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Partitioning of late gestation energy expenditure in ewesusing indirect calorimetry and a linear regressionapproach

To cite this Article: Kiani, Alishir, Chwalibog, André, Nielsen, Mette O. and Tauson,Anne-Helene , 'Partitioning of late gestation energy expenditure in ewes usingindirect calorimetry and a linear regression approach', Archives of Animal Nutrition,61:3, 168 - 178To link to this article: DOI: 10.1080/17450390701297644URL: http://dx.doi.org/10.1080/17450390701297644

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Partitioning of late gestation energy expenditure in ewesusing indirect calorimetry and a linear regression approach

ALISHIR KIANI1,2, ANDRE CHWALIBOG1, METTE O. NIELSEN1, &

ANNE-HELENE TAUSON1

1Department of Basic Animal and Veterinary Sciences, Faculty of Life Sciences, Copenhagen University,

Denmark, and 2Animal Science Group, Faculty of Agricultural Sciences, Lorestan University, Iran

(Received 2 September 2006; accepted 2 February 2007)

AbstractLate gestation energy expenditure (EEgest) originates from energy expenditure (EE) of development ofconceptus (EEconceptus) and EE of homeorhetic adaptation of metabolism (EEhomeorhetic). Even thoughEEgest is relatively easy to quantify, its partitioning is problematic. In the present study metabolizableenergy (ME) intake ranges for twin-bearing ewes were 220 – 440, 350 – 700, 350 – 900 kJ per metabolicbody weight (W0.75) at week seven, five, two pre-partum respectively. Indirect calorimetry and a linearregression approach were used to quantify EEgest and then partition to EEconceptus and EEhomeorhetic.Energy expenditure of basal metabolism of the non-gravid tissues (EEbmng), derived from the interceptof the linear regression equation of retained energy [kJ/W0.75] and ME intake [kJ/W0.75], was 298 [kJ/W0.75]. Values of the intercepts of the regression equations at week seven, five, and two pre-partum were311, 398, and 451 [kJ/W0.75], respectively. The difference between the intercepts for different weeks wasused to calculate EEhomeorhetic. The remaining part of EEgest was considered to be EEconceptus. Inconclusion, the good agreement between our values of EEconceptus and those in the literature indicatesthe method’s validity.

Keywords: Energy expenditure, gestation, gravid tissues, indirect calorimetry, ovine

1. Introduction

Increased energy expenditure during late gestation (EEgest) originates partly from the energy

expenditure required for the maintenance and growth of conceptus (EEconceptus) (Graham

1964; Langlands & Sutherland 1968; Rattray et al. 1974a) and partly from increased

metabolism in the non-gravid tissues linked with the homeorhetic adaptation of metabolism.

The latter includes the regulation of nutrient partitioning and metabolism during pregnancy

(Bell 1995; Bell & Bauman 1997; Bauman 2000) as well as increased metabolic work in

different maternal organs, such as the liver (Freetly & Ferrell 1997), heart (Rosenfeld 1977),

and mammary gland (Rosenfeld 1977). Energy expenditure associated with this is here

Correspondence: Prof. Andre Chwalibog, Department of Basic Animal and Veterinary Sciences, Faculty of Life Sciences,

Copenhagen University, Groenegaardsvej 7, DK-1870 Frederiksberg C, Denmark. Tel: þ45 3528 3044. Fax: þ45 3528 3020.

E-mail: ac@kvl.dk

Archives of Animal Nutrition

June 2007; 61(3): 168 – 178

ISSN 1745-039X print/ISSN 1477-2817 online ª 2007 Taylor & Francis

DOI: 10.1080/17450390701297644

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termed EEhomeorhetic. However, it has yet not been clearly established to what extent

the increase can be ascribed to EEconceptus and to what extent homeorhetic adaptations of

the maternal metabolism may impact the overall energy expenditure of the pregnant

female.

Traditionally, the comparative slaughter technique (CST) has been used to quantify one

part of the EEgest, namely the EEconceptus. In animal studies using CST, retained energy (RE)

in gravid tissues is technically determined by chemical analysis of the entire gravid tissue

obtained from the slaughtered animal. The energy expenditure is calculated as the difference

between the metabolizable energy (ME) available to the gravid tissues (dietþmobilized body

reserves) and RE (Rattray et al. 1974a). Although CST might seem a relatively accurate

technique for determining EEconceptus, its does not provide any quantitative data regarding

EEhomeorhetic. It is therefore not known to what extent EEhomeorhetic contributes to EEgest and

hence the extent of the error introduced by using CST.

