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THE EFFECT OF DIETARY FIBER AND BODY CONDITION
ON THE MILK PRODUCTION, DRY MATTER INTAKE AND
BLOOD METABOLITES OF PERIPARTUM DAIRY COWS

BY

Robert Arnold Patton

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Department of Animal Science

1989

b048965

ABSTRACT

THE EFFECT OF DIETARY FIBER AND BODY CONDITION ON THE MILK
PRODUCTION, DRY MATTER INTAKE AND BLOOD METABOLITES
OF PERIPARTUM DAIRY COWS

BY

Robert Arnold Patton

The effects of three different levels of ration ADF
and body condition on dry matter intake and milk production
in peripartum cows were evaluated. Thirty cows from two
experimental herds were blocked by location, parity,
expected calving date and balanced for body condition
(multiparous-la; primiparous-lZ). Cows were body condition
scored and were labeled thin (score <8 2.5) or fat (score >
2.5) on a scale of 1-5. Blood metabolites were also
measured. Cows were placed on experiment three weeks before
expected calving date and fed the herd dry cow ration. On
day of parturition cows were abruptly changed to
experimental diets which were fed for the next 11 weeks.
Actual ration fiber levels were 17.4, 20.2 and 22.8% ADF
and 33.4, 36.2 and 38.2% NDF respectively.

Prepartum fat cows tended to eat more, weighed more,
gained more weight, had higher plasma insulin
concentrations and had lower ratios of B-hydroxybutryic
acid (BHBA):acetoacetic acid (ACAC) than did thin cows.

Primiparous cows weighed less and ate less than the

multiparous cows both before and after parturition.
Postpartum cows fed 17% ADP ration produced more milk than
those fed 23% ADP. Milk components were unaffected by
either ration or body condition. Dry matter intake as a
percentage of body weight tended to be higher for cows fed
17% ADP than 23%. NDP consumed was not different among
treatments. ADP intake, however, tended to be lower for
17% ADP than 23% ADP ration on a percent of body weight
basis. Correlation of ration NDP with dry matter intake was
-.09 and ADP was -.15. Body condition had no effect on any
intake parameter. Plasma insulin concentrations were not
different between thin and fat cows, although primiparous
cows tended to have higher insulin concentration along with
significantly higher plasma glucose and lower NEPA.

Plasma levels of NEPA and ratio of ketones were unaffected
by ration or body condition. Cows fed rations with 17% and
20% ADP had significantly lower levels of BHBA than did
those fed 24% ADP. Severity and duration of negative
energy balance were not affected by ration or body
condition.

Under the conditions imposed by this experiment,
neither ration fiber level nor body condition had a
significant impact on dry matter intake. It is concluded
that in early lactation, the hormonal drive for milk
production dominates the effects of ration and body

condition on dry matter intake.

DEDICATION

Robert D. McCarthy

(1933-1987)

Judith C. Patton

Because they never gave up on me.

The dairy farmers of Michigan, New York and Pennsylvania

Because they have taught me much.

-iv

ACKNOWLEDGMENTS

In any undertaking of this size, numerous people
contribute their time, talents and ideas who will never
receive the full credit due them. This thesis is no
exception. Yet so many individuals have contributed so
much that they deserve some special recognition. Special
consideration must be given to:

Dr. Maynard Hogberg, Department Chairman, for placing
the facilities of the Department of Animal Science at my
disposal. Appreciation is also expressed for providing an
assistantship working in Extension and for rescuing a tight
budget.

Dr. Herbert Bucholtz, major professor, for being not
only an advisor but a friend and colleague. We learned
much together and had fun the whole time.

The rest of my graduate committee: Dr. Roy Emery,
whose breath of knowledge about the field of dairy cattle
nutrition continues to amaze me; Dr. Michael Allen, whose
insight into rumen function and fiber digestion has opened
up a new world of investigation to me; Dr. John Gill, who
has taught me not only statistics but also developed a
philosophy of research; and Dr. Thomas Herdt, who was ever
ready with discussions about metabolism.

Dr. Mary Schmidt, dairy herd manager, who supported me
with ideas, labor and enthusiasm. Mary always gave more
than she received and did so willingly.

Paul Naasz and Steve Nelson, of the Upper Peninsula
Experiment Station, who ran the trial as if it were their
own. They weighed, bled, scored cows and recorded data to
an extent beyond what was requested. They contributed
observations and insight at all times. Every piece of data
was collected with the highest degree of professionalism.

Katie Naasz, who shared her home and friendship.
Katie and Paul have become friends for a lifetime.

The staff at both the campus and UP station. Everyone
of these people has given a measure of themselves. They
were always willing and always helpful.

James Liesman, whose friendship, knowledge of
metabolism and statistics were constantly at my disposal.
Jim is absolutely the smartest man I ever met. He handles
all situations with a calm wit that belies the intensity of
thought he contributes.

Fellow graduate students Louis Poster for body scoring
the campus cows and Luis Solorzano for ideas and far
ranging discussions concerning dairy cattle nutrition. To
Alan Ealy for the insulin assay.

Technicians Lori Harms, Jeff Horning and Cathy Cook
for help with lots of thankless labor. To Cathy O'Hare for
assistance with the non-esterified fatty acids.

Other members of the Department of Animal Science,
both faculty and staff, who in a thousand helpful ways have
made my stay at Michigan State enjoyable.

The Pertrell Company of Bainbridge, Pennsylvania who
have contributed financial support.

Mary and Jake Patton who have supported me with labor
and love, and especially Cari Patton whose labor made many
of the assays possible in a timely fashion. These are my
children and no parent could be prouder than I am.

Lastly and foremost my wife, Judith Patton, without

whose love, labor and wise counsel, this project could not
have been completed.

vi

TABLE

LIST OF TABLES . . . . .
LIST OF FIGURES. . . . .

REVIEW OF LITERATURE . .

OF CONTENTS

General Considerations .

Dietary Effects on Peed Intake

Cow Pactors . . . .

Neural Hormonal and Metabolic

Effects on Peed Intake .

MATERIALS AND METHODS .

Cattle Handling and Feed Sampling.

Blood Handling and Analysis.

Milk Component Analysis.

Statistical Analysis
RESULTS. . . . . . . . .
Prepartum Cows . . .
Cows . . . . . . . .
Diet . . . . . . . .
Production . . . . .
Body Weight and Body
Dry Matter Intake. .
Blood Metabolites. .

..

Condition

Comparison of Lactation Weeks 8-11

Energy Balance . . .

DMI Regression Analysis.

Discussion . . . . .

vii

. xi-xii
.xiii-xiv

. . . .14
. . . .22

O O O .28

O O O .28

O O O .42
. . . .50
O O O .60

O O O .66

. . . 110
. . . 113

. . . 115

conCIus ions 0 O O O O O O O O O O O O O O O O O O O O 124
APPENDIX TABLES. . . . . . . . . . . . . . . . . . . . . 126

LIST OF REFERENCES 0 O O O O O O O O O O O O O O O O O O 156

viii

Table 1.
Table 2.
Table 3.
Table 4.
Table 5.
Table 6.
Table 7.
Table 8.
Table 9.
Table 10.
Table 11.

LIST OF TABLES

Composition of rations fed to dry cows.

Variable means and specific contrasts of

dry cow rations . . . . . . . . . .1. .

Approximate average ingredient of
experimental diets (percent of dry
matter basis) . . . . . . . . . . . . .

Nutrient composition of experimental
diets (percent of dry matter basis) . .

Weekly means and selected contrasts for
various feed variables for cows fed
three levels of ADP and at two body
conditions. . . . . . . . . . . . . . .

Weekly means and selected contrasts for
the differences between the composition
of the ration and the ORTS. . . . . . .

Source of variation of ADP levels in
the ration for experimental designs
employing either lactation week or
calendar week in the model (Type III
sum of squares) . . . . . . . . . . . .

Means and selected contrasts for milk
production variables for cows fed
three levels of ADP and at two body
conditions. . . . . . . . . . . . . . .

Treatment means and selected contrasts
for cows fed three levels of ADP and
at two body conditions for body
measurements. . . . . . . . . . . .

Treatment means and selected contrasts
for cows fed three ADP levels and at
two body conditions for feed intake
variables . . . . . . . . . . . . . .

Weekly means and selected contrasts of
blood metabolites and plasma insulin

among cows fed three levels of ADP and
at two body conditions. . . . . . . . .

ix

0 O 33

.46-48

. . 49

. 51

.52-54

.74-76

.83-85

Table 12.

Table 13.

Table 14.

Appendix

Appendix

Appendix

Appendix

Appendix

Appendix

Appendix

Appendix

Appendix

Correlation coefficients for explaining
dry matter intake variance by regression

models.

0 o o o o o o o o o o o o o o 0 096-98

Probability of significant P test and
differences between means for
experimental weeks 2-4 and weeks 8-11 . 99-107

Means and selected contrasts for
variables over the last four
experimental weeks. . . . . . . . . . . . 114

Table

Table

Table

Table

Table

Table

Table

Table

Table

1.

Mean weekly milk production
of cows fed three levels of ADP
and at two body conditions . . . . 126

Mean weekly milk fat percent of
cows fed three levels of ADP and
at two body conditions . . . . . . 127

Mean weekly milk protein percent
of cows fed three levels of ADP'
and at two body conditions . . . . 128

Mean weekly total milk solids

percent of cows fed three

levels of ADP and at two body
conditions . . . . . . . . . . . . 129

Mean weekly production (kg/week)

of 4% fat corrected milk of cows

fed three levels of ADP and at

two body conditions. . . . . . . . 130

Mean weekly weight (kg) of cows
fed three levels of ADP and at
two body conditions. . . . . . . . 131

Mean change in body weight (kg)

from second week of lactation

for cows fed three levels ADP

and at two body conditions . . . . 132

Mean weekly production of 4% fat
corrected milk as a percent of

body weight (kg/lOOkg body weight)

for cows fed three levels ADP and

at two body conditions . . . . . . 133

Mean weekly body condition score
for cows fed three levels of ADP
and at two body conditions . . . . 134

Appendix

Appendix

Appendix

Appendix

Appendix

Appendix

Appendix

Appendix

Appendix

Appendix

Appendix

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

Mean weekly change in body
condition score from week of
calving for cows fed three levels
ADP and at two body conditions . .

Mean weekly NDP concentration (%)
of rations for cows fed three
levels of ADP and at two body
conditions . . . . . . . . . . . .

Mean weekly ADP concentration

(%) of rations for cows fed

three levels of ADP and at two
body conditions. . . . . . . . . .

Mean weekly lignin content (%)
of rations for cows fed three
levels of ADP and at two body
conditions . . . . . . . . . . . .

Mean weekly ash content (%) of
rations for cows fed three levels
of ADP and at two body conditions.

Mean weekly dry matter intake
(kg/week) of cows fed three
levels of ADP and at two body
conditions . ... . . . . . . . . .

Average daily dry matter intake
as a percent of body weight
(kg/lookg body weight) for cows
fed three levels of ADP and at
two body conditions. . . . . . . .

Mean weekly consumption of NDP
(kg) for cows fed three levels
ADP and at two body conditions . .

Mean weekly consumption of ADP
(kg) for cows fed three levels

of ADP and at two body

conditions . . . . . . . . . . . .

Mean weekly consumption of lignin
(kg) for cows fed three levels of
ADP and at two body conditions . .

Mean weekly consumption of ash

(kg) for cows fed three levels of
ADP and at two body conditions . .

xi

135

136

137

138

139

140

141

142

143

144

145

Appendix Table 21. Mean weekly plasma concentration of
of glucose (mMoles) for cows fed
three levels of ADP and at two
body conditions. . . . . . . . . . 146

Appendix Table 22. Mean weekly plasma insulin
concentration (ng/ml) for cows fed
three levels of ADP and at two
body conditions. . . . . . .'. . . 147

Appendix Table 23. Mean weekly plasma concentration
of NEPA (mMoles) for cows fed
three levels of ADP and at two
body conditions. . . . . . . . . . 148

Appendix Table 24. Mean weekly whole blood
concentration of B-Hydroxy
butyric acid (mMole) for cows
fed three levels of ADP and at
two body conditions. . . . . . . . 149

Appendix Table 25. Mean weekly whole blood
concentration of acetoacetic
acid (mMoles) for cows fed three
levels of ADP and at two body
conditions . . . . . . . . . . . . 150

Appendix Table 26. Mean weekly plasma triacylglycerol
concentration (mMoles of triolein)
for cows fed three levels of ADP
and at two body conditions . . . . 151

Appendix Table 27. Mean weekly concentration of
plasma creatinine (mMoles) of
cows fed three levels of ADP
and at two body conditions . . . . 152

Appendix Table 28. Mean weekly calculated energy
balance of cows fed three levels
of ADP and at two body conditions. 153

Appendix Table 29. Pearson correlation coefficients
for selected variables with dry
matter intake. . . . . . . . . . . 154

Appendix Table 30. Pearson correlation coefficients

for selected variables with
milk production. . . . . . . . . . 155

xii

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

10.

11.

12.

13.

14.

LIST OF FIGURES

Mean weekly milk production of cows

fed three different levels of ADP . . . . . .
Regression plots of milk production of
cows fed three different levels of ADP. . . .

Regression plots of milk fat production
of cows fed three different levels of ADP . .

Regression plots of body weight of cows
at two different body conditions. . . . . . .

Regression plots of the effect of
interaction between ration 1 and body
condition on body weight. . . . . . . . . . .

Regression plots of the effect of
interaction between ration 2 and body
condition on body weight. . . . . . . . . . .

Regression plots of the effect of interaction
between ration 3 and body condition on body
we ight O O O O O O O O . O O O O O O O O O O O O

Mean weekly body condition score of cows
fed three different levels of ADP . . . . . .

Regression plot of mean weekly body
condition score of cows fed three different
levels Of ADF O O O O O O O O O O O O O O O O

Regression plots of the interaction of
ration 1 and and body condition on body
condition score . . . . . . . ._. . . . . . .

Regression plots of the interaction of
ration 2 and body condition on body
condition score . . . . . . . . . . . . . . .

Regression plots of the interaction of
ration 3 and body condition on body
condition score . .'. . . . . . . . . . . . .

Mean weekly dry matter intake of cows
fed three different levels of ADP . . . . . .

Mean weekly dry matter intake of cows at two
different body condition scores . . . . . . .

xiii

56

58

59

62

63

64

65

67

68

69

7O

71

72

73

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

Regression plots of the effect of the NDP
consumption in ration l and body condition
on body weight. . . . . . . . . . . . . . .

Regression plots of the effect of the NDP
consumption in ration 2 and body condition
on body weight. . . . . . . . . . . . . . .

Regression plots of the effect of the NDP
consumption in ration 3 and body condition
on body weight. . . . . . . . . . . . . . .

Regression plots of the effect of body
condition on ADP consumption. . . . . . . .

. 82

Mean weekly concentration of B-hydroxybutyric

acid (mMoles) in the whole blood of cows
fed three different levels of ADP . . . . .

Mean weekly concentration of acetoacetic
acid (mMoles) in the whole blood of
experimental cows . . . . . . . . . . . . .

Mean weekly concentration of plasma
nonesterified fatty acids (mMoles) of
experimental cows . . . . . . . . . . . . .

Mean weekly concentration of plasma
triacylglycerol (mMoles) of experimental
cows O O O O O O O O O O O O O O O O O O O O

Mean weekly concentration of plasma glucose
(mMoles) of experimental cows . . . . . . .

Mean weekly concentration of plasma insulin
(ng/ml) of experimental cows. . . . . . . .

Mean weekly concentration of plasma
creatinine (mMoles) of experimental cows. .

Regression plot of the effects of diet
on plasma nonesterified fatty acids . . . .

Mean weekly energy balance (MCal/week)
of cows fed three different levels of ADP .

Mean weekly energy balance (MCal/week)
at two body conditions. . . . . . . . . . .

xiv

. 86

. 89

. 9O

. 91

.111

.112

1

REVIEW OF LITERATURE

The peripartum dairy cow is unable to satisfy her
energy requirements from the diet (Coppock, 1985). This
condition occurs for three reasons: (1) milk flow is
increasing rapidly up to a point of 5-8 weeks post partum;
(2) maximum dry matter intake is not reached until 3-4
weeks after peak milk production: (3) there is a maximum
energy density that the cow can consume without digestive
upset (Wangesness and Muller, 1981). This implies that
during the early stages of lactation the dairy cow is in
negative energy balance with resultant loss of adipose and
protein tissue (Emery, 1988). Because there is some health
risk and may be some production loss associated with this
situation, it is desirable to increase dry matter intake to
the maximum level as soon as possible after parturition to
mitigate the period of negative energy balance.

The peripartum dairy cow can only obtain the
additional nutrients required for high milk production in
one of four ways: (1) increase the amount of feed
consumed: (2) mobilize storage depots of fat and protein;
(3) increase the rate of digestion and (4) increase the
rate of passage from the rumen.

The feed that a cow consumes depends on a complex
balance of the physical characteristics of the animal, the
environment in which she is placed, the characteristics of

the diet and the hormonal status of the cow (Forbes, 1986).

