determining metabolizable energy

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Determination of Metabolizable

Energy for Grazing

Raúl Cañas C., Roberto A. Quiroz, Carlos León-Velarde, and Adolfo Posadas



Authors’ affiliations

Raúl Cañas C., Biotecnología Agropecuaria S.A. ( BTA), & Centro Internacional de la Papa(CIP).Roberto Quiroz, Centro Internacional de la Papa (CIP).Carlos León-Velarde, Centro Internacional de la Papa (CIP) & International Livestock ResearchInstitute (ILRI).Adolfo Posadas, Centro Internacional de la Papa (CIP) & Department of Physics, UniversidadNacional Mayor de San Marcos.



SUMMARY

Grazing systems in harsh environments are common throughout the world, and animalproduction is the mainstay of the livelihoods of many resource-poor farmers. Grazing animalsdissipate much of the energy they consume, so reducing the efficiency of its conversion intoanimal products. This inefficiency is associated with the energy spent in exercise and the stressproduced by the low availability of energy in the pasture. This paper presents a method toquantify the dissipation of energy by grazing animals by considering it as a function of available

energy. Such an understanding is required in order to develop management strategies toincrease conversion efficiency.

Introduction

In grazing systems, animal production is obtained, indirectly, from solar energy producedin an abiotic environment. The availability of water, light, and nutrients in the ecotopedetermines the arrangement and the production of the phytocoenosis that, in turn, governsanimal production.

The aim of grazing systems is to allow available energy in the pasture to be harvested,concentrated and transformed into animal production. All these processes are governed by thelaws of thermodynamics and, in this particular case, apply to an open and dissipative systemthat is not in equilibrium.

The first law of thermodynamics–which states that energy cannot be created or

destroyed but can be converted from one form to another–has been widely utilized in animalproduction research. This law is applied in order to describe how much energy is in a food, aswell as in the quantification of how much work an animal can do or how much milk or meat itcan produce.

On the other hand, the second law of thermodynamics–which states that the entropy of increases in the irreversible processes and remains constant in the reversible processes–hasbeen less used to explain the processes which occur in biological systems or in their modeling(Kohn and Boston, 2000). In grazing systems, a direct implication of this law is that not all theenergy provided by the pasture is available for carrying out work or for producing milk or meat.This assertion can be expressed as:

Usable energy = Total energy supplied– unavailable energy

This relationship, in chemical and biological processes, is given by the Gibbs function



T = Absolute temperatureS = Entropy

As a result, a negative relationship exists between the usable energy and the entropy .That is, as entropy increases, there is a decline in the Gibbs free energy. It can be inferred,therefore, that the energy available to carry out work, in terms of generating products, is afunction of the “value” of the energy, and that this in turn depends on entropy.

Clausius conceived the concept of entropy for isolated systems, which can also bedefined as “a measure of disorder or chaos” (Cambel, 1993). In 1865 he arrived at the so-calledentropy function:

[ ]2 / T QdS ∂=

Where:

Q = Thermal energyT = Absolute temperature

According to Clausius, in these isolated systems, macroscopic entropy tends to increaseirreversibly, until a maximum is reached. When this occurs, the energy of the system is at aminimum and the system arrives at its state of equilibrium. This is expressed as:

[ ]3 0≥dS

Where:

dS = 0 when the process is reversible and dS>0 for irreversible processes

In real life, these systems are complex, open and dissipative, and exchange matter,energy, and entropy with their environment. That is, the systems not only produce internalentropy, but also experience an exchange of entropy with other systems or with their environment. The modification of the Clausius equation, to reflect the component of entropyexchange with the environment, was described by Prigogine (Cambel, 1993):

[ ]4 E I T dSdSdS +=

Where:dST = The net or total entropy changedS I = The component describing the entropy change within the system (as described



removed or, in other words, the system is provided with a sufficient quantity of negative entropy,in such a way that a manifestation of order is reached.

It is said (Nicolis and Prigogine, 1977) that for self-organizing systems dST<0. As aresult, the absence of equilibrium might–in relation to the type of mechanism of feedback inoperation–result in order. Therefore, the self-organizing capacity of the system can be modified.

Living systems are regarded as self-organizing, because they respond and adapt toenvironmental changes, within the limitations imposed by the aging process (Cambel, 1993).

