025,15, 321 10 of 11
References
1.
Valle, F.R.A.F.; Fontes, C.A.A.; Fernandes, A.M.; Oliveira, T.S.; Processi, E.F. Carcass traits and meat quality of Brangus
×
Zebu
steers in grazing systems receiving supplementation. Sci. Agric. 2021,78, e20190228. [CrossRef]
2.
Nunes, C.L.C.; Pflanzer, S.B.; Souza, J.H.R.; Chizzotti, M.L. Beef production and carcass evaluation in Brazil. Anim. Front. 2024,
14, 15–20. [CrossRef]
3.
Tufarelli, V.; Puvaˇca, N.; Glamoˇci´c, D.; Pugliese, G.; Colonna, M.A. The most important metabolic diseases in dairy cattle during
the transition period. Animals 2024,14, 816. [CrossRef] [PubMed]
4.
McGrath, J.; Duval, S.M.; Tamassia, L.F.M.; Kindermann, M.; Stemmler, R.T.; Gouvea, V.N.; Acedo, T.S.; Immig, I.; Williams, S.N.;
Celi, P. Nutritional strategies in ruminants: A lifetime approach. Res. Vet. Sci. 2018,116, 28–39. [CrossRef] [PubMed]
5.
Ponnampalam, E.N.; Priyashantha, H.; Vidanarachchi, J.K.; Kiani, A.; Holman, B.W.B. Effects of nutritional factors on fat content,
fatty acid composition, and sensorial properties of meat and milk from domesticated ruminants: An overview. Animals 2024,14,
840–878. [CrossRef] [PubMed]
6.
Weiss, W.P.; Pinos-Rodriguez, J.M. Production responses of dairy cows when fed supplemental fat in low- and high-forage diets.
J. Dairy Sci. 2009,92, 6144–6155. [CrossRef]
7. Grainger, C.; Beauchemin, K.A. Can enteric methane emissions from ruminants be lowered without lowering their production?
Anim. Feed Sci. Technol. 2011,166, 308–320. [CrossRef]
8.
Alvares, C.A.; Stape, J.L.; Sentelhas, P.C.; Moraes, J.L.G.; Sparovek, G. Köppen’s climate classification map for Brazil. Meteorol. Z.
2013,22, 711–728. [CrossRef] [PubMed]
9. Jenkins, T.C. Lipid metabolism in the rumen. J. Dairy Sci. 1993,76, 3851–3863. [CrossRef] [PubMed]
10.
Association of Official Analytical Chemist. Official Methods of Analysis Chemistry, 15th ed.; AOAC International: Arlington, VA,
USA, 1990.
11. Johnson, K.A.; Johnson, D.E. Methane emission from cattle. J. Anim. Sci. 1995,73, 2483–2492. [CrossRef]
12.
Primavesi, O.; Frighetto, R.T.S.; Pedreira, M.A.; Lima, M.A.; Berchielli, T.T.; Demarchi, J.J.A.A.; Manella, M.Q.; Barbosa, P.F.;
Johnson, K.A.; Westberg, H.H. Técnica do gás traçador SF6 para medição de campo do metano ruminal em bovinos: Adaptações
para o Brasil. Doc. Embrapa 2004,39, 1–76. (In Portuguese)
13. National Research Council. Nutrient Requirements of Beef Cattle, 6th ed.; National Academies Press: Washington, DC, USA, 1996.
14.
National Academies of Sciences, Engineering, and Medicine. Nutrient Requirements of Beef Cattle, 8th ed.; National Academies
Press: Washington, DC, USA, 2016.
15.
Holter, J.B.; Young, A.J. Methane Prediction in Dry and Lactating Holstein Cows. J. Dairy Sci. 1992,75, 2165–2175. [CrossRef]
[PubMed]
16.
Littell, R.C.; Miliken, G.A.; Stroup, W.W.; Wolfinger, R.D.; Schabenberger, O. SAS
®
for Mixed Models, 2nd ed.; SAS Publishing:
Cary, NC, USA, 2006.
17.
Sugiura, N. Further analysis of the data by Akaike’s Information Criterion and the finite corrections. Commun. Stat. -Theory
Methods 1978,7, 13–26. [CrossRef]
18.
Burnham, K.P.; Anderson, D.R. Multimodel inference: Understanding AIC and BIC in model selection. Sociol. Methods Res. 2004,
33, 261–304. [CrossRef]
19.
Mertens, D.R. Creating a system for meeting the fiber requirements of dairy cows. J. Dairy Sci. 1997,80, 1463–1481. [CrossRef]
[PubMed]
20.
Allen, M.S.; Bradford, B.J.; Oba, M. The hepatic oxidation theory of the control of feed intake and its application to ruminants. J.
Anim. Sci. 2009,87, 3317–3334. [CrossRef] [PubMed]
21.
Allen, M.S. Control of feed intake by hepatic oxidation in ruminant animals: Integration of homeostasis and homeorhesis. Animal
2020,14, s55–s64. [CrossRef] [PubMed]
22.
Hales, K.E.; Brown-Brandl, T.M.; Freetly, H.C. Effects of decreased dietary roughage concentration on energy metabolism and
nutrient balance in finishing beef cattle. J. Anim. Sci. 2014,92, 264–271. [CrossRef] [PubMed]
23.
Fuller, A.L.; Wickersham, T.A.; Sawyer, J.E.; Freetly, H.C.; Brown-Brandl, T.M.; Hales, K.E. The effects of the forage-to-concentrate
ratio on the conversion of digestible energy to metabolizable energy in growing beef steers. J. Anim. Sci. 2020,98, skaa231.
[CrossRef] [PubMed]
24.
Dijkstra, J.; Oenema, O.; Van Groenigen, J.W.; Spek, J.W.; Van Vuuren, A.M.; Bannink, A. Diet effects on urine composition of
cattle and N2 O emissions. Animal 2013,7, 292–302. [CrossRef]
25.
Spek, J.W.; Dijkstra, J.; Van Duinkerken, G.; Bannink, A. A review of factors influencing milk urea concentration and its relationship
with urinary urea excretion in lactating dairy cattle. J. Agric. Sci. 2013,151, 407–423. [CrossRef]
26.
Blaxter, K.L.; Clapperton, J.L.; Martin, A.K. The heat of combustion of the urine of sheep and cattle in relation to its chemical
composition and to diet. Br. J. Nutr. 1966,20, 449–459. [CrossRef]
27.
Moss, A.R.; Jovany, J.; Newbold, J. Methane production by ruminants: Its contribution to global warming. Ann. Zootech. 2000,49,
231–253. [CrossRef]
Animals 2025,15, 321 11 of 11
28.
Na, Y.; Hua, D.; Choi, Y.; Kim, K.H.; Lee, S.R. Effects of feeding level on nutrient digestibility and enteric methane production
in growing goats (Capra hircus) and Sika deer (Cervus nippon hortulorum). Asian-Australas. J. Anim. Sci. 2018,31, 1238–1243.
[CrossRef] [PubMed]
29. Maynard, L.A.; Loosti, J.K.; Huntz, H.F.; Wamer, R.G. Animal Nutrition, 7th ed.; McGraw-Hill: New York, NY, USA, 1979.
30. National Research Council. Nutrient Requirements of Beef Cattle, 7th ed.; National Academies Press: Washington, DC, USA, 2000.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual
author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to
people or property resulting from any ideas, methods, instructions or products referred to in the content.