General Considerations

The dry matter that a dairy cow conSumes is related to
her energy needs (Conrad, 1966). As in other species, it
is assumed that the cow eats to satisfy her energy
requirements and maintain an energy reserve (Baile, 1975).
Thus, a cow that requires more energy will consume more
kilograms of feed in an attempt to increase caloric intake.
When the caloric density of the ration is reduced on a dry
matter basis, the cow must consume more dry matter to
obtain the same amount of calories (Dinius and Baumgardt,
1970). When energy demands are only for maintenance and
low milk production, the relationship between feed
consumption and energy expenditure holds adequately. The
dairy cow may not follow this relationship as closely as
other species as evidenced by the "fat cow syndrome"
condition (Forbes, 1986). In this case, the cow has
consumed energy far in excess of her metabolic need.

It has been demonstrated that even at maintenance, as
the caloric density of the diet increases, dry matter
intake also increases (Forbes, 1986). These increases seem
to occur until the animal reaches a new "set point" or
degree of fattening. When this new set point is reached,
energy intake returns to previous normal levels (Cohn and

Joseph, 1962).

3
In the high producing cow, the increase in feed intake

continues until the caloric density approaches 1.75 MCal/
kg of ration dry matter. At this point dry matter intake
is also reduced (Wangesness and Muller, 1981). Although
this result is expected for cattle at maintenance or at low
levels of production because their energy needs have been
met, this same phenomena occurs in high producing cows who
are still energy deficient.

The total energy that the cow consumes is a function
of both the energy density of the diet and the amount of
dry matter that she eats. However, the amount of energy
that the cow actually utilizes is a function not only of
the feed consumed but also a function of the proportion of
the diet that is digestible, of_the rate of digestion and
of the digestibility depression caused by increased dry
matter intake (Mertens, 1987). If intake is increased a
digestibility decrease is observed (Conrad et al., 1964)
while if intake is restricted digestibility increases
(Staples et al., 1984). Conversely, Robinson et al.
(1987a,b) found a "protective mechanism" that allowed high
producing cows (i.e., those cows with higher dry matter
intake) to increase their rate of ruminal cell wall
digestion as intake and rate of passage increased.
Obviously, these differences in observations due to
increased intake cannot be explained: the observations of

Robinson et a1 need to be replicated.

4
There is considerable disagreement among nutritionists

about which dietary factors are most important in
controlling feed intake. It is generally assumed that in
the high producing cow, rumen fill will limit intake before

chemostatic mechanisms (Fisher et al., 1987).
Dietary Effects on Feed Intake

In terms of practical dairy cattle diets, energy will
be diluted by the fiber content of the diet (Mertens,
1982). It is well appreciated that the dairy cow has a
fiber requirement (Van Soest and Mertens, 1984). It is
also believed that a minimum fiber requirement for a given
physiological state is also the optimum fiber requirement
in terms of promoting a rumen environment that maximizes
digestion of dietary components, that encourages maximum
microbial protein synthesis and that supplies the optimum
amounts of volatile fatty acids and amino acids to the
animal. This optimum level may change with the productive
state of the cows (Wangesness and Muller, 1981).

The feed that a ruminant consumes has been divided
into various components as a means of describing them
nutritionally. The system of Van Soest (1982) has gained
widest acceptance. Using this system, feed components are
classified by their relationship to their role in the plant
cell. The carbohydrate portion of the feeds may be
classified as either structural (cell wall) or

nonstructural (starches and sugars). Nonstructual

5
carbohydrates are relatively soluble and are digested
relatively quickly in the rumen. Structural carbohydrates
are more slowly digested and take up space in the rumen for
longer periods of time. Cell walls are further classified
into their main components: pectin, hemicellulose,
cellulose and lignin. Neutral detergent fiber (NDP) is a
measure of total cell wall except for pectin which is
removed in neutral detergent solution. Acid detergent
fiber (ADP) is a measure of cellulose and lignin. Neutral
detergent fiber is a better measure of the total fiber
content of the diet than is ADP.

In general, legumes will contain more lignin and less
hemicellulose than will grasses at the same maturity (Smith
et al., 1972). As plants mature, lignin content increases
more rapidly in legumes and hemicellulose content increases
to greater amounts in grasses (Smith et al., 1971). As a
percent of dry matter, all cell wall constituents increase
as forage plants mature. With increasing maturity, the
percentage of the plant that is indigestible increases.
This increase is probably related to increased
lignification (Waldo et al., 1972). Higher levels of
lignin appear both to increase the time required for
bacterial attachment and to protect potentially digestible
cellulose and hemicellulose from bacterial enzymes (Varel
and Jung, 1986). Increased lignification does not appear
to change the rate of digestion of digestible cellulose
(Smith et al., 1972).

6
If the definitions of the feed fiber fractions are

well established, their significance to the physiology of
digestion is less well established. Conrad et al.
(1964), the Baumgardt group (Montgomery and Baumgardt,
1965: Dinius and Baumgardt, 1972) and Mertens (1982) have
all presented data indicating that the fiber content of the
forage is related to the dry matter intake. This
relationship is quadratic, implying that there is an
optimum fiber intake at an intermediate level. Conrad
(1966) and Orskov et a1 (1988) proposed that the
potentially digestible dry matter content of the diet was
highly correlated with dry matter intake explaining about
50% of the variation on different diets. Orskov et a1
(1988) were able to predict the dry matter intake of straws
from 48-hour in 215:9 digestibilities. Smith et al (1972)
had earlier established that digestibility of alfalfa could
be predicted from 48-hr in 213:9 incubations, but that
digestibility of grass hay was better predicted by 72 hr in
yitxg incubations. Mertens (1982) found dry matter
intake highly correlated with the neutral detergent fiber
(NDP) content across various forages while ADP was less
well correlated. Mertens (1981) has also suggested that
ADP is more closely related to the energy content of the
diet than is NDP. Peed energy is usually predicted by ADP
content (NRC, 1988). Calculations of Conrad et al. (1984),
however, indicate that lignified NDP content is a better

measure of feed energy.

Briceno et a1. (1987) compiling data from various
experiments argued that NDP content of the diet was not an
accurate predictor of intake across various forages.
However, this experiment may be criticized because NDF was
estimated rather than measured on each diet. Body size and
milk production explained the major differences in intake
on their experiments. Allen and Mertens (1988b) found a
relationship between NDP and intake in cows producing 18 kg
but not in those producing 32 kg. Van Soest (1982) has
suggested that the ADF content of the diet may reflect the
build up of indigestible portions of the diet and that this
may limit intake. The rate at which indigestible portions
of feed leave the rumen is a major determinant of feed
intake (Mertens and Ely, 1979.). Using sheep, Hogue (1987)
demonstrated that the indigestible NDP was an accurate
predictor of dry matter intake whereas NDP itself was not.
Patton et a1 (1988) suggested that NDP would be a measure
'of the bulkiness of the current meal and ADP would better
reflect the bulkiness of previously ingested, partially
digested meals. Therefore, both of these measures should
be better predictors of intake than either one alone. With
cows fed high levels of by product feeds and producing at
low levels, ADP was a more accurate predictor of feed
intake than NDP (MacGregor et al., 1976). The use of
either NDP or ADF as an indicator of potential feed intake

is therefore not conclusively established.

8
Deswysen and Ellis (1988) using crossbred cattle fed

3g libitgm corn silage with measured amounts of protein
supplement, measured the extent of NDP digestion in various
areas of the rumen and the total digestive tract, and
attempted to correlate it to voluntary dry matter intake.
In these experiments, there were strong negative
correlations between extent of NDP digestion in the ventral
rumen and in the duodenum and voluntary feed intake. Total
tract NDP digestion, however, was not related to feed
intake. They suggested that the end products of fiber
digestion rather than the fill properties of NDP may be
limiting intake. However, these animals were essentially
at maintenance and dry matter intake should have been
limited by the energy intake of the animals rather than by
rumen fill. '

Feed intake in the previous experiments was most
highly, and most negatively, correlated with the grams of
NDP that flowed through the omasal orifice. Because they
detected no differences in total tract NDP digestion with
different levels of dry matter intake, in spite of the fact
that higher levels of intake resulted in greater ruminal
outflow of potentially digestible NDP, these authors
suggested that if potentially digestible NDP left the
rumen, it would be digested post ruminally. This has also
been suggested by other authors (Robinson et. al.

1987,a,b).

9

In addition to the fiber content of the diet, other
ration factors known to influence feed intake are the rate
and extent of digestion (Allen and Mertens, 1988a) and the
rate at which particles are broken down to a size that has
potential to escape the rumen (Trolsen and Campbell, 1968).
These factors are interrelated and perhaps are confounded.
Feed particles must reach a size smaller than 4 mm before
they are able to pass from the rumen (Cardoza and Mertens,
1969).

Reducing particle size of forage is known to increase
DMI (Baumgardt, 1970). Grinding alfalfa hay increased rate
of digestion (Dehority and Johnson, 1961), but grinding did
not have the same effect on orchardgrass hay (Robles et
al., 1980). Woodford and Murphy (1988a,b), feeding higher
producing cows, found dry matter intake depressed when feed
particle size was reduced. Reducing the size of alfalfa
silage by rechopping, however, had no effect on dry matter
intake (Armentano et a1, 1988). Rodrigue and Allen (1960)
showed that grinding of forage increased the extent of
digestion in 21:29 but decreased digestion in 2129 because
of greater rates of passage from the rumen.

It is assumed when modeling rumen function that the
faster feed particles are reduced to a size that can escape
the rumen, the faster would be the rate at which the rumen
would empty (Mertens, 1987). Therefore, there would be
space in the rumen for ingestion of more feed. Size

reduction of feed particles is a function of initial

10

particle size (Ellis et al.,1987), chewing time and sheer
force (Latham et al., 1978) as well as rumination time
(Welch, 1982). Rumination has been shown to have the
greatest effect on the reduction of particle size and
therefore would probably have a large effect on feed intake
(Welch, 1982).

Ruminating time, total chewing time, number of boluses
ruminated per day and total rumen contractions have all
been shown to influence the rate of ruminal digestion.
These factors therefore, may have an influence on the
potential feed intake in cattle (Woodford et a1, 1986).
Total rumination time and total chewing time are positively
related to the amount of NDP consumed (Welch and Smith,
1970). Rumination time and total chews per gram of
ingested NDP, however, is reduced as NDP consumption
increases. Chewing, besides providing more saliva and a
better rumen environment, may increase the rate of
digestion by reducing the lag time for bacterial attachment
°(Galyean and Owens, 1988).

Feed particles that pass through the same size screen
will have different shapes (Emanuele and Staples, 1988).
Legume feed particles tend to shatter in shapes that are of
shorter lengths than grasses, although diameters will be
approximately equal. The leaves of legumes will display a
more rectangular pattern of shatter than will the stems.

Within a species the smaller the feed particles the greater

11
will be the rate of in 21219 digestion. Ehle (1984) was
able to show that differences in digestion may be
confounded by preferential sorting of leaf tissue into
smaller size fractions. However, Ehle et a1 (1982) using
protein feed particles and Cherney et al (1988) using grass
stem internodes, were unable to show consistent effects of
particle size on rate of digestion. Ellis et al (1987)
also found that rate of digestion was not related to
particle size, but lag time was related.

Dutch workers (Kwakkel et a1, 1986) using the in gaggg
technique found that rates of NDP digestion were not
different between grass silage and alfalfa silage but was
50% less for corn silage. Extent of digestion was least
for alfalfa silage probably because of a large lignin
component although the feed intake cf steers was 20%
greater for the alfalfa silage. Intakes of the grass
silage and corn silage were not significantly different
from each other. These observations led these workers to
the conclusion that the cell wall geometry may have a
greater affect on rate of digestion and intake than did the
amount of cell wall present in the feeds. Crude protein
levels in the diets and forage maturity differences may
have confounded these studies, however.

If dry matter intake was held constant, Korver (1984)
found that there was no difference between extent of NDP
digestion for NDP that is digestible among forages. The
similarity in rate of NDP digestion between different

12

forages was also shown by Jones et a1 (1988) using
orchardgrass and bermudagrass hays, although the dry matter
intake in this case was significantly greater for the
forage with the lower NDP value. These studies

demonstrate that the intrinsic nature of the fiber fraction
may have a great influence on its digestibility and hence
its potential intake.

Differences in level of intake (alfalfa greater than
grasses), rate of digestion (alfalfa greater than grasses)
and extent of digestion (alfalfa less than grasses) have
often been reported. But these studies generally failed to
standardize either the maturity, fiber content of the
forage or the particle size. From the previous
discussions, it is apparent that failure to standardize
these effects could severely magnify the intrinsic
differences in intake potential between grasses and
legumes.

French workers have proposed a fill unit system for
use in predicting the voluntary feed intake of ruminants
(Jarrige et a1. 1986). In this system all forages are
compared to a reference grass pasture which is arbitrarily
given a fill unit (FU) value of 1. Each forage is assumed
to have an intrinsic fill value. Voluntary feed intake is
then predicted in terms of fill units. Application of this
system to practical diets is largely untried. However, it

would be expected that ruminal conditions and the metabolic

l3
status of the animals would be expected to change the fill

value of a given forage.

Similar to using NDP, the intrinsic simplicity of the
system has great appeal. However, even the authors admit
it fails to account for the dynamics and differences that
are commonly observed in voluntary dry matter intake.

Perhaps the major failing of all attempts to predict
the voluntary feed intake is that they fail to remotely
account for the dynamics of rumen fermentation and
physiology. A complete recapitulation of all of these
factors is beyond the scope of review. In fact, they are
incompletely understood at best. Yet these interactions
may so completely overshadow any effects of dietary
constituents on dry matter intake, that the more important
of these will be mentioned.

Cow Factors

Dry cows consume less feed than lactating cows (Emery,
1988). Larger body weight animals consume more feed than
smaller animals, although growing animals consume more feed
than mature animals at the same body weight (Allison,
1985).

In early lactation space within the digestive system
may be limiting the amount of space available for feed. It
is known that the digestive system and the liver increase
in size 10% more within the first seven weeks of lactation

than the size of the digestive tract in the dry period

14

(Barnes et al., 1986).

The physiology of the cow and her environment also
affects dry matter intake. Animal factors identified as
having an effect on DMI include: milk production, body
size, stage of lactation, hormonal status, presence of
disease, temperature, humidity, palatability of the ration
and the number of times per day the ration is fed (NRC,
Pox, ed., 1987). Although the importance of these factors
on DMI is appreciated, a full review of them is beyond the

scope of this thesis.
Neural, Hormonal and Metabolic Effects on Feed Intake

That there is neural, hormonal and metabolic control
of intake in nonruminant species is_not questioned (Forbes,
1988). Evidence of their role in regulating feed intake in
the ruminant is more equivocal (Baile and Forbes, 1974).

As in nonruminant species, electrical stimulation of the
ventral-medial hypothesis will cause feeding behavior in
sheep already full fed. Severing the vagus nerve of sheep
will cause a cessation of eating to the point of starvation
(Baile, 1975). Data have also been presented that indicate
that stretch and osmolality receptors exist in the rumen
wall and that stimulation of these receptors will depress
feed intake. It is also well established that stimulation
of the rumen wall by fibrous feedstuffs will result in

increased rumination and remastication (Welch, 1982). All

15

of these factors argue for a large role of the neural
system in the acute regulation of feed intake. Grovum
(1986) has published a complete review of these factors.
However, in all species and the ruminant in particular, the
role of the nervous system in controlling dry matter intake
has been better described than quantitated.

Hormonal regulation of metabolism is redirected in
early lactation toward the production of milk as a dominant
metabolic process (Bauman and Currie, 1980). Hormones have
been investigated as regulators of feed intake because
changing hormonal levels are associated with increasing dry
matter intake in early lactation. .

Ruminants experience an insulin surge after feeding
(Chase et al. 1977a) suggesting a role for insulin in meal
cessation. But sham fed sheep also undergo insulin release
(Basset, 1975, cited by DeJong, 1986) suggesting the
nervous system may play as great a role in insulin release
as does nutrient supply. Propionate, B-hydroxybutyrate and
amino acids have all been shown to elicit an insulin
release in ruminants (Brockman and Laarveld, 1986).
Intravenous infusion of insulin will depress feed intake in
sheep as will glucagon (Deetz and Wagesness, 1981).
Although insulin has been shown to regulate glucose, fatty
acid and ketone concentrations in ruminants (Heitman et a1.
1986), the physiologic role of insulin as a feed intake
regulator has been questioned (DeJong, 1987).

Glucose levels are inversely correlated with feed

16

intake in rats (Forbes, 1986). Blood levels of glucose,
volatile fatty acids, ketones, nonesterified fatty acids
and amino acids have all been studied as possible metabolic
regulators of feed intake. In general the results are less
than unequivocal (Chase et al., 1977a,b: Istasse et al.,
1987: Sutton et al., 1988). Because of ruminal
fermentation, little glucose as such is available for
absorption (Baldwin, 1985) . Blood levels of glucose are
low and relatively constant in the ruminant and arise
almost entirely from continuous gluconeogenesis.
Intravenous infusion of relatively high levels of glucose
into sheep did not result in cessation of eating behavior.
Physiological mechanisms allowed for the rapid clearance of
glucose from the blood stream with no effects on the
animals (Thye et al., 1970).

