Q
UANTITATIVE
A
SPECTS OF
R
UMINANT
D
IGESTION AND
M
ETABOLISM
Second Edition
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Q
UANTITATIVE
A
SPECTS
OF
R
UMINANT
D
IGESTION
AND
M
ETABOLISM
Second Edition
Edited by
J. Dijkstra
Animal Nutrition Group
Wageningen University
The Netherlands
J.M. Forbes

Includes index.
ISBN 0–85199–814–3 (alk. paper)
1. Rumination. 2. Digestion. 3. Metabolism. 4. Ruminants. I. Dijkstra, J. (Jan), 1964– II.
Forbes, J. M. (John Michael), 1940–III. France, J. IV. Title.
QP151.Q78 2005
573.3’1963- -dc22
2004029078
ISBN 0 85199 8143
Typeset by SPI Publishing Services, Pondicherry, India
Printed and bound in the UK by Biddles Ltd, King’s Lynn
Contents
Contributors ix
1. Introduction 1
J. Dijkstra, J.M. Forbes and J. France
DIGESTION
2. Rate and Extent of Digestion 13
D.R. Mertens
3. Digesta Flow 49
G.J. Faichney
4. In Vitro and In Situ Techniques for Estimating Digestibility 87
S. Lo
´
pez
5. Particle Dynamics 123
P.M. Kennedy
6. Volatile Fatty Acid Production 157
J. France and J. Dijkstra
7. Nitrogen Transactions in Ruminants 177
J.V. Nolan and R.C. Dobos
8. Rumen Microorganisms and their Interactions 207

A.W. Bell, C.L. Ferrell and H.C. Freetly
21. Lactation: Statistical and Genetic Aspects of Simulating
Lactation Data from Individual Cows using a Dynamic,
Mechanistic Model of Dairy Cow Metabolism 551
H.A. Johnson, T.R. Famula and R.L. Baldwin
vi Contents
22. Mathematical Modelling of Wool Growth at the Cellular
and Whole Animal Level 583
B.N. Nagorcka and M. Freer
23. Voluntary Feed Intake and Diet Selection 607
J.M. Forbes
24. Feed Processing: Effects on Nutrient Degradation
and Digestibility 627
A.F.B. Van der Poel, E. Prestløkken and J.O. Goelema
25. Animal Interactions with their Environment:
Dairy Cows in Intensive Systems 663
T. Mottram and N. Prescott
26. Pasture Characteristics and Animal Performance 681
P. Chilibroste, M. Gibb and S. Tamminga
27. Integration of Data in Feed Evaluation Systems 707
J.P. Cant
Index 727
Contents vii
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Contributors
R.E. Agnew, Agricultural Research Institute of Northern Ireland, Large
Park, Hillsborough BT26 6DR, UK.
D. Attaix, Institut National de la Recherche Agronomique, Unite
´
de Nutri-

The Netherlands.
W.T. Dixon, Department of Agricultural, Food and Nutritional Science,
University of Alberta, Edmonton, Alberta T6G 2P5, Canada.
R.C. Dobos, Beef Industry Centre of Excellence, NSW Department of
Primary Industries, Armidale, 2351 Australia.
ix
F.R. Dunshea, School of Veterinary and Biomedical Sciences, Murdoch
University, Murdoch, WA 6150, Australia; and Department of Pri-
mary Industries, Werribee, VIC 3030, Australia.
G.J. Faichney, School of Biological Sciences A08, University of Sydney,
NSW 2006, Australia.
T.R. Famula, Department of Animal Science, University of California,
Davis, CA 95616-8521, USA.
C.L. Ferrell, USDA ARS, Meat Animal Research Center, Clay Center, NE
68933, USA.
J.M. Forbes, Centre for Animal Sciences, School of Biology, University of
Leeds, Leeds LS2 9JT, UK.
J. France, Centre for Nutrition Modelling, Department of Animal and
Poultry Science, University of Guelph, Guelph, Ontario N1G 2W1,
Canada.
M. Freer, CSIRO Plant Industry, GPO Box 1600, Canberra, ACT 2601,
Australia.
H.C. Freetly, USDA ARS, Meat Animal Research Center, Clay Center, NE
68933, USA.
M. Gibb, Institute of Grassland and Environmental Research, North Wyke
Research Station, Okehampton, Devon EX20 2SB, UK.
J.O. Goelema, Pre-Mervo, PO Box 40248, 3504 AA Utrecht, The Nether-
lands.
G.S. Harper, CSIRO, Division of Livestock Industries, St. Lucia, QLD
4067, Australia.