Based on what has been stated in the previous paragraphs, we can hypothesize that agrazing system is an open and dissipative system that can be regarded as self-organizing. Thetotal energy of the pasture, which is extracted and concentrated by the grazing animal, is nottotally available for transformation into animal products. This is due to the dissipation of energy,which corresponds to the entropy that is exchanged with the environment, in an irreversibleprocess. The magnitude of this entropy expenditure is a function of the energy value given bythe caloric availability of the pasture and by the caloric density of the animal (Cañas & Gastó,1974). Therefore, when evaluating the behavior of grazing animals, there are at least twoimportant components: (1) the determination of the amount of energy consumed and (2) the

quantification of the energy expended by the animal when obtaining its food. The quantificationof these components is vital if a better understanding is to be achieved of animal productionsystems that involve grazing (Rozas et al., 1978, Hodgson et al., 1994).

The present article describes how to estimate the energy costs incurred by a grazinganimal as it tries to meet its energy demands. These costs include both the energetic costdirectly associated with exercise and movement, and the costs associated with non-physicalactivities. This measure of disorder or chaos –namely the energy cost associated with grazing-is assessed for different animal species, pastures and grazing systems.

Materials and Methods.

In order to calculate the energy cost of grazing for sheep and cattle, relevant data from anumber of previously published studies was compiled and utilized. The data includedinformation on types of grazing systems–rotational and continuous–in different pasture types, inaddition to information on the level of stress suffered by the animals.

The methodology is based on the energy expenditure of an animal when grazing (Cañasand Gastó, 1974). These authors called this requirement the “energy harvesting cost”. Themethod consists of balancing the metabolizable energy consumed through grazing (MEI) withthe energy expenditures for maintenance (MEm) and production (MEp), and with the energyexpended in temperature regulation (MEtr). When MEI > MEm + MEp + MEtr, the difference is



1978). A continuous grazing system was utilized, and it was observed that greater consumptionlevels were obtained with high stocking rates, but that there was also a concomitant reduction in

weight gain. Consumption of dry matter was calculated from measurements of total amount of feces produced per animal (for 6 animals) and from a determination of the digestibility of the drymatter consumed. In vitro digestibility was determined weekly in extrusa samples collectedthrough esophageal cannulated animals. Extrusa samples were used to determine thedigestibility of the selected diet by the in vitro method (Tilley and Terry, 1963).

Using data from another research program (Hull and Meyer, 1957, 1967; Hull et al.,1961) a comparative energy balance was calculated for sheep and Hereford cattle grazing apure stand of alfalfa (Medicago sativa) and a mixture of white clover (Trifolium repens) anddactylis (Dactylis glomerata). It was then possible to compare the energy requirement for grazing of these two animal species for two pasture types.

Data from experiments carried out by Salas and Paladines (1988) were also used. Inthose experiments, Merino sheep grazed mixed pasture composed of Trifolium pratense,Trifolium repens, and Tetrone sp. under two grazing systems continuous and rotational (theanimals returned to the same paddock every three days). Organic matter intake was estimated,individually, for 5 animals using measurements of total feces produced per animal and of the in

vitro digestibility of the organic matter (assessed from extrusa samples obtained fromesophageal cannulated animals). Other response variables measured were grazing time andthe weight of adrenal glands. These measurements allowed an assessment to be made of thestress associated with grazing. Analysis of these data enabled the development of hypothesesabout the physiological bases of the non-physical component of grazing’s energy requirement.

Results and discussion.

Quantifying the energy requirement for grazing (ME gr )

Cañas and Gastó (1974) proposed that the magnitude of the MEgr of animals dependson the availability of forage per unit area, expressed as the metabolizable energy density per pasture area. This concept requires a measure of the concentration of the energy contained inthe pasture per unit of volume. Measuring this is complicated since, in addition to theavailability of forage per unit area, the height of the canopy is also needed in order to obtain areal evaluation of the volume of forage per unit area. In the present study, a simpler method isproposed for assessing the energy requirement for grazing. The concentration of energy in thepasture is expressed as the amount of metabolizable energy of the pasture available per unitarea. This caloric availability is used as a proxy for the metabolizable energy density of thepasture.

Table 1 shows the estimated mean values of dry matter intake (DMI) per animal per day



decrease in the availability of metabolizable energy for production. This difference correspondsto the part of the entropy or chaos that the system dissipates or exchanges with the

environment, i.e. what we have termed the MEgr.

Figure 1 shows a graphic representation of grazing entropy, expressed in terms of themetabolizable energy (kJ) required per live weight unit (kg), and expressed as a function of theavailability of metabolizable energy per hectare (MJ ME/ha). The equation is of the exponentialtype:

( ) [ ]5 * Be AY X += −λ

Where:

Y = Entropy or ME gr ; (kJ/kg body weight).A = The value of (Y–B) when X tends to Ø.B = The asymptotic value of Y when X tends to + ∞.λ = The rate of exchange of Y in relation to X.