Monogastric species with lower blood sugar tend to eat
more in order to maintain glucose homeostasis (Forbes,
1986). Sheep that were treated with phlorizin to increase
urinary clearance of glucose experience only a short
duration of lower blood glucose and no apparent effect on
feeding behavior over the duration of these experiments.
Apparently the animals were able to increase the rate of
gluconeogenesis in order to maintain constant levels of
blood glucose (Bergman, 1973).

Bovine ketosis is characterized by depressed appetite,

low blood glucose and high blood ketones (Foster, 1988).

17
It has been suggested that high levels of blood ketones

negatively affect intake overriding the effect of low blood
glucose (Baird, 1982). Definitive experiments for proof
of this theory are lacking although intravenous infusion of
3-hydroxy butyrate into normal dairy cows produced no
decrease in dry matter consumption . Herdt et al. (1981)
when studying metabolic profiles of peripartum cows were
able to show a positive correlation between blood glucose
and energy intake as well as an inverse relationship of
blood 3-hydroxy butyrate with blood glucose. Blood free
fatty acids were also negatively correlated with calculated
energy intake.

Because cows in negative energy balance have elevated
levels of serum bound nonesterified fatty acids, several
studies have measured blood free fatty acid levels and
attempted to correlate them with dry matter intake (Radloff
et al., 1971) In general high levels of serum NEFA have
been associated with lower feed intake although the
relationship is less than perfect and no causal
relationship has been demonstrated.

Because blood volatile fatty acids (VFA) rise
immediately after a meal in direct response to the type and
amount of feed consumed, they have also been investigated
as short term regulators of feed intake in ruminants.
Although acetate infused intraruminally has been shown to
be a potent inhibitor of feed intake at pharmacological

doses (Baile, 1975), no such inhibition occurs at

18

physiological doses (DeJong, 1986). Propionate infused
intravenously also inhibits feeding at pharmacological
doses (DeJong et a1, 1981), but shows a variable response
at physiological doses (Anil and Forbes, 1980). (Although
these experiments seem to preclude the VFA as acute
regulators of feed intake, their potential role as long
term regulators have not been adequately documented. This
rise in blood VFA may be less important as ruminants that
are not force fed show less blood VFA variation over the
course of the day (Coggins and Field, 1976).

Intensive investigations with non-lactating cows over
short time periods have shown no correlation between
voluntary food intake and blood acetate or propionate
(Bines and Morant, 1983). Blood butyrate and total blood
ketones were negatively correlated with voluntary feed
intake in immediate meals but were positively correlated
with later meals. In these studies, blood NEFA level
immediately preceding a meal was the single metabolite
most positively and significantly correlated with
voluntary dry matter intake. This has also been
demonstrated in swine (Forbes, 1986), but is in
disagreement with the data of Russel and Doney (1969) who
found that blood levels of NEPA were strongly negatively
correlated with the voluntary feed intake of sheep.

Belgian workers (Paquay et al., 1979) attempted to

elucidate the long term regulation of feed intake of

19
mature, non-lactating sheep which were fed constant amounts
of roughage and either grain restricted to meet maintenance
requirements or grain 3g lipiggm over a seven month period.
In these experiments, the ad 1121222 fed sheep ate more
total dry matter per day and gained more weight in the
initial weeks of the experiment, but had returned to near
maintenance levels by the end of the experiment. Initially
blood glucose was higher, but blood ketone bodies and NEPA
concentrations were lower in the sheep consuming more
grain. These differences had disappeared by the end of the
experimental period. Changes in the fatty acid composition
of all blood lipids were noted. These alterations may
represent changes due to dietary fatty acid composition
rather than a role for fatty acid compositional changes in
feed intake regulation, as suggested by these workers.

Daughters of sires with low production potential are
known to have lower blood levels of FFA, glucose and ketone
bodies as well as lower dry matter intakes than daughters
of sires with higher genetic potential (Korver, 1988).

It is believed that dairy cattle that produce greater
quantities of milk are in negative energy balance for
longer periods of time (Coppock, 1985). It has also been
suggested that dairy cows that are fatter at parturition
have lower dry matter intakes but produce higher amounts of
FCM (Treacher et al, 1986: Garnsworthy and Topps, 1982:
Seymour and Polan, 1986: Kunz et al., 1985), although

nearly identical experiments have yielded conflicting

20

results (Nocek et al., 1986: Boisclair et al, 1985:
Garnsworthy and Gardner, 1987). The production increase of
FCM is assumed to be due to more fat reserves which the
animal can mobilize for milk production. The length of
time spent in negative energy balance is associated with
longer periods of anestrus. There is also a negative
correlation between body condition at calving and days of
anestrus (Butler et al.,1981). Increases in body score
lower the number of days anestrus in most but not all
studies. In all experiments, cows with greater body
condition lost more body condition and body weight for a
longer period of time during subsequent lactation. Pat
cows had higher plasma NEFA levels after parturition (Reid
and Roberts, 1983: Reid et al. 1986) and elevated blood
ketones.

It is suggested that cows that calve in thinner
condition are more energetically efficient (i.e., more of
the feed energy is used directly for milk production) than
those in fatter condition (Garnsworthy and Jones, 1987:
Treacher et a1. 1986). They may also lose less body
protein (Reid et al., 1986). Beylea et a1. (1986) found
protein losses to be a relatively constant percent of total
body tissue. Cows in fat body condition may also have more
protein mass.

The disease condition known as "Pat Cow Syndrome" is

characterized by the infiltration of fat into hepatic

21

tissue, decreased feed intake, greater incidences of
ketosis, retained placenta and decreased reproductive
performance (Emery et al, 1969: Reid and Roberts, 1983:)
This condition is assumed to have excess body fat reserves
as a predisposing condition. It appears that all dairy cows
have some degree of hepatic fat infiltration immediately
after parturition (Gerloff et a1, 1986). Because of this,
nutritionists have been reluctant to recommend higher body
levels of fat at calving even though it appears that milk
production and reproductive performance may be enhanced.
On a practical basis dairy farmers can manipulate the
ration only slightly to increase dry matter intake.-
Increasing the amount of grain (NRC, 1988) and forage
quality (Coppock, 1985) increase intake if the nutrient
density of the ration is limiting. 'Either lack of or
excess dietary protein has been shown to lower dry matter
intake (Owens and Goetsch, 1986). Forages preserved as
silage are known to reduce feed intake (Wilkinson et a1,
1976) although the exact nature of this depression is not
known (Shaver et al., 1985). Feeding more meals per day
and/or milking more times per day (DePeters et a1, 1985)
has been shown to increase dry matter intake. Addition of
buffering compounds to the ration has increased dry matter
intake in studies with cows fed high grain, low forage
diets but not when alfalfa makes up the major portion of
the forage (Erdman, 1988). Addition of flavoring compounds

has not resulted in increased feed intake because the cow

22

appears to have limited ability to discriminate flavors

(Coppock, 1985).

In summary these conclusions can be drawn.

1.

The integration of factors that regulate feed
intake is still not well understood.

Dietary fiber has a role in regulating feed
intake either by diluting out the energy

content of the diet or by taking up space

for more digestible dietary components.

The influence of the degree of body fatness

on feed intake or milk production is not well
understood.

At present there has not been identified a blood
metabolite or group of metabolites that appear to
have a dominate role in regulating feed intake.
At the present time practical recommendations
for increasing dry matter intake on commercial

farms are few.

MATERIALS AND METHODS

CATTLE HANDLING AND FEED SAMPLING

Thirty Holstein cows from the Michigan State

University Campus (n-12) and Upper Peninsula herds (n=18)

were utilized in a split block design with factorial

arrangement of treatments. Cows were blocked by parity,

location and date of expected calving. The campus

23

location had one block of primiparous and one block of
multiparous cows. The Upper Peninsula location had two
blocks of multiparous and one block of primiparous cows.
Multiparous cows were all in either the second or third
lactation. Within each block, two cows were assigned to
each of three calculated ration formulations: 16% (ration
l), 20% (ration 2) and 24% ADP (ration 3) depending on body
condition score so as to make a 3 by 2 factorial
arrangement of treatments. Cows were designated either as
fat or thin using the body condition scoring system of NIRD
(Mulvany, 1979). Fat cows had body condition scores
greater than 2.5 while thin cows had body condition scores
less than or equal to 2.5. Rations were formulated to meet
National Research Council (1978) guidelines for crude
protein, minerals and vitamins for cows producing 40 kg of
milk and weighing 550 kg.

Cows were placed on experiment three weeks before
expected calving date and fed the herd dry cow ration. On
day of parturition, cows were abruptly changed to
experimental rations and continued on these rations until
11 weeks after parturition. Because there was no way to
standardize calving day of the week, data from the first
week of lactation was not used.

All cows were housed in comfort tie stalls and
individually fed a total mixed ration offered twice daily.

Feed was offered at 03:30 and 13:00 at the Campus location

24
(CL) and at 07:30 and 17:30 at the Upper Peninsula location
(UP). Feed was weighed at feeding and offered to an
approximate 10% refusal. Orts were collected and weighed
once each day. All cows were milked twice daily with milk
production recorded at each milking. Cows at CL were
milked in a Boumatic walk through parlor with automatic
production recording while those at UP were milked in
their stalls with a DeLaval pipeline milker. Production at
the UP station was measured with Michigan DHIA approved
Waiko Milk Meters. Cows at both locations were weighed
Monday of each week. Blood samples were obtained from
coccygeal vessels 1 hour before feeding either on Monday
(CL) or Wednesday (UP) of each week. Cows were body scored
at the same time by experienced evaluators. Two evaluators
were employed at the CL herd and three at the UP station.
One evaluator was common to both locations. Body scores
were recorded as the average of the evaluator's scores.

At each feeding a 0.45 kg sample was saved from the
feed allocation of each cow. Samples were bagged in
plastic bags, securely fastened and individual feed samples
from a given feeding immediately frozen in large plastic
bags at -30' C. At the end of each weekly feeding period,
the fourteen samples were unfrozen, composited, completely
mixed by hand and an approximately 1.5 kg sample saved for
fiber analysis. Approximately 50 grams of the composited
sample was retained for dry matter determination. Samples

:for dry matter were placed in tared 9 x 4 mm aluminum pans,

25

weighed and dried at 55° C for 72 hours. This weight was
taken as the dry weight. Percent dry matter was determined
by the formula:

Dry matter % a dry weight/ wet weight

Twenty-five percent of each feed refusal was retained,
bagged, frozen and composited as for the feed samples.
Samples were retained for dry matter determination and
chemical analysis using the same protocol as for the feed
samples.

All 1.5 kg samples for chemical determination were
placed in 24 x 40 x 10 cm aluminum pans and oven dried at
55' C for 72 hours. These samples were removed from the
oven and the entire contents of’a pan ground by a Wiley
Mill initially through a 3 mm screen and then subsequently
through a 1 mm screen. After thoroughly mixing the finely
ground sample, about 100 gm were retained in plastic
collection vials until further compilation.

Individually ground samples were composited by adding
2 g of sample from each ground sample for all cows on a
particular experimental diet within a given week.
Composited feed samples for a given diet-week were analyzed
sequentially in duplicate for NDP%, ADP%, lignin% and ash%
by the method of Goering and Van Soest (1972). Reported
values of feed fiber constituents are the average of

duplicate analysis. If difference in NDF% between

26

duplicates was greater than 1.5 units, samples were rerun
in duplicate and the average of the nearest three was
reported. Orts were compiled proportionally by weight over
a two week period for individual cows and analyzed
sequentially for fiber fractions. I

Crude protein was determined on samples composited
over the whole experiment within diet and location as
Kjeldahl nitrogen (AOAC, 1975) to verify adequate crude

protein content.

BLOOD HANDLING AND ANALYSIS

Blood samples were obtained via 12 ml syringe and
added to Vacutainers (Becton and Dickinson, Rutherford,
N.J.). Three Vacutainers were filled as follows: a 4 ml
tube with heparin and sodium fluoride added for glucose
determination: and two 10 ml tubes with added sodium
heparin for other blood analysis. All blood samples were
kept immersed in ice immediately upon collection and kept
there until removed for processing. Ketones were analyzed
by the procedures of Williams, Mellanby and Krebs (1973)
and Williams and Mellanby (1973). All chemicals were
obtained from Sigma unless otherwise specified.
Centrifugation of blood to obtain plasma as well as for
ketone preparations was for 10 minutes after reaching
maximum speed in either an IEC model K (CL) or a Sorvall
model SS-l (UP) centrifuge. Blood for glucose determination

was spun immediately upon returning to the lab in the same

27

Plasma triglycerides were analyzed by adaptation of the
Sigma Serum Triglyceride kit as follows. A 1 ml aliquot of
blood plasma was extracted with 7 ml of 3:2
hexane:isopropanol. Three and one half ml of 7% sodium
sulfate was added to the extraction mixture to facilitate
separation of the aqueous and solvent phases. The solvent
phase was pipetted off and added to 0.6 gm of Triglyceride
Purifier (Sigma) to remove phospholipids. After shaking
for 10 minutes, the purifier was separated from solvent by
centrifugation and the supernatant pipetted into a clean 15
x 85 glass test tube. Five m1 of 7:2 hexane isopropanol
was added to the Triglyceride Purifier tube. The mixture
was vortexed for 15 sec, recentrifuged and the solvent
pipetted off into the sample tube.

The sample tube was evaporated to dryness in a sand
bath under a continuous stream of N2. One ml of
isopropanol was used to dissolve the isolated lipid.
Heating in a 60‘ C water bath was required to dissolve some
samples. Analysis by thin layer chromatography showed that
phosphorus containing lipids had been quantitatively
removed. One half ml of 5 N potassium hydroxide was added
to the sample and left standing overnight to saponify the
sample. The next day, 0.5 m1 of sodium periodate solution
was added to the test tube. The periodate solution was
prepared by dissolving 1.25 g of sodium m-periodate in 500
of 2 N acetic acid. After 10 minutes, color reagent was

added. Color reagent was prepared by mixing 200 ml of a 2

28

M ammonium acetate solution with 400 ml of isopropanol and
1.5 ml of acetylacetone. Samples were incubated for 30
minutes in a 60‘ C water bath to fully develop color.

Because blood pigments were found to interfere with
light absorption, the sample was washed with 2 ml of hexane
before reading absorbance at 410 nm. Extraction of 10
standards of .2 mg of triolein, yielded at recovery of 99.8
i 2.76%. Extraction and triglyceride readings on 10
separate 1 ml aliquot of a standard serum had a coefficient
of variation of 5.12%. Addition of standards of 0.025,
0.05, 0.1, 0.2 and 0.3 mg of triolein to standard serum
indicated linear recovery.

Plasma insulin was determined by specific double

antibody radioimmunoassay using the method of Villa-Godoy
(1987).

MILK COMPONENT ANALYSIS

Analysis of milk components was determined weekly.
They were analyzed for fat%, protein%, and total solids%
by Michigan DHIA. Reported butterfat %, protein % and

totals solids % are the average of am and pm samples.

STATISTICAL ANALYSIS
Statistical analysis was performed using the general
linear model (GLM) of SAS (SAS Institute Inc. Cary, N.C.,

release 5.18, 1986.) as a split block in time. The model

was:

29
Yijklm - u + a1 + Bj + (aB)1j + Ck + D1 + + (aC)ik +
(so)jki + (ascujk + Eijklm
where inklm - observed variable of each individual
cow for a given treatment in a given week of lactation in
a given block.
u - sample mean

a1 - effects of diet

83 - effects of body condition

- Ck - effects of lactation week

D1 - effects of block

(aB)ij - diet x body condition interaction

(aC)ik - diet x lactation week interaction '

(Bc)ij - body condition x lactation week interaction

(aBC)ijk - ration x body condition x lactation week

interaction '
and Eijklm - total pure error composed of
(aBD)ij1 - ration x body condition x block
interaction - whole plot error
(aBCD)ijkl - ration x body condition x lactation

week x block interaction - subplot error

Correlations between dependent variables were
generated using the GLM model of SAS. For variables with a
significant week of lactation effect, regression equations
were generated by cow using GLM of SAS. The model
included:

30
Y - 80 + 81x + 32x2 + 83x3
where Y - predicted variable value
30 - intercept
51 - coefficient of linear effect of lactation week
82 - coefficient of quadratic effect of lactation week
83 - coefficient of cubic effect of lactation week
x - lactation week
Univariate analysis of variance was performed on the
generated intercept and coefficients to test differences
for a given regression parameter among rations, body
condition, blocks and interaction. The model for slope
parameters included:
Y1 - u + a1 + 83 + (aB)ij + Ck + Eijkl
Where Yijkl a dependent slope parameter
u = mean slope parameter.
ai - fixed effect of diet
Bj a fixed effect of body condition
Ck a random effect of block
(33)1j a ration by body condition interaction
and Eijkl - the residual error

Overall differences between regression equations due
to ration, body condition, block and interaction were
tested using the multivariate analysis Procedure of SAS.
The model included those terms above.

Tests for partitioning of the variance in dry matter

intake and milk production were determined by using the

31

centrifuges and at the same speed as was reported for blood
ketones. Plasma and deproteinized whole blood for ketone
analysis were pipetted into blood dilution vials and held
at -30‘ C until thawed for analysis. In all cases blood
plasma for glucose was separated and frozen within 30
minutes of sampling. Ketone preparations were frozen
within 2 hours of blood collection and blood plasma was
frozen within 3 hours.