Measuring the O2 consumption of gravid tissues seems a promising method for EEconceptus

estimation (Reynolds et al. 1986; Bell et al. 1987; Bell et al. 2005), though using the method

to estimate EEhomeorhetic simultaneously with EEconceptus is complicated. As well, technical

difficulties with the required surgery restrict the technique’s application, especially in making

repeated measurements in the same animal within short time intervals.

Measuring gaseous exchange (O2 consumption and CO2 and CH4 production in

ruminants) by means of indirect calorimetry, in combination with nitrogen balances, is often

used to quantify whole body energy expenditure (EE) in the whole animal. During late

pregnancy, however, different metabolic rates in different tissues (i.e. non-gravid vs. gravid

tissues) make it difficult to quantify the components of the whole body EE separately. In this

study we aimed to evaluate a new approach in which data from gaseous exchange

measurements analysed using linear regression are used to quantify and partition the

contributions of EEconceptus and EEhomeorhetic to EEgest in twin-bearing ewes during late

gestation.

2. Materials and methods

2.1. Experimental animals and feeding

Twenty twin-bearing Shropshire ewes aged 3 – 4 years were used in the experiment. The ewes

grazed on a grass field during the first and second trimesters of gestation, and thereafter were

shorn and kept indoors. All ewes were fed hay silage (Table I) ad libitum for two weeks to

adapt to the ration, and then at approximately maintenance level for weeks eight and seven

pre-partum. During the last six weeks of gestation, half of the ewes were adequately fed (group

A) according to the National Research Council (NRC 1985) on a diet containing hay silage,

barley (200 g �d71), and a protein supplement (Table I). The protein supplement was

adjusted weekly, increasing from 25 g �d71 to 200 g �d71 over the last six weeks of gestation

in the group A. The restricted group (R) was fed restrictedly in late pregnancy, receiving only

hay silage equivalent to 60% of their energy and protein requirements until the day of

parturition. The rations for individual ewes were adjusted weekly based on the body weight of

the ewe in accordance with NRC (1985). All animals had free access to water, and feed was

offered in two equal amounts at 10:00 and 15:00 h. Body weight was recorded weekly. All

ewes were kept in the same stable (temperature 8 – 148C, humidity 75 – 85%) except when

placed in metabolic cages (59 cm wide, 160 cm long and 80 cm high) for balance trials. All

experimental procedures complied with the guidelines of and were approved by the National

Committee on Animal Experimentation, Denmark.

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2.2. Balance trials and indirect calorimetry

Balances and respiratory measurements were made at week seven, five, and two pre-partum.

Each balance trial lasted for seven days, two days as adaptation period without any collection,

followed by five days of daily faeces, urine (collected in 60 ml 10% sulphuric acid and 10 ml

citric acid), and feed residue collection. Each day, 10% of the total amounts collected were

stored at 7188C for later chemical analyses. An open-air circuit system (temperature 15 –

188C, humidity 65 – 75%, 12-h light-dark cycle) consisting of two respiration chambers was

used to measure 22 h of respiratory gaseous exchange in the middle of each balance trial.

Outgoing air was analysed every 3 min for the concentration of O2 using a paramagnetic

analyser (Magnos 4G, Hartmann & Braun AG, Frankfurt, Germany), and for the

concentrations of CO2 and CH4 using an infrared gas analyser (Uras 3, Hartmann & Braun

AG) (Chwalibog et al. 2004). Although each individual ewe was put in respiration chamber

three times, the data of respiratory gaseous exchange of four ewes at week five pre-partum were

omitted due to technical problems. The gross energy content of feed and faeces was measured

using an adiabatic bomb calorimeter (System C700, IKA Analysentechnik GmbH,

Heitersheim, Germany). The energy content of urine was calculated from the equation

proposed by Hoffmann and Klein (1980). The nitrogen content in feed, faeces, and urine was

determined by means of the Kjeldahl method using the Tecator-Kjeltec system 1026 (Tecator

AB, Hoganas, Sweden) distilling unit.