The exchange rate λ is not monotonic, and varies exponentially with the availability of metabolizable energy in the pasture. This rate is expressed as:

( ) [ ]6 * *0

1 X K eK X −=λ Where:

X = The availability of metabolizable energy per hectare (MJ ME/ha)K 0 = The value of λ when the availability approaches zero MJ/haK 1 = The exchange rate

By substituting equation [6] in [5], equation [7] is obtained. This equation describes theMEgr in relation to the availability of metabolizable energy in the pasture, per hectare:

( )( ) [ ]7 **1

0 * Be AY X K eK += −

Using equation [7] with the data of Cañas and Paladines (1967) and Rojas andPaladines (1967), the following parameters were obtained:

A = 108.78 (kJ ME/kg body weight)K0 = 1 x 10 –7 (per MJ/ha)

K1 = 0.0008843 (per MJ/ha)B = 33 47 (kJ ME/kg BW)



In the biological interpretation of equation [8] it is proposed that, when the availability of ME is very small (values approaching 0), the MEgr remains approximately constant (with a left

asymptotic value of 142 kJ/kg BW). For an energy availability of less than 9,200 MJ/ha, theexchange rate is 1 x 10-5 % per unitary increase in available energy (MJ/ha). When energyavailability falls within the range of 9,200 to 21,000 MJ/ha, the change rate is 0.08843% per unitof increase in available energy. For values of availability greater than 21,000 MJ/ha (1,850 kgDM/ha, under the conditions found in the experiment from which data was used in this analysis),the MEgr tends to be constant (right asymptotic). That is, the energy requirement for grazingbecomes constant and parallel to the X-axis, with a value of 33.5 kJ per kg of body weight.

In addition, the constant value ‘A+B’ represents the maximum value of the MEgr, or theentropy the animal exchanges with its environment. This entropy seems to have twocomponents. The first component is associated with physical work, attributable to physicalactivity during grazing. The value of 33.5 kJ/kg BW is valid when considering flat land. If thetopography of the land under grazing is irregular (hilly), the asymptotic value of 33.5 should beincreased. The second component is related to loss due to the stress produced by low forageavailability. When the availability of ME is less than 9,200 MJ ME/ha, the MEgr reaches itshighest value, which tends to be constant. It is worth mentioning that, in this work, it isproposed that when B increases due to the topography of the land, the value of the term A + B

remains constant.

In thermodynamic terms, it can be inferred that the grazing system studied is efficientonly when the energy availability in the pasture is equal to, or greater than, 21,000 MJ/ha.Lower energy availabilities produce an increase in the energy dissipation of the system, i.e. anincrease in chaos. In order to return to the level of order required, there is a need to introduceexogenous energy, in the form of feed supplementation.

The type of animal effect

Figure 2 shows a graphic comparison of the energy requirements of different species. Ingeneral, it can be observed that the shape of the response is broadly similar for all species,although the values are different. The shifts are due to particular attributes of each species,some of which are addressed below.

Cattle and sheep. Using data from experiments with two different pasture types (alfalfa and

dactylis), grazed by sheep and cattle under a continuous grazing system (Hull and Meyer, 1957,1967; Hull et al., 1961) the ME gr was estimated following the methodology described above.Comparing the ME gr of sheep and cattle, grazing the same pasture, it was found that theHereford cattle had a ME gr 1.4 and 1.6 times greater than that of Corriedale sheep for thelegume and grass pastures, respectively. Therefore, although the shape of the curves is similar for both species, the cattle response is shifted upwards. This means that, for the same energy

il bili h ME i i d b f f i l 1 5 (T bl 2)



It can thus be suggested that grazing, when forage is scarce, results in energydissipation that is generated by an endocrine effect, and which is associated with a stress

causing situation produced by competition for food. It can be stated that, when the availability of forage is high, the energy invested in the MEgr is explained by the muscular work that thisimplies. However, when food becomes scarce, in addition to the greater physical effort theanimals have to make, they are subject to a situation of stress that demands a substantialquantity of additional energy. This additional expenditure should be calculated, so that it can beincluded as a proportion of the maintenance requirement for grazing. An alternative way of accounting for this dissipation of energy is to include it in what is called the “ecologicalrequirement of maintenance” (Cañas, 1999). This includes the maintenance requirement MEm,in addition to the energy required for the regulation of temperature (MEtr) and the energyrequired to cover the MEgr.

Effect of the grazing system.