Glucose and creatinine were measured using diagnostic
kits obtained from Sigma Chemical, St. Louis, Mo.
Absorbance readings were obtained on a Guilford model 2400-
S spectrophotometer. Nonesterified fatty acids (NEFA) were
determined by using NEFA-C kits obtained from Wako
Pharmaceutical (Dallas, Texas) after dilution by the method
of McCutcheon and Bauman (1986). Absorbance of NEFA was
read on a Guilford 2400 with a sipper attachment.

Linearity was obtained on all analysis. Recovery of
glucose, creatinine and NEPA were determined to be 102.4%,
96.8% and 100.7% with a coefficient of variation of 6.8%,
12.8% and 1.2% respectively. Determination of mMole of
ketones, glucose, creatinine and NEPA in plasma was

calculated by the following formula:

Initial Absorbance of sample-Final Absorbance x of standard

 

Initial Absorbance of standard - final absorbance standard

32
regression procedure in GLM of SAS in a stepwise
elimination procedure. Variables with R2 < .20 were
dropped from the model. Variables were tested for linear,
quadratic and cubic effects.

Comparison of means between primiparous and
multiparous cows were determined using Student's t test for
differences between treatment means of unequal replication.
Specific comparisons among ration and body condition means
over the first three treatment weeks were compared against
the Bonferroni t statistic (Gill, 1978).

Calculation of ration energy (NEl /kg) was from 1988
NRC (Sixth revised edition). Calculation of 4% fat
corrected milk was also from NRC.

Energy Balance was calculated as from Villa-Godoy

(1987).
RESULTS

PREPARTUM COWS

Prepartum cows showed no significant differences due
to ration in any blood variables except for plasma
concentrations of triacylglycerol ( ration 1 less than
ration 2 and ration 1 less than ration 3, P<.01). Dry cow
diet formulation is presented in Table 1. Means and
contrast significances for all dry period variables are
presented in Table 2. Because experimental diets were not
offered until day of parturition, the finding of lower

plasma triacylglycerol for cows fed ration l was considered

33

Table 1. Feed composition of prepartum rations (percent of dry
matter basis).

 

Location Feed Percent
Campus Haylage 18.8 %
Cornsilage 65.4 %
Shelled corn 6.5 %
Soybean meal (44%) 7.2 %
Trace mineral salt 0.4 %
Vitamin-mineral
-premix * 0.4 %

Upper Penninsula

Haylage 88.8 %
Shelled corn 10.6 %
Trace mineral salt 0.2 %
Vitamin-mineral

premix * . 0.4 %

* Formulated to provide 0.25% calcium, 0.18% phosporus,
0.25% magnesium of total ration dry matter as well as
1000 IU of vitamin A, 125 IU of vitamin D and 12 IU of
vitamin E per 0.45 kg of ration dry matter.

34

 

9. 8.3 «.88 2me .802 > 83302 2
9. 25 23» 8&8 n > m 832
P. 82.. 8&8 6.8» N > 2 828 832
E 8..” 268 0.86 n > 2 828
9. 8.2 5.88 8.6% . 92 > 22. 82880 88 08203 168
86 E 829. 2.2 2.0 8.0 .802 > 83302 92
E 829. 26 2.2 2.2 n > m 838
E 8.29. 26 8.2 8.2 _ n > 2 830m 838
E 8222 26 2.2 8.2 n > 2 838
0822. soon
9. 819. $6 8.2 8.2 02 > 55. 82880 88 E 8228
8.0 E 8...“ 2.8 8.2. 28.2 > 82332 02
9. 8.2 8.8 8.8 n > a 820m
9. 8.2 8.8 8.8 u > 2 820m
9. 8.2 8.8 8.8 n > 2 830m 838
82g
9. and 3.8 8.3 you > 5.5. .533 moon Havana E
snug-ha n.— 3g am Can i 9mg EDT—Um Egg Gang

882288

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88a30~§8§88883§8§§8§288u5898u8 2038.

35

 

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000.0 00.0 00.0 0 > 0 832
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000.0 00.0 00.0 0 > 2 832 .
0,2000 0.032.380
32.0 00.0 02.0 03 > :32. 832280 0000 008. :2 200
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. 88m
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36

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n 00.0 00.0 02.0 20302 > 28.33002 #02

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0 00.0 00.00 00.00 .2302 > 28233002 #02

0 00.0 00.00 00.00 0 > 0 8.32

a 00.0 00.00 00.00 0 > 2 82332 8232

a 00.0 00.00 00.00 0 > 2 5232

a 00.0 00.00 20.00 300 > 5.5. 8.32080 0000 .202 5292
a 00.0 00.20 20.00 .2302 > 8.33002 902

0 00.0 00.20 00.00 0 > 0 5332

n 00.0 00.00 02.00 0 > 2 2.02322 c0232

0 00.0 00.20 02.00 0 > 2 82322

a 02.0 0.00 2.20 900 > 222222. 832080 0600 .002 8232

8300.235 0 32.5 920 :00: 0:00: 900.380 20300200 022003002. 022202.202,

008202820

2200220000503 . N 0.30.2.

37

 

828000302
308200020

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00 00230 00.0 00.0 00.0 0 > 2 8300
3829 080 .20 0
92 002? 00.0 00.0 00.0 300 > :25. 232320000 >000 0002220000 .090
20.0 E 00.0 02.00 00.02 0302 > 8300002 302
00 00.0 00.00 00.20 0 > 0 8300
E 00.0 00.20 00.00 0 > 2 8300 8300
02.0 E 00.0 00.00 00.00 0 > 2 8300
92 00.2 00.00 00.00 300 > 222220. 5232080 0000 008.080 000
20.0 92 002x92 00.0 20.0 00.0 _ 0302 > 830802 302
002 00232 02.0 00.0 00.0 0 > 0 8300
00 00202 02.0 00.0 00.0 0 > 2 8300 8300
92 00230 02.0 00.0 00.0 0 > 2 8300
300203 008 .96 0
9. 002? 00.0 00.0 00.0 U00 > 222222. 002320000 0000 0950000 .092
20.0 00 0.0 00.00 00.00 0302 > 833002 302
00 02.2 00.00 02.00 0 > 0 830
0.2 02.2 02.00 00.00 0 > 2 8300 8300
00 02.2 00.00 00.00 0 > 2 8300
E 00.0 00.00 00.00 300 > 025. 832080 080 00.538 002
0 3200 30 000: 0000: 300380 088200 #350009 020030>

283383 .0 0200.2.

38

 

30200232520

2.302 020.0 020.0 020.0 .2302 > 8303002 302
20.0 225... 020.0 000.0 000.0 0 > 0 8300
20.0 2.50. 020.0 000.0 . 020.0 0 > 2. 8300 8300
20.0 2.5.0 020.0 000.0 020.0 0 > 2 8300
002.30.350.80
25.00 000.0 000.0 000.0 300 > 0202. 832280 080 060 08020
2.50. 000.0 03.0 000.0 00302 > 8303002 302
22$... 000.0 000.0 020.0 0 > 0 8300
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28202 000.0 000.0 000.0 0.> 2 8300
8.3.538
2.50. 00.0 000.0 000.0 300 > 0202. 832280 080 0000 08020
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03 000.0 00.0 02.0 0 > 0 8300
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20.0 N 000.0 02.0 00.0 30302 > 8303002 302
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8230030302 0 03200 I 0082 008: 300.2380 2838200 3850332.

200823080 .0 0230.2.

39

 

308202520

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830002200260
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20.0 28.20 0000.0 000.0 000.0 0 > 2 82300 83003588
300030
2.5... 0200.0 000.0 020.0 300 > :05. 8232080 0000 2.200.200. 000020
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20.0 2.50. 03.0 000.0 000.0 0 > 0 82300
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20.0 2.5.0 03.0 000.0 000.0 0 > 2 82300
830992.850
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60033080 .0 02000.

40

 

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2.5.: 200.0 000.0 200.0 0 > 0 80300
2.58 200.0 200.0 000.0 0 > 2 52300 8038
2.5: 200.0 000.0 000.0 0 > 2 82300
83588
2050: 30.0 000.0 000.0 300 > 0202. 5230080 0000 52:22 030020
823000035 0 032.5 a :00: 0:00: 3000308 00300200 35030002. 0200200>

308202.520
20082358 .0 0200.2.

41

due to random differences between cows selected for ration
1. There was also significantly less (P<.05) ADP in the
rations fed at the CL station. There was also a trend
(P<.10) toward lower NDF content in the dry cow rations of
the CL herd. This may have been caused by the inclusion of
corn silage in the dry cow ration at the CL location.
Consumption of ADP (P<.Ol) but not NDF (P>.80) was greater
at the UP location.

Prepartum body condition, however, resulted in several
significantly different variables. Cows in fat body
condition prepartum had a significantly higher body
condition score (P<.Ol), gained significantly more body
condition (P<.05) in the weeks prior to parturition and
tended (P<.lO) to weigh more than those in thin body
condition. They tended to eat more (P<.10) which resulted
in a tendency to consume more NDF, ADP and acid detergent
lignin (P<.10). Fatter dry cows had higher levels of
plasma insulin (P<.05) but tended to have lower blood BHBA

concentrations (P < .10).

COWS

Although 30 cows initially began on trial, two cows
were removed from the data set. Both were first lactation
cows on ration l and assigned to fat body condition. One
was from the UP herd and one from the CL herd. The UP
heifer had a severe case of mastitis at parturition

resulting in a loss of one quarter. Although she

42

subsequently recovered, her milk production was so
abnormally low as to bias the data set. The CL heifer was
diagnosed with a displaced abomasum at 3 weeks of
lactation. Corrective surgery was performed, and she was
placed back on trial. However, 3 weeks later she was again
diagnosed with a displaced abomasum. Because these
incidents resulted in prolonged periods of reduced dry
matter intake, she was also dropped from the data set.

Additionally, two other cows, both assigned to ration
2 from the UP Experiment Station, were also diagnosed with
displaced abomasums upon parturition. The displacements
were corrected surgically, and the cows remained on trial
and continued without further incidence.

All four primiparous cows on ration 1 showed some
evidence of laminitis. Two of these, one at the UP and one
at CL herds, were severe enough so as to interfere with
walking. No founder symptoms were detected in multiparous
cows on ration 1 or in the cows fed any other diet.

DIET

Diet composition for lactating cows is presented in
Table 3 and nutrient composition for these diets is
jpresented in Table 4. Although total mixed diets were
«calculated to contain 16, 20 and 24% ADF, actual mean
ciietary ADF levels were 17.36, 20.25 and 22.77% (+0.33).
anaese differences were significant, however, (ration 1 vs

ration 2; ration 1 vs ration 3; and ration 2 vs ration 3,

 

43

 

Table 3. Approximate average ingredient composition of
experimental diets (percent of dry matter basis).
Diet
1 2 3
Location Ingredient
Campus Haylage 23.3 33.2 42.8
Shelled Corn 53.0 43.2 35.2
Soybean Meal
(44%) 22.1 22.1 20.5
TH salt .45 .45 .45
Limestone .35 .35 .35
Dicalcium
phosphate .55 .55 .55
Vitamin-trace
mineral mix .19 .19 .19
Forage:concentrate 23:77 33:67 43:57
Upper Penninsula
Haylage 29.0 39.6 49.2
Shelled corn 49.2 39.6 32.0
Soybean meal I
(44%) 20.7 19.5 17.7
TM salt .41 .41 .41
Sodium mono- ,
phosphate .40 .39 .39
Vitamin-trace
mineral mix .41 .41 .41
Forage:concentrate 29:71 40:60 43:57

44

Table 4. Nutrient composition of experimental diets (percent of
dry matter basis).

 

DIETS
Fraction 1 2 3
Neutral
detergent fiber 33.38 36.15 38.19
Acid detergent
fiber 17.36 20.25 22.77
Acid detergent 3.00 3.55 4.24
lignin
Ash 6.23 6.75 7.32
Net energy*
lactation (MCal/kg) 1.73 1.67 1.63
ORTS
Neutral _
detergent fiber 34.98 38.15 39.22
Acid detergent
fiber 18.08 21.63 23.98
Acid detergent 3.05 3.85 4.41,
lignin
Ash 6.51 6.90 7.48

* Calculated value from ADF

45
P<.Ol) (Table 5). Average crude protein content of the
diets were 17.96, 18.13 and 18.22% for the respective
diets. All diets contained significantly different amounts
of energy (P < .01), NDP (P < .01) and lignin (P < .01)
(Table 5), but not ash. Percent fiber composition of orts
was numerically higher than the ration for all fiber
fractions although this difference was not significantly
different from the ration (Table 6: P > .10). Because of
changes in the composition of the haylage, the fiber
fractions of the total diet changed significantly over
time. This data is presented in Appendix Tables 11914.
This resulted in significant individual variation of feed
composition among cow blocks depending on date of
parturition.

Caution must be applied to the summary statistics used
in the analysis of feed constituents. ‘The statistical
model selected included lactation week. This is an
adequate model for most dependent variables, but as already
noted, experimental cows did not all calve in the same
week. In fact week of parturition covered a 16-week time
span. The percent fiber in the diet, both ADP and NDF
varied over this time span as noted above. Use of
lactation week in the model, therefore, resulted in an
inflated error term. Realizing this could bias
interpretation of the experiment, the percent of fiber in
the diet and DMI were reanalyzed by replacing the lactation

week term in the model with actual calendar week. The

446

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50

model for DMI was also run using the_actual ADF level of
the ration as a covariate.

The model using lactation week explained 79% of the
variation in AD? percent of the ration (Table 7). In
contrast to this model, the model with calendar week
explained 95% of the total variation for ADP percent of the
ration. There was a significant block effect when
analyzing ADP percent in the rations if the model contained
either lactation week or experimental week because blocks
were confounded with date of parturition to some extent.
Thus, blocks were somewhat confounded with calendar week.
In both cases ADF percent of the ration was significantly
different (P<.OOOl) among diets (Table 7).

Significance level of dry matter intake was not
affected by the replacement of lactation week with calendar

week or by use of ADP as a covariate.

PRODUCTION

Milk production was significantly greater (P<.05) for
cows fed ration 1 than those fed ration 3. Ration 2 was
not significantly different from the other two (P>.lo,
Table 8), although ration 2 was almost numerically equal to
ration 1. Production of 4% fat corrected milk (4 FCM) per
100 kg of body weight was higher for ration 1 than ration 3
(P<.05). This difference was more tentative (P < .10)
based on total weekly 4% FCM production. Milk production,

milk composition and component yield were unaffected by

51

Table 7. Source of variation of ADF levels in the ration for
experimental designs employing either lactation week or calendar
week in the model (Type III sum of squares).

Model: Lactation Week

 

 

Source of Degrees Sum of
Variation of Freedom Squares
Ration 2 1464.3475
Body Condition 1 2.2728
Ration X Body Condition 2 6.2810
Block 4 246.7486
Ration X Body Condition X 18 160.6890
Block
Lactation Week 9 155.5199
Ration X Lactation Week 18 35.8975
Body Condition X 9 24.3830
Lactation Week
Ration X Body Condition X 18 25.2208
Lactation Week
Error 198 595.9665
Total 279 2718.6499
Model: Experimental Week
Source of Degrees Sum of
Variation of Freedom Squares
Ration 2 722.4887
Body Condition 1 .0450
Ration x Body Condition 2 .8514
Block 4 220.5189
Ration X Body Condition X 18 39.5602
Block .
Experimental Week 22 408.4732
Ration x Experimental Week 39 69.7884
Body Condition X 21 4.7287
Experimental Week
Ration X Body Condition X 30 6.1325
Experimental Week
Error 139 256.8861

Total 279 2718.6499

552

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55

body condition (P>.10). Milk composition was also
unaffected by ration (P>.10). Total weekly production of
milk protein was greater for cows fed ration 1 than 3
(P<.05). There was a trend (P<.10) for cows on ration 1 to
produCe more kg of total weekly milk solids. Weekly milk
fat yield was not affected by either body condition or
ration. Weekly production variables are presented in
Appendix Tables 1-6.

Primiparous cow blocks produced less milk (P<.01) than
multiparous cows. As a result, they produced less 4% FCM,
less kg 4% FCM per 100 kg of body weight, less kg milk fat
and less kg of milk protein (P<.01). Percent of milk
components was not different between older and first
lactation cows (P>.10).

Obviously week of lactation had a strong effect
(P<.01) on the amount of milk produced (Figure l) and, as a
result, had a corresponding effect on kg of milk components
produced (P<.01).

Analysis of coefficients of individual lactation
curves generated by regression (mean R2-.82) to gain
insight into how the ration was affecting production
indicated that the intercept parameter was not different
among diets (P>.10). There were, however, significant
differences between linear, quadratic and cubic effects of
lactational week and treatment (ration 1 vs ration 2,

ration 1 vs ration 3 and ration 2 vs ration 3, P<.Ol) for

K6

56

 

 

 

 

 

 
 

 

T l l I I

6 7 3 _ 9 10 H
WEBG
D Nation! 1’ Ration: 9 NotionS

Figure 1 . Mean weekly milk production of cows fed three diflerent levels of ADP.