England, Armidale, 2351 Australia.
E.K. Okine, Department of Agricultural, Food and Nutritional Science,
University of Alberta, Edmonton, Alberta T6G 2P5, Canada.
D.W. Pethick, School of Veterinary and Biomedical Sciences, Murdoch
University, Murdoch, WA 6150, Australia.
N. Prescott, Silsoe Research Institute, Wrest Park, Silsoe, Bedford MK45
4HS, UK.
E. Prestløkken, Felleskjøpet Fo
ˆ
rutvikling, Department of Animal and Aqua-
cultural Sciences, Agricultural University of Norway, PO Box 5003,
N-1432 A
˚
s, Norway.
D. Re
´
mond, Institut National de la Recherche Agronomique, Unite
´
de
Nutrition et Me
´
tabolisme Prote
´
ique, Theix, 63122 Ceyrat, France.
C.K. Reynolds, Department of Animal Sciences, The Ohio State University,
OARDC, 1680 Madison Avenue, Wooster, OH 44691-4096 USA.
J.B. Russell, Agricultural Research Service, USDA and Department of
Microbiology, Cornell University, Ithaca, NY 148531, USA.
I.C. Savary-Auzeloux, Institut National de la Recherche Agronomique,
Unite

3
1
Animal Nutrition Group, Wageningen Institute of Animal Sciences,
Wageningen University, P.O. Box 338, 6700 AH Wageningen,
The Netherlands;
2
Centre for Animal Sciences, School of Biology,
University of Leeds, Leeds LS2 9JT, UK;
3
Centre for Nutrition Modelling,
Department of Animal & Poultry Science, University of Guelph, Guelph,
Ontario N1G 2W1, Canada
Preamble
Ruminant animals have evolved a capacious set of stomachs that harbour
microorganisms capable of digesting fibrous materials, such as cellulose. This
allows ruminants to eat and partly digest plants, such as grass, which have a
high fibre content and low nutritional value for simple-stomached animals.
Thus, animals of the suborder Ruminantia, being plentiful and relatively easy
to trap, became prime targets of hunters and, eventually, were domesticated
and farmed. Today, ruminants account for almost all of the milk and approxi-
mately one-third of the meat production worldwide (Food and Agriculture
Organization, 2004) (Fig. 1.1). It is not surprising, then, that a great deal of
research has been carried out on the digestive system of ruminants, leading to
studies on the peculiarities of metabolism that cope with the unusual products
of microbial digestion. The reading list at the end of this chapter gives some of
the books in which the biology of ruminants is reviewed.
As qualitative knowledge increased, so it became possible to develop
quantitative approaches to increase understanding further and to integrate
various aspects. Initially this was achieved by more complex statistical analysis,
but in recent years this has been supplemented by dynamic mathematical

estimate the rate and extent are described in Chapters 2 and 4, respectively.
The microbial activity in the reticulorumen gives the host the ability to eat
and utilize forages. Chapters 8 and 9 review the dynamics and energetics of this
microbial population. Most of the material digested in the rumen yields short-
chain fatty acids, known as volatile fatty acids (VFA), which are absorbed
through the rumen wall. Acetic acid is produced in the greatest quantities,
around 20–50 moles per day in dairy cows, while propionic acid is usually
produced at about one-third of the rate of acetic acid. Butyric acid accounts for
around 10% of the total acid production, while valeric and isovaleric acids each
Beef and veal
Buffalo
Goat
Mutton and lamb
Other ruminants
Non-ruminants
Non-ruminants
Buffalo
Sheep
Goat
Cow
Fig. 1.1. Relative contribution of various groups of ruminants and non-ruminants to the
production of meat (left graph) and milk (right graph) worldwide in 2003 (Food and Agriculture
Organization, 2004).
2 J. Dijkstra et al.
form about 1% to 2%. The ratio of acetic:propionic acids is higher for forage
diets than for concentrate diets (see Chapters 6 and 10).
Much of the dietary protein, as well as the urea that is recycled via the
saliva, is metabolized to ammonia. Both ammonia and amino acids or small
peptides are available for microbial protein synthesis (see Chapters 7 and 10).
Omasum