As well as having a suprarenal cortex that was of relatively larger proportions, animals incontinuous grazing systems were found to have a greater MEgr than those in rotational grazingsystems (Table 3). This could be explained by the greater stress suffered by animals under

continuous grazing. Salas and Paladines (1988) observed that animals in continuous grazingsystems, with high grazing pressures, exhibited behavior patterns that were different fromanimals in rotational grazing systems, even though the grazing pressure was the same.Animals in the continuous grazing system were constantly moving for more hours of the day,while seeking their food (Table 3). The suprarenal glands of these animals also exhibited agreater mean weight, indicative of a physiological response to the continual stress suffered. Itwas also reported that, when the availability of forage was less than 400 kg DM/ha, the animalsin the rotational grazing system lay down as if they expected to be moved to another site wherethere was more forage. By contrast, the animals under the continuous grazing system, whichhad a similar forage availability, experienced greater stress and consequently had a greater MEgr. The results indicate that, under high grazing pressures, the use of rotational grazing hasadvantages over continuous grazing systems. However, this difference is not observed under low grazing pressures, where there seems to be no advantage inherent in the rotational system.

Thus, rotational grazing is recommended when high grazing pressures are used.Shepherds are usually employed in such a situation. The other option, which is based on theself-organizing characteristic intrinsic to living beings, allows for the adaptation of animals to

environmental changes. Under the above grazing conditions, it is recommended that animalsthat exhibit the lowest symptoms of stress be selected for breeding. This recommendation isbased on the hypothesis that the behavioral response to stress is heritable and that habituationdoes not occur with regard to this effect. Thus, a modification of the pattern asserted as areaction to stress could be achieved if selection is carried out on this basis.

Wi h d hi f f li i i i i di i ll l



steers, selected for maximum production under conditions of maximum forage availability, havea greater MEgr than local breeds of sheep on the Andean Altiplano or Tibetan Yaks.

Equations for different species

We hypothesize that the relationship describing the change of MEgr as a function of energy availability is unique; however, the parameters of this relationship will depend on thespecies and on the animal breed. This hypothesis implies that when evaluating animalperformance, one should be able to separate architecture from functioning. In our particular case, where the response of different animals could be described with one equation withdifferent parameters implies that the animal species studied presented similar function butdifferent architecture (Figure 2).

It is assumed that the inflexion point of all the species considered share a commontangent line. The distance between the inflexion points is, thus, an indication of the adaptabilityof a particular animal species to stressed environments, relative to other species. The columnlabeled “factor” in Table 4 indicates, with respect to the Corriedale sheep, the relativeadaptability of the species considered in this paper. If these assumptions hold true, the

derivative of each equation, with respect to the available energy (Figure 3), shows, for each of the species, the change in entropy expenditure that results from stress. It is worth noting thatthe levels of stress experienced by animal species that have been selected for survival under harsh environments, such as the criollo sheep, yaks or wild boar, are smaller than those of animals selected for better environments.

Improved breeds of animals will not perform well in grazing systems that have energyavailability values below 20,000 MJ ME/ha. Indicators that measure the level of stress shouldbe defined, in order to test the adaptability of crossbred animals to stressed environments.

Implications for Management

Animals grazing grasslands in stressful environments tend to dissipate a high proportionof the energy they consume, due to the low energy availability. The level of dissipation might bereduced through grassland improvement in a few small areas by means of expensiveinterventions. An in situ quantification of the level of stress experienced by the grazing species

might be an approach useful in developing strategic management systems. For example,rotational or shepherd-guided grazing seems to substantially reduce the level of stressexperienced by the animals, and thus the amount of energy dissipated. The use of animals thathave been selected to perform satisfactorily under prolonged energy shortages is highlydesirable. The introduction of “improved” breeds of animals is doomed to failure.



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Table 1. Relationships among forage availability and digestibility, and dry matter consumption,

weight gain, and energy requirements of grazing Corriedale sheep .

Availability Dry Matter Digestibility Weight Energy Requirement

Forage Energy Consumption Organic Matter Gain For Grazing

(kg DM/ha) (MJ EM/ha) (g/day) (%) (g/day) kJ ME/ kg BW

747 5,753 1,345 80 140 138,07

838 6,330 1,254 78 78 142,25

929 7,121 1,392 79 147 138,07

1,135 8,910 1,287 81 141 117,15

1,233 9,820 1,110 82 168 58,57

1,573 12,493 1,151 82 173 66,94

1,707 13,418 1,225 81 213 58,57

1,901 15,087 1,056 82 181 33,47

ME = metabolizable Energy MJ. Source: Cañas & Paladines, 1967

BW = live weight of the animal (kg)



Table 2. Energy balance and the estimation of the energy required for grazing sheep and young bulls on alfalfa or mixed white clover and

ryegrass pastures.