57
all coefficients (Figure 2).

Similar analysis on regression equations on kg of milk
fat produced differences in intercept and linear
coefficients as well as trends for quadratic and cubic
coefficients (Figure 3). Milk fat percent was not affected
differently (P>.10).

Analysis of regression equations for weekly milk
protein percent, total kg of milk protein, milk solids
percent and total solids production produced no evidence
that rations were affecting slope parameters (P>.10).

Neither univariate or multivariate analysis indicated
that body condition had any effect on coefficients of
either milk or milk constituents (P>.10).

A word of caution must be applied to the
interpretation of these regression equations. The
intercept parameter can be interpreted as the starting
point assuming the equation adequately describes the
relationship. The linear slope approximates the initial
increase or decline from the intercept while the quadratic
coefficient describes the rate of change when the equation
reaches its maximum or minimum. Cubic effects may be
viewed as reflecting lack of symmetry in the curve since a
pure second degree curve is necessarily symmetrical about

the maximum or minimum.

K6

 

58

 

 

 

 

n ITTlrrUIIIIlrTIjIllTrIlIIIWIIIIIITIIIIITIIIIIIIIIIIFIII

O- 1 2 3 4 a 6 7 B 9 10 11
was
D Rationl 1' "1:!an 9 fiction!

Figure 2. Regression plots at milk production at cows ted three diflerent levels of ADP.

K6

59

1.6

 

 

1.5-

 

1.4 "l "

l‘
1 . . ‘ u 3'
1.3 q ' ‘ g

1.1 - ' ?

07"

 

0.6

 

 

IIIIIIIIIIIIIIIllIIrllllIIIIIIIIrIIIIITIIIIIIIIIIIIIrI
O 1 2 .‘l 4 a 6 7 ,8 9 1O 11

was
I] Nation 1 '1' Nation 2 9 fiction .3

Figure 3. Regression plots at milk tat production of cows led three different levels oi ADF.

60
BODY WEIGHT AND BODY CONDITION

Body weight, body weight loss, body condition score
and loss of body condition were not affected by the ration
consumed (P>.10) (Table 9). Fat cows weighed more (P<.05)
and lost more body weight than thin cows (P<.05) but there
was no difference between fat or thin cows in body
condition score or change in body condition score (P>.10).
Because the fat cows had significantly higher body
condition scores prepartum, a majority of the loss of body
condition must have occurred in the week of and in the
first week after parturition which was not measured. This
implies that loss of body condition is quite rapid.'

There was a strong effect of time on body weight, body
weight loss, body condition score and change in body
condition score (P<.01). Analysis of the cubic regression
equation for effects of body condition on body weight
revealed that the intercept was the only significantly
different parameter among rations (P<.05, Figure 4).
Multivariate analysis of variance revealed a trend for an
interaction of body condition and ration (P<.10). These
interactions are represented in Figures 5, 6 and 7. Visual
analysis leads one to conclude that the cows consuming
ration 2 and in heavy body condition lost weight at a
slower rate than those cows fed ration l or 3.

As would be expected, body condition had a significant
effect on body condition score (P<.05); that is fat cows

had higher body condition score than thin cows. But the

61

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L98

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62

 

 

 

 

 

O

 

IIITIIITIIFIIIIIIIIIIIIIT

1 2 a 4 a 6 7 a 9 10 11
m0 ‘
El Thin Body Condition (<25) + Fat Body Condition (>25)

Figure 4. Regression plots of the body weight of cows at two different body conditions.

63

1.42

 

1.4 -

1.3-

1.3-

1.34-

1.23"

1.15"

LBS

(Thoueonde)

1.26--
1.25

1.24- a“

1.22- ._.

1.2 "i

 

 

1.18 "‘

Ci Thin Body Condition (<25) + Fat Body Condition (>25)

Figure 5. Regression plots of the effect of interaction between ration 1 and
body condition on body weight.

64

 

1.8

t7-

1.6 "

1.8“

L98

(rhoueartde)

‘ Ll L I l l .
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O 1 2 .3 4 s 6 7 8 9 lo 1 1
was 1
El Thin Body Condition (<25) + Fat Body Condition (>25)

Figure 6. Regression plots of the effect of interaction between ration 2 and
body condition on body weight.

65

1.44

1.42

 

1.4 “
1.3- '
1.3-1 .1
1.34-
1.32-

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L38
("wuuuddl

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1.2“ “ --,--.- .w‘ " ‘—___ 
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12- _

 

 

 

‘43 1111111111IlfrllllirllfflllilirlrillftllIIIIIIITIIIII

0 1 2 .3 4 s 6 7 a 9 10 1 1
. we .
0 Thin Body Condition (<25) + Fat Body Condition (>25)

Figure 7. Regression plots of the effect of interaction between ration 3 and
body condition on body weight.

66

loss of body condition was not different between fat and
thin cows (P>.10) . Week of lactation had a significant
effect on body condition score and change in body condition
score. A significant body condition by time interaction
was also detected (P<.05). Additionally, there tended to
be interaction between week of lactation and body condition
for body weight, body condition score and change in body
condition score (P<.10).

Univariate analysis of the regression equations for
body condition score (mean R2-.66) revealed that the
intercept was the only parameter that was affected by body
condition. Also revealed by MANOVA was a significant
diet by body condition interaction for the regression
equations (p<.os, Figures 8, 9, 10, 11, 12). Visual
analysis of regression plots revealed that this was due to
the fat cows on ration l which-fattened in the last weeks
of the experiment. This fattening was detected as an

increase in body weight.

DRY MATTER INTAKE

Total dry matter intake was not significantly affected
by ration (Figure 13) or body condition (Figure 14)
(P>.10) (see also Table 10 and Appendix Tables ll-20).
There was a large effect of lactation week (P<.Ol) as well
as a highly significant difference in the DMI between
primiparous and multiparous cows (P<.0l). In this

experiment, multiparous cows ate almost 38% more.

SCORE

67

 

 

 

 

 

Figure 8. Mean weekly body condition score of cows fed three different levels of ADP.

860 RE

 

68

 

 

 

 

1.6“ ..
1-5 IIIIIIIIIIilll1111IIIIIITTIIIHIIII'IHIIIII11111111111
O 1 2 a 4 a 6 7 8 9 1O 11
WEBG
CI RATION1 '1' RATION2 9 NATION:

Figure 9. Regression plot of body condition score of cows fed three different levels of ADF.

860 RE

69

 

 

 

O

 

lllrlllllflillIITIIIIIIITIIIIllllTllllIIliIllIIIITIIIT
1 2 .3 4 a 6 7 8 9 10 11

El Thin Body Condition (<25) + Fat Body Condition (>25)

Figure 10. Regression plots of the interaction of ration 1 and body condition
on body condition score.

860 RE

4.4

70

 

u.

4-
aa-
.16-
34‘
32-:

3..
28-
26-

24"

2 -
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S 0
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has: '-
llllrlllIrIllIIIIITIIIIIIIIIIIIIIIIIIIIllllllllerllTl
1 2 .3 4 a 6 7 8 9 10 11
m

E] Thin Body Condition (<25) + Fat Body Condition (>25)

Figure 11. Regression plots of the interaction of ration 2 and body condition

on body condition score.

SCORE

.11

71

 

a-
2.9
1.1
27"
26-

24"
236-1

21 '1

2 u
1.9 '1
1.8 ‘
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i:
N
J
6‘
N
.V
j
‘0‘
IllrllilllIIITIIIIII[IIIIIIIITITIIIIIIIIIIIIIIIIIIIITI
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WEBG

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+ Fat Body Condition (>25)

11

Figure 12. Regression plots of the interaction of ration 3 and body condition

on body condition score.

KC

72

 

 

 

 

 

17°
1. - L L a
120 "i
140 "
133 ‘
120 "'
it
110 I I I I I I I I I
2 3 4 5 6 7 a 9 1O 11
m
:1 fiction 1 '1' Mb!) 2 9 fiction 3

Figure 13. Mean weekly dry matter intake of cows fed three different levels of ADF.

KG/WEEK

73

 

 

 

 

17°
19 "‘
1.10 d / I E c I
140 6
1.!) "l
120 "1
“O I I I I 1 I I I I

2 .3 4 a 6 7 8 9 1O 1 1

111E516
U Thin Body CODdiiiOi'l (<25) + Fat Body Condition (>25)

Figure 14. Mean weekly dry matter intake of cows at two different body condition scores.

'74

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77

Regression equation analysis revealed no differences in
intercept or slope parameters (P>.10) among diets or
between body conditions.

Dry matter intake as a percent of body weight did tend
to be higher (P<.10) for ration 1 than ration 3.i
Primiparous cows consumed less dry matter as a percent of
body weight than did multiparous cows (P<.01). Analysis of
parameters for regression equations revealed no differences
due to ration or body condition (P>.10).

Ingested amount of NDP and ash were not different for
either rations or body condition (P>.10). ADF intake
tended to be greater for cows consuming ration 3 than
ration l (P<.10) while lignin intake was significantly
higher for cows fed ration 3 than ration l (P<.01). First
lactation cows, because of lower dry matter intake, ate
significantly less NDF, ADP, lignin and ash (P<.01). For
all rations, consumption of all fiber fractions as a
percent of body weight was only slightly different, but
less significantly so than that of total fiber intake
(Table 10). As a percent of body weight, primiparous
blocks ate less fiber constituents than mature cows
(P<.05).

Univariate analysis of the regression equation
parameters for amounts of ingested NDF among rations
indicated that there were no differences in intercept or

slopes of the regression line (P<.10). There was no

evidence from the Manova of 23y differences in NDF intake
(P>.10). That is, the regression equation confirmed that
the cows all consumed the same amount of NDF. There was
evidence for a body condition by ration interaction
(Figures 15, 16 and 17). Visual analysis of the regression
plots indicated that fat cows eating ration 2 consumed more
NDF than the thin cows. For cows consuming rations l and
3, the thin cows consumed more NDF than did fat cows. .
Similar analysis of the regression equations for ingestion
of ADP indicated a significant effect of body condition
(P <.05) on ADF consumption (Figure 18). Fat cows consumed
more ADF than thin cows. ‘
BLOOD METABOLITES

Blood metabolite and insulin concentrations were
unaffected by ration (P>.10, Table 11) except for B-hydroxy
butyric acid (BHBA) (ration 1 less than ration 3, P<.05:
ration 2 less than ration 3, P<.10) (Figure 19). There was
a trend for T6 to be affected by diet (ration 1 less than
ration 3, P<.10). Ratio of BHBAzacetoacetic acid was
significantly affected by body condition with thin cows
having significantly (P<.05) higher ratios than fat cows.

All blood metabolites showed significant differences
with advancing lactation (P<.05) except ketone ratios and
plasma insulin (P>.10, Figures 20, 21, 22, 23, 24 and 25).

Analysis of regression coefficients and MANOVA testing
revealed no effect of diet or body condition on any blood

variable except NEFA. Univariate analysis of the

K6

79

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Flame 15. Regression plots oi the effect of the NDP consumption in ration 1 and
body condition on body weight.

K6

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‘0 IIIIIIIIIItillrtlilllllilitlllllllllIIIIIIIIIIIIIIIIIT
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El Thin Body Condition (<25) + Fat Body Condition (>25)

Figure 16. Regression plots of the eitect oi the NDP consumption in ration 2 and
body condition on body weight.

11

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Figure 17. Regression plots of the effect of the NDF consumption in ration 3 and
body condition on body weight.

 

11

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Figure 18. Regression plots of the effect of body condition on ADF consumption.

133

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86

 

 

 

 

3‘ I I I I I i I I
2 a i‘ a 6 7 a ' 9 1O 11
WEB-G
U MON 1 ‘1' “ON 2 9 RATIDN 3

Figure 19. Mean weekly concentration of B-hydroxybutyric acid (mMoles)in the whole blood of
cows fed three different levels of ADF.

mMOLE

0.034

87

 

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0.024 n
0an -
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experimental cows.

 

Figure 20. Mean weekly concentration of acetoacetic acid (mMoles) in the whole blood of

 

mMOLE/ML

 

 

0.1 I I

 

 

 

Figure 21. Mean weekly concentration of plasma nonesterified fatty acids (mMoles)
of experimental cows.

11

89

0.01

 

mMOLE/ML

 

 

 

 

Figure 22. Mean weekly concentration of plasma triacylglyCerol (mMoles) of experimental cows.

mMOi£

 

90

 

 

 

 

Figure 23. Mean weekly concentration of plasma glucose (mMoles) of experimental cows.

rte/Ml-

O4

91

 

0.25 -
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03 -‘
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1O

11

Figure 24. Mean weekly concentration of plasma insulin (ng/ml) of experimental cows.

mMOLE

0.16

92

 

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Figure 25. Mean weekly concentration of plama creatinine (mMoles) of experimental cows.

93

coefficients of the NEFA regression equations revealed a
trend for the intercept and linear effects of lactation
week to be different among rations (P<.10) while quadratic
and cubic effects were non-significant (P>.lo, Figure 26).
First lactation cows had significantly lower NEFA levels
(P<.05) but significantly higher plasma levels of glucose

(P<.01) and insulin (P<.05) than did multiparous cows.
COMPARISON OF LACTATION WEEKS 8-11

As data from this experiment became available, it
became increasingly clear that ration and body condition
effects would be hard to measure in early lactation. It
appeared as though the hormonal, neurological and metabolic
effects of parturition were so great as to obscure the
effect of ration or body condition. For this reason, a
subset of data was prepared, consisting of only the last
four lactation weeks of the experiment. Visual analysis of
graphic data indicated that this period was relatively free
from parturition effects.

Before examining this subset in more detail, it was of
interest to compare the early weeks of lactation with the
later weeks to see if there was a difference in the values
of meaningful variables. The first three weeks of the
experimental period (weeks 2-4) were chosen as the other
comparison period because these weeks appeared to represent

the maximal influence of the effect of parturition

mMOLES

94

1.8

 

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15 -'
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1.4 "'
1.3 "
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02 ‘
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0 1 2 3 4 a 6 7 8 9 10

was .
U 16% AU' '1' 205: MI" 0 24% AU’

 

Figure 26. Regression plot of the effects of diet on plasma free fatty acid levels.

 

 

95
compared to those weeks that represented the maximal

effects of dietary treatments (weeks 8-11). Because the
prior selection of weeks to compare was made after initial
study of the data, the probability of treatment effects
have been conservatively estimated using the Bonferroni t
statistic rather than the Students t for comparison of
differences between treatment means.

There were significant differences for all variables
between the early and late period except plasma creatinine
and insulin, kg of milk protein/week and production of 4%
FCM/loo kg of body weight (Table 12).

When only the last four lactation weeks of the
experiment are considered, it becomes obvious that ration
and body condition are having effects not seen earlier
(Table 13). There is no significant effect due to
lactation week during the last four weeks of the
experiment. This indicates that the cows were in a more
stable metabolic and productive state. There was also less
of a spread in the ration fiber levels (16.9 %, 19.1 % and
21.7% ADF and 33.0 %, 34.1 % and 36.9% NDF for rations l, 2
and 3 respectively). Body condition scores were also
narrowed at this time (mean of 1.6 for thin cows and 1.82
for fat cows). Although feed intake and blood metabolites,
with the exception of BHBA, were not significantly affected
by ration during the final weeks of the experiment, several
production variables were significantly different.

The mean weekly production of milk was the same for

536

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N66 86 N66 . N > 6 563m 8636
666 :6 N66 6 > 6 86656
88m
666 666 N66 86 . you > :65. 83666.8 38 8369.8 38
666 9. 366 6666: 2.6? .6366 > 566386 ”E6
9. 6666 66.66.. 3.66.. 6 > N 8396
62 66.66 3.66.. 66.3.. N > 6 SHE 836m
9. No.66 6666.. 666? 6 > 6 836m
6.56.3
666 E 3.66 66.3: 6666- 63 > :68. 86669.8 68 668. no 686
666 9. B66 N336 66666 6366 > 83386 36
E 6666 66.666 66.666 6 > N 8396
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9. 6N3 3.666 363. 6 > 6 86.56
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38. B 8366 666 E 866 66.36 866m gnu > :26. 83688 .68 366m: 686
656606.635 .6 B65 .86 :8: 88: ”$5.8 36866.6 egg 66666.3,

6886683 .66 0666.6.