2.3. Calculations

The whole body energy expenditure in pregnant animals originates mainly from four major

sources: (a) energy cost of basal metabolism of non-gravid tissues (EEbmng), (b) EE associated

with weight change in non-gravid tissues (EEngch), (c) EE of maternal homeorhetic adaptations

to gestation (EEhomeorhetic), and (d) EE of conceptus growth and maintenance (EEconceptus).

Animal activity and thermoregulation are other components that contribute to whole body EE.

The activity level of housed, pregnant ewes is reduced to a negligible amount of less than 20 kJ/

W0.75 according to Agricultural and Food Research Council (AFRC 1993), so in the present

study the animal activity and thermoregulation contributions to total EE have been ignored.

ME intake was obtained by subtracting gross energy loss via faeces (FE), urine (UE), and

methane (CH4E) from gross energy intake. Whole body EE [kJ] was calculated from the daily

gaseous exchange and mean urinary nitrogen excretion (UN) in accordance with Brouwer

(1965), as follows:

EE ½kJ� ¼ 16:18 ½kJ=l� �O2 ½l� þ5:02 ½kJ=l� �CO2 ½l� �2:17 ½kJ=l� �CH4 ½l� �5:99 ½kJ=g� �UN ½g�ð1Þ

Table I. Chemical compositions of the rations ingredients.

Hay silage Barley Protein supplement

Dry matter [%] 58.0 88.7 89.5

Ash [%] 10.0 2.2 5.1

Crude protein [%] 8.2 10.4 45.4

Crude fat [%] 1.6 2.3 5.7

Gross energy [MJ/kg DM] 18.4 18.3 20.9

Intakes and digestibilities of two feeding regimes are presented in Table II.

170 A. Kiani et al.

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Retained energy (RE) was calculated as the difference between ME intake and whole body

EE. EEbmng [kJ/W0.75] was derived from the intercept of a linear regression equation of RE

[kJ/W0.75] on ME intake [kJ/W0.75], where W0.75 was the metabolic body weight of the

pregnant ewe. Conceptus weight (CW) at different times (t) was estimated using the following

equation (Robinson et al. 1977):

CWðtÞ ¼ BrW 2:42� 17:564e�0:0198ðtÞ � 0:00079 Nþ 0:0046 BWewe ð2Þ

where BrW [kg] is total lamb birth weights, N is the number of foetuse(s), and BWewe the

weight [kg] of the ewe at mating time. Non-gravid tissue weight at different times in gestation

was calculated by deducting the estimated conceptus weight (above equation) from the weight

of the pregnant ewe. The difference between non-gravid tissue weights at two different times

was assumed to be the weight change in non-gravid tissues. For EEngch calculation, the ME

values of 23.85 MJ/kg and 20.0 MJ/kg were used for weight gain and weight loss, respectively

(AFRC 1993). Moreover, the efficiencies of the energy use for gain and body reserve

utilization were assumed to be 0.64 and 0.84, respectively (AFRC 1993).

Linear regression equations of RE [kJ/W0.75] on ME intake [kJ/W0.75] were fitted at

different weeks in gestation. The differences between intercept of the separate linear

equations at seven, five, and two weeks pre-partum were used to calculate EEhomeorhetic. The

EEconceptus was obtained by subtracting EEbmng, EEngch, and EEhomeorhetic from whole body

EE. Additionally, the energy cost for the maintenance and growth of 1 kg conceptus was

estimated from linear regression of EEconceptus on conceptus weight [kg].

2.4. Statistical analyses

Simple linear regression analyses for the complete set of observations (n¼ 56) and for

the different weeks pre-partum (seven: n¼ 20, five: n¼ 16, and two: n¼ 20) were performed

using the REG procedure in SAS (Freund et al. 1991). The square root of mean standard

error (RMSE) as an indicator of variance, the standard error of the intercept (Sa),

and regression coefficient (Sb) were reported. Body weight of ewes, estimated conceptus

weight and partitioning of EEg were analysed by a mixed model according to the following

model:

Yik ¼ mþ ai þ uk þ eik;

where Yik was the observed independent variable, m was the overall mean of the observations,

ai was the effect of weeks pre-partum (i¼ seven, five, two), uk was the random ewe effect, and

eik was the residual variance. Because at seven weeks all ewes were fed with same level of

intake, they were excluded in data analysis for digestibilities, and energy and nitrogen

balances, therefore the following mixed model was used:

Yijk ¼ mþ ai þ bj þ ðabÞij þ uk þ eijk;

where Yijk was the observed independent variable, m was the overall mean of the observations,

ai was the main effect of feed intakes (i¼A, R), bj was the effect of weeks pre-partum (j¼five,

two), (ab)ij was the interaction between intake level and weeks pre-partum, uk was the random

ewe effect, and eijk was the residual variance. If the systematic interaction effect did not reach

significance (p5 0.05), the interaction was eliminated from the model. Values were reported

as least square means. The residual variance of the mean was reported as standard errors.