Ro
C
V
D
DB
VB
Fig. 1.2. Movement of digesta within the
reticulorumen, omasum and abomasum:
oesophagus (E), reticulum (R), reticulo-
omasal orifice (Ro), cranial sac (C), dorsal
rumen (D), ventral rumen (V), dorsal blind
sac (DB), ventral blind sac (VB), omasum (O)
and abomasum (A).
Introduction 3
increases in digesta flow that occur with increasing intake are the result of
increases in the amount of digesta propelled per contraction rather than in the
number of contractions. Digestion in the small intestine is similar to that in
simple-stomached animals.
The large intestine
The flow of digesta to the caecum and proximal colon from the ileum is intermit-
tent and can be followed by periods of quiescence, which may range from 30 min
to 5 h. Digesta in the caecum and proximal colon are subjected to both peristaltic
and antiperistaltic contractions so that digesta are mixed as well as being moved
towards the distal colon. There is further VFA production and absorption in the
large intestine but its main function is probably the absorption of water.
The flow of digesta through the distal colon differs between sheep and
cattle. In sheep, bursts of spiking activity, which last less than 5 s and do not
propagate, result in the segmenting contractions that are responsible for the
formation of faecal pellets as the digesta pass through the spiral colon. By
contrast, in cattle bursts of spiking activity of long duration propagate along the

agricultural production systems. However, the slow rate of digestion means that
feed particles remain in the rumen for long periods and rumen capacity
becomes a limiting factor to further intake; the slower and less complete the
digestion of a particular feed, the greater is the importance of physical factors,
compared to metabolic factors, in the control of feed intake (see Chapter 23).
The ability of ruminants to select a balanced diet from imbalanced foods offered
in choice has become better established since publication of the first edition of
this book and modelling of intake has been extended to food choice in this
chapter.
Feeding large amounts of rapidly fermented carbohydrate produces
sudden changes in acid and gas production that are sometimes beyond the
adaptive ability of the animal. The pH of rumen fluid falls from a normal level
of 6.0 to 6.2, causing cessation of motility and reduction in feed intake.
Excessive gas production causes bloat, under some circumstances, and a re-
duced acetate:propionate ratio depresses milk fat synthesis. A consequence
of microbial protein synthesis in the rumen is that some of the protein in
the diet can be replaced by non-protein nitrogen, typically urea. High-quality
protein sources can be protected against ruminal degradation to obtain
more benefit from their superior balance of amino acids or to better match
the amount of degradable carbohydrates. Moreover, and depending on the
starch degradation characteristics, starch sources may be protected against
ruminal degradation to avoid low pH levels, or starch degradation may be
enhanced to promote energy supply to the microbes in the rumen. The effect
of various technological treatments on nutrient digestibility is discussed in
Chapter 24.
These adaptations and their metabolic consequences have important
effects on productive processes; these are discussed in Chapter 19 (growth),
Chapter 20 (pregnancy), Chapter 21 (lactation) and Chapter 22 (wool).
In the developed world, cattle are often kept in automated, intensive
systems. In these intensive systems, a much better management control over

(levels of organization), and to review the different types of model that may
be constructed.
Organizational hierarchy
Biology, including ruminant physiology, is notable for its many organizational
levels. It is the existence of the different levels of organization that give rise to
the rich diversity of the biological world. For the animal sciences, a typical
scheme for the hierarchy of organizational levels is shown in Table 1.1. This
scheme can be continued in both directions and, for ease of exposition, the
different levels are labelled . . . , i þ 1, i, i À 1, . . . . Any level of the scheme can
be viewed as a system, composed of subsystems lying at a lower level, or as a
subsystem of higher level systems. Such a hierarchical scheme has some
important properties:
1. Each level has its own concepts and language. For example, the terms of
animal production such as plane of nutrition and liveweight gain have little
meaning at the cell or organelle level.
Table 1.1. Levels of organization.
Level Description of level
i þ 3 Collection of organisms (herd, flock)
i þ 2 Organism (animal)
i þ 1 Organ
i Tissue
i À 1 Cell
i À 2 Organelle
i À 3 Macromolecule
6 J. Dijkstra et al.
2. Each level is an integration of items from lower levels. The response of the
system at level i can be related to the response at lower levels by a reductionist
scheme. Thus, a description at level i À 1 can provide a mechanism for
behaviour at level i.
3. Successful operation of a given level requires lower levels to function

modelling voluntary feed intake in a growing, non-lactating ruminant. An
empirical approach to this problem would be to take a data set and fit a linear
regression equation, possibly:
I ¼ a
0
þ a
1
W þ a
2
dW=dt þ a
3
D (1:1)
Introduction 7
where I denotes the intake, W, liveweight, D, measure of diet quality and
a
0
, a
1
, a
2
,anda
3
are parameters.
We note that level i behaviour (intake) is described in terms of level i
attributes (liveweight, liveweight gain and diet quality). As this type of model is
principally concerned with prediction, direct biological meaning cannot be
ascribed to the equation parameters and the model suggests little about the
mechanisms of voluntary feed intake. If the model fits the data well, the
equation might be extremely useful though it is specific to the particular
conditions under which the data were obtained, and so the range of its predict-

which describe how the state variables change with time:
dX
i
=dt ¼ f
i
(X
1
, X
2
, ..., X
q
; S); i ¼ 1, 2, ..., q (1:2)
where S denotes a set of parameters, and the function f
i
gives the rate of
change of the state variable X
i
.
The function f
i
comprises terms that represent individual processes (with
dimensions of state variable per unit time), and these rates can be calculated
from the values of the state variables alone, with of course the values of any
parameters and constants. In this type of mathematical modelling, the differ-
ential equations are formed through direct application of the laws of science
8 J. Dijkstra et al.
(e.g. the law of mass conservation, the first law of thermodynamics) or by
application of a continuity equation derived from more fundamental scientific
laws.
If the system under investigation is in steady state, the solution to Eq. (1.2)