102

 

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66(6: NN6.6 66.6 N6.6 N >.6 666666 666666
6a<mc 6N6.6 66.6 N6.6 6 >.6 666666
6666: 666.6 66.6 66.6 666 626666 666666666 6666 6666666 666666
.65666 666.6 66.6 . 66.6 66666 6.666666666 666
.6566— 666.6 66.6 66.6 6 >.N.co666m
6.3... 36.6 666 66.6 N > 6 SHE SHE
6.5.6 366 666 66.6 6 > 6 SHE
.6666. 666.6 66.6 66.6 666 >26666 666666660.6666 6666666666 666666
6.3: 666.6 666 666 66666 > SH66066 666
66$... 6666 6N6 66.6 6 > N SHE
6.566 6666 66.6 666 N > 6 SHE SHE
6% 666.6 6N6 66.6 6 > 6 SHE 66666 66666
6666666666
6.36. 6666 6N6 66.6 _ 666 > 6666. SHHSO .6666 :86 666666
66.6 6.5... 3666 6666.6 6666.6 66666 >. SH66666 666
6.566 6666.6 6666.6 6666.6 6 > N SHE
66$... 6666.6 66.666 66666 N > 6 SHE SHE
.66666 6666.6 6666.6 6666.6 6 6.6 666666
606.6963
6.62:. 6666.6 6666.6 6666.6 666 626666 666666660 6666 -6666666 666666
.6666. 666.6 66.6 66.6 66666 6.666666666 666
6.5... N666 66.6 666 6 > N SHE
6.5... N666 666 66.6 N > 6 SHE SHE
66$.- N666 66.6 666 6 > 6 SHE
666.v6. 666666660
668 B SHE 66$: 666.6 66.6 66.6 666 > 5666. SHHSo 6666 668666 666666
666666666666 6 66666. .666 .6666 6666:” 66666666 66666666 666666666 66666666

8665688 .66 6666.6.

103

3.0

 

66.6 6 66.6 66.6 66666 > SH66666 666
66.6 6 66.6 66.6 66.6 6 > N SHE
66.6 6 66.6 66.6 N6.N N > 6 SHE SHE
66.6 6 66.6 No.6 EN 6 > 6 SHE
66.6 6 66.6 N6.6. 66.6 666 > .6666. SH6668 6666 6 666666 SHE
6 66.6 66.66 66.66 6366 > SH66666 666
66.6 6 6N.6 66.6N 6.6.66 6 > N SHE
66.6 6 6N.6 66.66 66.66 N > 6 SHE SHE
66.6 6 66.6 66.6N 66.66 6 > 6 SHE
6 66.6 6N.66 6N.66 666 > 6666. SH6668 6666 6 .696 SHE
6 66.6 66.66 66.66 66666 > .SH66666 666
66.6 6 N6.6 66.66 66.66 . 6 > N SHE
66.6 6 N6.6 66.66 66.66 N > 6 SHE SHE
66.6 6 66.6 66.66 66.66 . 6 > 6 SHE
6 66.6 6N.66 66.66 666 > 6666. SH66666 6666 6 .666 SHE
666.6 66.6 666.6 66666 > 86666666 666
666.6 666.6 666.6 6 > N SHE
666.6 666.6 N66.6 N > 6 SHE SHE
666.6 666.6 N66.6 6 > 6 SHE
306.. 0.3606
N66.6 666.6 N66.6 666 > 6666. SH6668 6666 .6686 666666
666.6 666.6 666.6 66666 > SH66666 666
666.6 666.6 N66.6 6 > N SHE
666.6 N66.6 N66.6 N > 6 SHE SHE
66.6 666.6 666.6 N66.6 6 > 6 SHE
mooé 36.6 2.66 66.6 > 5.5. 6866666660 .3666 am 66663
6666666666 6 6665 666 666: 6666: 6666686 66666666 666666666 6666666>

6662666686 .66 6666.6.

104

 

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No.0 » 3.0 no.0 006 N > a 530% sound

no.0 » 3.0 9.0 006 n > A 8.3mm
a 3.0 no;J .36 you > 55. 003.830 >08 0 can mac
n 60.0 066 3..” H33 > 8.3303 um."

m0.0 » 00.0 en... 066 n > N 830%

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3.0 a 60.0 3.0 mm.N n > .n 8.3mm
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a 8.0 3.8 3.8 H33 >3338~ ufl

8.0 n 8.0 3.8 2.8 . n > a 83mm

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» 8.0 mmén 606m n > N 8.3mm

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no.0 « 3.0 mmén 00.00 m > .n 5.39”

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.2680 .2 038.

105

 

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9. 83}! 36 38 3.8 n > a 538 SE8
9. 83B: 36 2.3 33 n > a 838 £38 38.
9. o3\
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9. 2.6 3.3 3.3 n > m 538
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9. $5 3.3 3.3 n > 3 838
36% 382
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B 36 33 mg. a > H 538 538
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78.x: E 83 3.3 3.3 n > a 838
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3.8V 9. 3.3 3.3 3.3 n > a 838
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833980 8 E 3.3 «.3 3.3 you > 35. 833 38 E80 .32
93% m 33.5 93 :8: 28: 3.58 8838 £3.53 333.3,

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106

 

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36 a 36 3.7 36.. N > H 838 838
3.86 .86 u 36 3:? 36: n > a 838 m8 8 88
38.3 :85 an 503.3 .32
833.8 88 a 36 8.7 3.3.. you > 35. 833.8 88 5 888.38
36 a 36 3.? 3.3.. 83 > 83303 33
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36 a 36 8.? 36. n > H 838 m8 8 8n
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9. 638.. N66 36 36 83 > 83303 33
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9. 6380. 86 36 86 N > a 838 838
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38: 3.3 3.3 33.3 3 > 3 838
8.33
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9.38: 366 33 3.3 N > 3 838 838
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80:53:03 . 3 0339

108
rations 1 and 2 during this period. Both ration 1 and 2

resulted in significantly higher milk production than
ration 3 (P<.05). There was no significant difference in
milk composition among diets, although production of milk
protein and total milk solids was significantly less for
ration 3 than the other two rations (P<.05).

There was also a significant ration by body condition
interaction effect on body weight (P<.Ol) and a trend for a
significant ration by body condition interaction effect on
milk production and plasma glucose (P<.10). The fat cows
fed ration 2 weighed more and produced more milk than did
thin cows fed the same ration. Thin cows produced more
milk than fat cows on rations 1 and 3. Fat cows weighed
more than thin cows fed ration l and 2 but not ration 3.
Because all fat cows weighed more than thin cows at
parturition, fat cows fed ration 3 must have lost greater
amounts of weight by the last weeks of the experiment.
Plasma glucose levels were higher for fat cows fed ration 1
than thin cows fed ration 1. For cows fed rations 2 and 3
plasma glucose was higher for thin cows.

During the last four experimental weeks, body
condition had a significant effect on the milk fat percent
(3.19 and 3.56 for thin and fat cows respectively, P<.05).
This certainly indicates that fat body condition at calving
has positive effects on milk production in the later weeks

of lactation.

109
Dry matter intake, both in total or as a percent of

body weight, was not significantly different among diets
(P>.10) over the last 4 experimental weeks. However, DMI
was linear with ration ADF during this period (164.3
kg/week, 157.8 kg/week and 148.0 kg/week for diets 1, 2 and
3 respectively). Dry matter intake was also linear with
NDF content.

Milk production, however, was not linear with ration
fiber level (269.0 kg/week, 269.1 kg/week and 232.2 kg/week
for rations 1, 2 and 3 respectively). Efficiency of
production (kg milk/kg DMI) was numerically, but not
significantly, higher on ration 2 (1.71) than for ration 1
(1.64) or ration 3 (1.61). Consumption of NDF and ADF,
either in total or per 100 kg of body weight was not
different among dietary treatments or between body
conditions (P>.10). Lignin intake, however, was different
(P<.01) both on a total and percent of body weight basis
among all rations. From strictly a statistical point of
view, both NDF and ADF but not lignin could be considered
as potential regulators of intake in the last four weeks of
this experiment. Production of 4% FCM/100 kg of body weight
tended (P<.10) to be lower for cows fed ration 3 than those
fed ration 2. Production of 4% FCM was significantly
higher for cows fed rations 1 and 2 compared to ration 3

(P<.05).

110
ENERGY BALANCE

Calculations of energy balance used in this study in
absolute terms are of little value because energy content
of the diets were estimated rather than determined by
digestion trials. But the relative values do allow
comparison of diets, given the assumption that energy
requirements vary by body weight and milk production (NRC,
1988). Although heifers have an additional requirement for
growth, this requirement has been deleted from the
calculation. It was felt that this calculation should
allow detection of the relative amounts and duration of
negative energy balance among diets and between body
conditions. This data is represented graphically in
Figures 27 and 28. It is obvious that neither ration or
body condition had a significant effect (P>.10) on the
duration or length of negative energy balance. It is also
apparent that in this study high milk production did not
result in greater energy deficit; the cow simply reduced
the amount of milk she produced to accommodate the amount
of energy deficit that she could tolerate. This result
further suggests that in early lactation hormonal control
of feed intake is more important than dietary control, but
dietary control is more important for milk production.

This finding of no difference in energy balance among
diets or between body conditions is not supported by the
current literature as previously reviewed. Most authors

have found the degree of energy deficiency to be more

M60 I

111

 

m—
“-1
a-
”a

10"

 

 

 

 

 

 

I I I I I I
5 G 7 a 9 10 11
was .
D RATIONI + NATIONZ 9 NATIONS

Flgure 27. Mean weekly energy balance (MCal/week) of cows led three levels of ADF.

MCal

112

 

mu-

m:

20%

10"I

 

 

-10 "
-m 'l
-3 1

-‘o-i

 

 

r
J 4 5

El Thin Body Condition (<25) + Fat Body Condition (>25)
Flgure 28. Mean weekly energy balance (MCal/week) of cows at two body conditions.

113

severe and longer lasting than in the present study. Since
most of the conclusions about energy balance have been
arrived at by calculations performed exactly as in this
study, the differences between these other investigations

and the current study is inexplicable.

DMI REGRESSION ANALYSIS

The regression model which best predicted intake
consisted of the following terms:

DMI - Parity + Body weight + milk production + NEFA
(R2 -.73). _

However the R2 for NEFA was only .09, much less than
the a priori selected minimum R2 of .20.

The basic model was:

DMI- Parity + body weight + milk production (R2 = .53)

Adding the quadratic or cubic effects for body weight
or milk production improved the model only slightly. For
any variable selected except these three, the R2 never rose
above the .09 reported for NEFA. Linear and quadratic
terms were tried for all variables without effect.

The percent of variation that was explained by the
basic model is presented in Table 14. Milk (R2 - .48)
explained 15 percent, parity explained 14.1 percent and
body weight 9.6 percent. Parity plus milk explained the
largest percent of variation at 17 percent.

Adding fiber terms, either linear, quadratic or cubic,
to the basic model only improved the R2 slightly. Lignin

114

Table 14. Correlation coefficients for explanation
of dry matter intake variance by
regression models.

 

Model Variable R2
Milk + parity + milk .48
body weight parity .44
body weight .30

parity + milk .53
body weight + milk .48

Parity + body weight .44
parity + body weight

+ milk .53

Milk + parity + milk . .48
body weight + parity .44

NEFA body weight .29

NEFA .09

milk + NEFA .54

parity + NEFA .54

body weight + NEFA .55

parity + milk .53

body weight + milk .43

parity + body weight .44

parity + milk

+ NEFA .73
body weight + milk

+ NEFA .69
parity + body weight

+ NEFA .68
parity + body weight

+ milk .53

parity + body weight
+ milk + NEFA .73

115

was always improved the model more than ADF. ADF always
improved the model more that NDF. However, none of these
fiber fractions had an R2 that was significant.
DISCUSSION

The first stated objective of this study remains
unfulfilled. It is relatively easy to say that with the
fiber levels and cows used in this study, ration fiber as
measured by NDF, ADF or lignin had no statistically
significant effect on intake. However, feed intake of cows
fed ration 3 was numerically lower than cows fed the other
2 diets. It was postulated that if NDF were limiting
intake, total dry matter intake would be depressed at
different levels of ADP intake. Conversely, if ADF were
limiting intake, it was believed that levels of NDP intake
would be different. Total dry matter intake, however, was
statistically the same on all ration levels of fiber (P>
.10). This is probably due to the high degree of
association of NDF with ADP on these diets.

The fact that the cows ate a constant amount of NDP
and that the ratio of ingested NDFzADF was significantly
different among diets (P<.01) argues for the point that NDF
can affect intake as first proposed by Mertens (1982).
However, the fact that DMI/100 kg of body weight tended to
be different between rations 1 and 3 by the very same
probability (P<.07) that ADP/100 kg of body intake was

different argues that ADP may be as effective a regulator

116
of DMI as NDF. Pearson correlations of NDF (R2 -.09,

P<.12) and ADF (R2--.15, P<.Ol) with DMI indicate that ADF
is better correlated with DMI than NDF in this study
(Appendix Tables 29 and 30). However, neither were
correlated well enough to be considered a regulator of
intake. Thus, the problem is unresolved.

It must also be recognized that the levels of NDF in
the experimental rations were all higher than currently
recommended for optimum production of 4% FCM for cows
producing over 40 kg/day (Mertens, 1987; NRC 1989).
Therefore, it may be that levels of NDP in the experimental
diets were all high enough to depress feed intake on each
of the experimental rations. Several observations argue
against this hypothesis, however.

Comparison of actual DMI with predicted DMI from the
1988 NRC reveals that for stated amounts of milk and body
weight, actual DMI was at or above predicted levels in
spite of the fact that almost one third of the animals were
primiparous cows who are known to have lower DMI per 100 Kg
of body weight than older cows (DePeters et al, 1986).

Also the fact that each first lactation cow fed ration
I suffered from laminitis is of great concern. Founder is
considered to have its origin in ruminal lactic acidosis
(Manson and Leaver, 1988), which is perceived to be
prevented by high fiber diets.

Lastly, when using the regression analysis as a tool

to explain variation in DMI on this data set, no fiber

117

fraction was correlated with DMI with an R2 as high as .05
if milk production, parity and body weight were included in
the model. Analysis of the cubic regression for ingested
hemicellulose (i.e., the difference between ingested NDP
and ingested ADP) revealed no differences in any of the
slope parameters including the intercept among the
experimental rations.

Ration NDP has failed to regulate feed intake of early
lactation cows in a number of experiments (Broderick, 1985:
DePeters et al., 1986: Sutton et al, 1988).

There are three possible explanations for the results
obtained regarding the effects of fiber on intake found in
this study: (1) ADP and NDP are so highly correlated on
normal mixed forage:concentrate diets that even with
grasses included, any differences between the effects of
NDP and ADP on DMI are obscured: (2) the diets were high
in NDF and the spread in NDP or ADP content among diets was
not great enough to produce a detectable difference: (3) in
early lactation the physiological and/or hormonal set point
of the cow controls intake to a much larger degree than
does fiber level.

A comparison of the feed intake between thin and fat
dry cows (thin > fat, P<.05), indicates that feed intake
was different based on energy demand. Pat cows were
heavier and were gaining more weight (P<.05) and therefore

had higher energy requirements. As proposed by Conrad

118
(1966) for animals at or near maintenance, DMI is regulated
by the animal's need to extract total calories from the
diet.

After parturition, it appears that the cows ate dry
matter to the capacity of their digestive systems. It is
possible that the trend for ration 3 to be consumed at
lower levels may be more influenced by the difference
between both the extent and rate of digestion between the
forage and grain portion of the diets (Mertens, 1977) than
by differences in NDP or ADP levels in the diet.

It also appears clear that body condition has a
minimal effect on DMI or milk production during early
lactation. These results were also unexpected, although in
several studies, body condition has had no effect on DMI or
milk production (Boisclair et al, 1986: Kunz et al, 1985).
Comparison of these results with those of previous studies
(Garnsworthy and Topps, 1987: Treacher et al, 1986; Seymour
and Polan, 1986:) must be made with some caution. The cows
in this study were not as widely divergent in body
condition (thin - 2.26, fat a 3.24) as those in most other
studies. Also, the design of their experiments required
making cows intentionally thin or fat in the last trimester
of lactation and during the dry period, thereby overriding
the animal's metabolic set point (Kennedy, 1966) for the
maintenance of body reserves. This may have predisposed
those cows whose natural body condition is thin to ingest

less dry matter after calving in order to reach their set

119

point of body fat (Baile and Della Ferra, 1974), or they
may have deposited excessive amounts of fat in the liver
with resulting decreases in dry matter intake (Morrow,
1976: Reid and Roberts, 1983).

There is some evidence, given the basic experimental
design differences, that the results may not be as
different as at first supposed. The regression plots of
fat cows fed the highest fiber diet did trend toward having
lower NDP intakes (Figure 17), i.e., these cows had a
significant ration by body condition interaction. From
similar plots of body weight for fat cows fed the low fiber
ration, it can be seen that this group gained substantial
weight (Figure 5). These results are the same as obtained
by Topps and Garnsworthy (1986). The cows in the present
study peaked in both milk production and dry matter intake
before those in most other studies and overall produced
more milk and consumed more dry matter during that time.
The work of Nocek et al (1986) is perhaps most closely
related to this study. The results these workers obtained
were similar to those of the present study.

Changes in milk production, DMI, body weight, body
condition and blood metabolites due to advancing lactation
are well documented in other literature, and therefore will
not be dealt with other than to say that those changes
observed in the present study are similar to those

previously reported.

120

The last stated objective of this study also was
unfulfilled. Although significant effects on blood
metabolites were observed due to ration and body condition,
none of these was significantly correlated with either DMI
or milk production so as to be a useful tool in predicting
dry matter intake or milk production (Appendix Tables 29
and 30). This finding is supported by other researchers
(Thye et al, 1970: Ducker et al, 1985). Also, even those
variables with sufficient correlation to warrant inspection
added no significant amount of accuracy to the DMI
regression model. Nevertheless, some of the aspects of
this blood profile work are useful in explaining some of
the results of this study.