Partitioning energy expenditure in ewes 171

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The means were compared by the Duncan test and any differences with p5 0.05 were

considered significant.

3. Results and discussion

3.1. Energy and nitrogen balances

Energy and nitrogen balances as well as digestibilities in twin-bearing ewes fed an adequate

or restricted energy and protein supply during the last six weeks of gestation are shown in

Table II. Values of energy and nitrogen balances at week seven before feeding treatments were

omitted from the statistical analysis but included in the table for comparison. Ewes (n¼ 20)

were generally in negative energy balance (72.3+ 0.29 MJ/d), but in slightly positive

nitrogen balance (2.6+ 0.53 g/d) in week seven pre-partum. The ration in week seven pre-

partum had been designed to fulfil the dietary requirements of the ewes. The negative energy

balance in week seven pre-partum, when the ewes entered into the experiment, can probably

be ascribed to relatively high metabolic rates due to the lag time for the adjustment of

metabolism and size of visceral and other organs to a lower dietary intake (Koong & Ferrell

1990; Yen 1997). In the present study thermoregulations and the animal activity were not

recorded. Shearing the ewes two weeks before the experiment might have increased the whole

body energy expenditure, hence causing negative energy balance at seven weeks pre-partum.

Furthermore, ewes had their first experience of staying inside the metabolic cages and

respiratory chambers; probably causing more animal activity. Animals’ activity could have

increased the whole body energy expenditure at week seven pre-partum resulting in negative

energy balance.

3.2. Basal energy expenditure in pregnant ewes

To ensure valid regression estimates, it is essential to have observations over a wide range of

ME intakes (Birkett & de Lange 2001). In the present study, ewes were fed at two intake levels

Table II. Digestibilities and energy and nitrogen balances in pregnant ewes fed with either adequate (A) or restricted

(R) energy and protein intake during the last six weeks of gestation.

Weeks pre-partum (P)7 5 2 p-values

Intake level (D) SE A R A R SEM D P D6P

n 20 10 10 10 10

DOM [%]* 78 1.0 79b 77b 85a 78b 1.1 50.001 50.01 0.07

DE [%]# 63 1.0 68b 66b 73a 66c 0.7 50.001 50.01 50.01

DCP [%]x 62 0.9 64b 62bc 70a 61c 0.7 50.001 50.01 50.001

ME [MJ �d71]{ 7.0 0.21 15.3b 9.2d 19.9a 11.9c 0.46 50.001 50.001 0.01

TEE [MJ �d71]{ 9.4 0.27 12.9b 11.2d 14.7a 13.0c 0.44 50.01 50.001 –

RE [MJ �d71]{ 72.3 0.29 3.2b 72.5c 4.9a 70.8c 0.56 50.001 50.01 –

DN [g �d71]þ 13.3 0.35 24.1b 14.9c 34.2a 15.7c 0.58 50.001 50.001 50.001

NU [g �d71]k 10.7 0.56 14.0b 10.8c 16.8a 9.8c 0.55 50.001 0.04 50.01

RN [g �d71]** 2.6 0.53 10.0b 4.2d 17.4a 5.9c 0.38 50.001 50.001 50.001

*DOM, digestibility of organic matter; #DE, digestibility of energy; xDCP, digestibility of crude protein; {ME,

metabolizable energy; {TEE, whole body energy expenditure; {RE, retained energy; þDN, digestible nitrogen; kUN,

nitrogen excreted in urine; **RN, retained nitrogen; Values are least square means. Means without a common

superscript letter within a row differ significantly (p5 0.05).

172 A. Kiani et al.

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and the ME intake range was 220 – 440 kJ/W0.75 at seven, 350 – 700 kJ/W0.75 at five, and

350 – 900 kJ/W0.75 at two weeks pre-partum. The range of ME intake was from adequate

(100%) in accordance with the NRC (1985) to about 50 – 60% of the energy and protein

requirements of twin pregnant ewes.