Live

Weigh

t

Weight

Gain (MEI) Energy Requirement (kJ ME/day) ME gr as proportion of : ME gr per BW

kg kg/day kJ/day(ME

m)

kJ/day

(MEp)

kJ/day

(MEgr

)

kJ/dayMEI ME m kJ/kg

Alfalfa

Young Bulls 272 0.755 99,872 36,430 12,824 50,618 0.51 1.39 184

Sheep 34 0.155 15,029 7,657 2,916 4,456 0.30 0.58 130

White Clover – Rye GrassYoung Bulls 272 0.800 125,261 36,430 14,079 74,756 0.60 2.05 276

Sheep 34 0.141 15,866 7,657 2,565 5,644 0.36 0.74 167

MEI = Metabolizable Energy Intake

MEm = Energy Requirement for Maintenance

MEp = Metabolizable Energy Requirement for Production

MEgr = Metabolizable Energy Requirement for Grazing



Table 3. Effect of the grazing system on the energy required for grazing and the

physiological response as determined by the size of organs.

Continuous Grazing

Availability

Rotational Grazing

Availability

High Low High Low

Variables

Forage Availability (kgMS/ha) 5,105 884 5,105 884

Energy Availability (kJ ME/ha) 48,442 8,389 48,442 8,389

Average Animal Weight (kg) 41.4 31.2 37.7 31.6

Energy Consumption (kJ ME) 12,878 13,322 10,682 9,088

Weight Gain (kg/day) 0.27 0.01 0.23 0.01

MEgr (kJ/day) 2,326 8,494 1,410 4,121

MEgr (kJ/kg BW) 54.4 272 37.6 130

MEgr (% ME m) 39 176 25 84

Average Digestibility (%) 70 70 70 70

Total Observation Time (h) 16 16 16 16

Standing w/o eating (hours) 4.52(c) 10.31(a) 4.3(c) 8.57(b)

Lying down (hours) 8.3(a) 3.8(b) 8.35(a) 4.65(b)

Shutdown without eating

(hours) 3.18(a) 1.89(b) 3.35(a) 2.78(ab)

Ruminating (hours) 4 4 4 4Grazing (% of the animals) 27.1 61.7 25.7 52.6

Organ Weights

Thymus (% empty weight) 0.041(b) 0.016(c) 0.057(a) 0.028(bc)

Suprarenal (% empty weight) 0.0052(c) 0.0080(b) 0.0058(c) 0.0096(a)

Suprarenal cortex (% total

gland) 53.06(b) 76.4(a) 43.26(b) 68.4(a)

Heart (% empty weight) 0.48(c) 0.56(a) 0.50(bc) 0.54(ab)

Liver (% empty weight) 1.95(ab) 1.77(bc) 1.97(a) 1.73(c)

Kidneys (% empty weight) 0.31(b) 0.36(a) 0.29(b) 0.33(b)



Table 4. Assessing the parameters of the equation describing the

entropy (ME gr ) of different animal species as a function of

energy availability. (K 0 = 1 x 10 -7 and K1 = 8.843 x 10 -4)

A B K0 K1 Factor (f)

Bovines

Hereford 163.18 50.21 0.0000001 0.0008843 1.5

Yak 66.94 20.92 0.0000001 0.0008843 0.6

Sheep

Corriedale 108.78 33.47 0.0000001 0.0008843 1.0

Criollo high

plateau, Andes 54.39 16.74 0.0000001 0.0008843 0.5

Swine

L. X L.W. 209.20 64.43 0.0000001 0.0008843 1.9

Wild Boar 100.42 30.96 0.0000001 0.0008843 0.9

MEgr = Metabolizable energy required for grazing

L. X L.W. = Landrace and Large White cross



Figure 1. Functional relationship between the entropy (ME gr ) and the available energy

for Corriedale sheep grazing on mixed Phalaris tuberosum and Trifolium

repens pastures.

0

50

100

150

200

250

300

2500 5000 7500 10000 12500 15000 17500 20000 22500 25000 27500 30000

Energy Available (MJ/Ha)Corriedale

M E g r

( K J / K g P

V )



Figure 2 Theoretical curves for ME gr as a function of available energy for different animal species.

1 9



2 0

Figure 3. Derivatives of the theoretical curves for ME gr as a function of available energy for different animal

species.

0 0.5 1 1.5 2 2.5 3

x 104

-7

-6

-5

-4

-3

-2

-1

0

M E g r

V a r i a t i o n

( K J / K g P

V )

Energy Available Variation (MJ/Ha)

- CRIOLLO+ YAKo WILD BOARΔ CORRIEDALE* HEREFORD◊ LXLW

determining metabolizable energy

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