Ruminants are considered insulin insensitive (Brockman
and Laarveld, 1985). Insulin has been shown to be
responsible for general protein accretion (Horn et a1,
1986) and lipolysis regulation (Bergman, 1968). Study of
the present insulin data may help provide some insight into
the role of insulin in the high-producing dairy cow.

First lactation cows had higher levels of plasma
insulin and glucose, but lower levels of plasma NEPA than
did older cows (Table 10). This further reinforces that
there are large differences in the physiology of milking
heifers, even though their milk production is markedly less
than that of mature cows. The ratio of glucose:insulin or
glucose:ketone levels were not different between first

lactation and mature cows, however. Fat dry cows also had

121

higher levels of plasma insulin than thinner cows (mean =
.269 vs .345 ng/ml). There was no significant difference
between pre- and post parturient cows (P>.10). This is in
contrast to other data ( Ronge et al, 1988). An.
explanation for this result is difficult although the high
amount of grain fed to the cows after calving in the
present study may have resulted in a basal insulin
concentration (Bergman et al, 1970). Also, the lack of a
sufficient number of samples taken more than one week
before calving may have biased the data. Blood insulin
levels are known to decline one week preparturition (Rouge,
et al.).

Pat dry cows were in a period of substantial weight
and body condition gain compared to the thin dry cows
(P<.05). Higher plasma insulin levels may be interpreted
as the controlling mechanism for decreased
lipolysis/increased lipogenesis as has been shown in other
species (De Jonge, 1985). Since there is no demand for
insulin by the pregnant uterus of cattle (Brockman, 1985),
it may be assumed that the effects of insulin must be
exerted in muscle and adipose tissue.

Observations on the blood metabolites of primiparous
cows also support a role for insulin as a regulator of
lipolysis. If the postulation of tissue insensitivity is
accepted, then the higher insulin levels found in

primiparous cows can be interpreted as an attempt to reduce

122
the high plasma glucose concentration. This is difficult

to visualize, however, because with this scenario, fatty
acid levels would have to be the same for both first and
multilactational cows: the insensitivity to insulin should
be general for adipose tissue. NEFA levels were.
significantly lower for the primiparous cows (P<.05).
Therefore, lipolysis must have been inhibited to some
extent, strongly suggesting that adipose tissue in milking
cows is not insensitive to insulin. The plasma glucose
concentration and higher insulin concentration indicate an
increased supply of glucose from some source. There was no
difference in the ratio of glucose:insulin, which is
another indication that the tissues of the primiparous cows
were not more insulin insensitive than tissues of the older
cows. Therefore, the metabolism of younger cows must be in
some respect different from older animals. This difference
did not seem to be diet induced, but rather was reflective
of the status of the animal. It can easily be postulated
that this difference may well be due to the fact that the
primiparous cows were still growing and required both more
insulin and more glucose for tissue synthesis. However,
because no idea of production and clearance times for
glucose, NEPA or insulin are available from this study, a
full explanation must await results from other
investigators.

Blood ketone data is of similar interest. Cows fed

ration 3 had significantly higher levels of BHBA (P<.05)

123

than did those fed ration 1. Although blood glucose was
not different between these treatments, it was numerically
higher for cows fed ration 1 than ration 3 (.364 vs .386
mM). Because of this, there was a significant difference
in the ratio of glucose:BHBA in plasma (ration 1 > ration
3, P<.01). This is in agreement with the data of Gerloff
et al (1986) who showed an inverse relationship between
blood glucose and BHBA levels for cows with some degree of
hepatic lipidosis. Early lactation cows are thought to
undergo some degree of fat infiltration in the liver in
early lactation (Morrow, 1981; Watson and Williams, 1988)
with resultant increases in ketogenesis. Somewhat
surprisingly, there were no differences in the plasma
levels of NEPA between these rations (P>.10).

This difference in the glucose:BHBA ratio between
diets 1 and 3 indicates that a shift in either production
or clearance of BHBA must have occurred for the cows fed
these rations. Concurrently, one could postulate a
difference in the metabolic fate of NEPA. A hint as to what
this mechanism might be is provided by comparison of the
fat and thin cows. Cows that were fat had lower ratios of
BHBA:ACAC (P<.05). It should be recalled that fat cows
lost more body condition and therefore should have had
higher rates of ketogenesis. This result would indicate an
increased clearance of BHBA from the blood for extra

hepatic use or a reduction of fatty acid metabolism.

124

Heifer blocks also had higher (P<.01) glucose:BHBA
ratios. In this instance the level of BHBA was not
different between cows and heifers although the level
fatty acids was lower for the first lactation cows. The
rise in ratio was entirely due to glucose levels. Still it
is important that BHBA levels were the same even though
NEFA levels were lower. This may point to the fact that
ketones are far more important as metabolic fuels in the
ruminant than was previously thought. These findings
demonstrate the need for further research into how the
animal regulates the production and utilization of energy
producing substrate under different dietary regimes.

CONCLUSIONS

Several observations made in this study are at
variance with those of other workers. These have been
discussed where pertinent. It will be incumbent upon
future studies to justify these variances with the facts.

It is important to recognize that in the present study
both dietary ADP levels and body conditions were within a
narrow range. Fiber levels varied over time and
significantly among blocks. Although NDF levels in the
rations were high, daily NDF consumption as a percent of
body weight was also high (approximately 1.3%).

From this study within the conditions cited above as
well as those imposed by early lactation and relatively

high milk production, the following conclusions can be

made:

1.

125

Ration fiber levels had no statistically

significant effect on dry matter intake.

Body condition had no measurable effect on intake.
After peak milk production, body condition had a
significant and positive effect on milk fat test.

Cows in higher body condition lost more body

condition than cows with lower body scores.

No blood metabolite measured explained a
significant portion of the variation in dry-matter
intake.

Pat dry cows had higher blood insulin values than
thin dry cows. Primiparous post parturition cows
had higher blood insulin values with higher glucose

levels and lower NEPA levels than multiparous cows.

Pat post partum cows had lower ratios of BHBA:ACAC
than thin cows. Higher levels of BHBA were

associated with lower levels of plasma glucose.

Net energy balance was not different among
treatment groups. Neither diet nor body condition
changed the amount or duration of negative energy

balance.

APPENDIX TABLES

3126

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154

Appendix Table 29. Pearson correlation coefficients for selected
variables with dry matter intake.

 

Variable R2

Milk production .62 .0001
Body weight .48 .0001
Change in body weight -.12 .0444
Body condition score -.08 .1993
Change in body condition score -.02 .7409
4% FCM production .54 .0001
4% FCM/100 kg body weight .46 .0001
Milk fat 4 .03 .5917
Mik protein % -.02 .0001
Blood BHBA concentration -.23 .0001
Blood ACAC concentration 4.14_ .0155
Ketone ratio -.09 .1154
Plasma glucose .04 .4590
Plasma insulin -.01 .8543
Plasma NEFA -.34 .0001
Plasma triacylglycerol .04 .5345
Plasma creatinine -.03 .6399
Ration NDF content -.09 .1180
Ration ADP content -.15 .0100
Ration lignin content -.21 .0005
Energy balance .53 .0001

155

Appendix Table 30. Pearson correlation coefficients for selected
variables with milk production.

 

Variable R2 P

Dry matter intake .62 .0001
Body weight .62 .0001
Change in body weight .33 .0001
Body condition score -.11 .0693
Change in body condition score .10 .1043
4% FCM production .89 .0001
4% FCM/100 kg body weight .84 .0001
Milk fat % .09 .1212
Mik protein % -.29 .0001
Blood BHBA concentration -.12 .0432
Blood ACAC concentration .01 .9900
Ketone ratio .02 .6936
Plasma glucose -.14 .0181
Plasma insulin -.13 - .0352
Plasma NEFA -.06 .3127
Plasma triacylglycerol -.03 .6548
Plasma creatinine -.03 .6231
Ration NDF content .01 .9594
Ration ADP content -.14 .0188
Ration lignin content -.25 .0001

Energy balance -.21 .0005

LIST OF REFERENCES

156

Allen, M.S. and D.R. Mertens. 1988a. Evaluating
constraints on fiber digestion by rumen microbes. J.
Nutr. 118:261-270.

Allen, M.S. and D.R. Mertens. 1988b. Effect of diet fiber
level and forage source on intake and milk production
of Holstein cows in early or late lactation. ADSA
Annual Meeting Abstracts. (Abst. 171).

Allison, C.D. 1985. Factors affecting forage intake by
range ruminants: a review. J. of Range Mangmt. 38:4.

Anil, M.H. and J.M. Forbes. 1980. Feeding in sheep during
intraportal infusion of short-chain fatty acids and
the effect of liver denervation. J. Physiol. 298:407.

Armentano, L.E., S.C. Patore and P.C. Hoffman. 1988.
Particle size reduction of alfalfa did not alter
nutritional quality of high forage diets for dairy
cattle. J. Dairy Sci. 71:409.

Association of Official Analytical Chemists. 1975.
Official methods of Analysis. 12th ed. Assoc. Offic.
Anal. Chem. Washington D.C. ‘

Baile, C.A. 1975. Control of feed intake in ruminants. in
Digestion and Metabolism in the Ruminant p. 332. ed by
I.W. McDonald and A.C.I. Warner. University of New
England. Armidale, NSW.

Baile, C.A. and J.M. Forbes. 1974. Control of feed intake
and regulation of energy balance in ruminants.
Physiol. Rev. 54:160.

Baile, C.A. and M.A. Della-Fera. 1975. Nature of hunger
and sateity control system in ruminants. J. Dairy Sci.
64:1140.

Baird, G.D. 1982. Primary ketosis in the high-producing
dairy cow: clinical and subclinical disorders,
treatment, prevention and outlook. J. Dairy Sci. 65:1.

Baldwin, R.L., N.E. Forsberg and C.Y. Hu. 1985. Potential
for altering energy partition in the lactating cow.
J. Dairy Sci. 68:3394.

157

Barnes, R.J., R.S. Comline and A. Dobson. 1986. The
control of splanchnic blood flow, in Control of
Digestion and Metabolism in Ruminants p.41. ed by L.P.
Milligan, W.L. Grovum and A. Dobson. Proceedings of
Sixth Internaltion Symposium on Ruminant Physisology.
Prentice Hall. Englewood Cliffs, NJ.

Bauman, D.E. and W.B. Currie. 1980. Partitioning of
nutrients during pregnancy and lactation: a review of
mechanisms involving homeostasis and homeorhesis. J.
Dairy Sci. 63:1514.

Baumgardt, B.R. 1970. Control of feed intake and regulation
of energy balance, in Physiology of Digestion and
Metabolism in the Ruminant. p 235. ed by A.T.
Phillipson. Proceedings of Third International
Symposium. Oriel Press, Cambridge, UK.

Belyea, R.L., C.L. Babbitt, H.T. Sudwick and G.M. Zinn.
1986. Body protein losses estimated by nitrogen
balance and potassium-40 counting. J. Dairy Sci.
69:1817.

Bergman, E.N. 1968. Glycerol turnover in the non pregnant
and ketotic pregnant sheep. Am. J. Physiol. 215:865.

Bergman, E.N. 1973. Glucose metabolism in ruminants as
related to hypoglycemia and ketosis. Cornell Vet
63:341.

Bines, J.A. and S.V. Morant. 1983. .The effect of body
condition on metabolic change associated with intake
of food in the cow. Br. J. Nutr. 50:

Blum, J.W., '1‘. Reding, F. Jans, M. Wanner, M. Zemp and K.
Bachman. 1985. Variation of 3-methyl histidine in
blood of dairy cows. J. Dairy Sci. 68:2580.

Boisclair, Y., D.G. Grieve, J.B. Stone, O.B. Allen and G.K.
MacCleod. 1985. Effect of prepartum energy, body
condition and sodium bicarbonate on production of cows
in early lactation. J. Dairy Sci. 69:2636.

Briceno, J.V., H.H. Van Horn, B. Harris Jr. and C.J.
Wilcox. 1987. Effects of neutral detergent fiber and
roughage source on dry matter intake and milk yield
and composition of dairy cows. J. Dairy Sci. 70:298.

Brockman, R.P. and B. Laarveld. 1986. Hormonal regulation
of metabolism in ruminants: a review. Livest. Prod.
Sci. 14:313.

158

Broderick, G.A. 1985. Alfalfa silage or hay versus corn
silage as the sole forage for lactating cows. J. Dairy
Sci. 68:3262.

Butler, W.R., R.W. Everett and C.E. Coppock. 1981. The
relationship between energy balance, milk production
and ovulation in postpartum Holstein cows. J. Anim.
Sci. 53:742.

Cardoza, R.S. and D.R. Mertens. 1969. Effect of fiber
source and content on threshold size for passage and
fecal particle distribution. J. Diary Sci. 69 (Suppl.
1):134.

Chase, L.E., P.J. Wangsness, J.F. Kavanaugh, L.C. Griel,
Jr. and J.H. Gahagan. 1977. Changes in portal blood
metabolites and insulin with feeding steers twice
daily. J. Dairy Sci. 60: 403.

Chase, L.E., P.J. Wangsness and R.S. Martin. 1977. Portal
blood insulin and metabolic changes with spontaneous
feeding in steers. J. Dairy Sci. 60:410.

Cherney, J.H., D.J.R. Cherney and D.R. Mertens. 1988.
Fiber composition and digestion kinetics in grass stem
internodes as influenced by particle size. J. Dairy
Sci. 71. 2112.

Coggins, C.R.E., and Field, A.C. 1976. Diurnal variation in
the chemical composition of plasma from lactating
beef cows on three dietary enery.intakes. J} Agric.
$01., Camb. 86:595.

Cohn, C. and D. Joseph. 1962. Influence of body weight and
body fat on appetite of "normal" lean and obese rats.
Yale. J. Biol. Med. 34:598.

Conrad, H.R. 1966. Symposium on factors influencing the
voluntary intake of herbage by ruminants:
physiological and physical factors limiting feed
intake. J. Anim. Sci. 25:227.

Conrad, H.R., A.D. Pratt and J.W. Hibbs. 1964. Regulation
of feed intake in dairy cattle. 1. Change in
importance of physical and physiological factors with
increasing digestibility. J. Dairy Sci. 47:54.

Conrad, H.R., W.P. Weiss, W.O. Odwongo and W.L. Shockey.
1984. Estimating net energy lactation from components
of cell soluables and cell walls. J. Dairy Sci.
67:427.

159

Coppock, C.E. 1985. Energy nutrition and metabolism of the
lactating dairy cow. J. Dairy Sci. 68:3404.

Deetz, L.E. and. P.J. ‘Wangsness. 1981. Influence of
intrajugular administration of insulin, glucagon and
propionate on voluntary feed intake of sheep. J.
Anim. Sci. 53:427. _

Dehority, B.A. and R.R. Johnson. 1961. Effect of particle
size on the invitro cellulose digestion of forages by
rumen bacteria. J. Dairy Sci. 44:2242.

De Jong, A. 1986. The role of metabolites and hormones as
feedbacks in the control of food intake in ruminants,
in Control of Digestion and Metabolism in Ruminants, p
459. ed by L.P. Milligan, W.L. Grovum and A. Dobson.
Proceedings of Sixth International Symposium on
Ruminant Physiology. Prentice Hall, Englewood Cliffs,
NJ.

De Jong, A., A.B. Steffens, A.B. and L. DeRuiter. 1981.
Effects of portal volatile fatty acid infusions on
meal patterns and blood composition in goats.
Physiology and Behavior 27:683-689.

De Peters, E.J. and N.E. Smith. 1986. Forage quality and
concentrate for cows in early lactation. J. Dairy Sci.
69:135.

De Peters, E.J., N.E. Smith and J. Acedo-Rico. 1985. Three
or two times daily milking of older cows and first
lactation cows for entire lactations. J. Dairy Sci.
68:123-132.

Deswysen, A.G. and E.C. Ellis, 1988. Site and extent of
neutral detergent fiber digestion, efficiency of
ruminal digesta flux and fecal output as related to
variation in voluntary intake and chewing behavior in
heifers. J. Anim. Sci. 66:2678.

Dinius, D.A. and B.R. Baumgardt. 1970. Regulation of food
intake in ruminants. 6. Influence of caloric density
of pelleted rations. J. Dairy Sci. 53:311.

Donker, J.D., G.D. Marx and C.W. Young. 1983. Feed intake
and milk production from three rates of concentrate
for cows bred to differ in size. J. Dairy Sci.
66:1337.

Ducker, M.J., R.A. Haggett, W.J. Fisher and S.V. Morant.
1985. Prediction of energy status in first lactation
dairy heifers. Anim. Prod. 41:167.

160

Ehle, F.R. 1984. Influence of particle size on
determination of fibrous feed components. J. Dairy
Sci. 67:1482-1488.

Ehle, F.R., M.R. Murphy and J.H. Clark. 1982. In situ
particle size reduction and the effect of particle
size on degradation of crude protein and dry matter in
the rumen of dairy steers. J. Dairy Sci. 65:963.