A simple linear regression equation (n¼ 56) of RE [kJ/W0.75] on ME intake [kJ/W0.75] was

established as follows:

RE ½kJ=W0:75� ¼�298þ0:64 ME ½kJ=W0:75�ðR2¼ 0:83;RMSE¼ 51:7;Sa¼ 18:9;Sb¼ 0:04Þ

ð3Þ

Per definition, RE¼ME7EE. Therefore, the extrapolation of the retained energy to zero ME

intake equals basal energy expenditure; this value, in the present study, was found to equal 298 kJ/

W0.75 (0.3 MJ/W0.75). In the present study the zero-ME intercept was interpreted as the energy

cost of the basal metabolism of the non-gravid tissues. In another words, the value of the energy

expenditure at zero-ME intake was assumed as EE of pregnant ewe in fasted state. Therefore, this

value was expected to be very similar to the fasting heat production determined in other classical

ruminant nutrition studies. The value of 298 kJ/W0.75 was close to the 310 kJ/W0.75 (McNiven

1984) and 320 kJ/W0.75 (Blaxter 1982) values of fasting heat production reported in sheep. Present

value of 298 kJ/W0.75 was somewhat higher than the 238 kJ/W0.75 (Graham 1964) and lower than

the 350 kJ/W0.75 (Rattray et al. 1974a, 1974b) observed in non-pregnant ewes.

The value of 298 kJ/W0.75 was equal to the 294 kJ/W0.75 (Maintenance � km: 420 � 0.7)

estimated from ME/W0.75 intake and metabolic daily live weight gain for non-pregnant ewes

(Robinson et al. 1980). In earlier studies, the energy cost of maintenance for non-gravid

tissues of pregnant animals has been calculated based on the values obtained from non-

pregnant animals. The present study is the first attempt, to our knowledge, to make a direct

estimation using data from pregnant ewes. In spite of relatively good agreement between the

present value of 298 kJ/W0.75 and the previously reported values obtained using non-pregnant

ewes, using the value of 298 kJ/W0.75 for calculating EE of basal metabolism in pregnant ewes

might be disputable. However, it should be kept in mind that the values obtained from non-

pregnant ewes also are not correct values to be used for calculating energy expenditure of

basal metabolism in pregnant ewes because the physiological state of gestation makes

pregnant ewes completely different from non-pregnant sheep. Therefore we suggest that a

value of 0.3 MJ/W0.75 may be used for EEbmng in pregnant ewes.

3.3. Energy expenditure associated with maternal body weight change

Conceptus weight [kg] was estimated in accordance with Equation 2. This Equation 2 was

used because it was derived from a study of a fairly large number of ewes with a wide range of

body weights, ages (3 – 6 years) and litter sizes (twins, triplets) (Robinson et al. 1977).

Furthermore, the ewes’ feed intakes and lambs’ birth weights were similar to those in the

present study. Body weight of the ewes, estimated conceptus weight and non-gravid tissues

weight are shown in Table III.

For both weight gain and loss, EEngch was calculated in order to be able to estimate whole

body EE at zero weight change of non-gravid tissues. Applying the values of AFRC (1993) for

the energy content of weight gain (23.85 MJ/kg) and of weight loss (20.0 MJ/kg) and the

efficiency of utilization of non-gravid tissue weight gain (0.64) and loss (0.84), EEngch was

calculated. This contribution was highest at seven weeks pre-partum (approximately 11%),

and then declined to 7% in weeks five and two pre-partum, hence making a relatively small

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contribution to whole body EE. The higher proportion in week seven reflects the fact that all

the ewes had lost a considerable amount of weight before the feeding treatment commenced.