Baldwin, R.L. (1995) Modelling Ruminant Digestion and Metabolism. Chapman &
Hall, London.
Blaxter, K.L. (1989) Energy Metabolism in Animals and Man. Cambridge University
Press, Cambridge.
Church, D.C. (ed.) (1993) The Ruminant Animal: Digestive Physiology and Nutri-
tion. Waveland Press, Inc., Englewood Cliffs, New Jersey.
Introduction 9
Czerkawski, J.W. (1986) An Introduction to Rumen Studies. Pergamon Press,
Oxford, UK.
Food and Agriculture Organization (2004) FAOSTAT Data, 2004. FAO, Rome.
Forbes, J.M. (1995) Voluntary Food Intake and Diet Selection in Farm Animals, 1st
edn. CAB International, Wallingford, UK.
Getty, R. (ed.) (1975) Sisson and Grossman’s Anatomy of the Domestic Animals, 5th
edn. W.B. Saunders Co, Philadelphia, Pennsylvania.
Hobson, P.N. and Stewart, C.S. (eds) (1997) The Rumen Microbial Ecosystem, 2nd
edn. Blackie Academic & Professional, London.
Hungate, R.E. (1966) The Rumen and Its Microbes. Academic Press, New York.
McDonald, P., Edwards, R.A., Greenhalgh, J.F.D. and Morgan, C.A. (2002) Animal
Nutrition. Prentice-Hall, Englewood Cliffs, New Jersey.
Monod, J. (1975) Chance and Necessity: An Essay on the Natural Philosophy of
Modern Biology. Collins, London.
Reece, W.O. (ed.) (2004) Dukes’ Physiology of Domestic Animals, 12th edn. Com-
stock Publishing, Ithaca, New York.
Theodorou, M.K. and France, J. (eds) (2000) Feeding Systems and Feed Evaluation
Models. CAB International, Wallingford, UK.
Thornley, J.H.M. and France, J. (2005) Mathematical Models in Agriculture, 2nd
edn. CAB International, Wallingford, UK.
Thornley, J.H.M. and Johnson, I.R. (1989) Plant and Crop Modelling. Oxford Uni-
versity Press, Oxford, UK.
Van Soest, P.J. (1994) Nutritional Ecology of the Ruminant, 2nd edn. Cornell

Madison, WI 53706, USA
Introduction
Digestion in ruminants is the result of two competing processes: digestion and
passage. Rate of passage determines the time feed is retained in the alimentary
tract for digestive action and the rate and potential extent of degradation
determines the digestion that can occur during the retention time. To predict
dynamic flows of nutrients or static estimates of digestibility at various levels of
performance, the processes of digestion and passage must be described in
compatible mathematical terms and integrated. This chapter will focus on the
mathematical description or modelling of digestion, especially fermentative
digestion in the rumen because it typically represents the largest proportion
of total tract digestibility and is the first step in the digestive process for
ruminants that influences the processes that follow.
The digestive process involves the time-dependent degradation or hydroly-
sis of complex feed components into molecules that can be absorbed by the
animal as digesta passes through the alimentary tract. Conceptually, digestion
and passage can be described as multi-step processes using compartmental
models (Blaxter et al., 1956; Waldo et al., 1972; Baldwin et al., 1977, 1987;
Mertens and Ely, 1979; Black et al., 1980; Poppi et al., 1981; France et al.,
1982). Because feed components do not digest or pass through the digestive
tract similarly (Sutherland, 1988), an understanding about the nature of pas-
sage in ruminants provides an important framework for developing compatible
digestion models.
In ruminants, passage of digesta through the alimentary tract is a complex
process that involves selective retention, mixing, segregation, and escape of
particles and liquid from the rumen before they pass into and through the small
and large intestines. Mechanistically, the reticulorumen, small intestine and
large intestine differ in mixing and flow. The rumen operates as an imperfectly
stirred, continuous-flow reactor, whereas the small and large intestines act
ß CAB International 2005. Quantitative Aspects of Ruminant Digestion