Ellis, W.C., J.H. Matis, C. Lascano, M. Mahloogi and K.
Pond. 1987. Size reduction, fermentation and passage
of forage particles and forage intake by cattle, in

Feed Intake by Beef Cattle, p. 81, Oklahoma Agr. Exp.
Sta. -

Emanuele, S.M. and C.R. Staples. 1988. Effect of forage

particle size on in situ digestion kinetics. J. Dairy
Sci. 71: 1947 .

Emery, R.S., 1988. Feed intake and change in boyd
composition of lactating mammals. ISI Atlas of Sci.
Animal and Plant Sci. 1:51.

Emery, R.S., H.D. Hafs, D. Armstrong and W.W. Snyder. 1969.
Prepartum grain feeding effects milk production,

mammary edema and incidence of diseases. J. Dairy Sci.
52:345. '

Erdman, R.A. 1988. Dietary buffering requirements for the
lactating cow: a review. J. Dairy Sci. 71:3246.

Faix, S., L. Leng, M. Szanyiona and K. Boda. 1988.
Creatinine and insulin clearance at the different

nitrogen and energy intake in sheep. Comp. 'Biochem
Physiol. 91:689.

Fisher, D.S., J.C. Burns and K.R. Pond. 1987. Modeling ad
libitum dry matter intake by ruminants as regulated by

distension and chemostatic feedbacks. J. Theor. Biol.
126:407.

Forbes, J. M. 1986. The Voluntary Food Intake of Farm
Animals. Butterworths and Co. London. UK.

Foster, L.A. 1988. Clinical ketosis, in Veterinary Clinics
of North America vol 4, p253. ed by T.H. Herdt.

Galyean, M.L. and F.N. Owens. 1988. Fermentation,
digestion and passage in ruminants fed roughage and
concentrate diets. Southwest Nutrition and Management

Conference Proceedings, Tempe, Arizona. Feb. 4-5,
1988: 79-90.

161

Garnsworthy, P.C. and N.E.G. Gardner. 1987. Effect of
condition score at calving on milk yield, milk quality
and dry matter intake in lactating cows. Livest. Prod.
Sci. 17:Abst.4.

Garnsworthy, P.C. and G. P. Jones. 1987. The influence of
body condition at calving and dietary protein supply
on. voluntary food, intake and. performance in dairy
cows. Anim. Prod. 44:347.

Garnsworthy, P.C. and J.H. Topps. 1982. The effect of body
condition of dairy cows at calving on their food
intake and performance when given complete diets.
Anim. Prod. 35:113-119.

Gerloff, B.J., T.H. Herdt and R.S. Emery. 1986.
Relationship of hepatic lipidosis to health and
performance in dairy cattle. J. Am. vet. Med. Assoc.
188:845.

Gibson, J. P., A.C. Field and G. Wiener; 1987.
Concentration of blood constituents in genetically
high and low milk producing lines of British Fiesan
and. Jersey' cattle around calving and in early
lactation. Anim. Prod. 44:183.

Gill, J. L. 1978. Design and Analysis of Experiments in
the Animal and Medical Sciences. Iowa State
University Press. Ames, IA.

Goering, H.K. and P.J. Van Soest. 1970. Forage fiber
analysis (apparatus, reagents, procedures and some
applications). Agriculture Handbook no. 379. United
States Department of Agriculture-Agriculture Research
Service. Washington, D.C.

Grovum, W.L. 1986. 'The control of motility of the rumino-
reticulum, in Control of Digestion and Metabolism in
Ruminants, p. 18. ed by L.P. Milligan, W.L. Grovum and
A. Dobson. Proceedings of Sixth International
Symposium on Ruminant Physiology. Prentice Hall,
Englewood Cliffs, NJ.

Heitmanq R.N., S.C. Sensenig, C.K. Reynolds, J. M.
Fernandez and DJ. Dawes. 1986. Changes in energy
metabolite and regulatory hormone concentration and
net fluxes across splanchnic and peripheral tissues in
fed and progressively fasted ewes. J. Nutr. 116:2516.

162

Herdt, T.H., S.B. Stevens, J. Linn and V. Larson. 1981.
Influence of ration compositon and energy balance on
blood B-hydroxybutyrate (ketone) and plasma glucose
concentrations of dairy cows in early lactation. Am.
J. Vet. Res. 42:1177.

Hogue, D.E. 1987. Estimated indigestible neutral detergent
fiber as an indicator of voluntary feed intake by
lambs. Proceedings of 1987 Cornell Nutrition
Conference for Feed Manufacturers, p.61.

Horn, J., M.D.R. Stern, M. Young and D.E. Nouches. 1983.
Influence of insulin and substrate concentration on

protein synthetic rate in fetal tissues. Res. Vet.
Sci. 35:35.

Istassee, I., F.D.DeB. Howell, N.A. MacLeod and B.R.
Orskov. 1987. The effects of continuous or
intermittent infusion of propionic acid on plasma
insulin and milk yield in dairy cows nourished by
intra gastric infusion of nutrients. Livest. Prod.
Sci. 16:201.

Jaquette, R.D., A.H. Rakes and W.J. Croom, Jr. 1988.
Effects of body condition and protein on milk fat

depression in early lactation dairy cows. J. Dairy
Sci. 71: 2123.

Jarrige, R., C. Demarquilly, J.P. Dulphy, A. Hoden, J.
Robelin, C. Beranger, Y. Geay, M. Journet, C.
Malterre, D. Mical and M. Petit. 1986. The INRA "fill
unit" system for predicting the voluntary intake of
forage based diets in ruminants: a review. J. Anim.
Sci. 63:1737.

Jones, A.L., A.L. Goetsch, S.R. Stokes and M. Colberg.
1988. Intake and digestion in cattle fed warm or cool

season grass hay with or without supplemental grain.
J. Anim. Sci. 66:194.

Korver, A. 1984. Feed intake and production in dairy breeds
dependent on the ration. Neth. J. Agric. Sci. 32:59.

Korver, A. 1988. Genetic aspects of Feed intake and

efficiency in dairy cattle: a review. Livest. Prod.
Sci. 20:1.

Kunz, P.L., J.W. Blum, I.C. Hart, H. Bickel and J. Landis.
1985. Effects of different energy intake before and
after calving on food intake, performance and blood
hormones and metabolites in dairy cows. Anim. Prod.
40:219.

163

Kwakkel, R.P. J. van Bruchem, G. Hof and H. Boer. 1986.
The in sacco degradation of crude protein and cell
wall constituents in grass, alfalfa and maize silages.
Netherland J. Agric. Sci. 34:116.

Latham, M.J., B.E. Brooker, G.L. Pettiphor and P.J. Harris.
1978. Adhesion of Bacteriodes succinogenes in pure
culture and in the presence of Ruminococcus
flavefaciencs to cell walls in leaves of perennial rye
grass (Lolium perenne) . Appl. Environ. Microbiol.
35:116.

MacGregor, C.A.,F.G. Owens and L.D. McGill. 1976. Effect
of increasing ration fiber with soybean mill run on
digestibility and lactation performance. J. Dairy
Sci. 59:682.

McCutcheon, S.M. and D.R. Bauman. 1986. Effect of chronic
growth hormone treatment on responses to epinephrine
and thyrotropin releasing hormone in cows. J. Dairy
SCi. 69:44. '

Manson, E.J. and J.D. leaver. 1988. The influence of
concentrate amount on locomotion and clinical lameness
in dairy cattle. Anim. Prod. 47:185.

Martz, F.A. and R.L. Belyea. 1986. Role of particle size
and forage quality in digestion and passage by cattle
and sheep. J. Dairy Sci. 59:68.

Mertens, D.R. 1982. Using neutral detergent fiber to
formulate dairy rations . in Proceedings Georgia
Nutrition Conference. p. 116.

Mertens, D.R. 1983. Using neutral detergent fiber to
formulate dairy rations and estimate the net energy
content of forages. in Proceedings of Cornell
Nutrition Conference for Feed Manufacturers. p 60.

Mertens, D.R. 1987. Predicting intake and digestibility
using mathematical models of ruminal function. J.
Anim. Sci. 64:1548.

Mertens, D.R. and L.O. Ely. 1979. A dynamic model of fiber
digestion and passage in the.ruminant for evaluating
forage quality. J. Anim. Sci. 49:1085.

Mertens, D.R. and L.O. Ely. 1982. Relationship of rate and
extent of digestion to forage utilization: a dynamic
model evaluation. J. Anim. Sci. 54:895.

164

Montgomery, M.J. and B.R. Baumgardt. 1965. Regulation of
food intake in ruminants I. Pelleted ration varying in
energy concentration. J. Dairy Sci. 48:1053.

Mulvany, P. 1977. Dairy cow condition scoring. National
Institute for Research in Dairying, Report no. 4468.

National Research Council. 1978. Nutrient Requirements of
Dairy Cattle, Fifth edition. National Academy Press,
Washington, D.C.

National Research Council. 1988. Nutrient Requirements of
Dairy Cattle, Sixth edition. National Academy Press,
Washington, D.C.

National Research Council. 1987. Feed Intake of Food
Producing Animals. ed by D.G. Fox. National Academy
Press, Washington D.C.

Nocek, J.E., R.L. Steele and D.G. Braund. 1985. Prepartum
grain feeding and subsequent lactation forage program
effects on performance of dairy cows in early
lactation. J. Dairy Sci. 69:734.

Orskov, E.R., G.W. Reid and M. Kay. 1988. Prediction of
intake by cattle from degradation characteristics of
roughage. Anim. Prod. 46:29.

Owens, F.N. and A.L. Goetsch. 1986. Digesta passage and
microbial protein, in Control. of Digestion and
Metabolism in Ruminants, p. 196. ed by L.P. Milligan,
W.L. Grovum and A. Dobson. Proceedings of Sixth
International Symposium. on Ruminant Physiology.
Prentice Hall, Englewood Cliffs, NJ.

Paquay, R., F. Doize and J. Cl. Bouchant. 1979. Long term
control of voluntary food intake in sheep. Ann. Rech.
Vet. 10:223.

Patton, R.A., H.F. Bucholtz and M.S. Allen. 1988. Practical
implications of dry matter intake. Mimeograph. Dept.
of Anim. Sci., Michigan State University. East
Lansing, MI.

Radloff, H.D., L.H. Schultz and W.G. Hackstra. 1966.
Relationship of plasma free fatty acids to other blood
components in ruminants under various physiological
conditions. J. Dairy Sci. 49:179.

Reid, I.M. and C.J. Roberts. 1983. Subclinical fatty liver
in dairy cows-current research and future prospects.
Irish Vet. J. 37:104.

165

Reid, I.M., C.J. Roberts, R.J. Treacher and L.A. Williams.
1986. Effect of body condition at calving on tissue
mobilization, development of fatty liver and blood
chemistry of dairy cows. Anim. Prod. 43:7.

Robinson, P.H., S.Tamminga. and..A.M. 'Van ‘Vuuren. 1987a.
Influence of declining level of feed intake and
varying the proportion of starch in the concentrate on
milk production and whole tract digestibility in dairy
cows. Livest. Prod. Sci. 17:19.

Robinson, P.H., S. Tamminga and A.M. Van Vuuren. 1987b.
Influence of declining level of feed intake and
varying the proportion of starch in the concentrate on
rumen ingesta quantity, composition and kinetics of

ingesta turnover in dairy cows. Livest. Prod. Sci.
17:37.

Robles, A.Y., R.L. Belyea, F.A. Martz and M.F. Weiss. 1980.
Effect of particle size upon digestible cell wall and
rate of in vitro digestion of alfalfa and orchard
grass forages. J. Anim. Sci. 51:783.

Rodrigue, C.B. and N.N. Allen. 1960. The effect of fine
grinding of hay on ration digestibility, rate of

passage, and fat content of milk. Can. J. Anim. Sci.
40:23.

Ronge, H., J. Blum, C. Clement, F. Jans, H. Leuenberger and
H. Binder. 1988. Somatomedin C in dairy cows related

to energy and protein supply and to milk production.
Anim. Prod. Sci. 47:165.

Russel, A.J.F., and J.M. Doney. 1969. Observations on the
use of plasma free fatty acid concentrations in the
determination of maintenance requirements of sheep. J.
Agric. Sci. 72:59.

Seymour, W.M. and C.E. Polan. 1986. Dietary energy
regulation during gestation on subsequent lactational
response to soybean meal or dried brewers grains. J.
Dairy Sci 69:2837.

Sharma, B.K., R.A. Erdman and J.B. Reeves,III. 1988. Rate
and extent of in situ digestion of medium and high
quality alfalfa and orchardgrass neutral detergent
fiber as determined by extended periods of incubation
time. J. Dairy Sci. 71:3509.

Shaver, R.D., R.A. Erdman and J.H. vandersall. 1984.
Effects of silage pH on voluntary intake of corn
silage. J. Dairy Sci. 67:2045.

166

Smith, L.W., H.I<. Goering, D.R. Waldo and C.H. Gordon.
1971. In vitro digestion rate of forage cell wall
components. J. Dairy Sci. 54:71.

Smith, L.W., H.K. Goering and C.H. Gordon. 1972.
Relationships of forage compositions with rates of
cell wall digestion and indigestibility of cell walls.
J. Dairy Sci. 55:1140.

Staples, C.R., R.L. Fernando, G.C. Fahey, Jr., L.L. Berger
and E.H. Jaster. 1984. Effects of intake of a mixed
diet by dairy steers on digestion events. J. Dairy
Sci. 67:995.

St. C. Neal, H.D., C. Thomas and J.M. Cobby. 1984.
Comparison of equations for predicting voluntary
intake by dairy cows. J. Agric. Sci. Camb. 103:1

Sutton, J.D., J.A. Barnes, S.V. Morant and D.J. Nappier.
1987. A comparison of starchy and fibrous concentrates
for milk production, energy utilization and hay
intake by Friesian cows. J. Agric. Sci. Camb. 109:375.

Sutton, J.D., I.C. Hart, S.V. Morant, E. Schuller and A.D.
Simmons. 1988. Feeding frequency for lactating cows:
diurnal patterns of hormones and metabolites in
peripheral blood. in :relation. to milk fat
concentration. Brit. J. Nutr. 60:265.

Thomas, J.W., L.A. Moore, M. Okamoto and J.F. Sykes. 1961.
A study of factors affecting rate of intake of heifer
fed silage. J. Dairy Sci.

Thye, F.W., R.G. Warner and P.D. Miller. 1970.
Relationships of various blood metabolites to

‘voluntary feed. intake in lactating ewes. J. Nutr.
100:565.

Treacher, R.J., I.M. Reid and C.J. Roberts. 1986. Effect
of body condition at calving on the health and
performance of dairy cows. Animal Prod. Sci. 43:1.

Troelsen, J.E. and J.B. Campbell. 1968. Voluntary
consumption of forage by sheep and its relation to the
size and shape of particles in the digestive tract.
Anim. Prod. 10:289.

Van Soest, P.J. 1982. Nutritional Ecology of the Ruminant.
O. and B. Books, Corvallis. OR.

167

Van Soest, P.J. and D.R. Mertens. 1984. The use of NDF
versus ADF in balancing rations, in Proceeding of
Monsanto Technical Symposium. Nutr. Chem. Div. p. 75.

Varel, V.H., and H.G. Jung. 1986. Influence of forage
phenolics on ruminal fibrolytic bacteria and in vivo
fiber degradation. Appl. Environ. Microbiol. 52:275.

Verde, L.S. and A. Trenkle. 1987. Concentration of hormones
in plasma from cattle with different growth potential.
J. Anim. Sci. 64:426.

Villa-Godoy, A. 1987. Ph.D. Thesis. Influence of negative
energy balance and body condition on luteal function
and estrous behavior in dairy cattle. Michigan State
University, East Lansing. '

Waldo, D.R. 1984. Effect of forage quality on intake and
forage-concentrate interactions. J. Dairy Sci. 69:617.

Waldo, D.R., L.W. Smith and E.L. Cox. 1972. Model of
cellulose disappearance from the rumen. J. Dairy Sci.
55:125.

Wangsness, P.J. and L.D. Muller. 1981. Maximum forage for
dairy cows: a review. J. Dairy Sci. 64:1.

Welch, J.G. 1982. Rumination, particle size and passage
from the rumen. J. Anim. Sci. 54:885.

Welch, J.G. and A.M. Smith. 1970. Forage quality and
rumination time in cattle. J. Dairy Sci. 58:797.

Wilkinson, J.M., J.T. Huber and H.E. Henderson. 1976.
Acidity and proteolysis as factors affecting the
nutritive value of corn silage. J. Anim. Sci. 42:208.

Williams, D.H., J. Mellanby and H.A. Krebs. 1962. Enzymatic
determination of D(-)-B-hydroxybutyric acid and
acetoacetic acid in blood. Biochem. J. 82:90.

Woodford, J.A., N.A. Jorgensen and G.P. Barrington. 1986.
Impact of dietary fiber and physical form on
performance of lactating cows. J. Dairy Sci. 69:1035.

Woodford, S.T. and M.R. Murphy. 1988a. Effect of forage
physical form on chewing activity, dry matter intake,
and rumen function of dairy cows in early lactation.
J. Dairy Sci. 71:674.

Woodford, S.T. and M.R. Murphy. 1988b. Dietary alternation
of particle breakdown and passage from the rumen in
lactating dairy cattle. J. Dairy Sci. 71:687.

   

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