3.4. Contributions of EEhomeorhetic and EEconceptus to EEgest

The energy expenditure of the homeorhetic adaptation of metabolism in non-gravid tissues

(EEhomeorhetic) was estimated from separate linear regression equations of RE [kJ/W0.75] on

ME intakes [kJ/W0.75] at week seven [(4), n¼ 20], five [(5), n¼ 16)], and two [(6), n¼ 20]

pre-partum using the following equations:

RE ½kJ=W0:75� ¼ �311þ 0:78 ME ½kJ=W0:75� ð4ÞðR2 ¼ 0:28;RMSE ¼ 41:9;Sa ¼ 82:5;Sb ¼ 0:29Þ

RE ½kJ=W0:75� ¼ �398þ 0:83 ME ½kJ=W0:75� ð5ÞðR2 ¼ 0:80;RMSE ¼ 50:6;Sa ¼ 52:6;Sb ¼ 0:11Þ

RE ½kJ=W0:75� ¼ �451þ 0:87 ME ½kJ=W0:75� ð6ÞðR2 ¼ 0:93;RMSE ¼ 38:4;Sa ¼ 36:3;Sb ¼ 0:06Þ

In Equations 4, 5 and 6, the zero-ME intake was assumed as EE of fasted pregnant ewes

at different time of gestation. In these equations, the value obtained at zero ME intake

intercepts represent the energy cost of basal metabolism plus the energy associated

with the homeorhetic adaptation of metabolism (EEbmngþEEhomeorhetic). The values were

found to be 311, 398, and 451 kJ/W0.75 at week seven (4), five (5), and two (6) pre-

partum, respectively. The reason for the low R2 value for (4) at week seven might be due

to a relatively narrow ME intake range [220 – 340 kJ/W0.75]. As mentioned earlier, a wide

range of ME intake is essential to avoid inconsistent values of the regression coefficients

(Birkett & de Lange 2001).

Table III. Body weight of the ewes, estimated conceptus weight and partitioning of late gestation energy expenditure

in ewe at week seven, five and two pre-partum.

Week pre-partum 7 5 2 SEM p-value

n 20 16 20

Body weight [kg] 75.0c 76.6b 81.0a 1.66 50.001

Non-gravid tissues weight [kg] 71.6a 67.2b 65.9c 1.50 50.001

Conceptus weight[kg] 3.2c 8.2b 13.3a 0.27 50.001

EEngch [kJ �d71]* 1.2a 0.4c 0.7b 0.08 50.001

EEgest [kJ/kg conceptus �d71]# 292b 569a 467a 45.3 50.001

EEconceptus [kJ/kg conceptus �d71]{ 184 279 197 46.4 NS

EEhomeorhtic [kJ/kg conceptus �d71]{ 108c 292a 270b 6.6 50.001

*EEngch, Energy expenditure of non-gravid tissue weight changes, applying the values of AFRC (1993) for the energy

content of weight gain (23.85 kJ/g) and of weight loss (20.0 kJ/g) and the efficiency of utilization of non-gravid tissues

weight gain (0.64) and loss (0.84); #EEgest, Energy expenditure of gestation; {EEhomeorhetic, Energy expense of

maternal homeorhesis in non-gravid tissues; {EEconceptus, Energy expenditure of conceptus growth; Estimated values

of conceptus weight [kg] are according to Equation 2. Values are least square means. Within a row, means without a

common superscript letter differ significantly (p5 0.05). NS, Not significant.

174 A. Kiani et al.

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At each time point, EEhomeorhetic was calculated from the difference between the value

of 298 kJ/W0.75, obtained from (3), and the estimated values of 311, 398, and 451 kJ/W0.75

at week seven, five, and two pre-partum, respectively. Eventually, EEconceptus was

obtained by subtracting EEbmng, EEngch, and EEhomeorhetic from the whole body EE for all

individuals.

The total energy expenditure associated with the non-gravid tissues (EEnon-gravid) is the sum

of the EEbmng and EEhomeorhetic. The energy expenditure of homeorhetic metabolism

adaptations per conceptus weight [kg] can be extrapolated as it is shown in Equation 7.

According to Equation 7, the energy expenditure of homeorhetic metabolism adaptations was

found to have increase by 271 kJ per kg conceptus growth during the last six weeks of

gestation [See Figure 1 and Equation 7], as follows:

EEnon-gravid½kJ� ¼ 6906 ½kJ� þ 270:6 ½kJ=kg� CW½kg� ð7Þðn ¼ 60;R2 ¼ 0:78;RMSE ¼ 633;Sa ¼ 177;Sb ¼ 19Þ

Furthermore, the overall energy expenditure of maintenance and growth of one kg conceptus

can also be extrapolated from the slope of the simple linear regression equation of EEconceptus

[kJ] on conceptus weight [kg], as follows (see Figure 2):

EEconceptus½kJ� ¼ 233:8 ½kJ=kg� CW½kg� ð8Þðn ¼ 56;R2 ¼ 0:79;RSME ¼ 1126;Sb ¼ 16Þ

The present value of 234 kJ per kg conceptus is in very good agreement with the 240 kJ/kg

calculated from foetal O2 consumption (assuming 21.1 kJ/l O2) previously reported for sheep

Figure 1. Energy expenditure of the non-gravid tissues in twin-bearing ewes during the late gestation. Linear

regression equation (––): EEnon-gravid [kJ]¼ 270.6 CW [kg]þ6906 , R2¼ 0.78, n¼60, RMSE¼634, Sa¼19,

Sb¼177. Lower and upper predicted values (—) with 95% confidence interval.

Partitioning energy expenditure in ewes 175

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(Bell et al. 1987). However, the present value of 234 kJ/kg conceptus was significantly lower

than the 356 kJ/kg conceptus (Rattray et al. 1974a) estimated via a CST experiment in sheep.

Although there is general agreement that CST provides 5 – 10% higher estimates of energy

expenditure than indirect calorimetry data do (McCracken & Rao 1989; Webster 1989;

Quiniou et al. 1995; Birkett & de Lange 2001), the marked differences in estimated

EEconceptus values require a better explanation. In CST studies, an assumption is made with

respect to the calculation of the energy expenditure of the gravid tissue metabolism. The

differences between the RE in gravid tissues obtained using CST and the available ME, is the

assumed energy expenditure of conceptus growth. This assumption is now known to be

incorrect, as the ME-RE also includes EEhomeorhetic. From the results of the present study and

others (Bell et al. 1987), we conclude that the EEconceptus values obtained using CST may be

markedly overestimated.

Gestation contributes approximately 0.5 MJ (271þ 234 kJ) per kg conceptus to the

increase in late gestation energy expenditure in sheep [(7) and (8)]. The present study showed

that EEconceptus accounted for approximately 46% of EEgest, and hence that 54% of EEgest was

associated with the homeorhetic adaptation of metabolism in non-gravid tissues. In dairy

cows, 44% of the energy expenditure of gestation was found to be attributable to the

EEconceptus (Brody 1945; Ferrell et al. 1976; Reynolds et al. 1986); hence, it was implied

that over 50% of the EEgest in the cow was associated with metabolism of the non-gravid

tissues (Reynolds et al. 1986; Bell et al. 2005). Freetly and Ferrell (1997) estimated that

49% of the EEgest in ewes was attributable to gravid uterine tissues. Among non-gravid

tissues in pregnant ewes, the liver (Freetly & Ferrell 1997), heart (Rosenfeld 1977), and

mammary gland (Rosenfeld 1977) are the main contributors, although the increased energy

expenditure of other tissues, such as the kidneys, pancreas, and skin, may also contribute to

EEhomeorhetic.

Figure 2. Energy expenditure of the conceptus growth in twin-bearing ewes during the late gestation. Linear

regression equation (––): EEconceptus [kJ]¼234 CW [kg], R2¼0.79, n¼56, RMSE¼ 1126, Sb¼ 16. Lower and

upper predicted values (—) with 95% confidence interval.

176 A. Kiani et al.

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4. Conclusion

In conclusion, our study has shown that indirect calorimetry in combination with nitrogen

balance and linear regression analysis is suitable for estimating and partitioning the EEgest into

its components (i.e. EEconceptus and EEhomeorhetic). Furthermore, the results showed that the

increased energy expenditures of both gravid and non-gravid tissues contribute equally to

increased energy expenditure during gestation in sheep. The simplicity of the method and its

ability to produce repeatable measurements of EEconceptus over short time intervals with the

same animal makes it useful, especially for studies of foetal energy metabolism. Based on our

experiment, we recommend that the values of 0.3 MJ/W0.75 for the energy expenditure of

basal metabolism of non-gravid tissues along with 0.5 MJ per kg increase in gravid tissue

weight be used for twin-bearing ewes.

Acknowledgements

This study was financed by the Iranian Ministry of Research, Science and Technology and by

Faculty of Life Sciences, Copenhagen University, Denmark. The authors wish to thank

A. Ali, M. Stubgaard, and K. Thorhauge, and the technical staff at the experimental farm for

their assistance.

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