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This is to certify that the

thesis entitled

PERIPARTUM RESPONSES OF LATE PREGNANT DAIRY COWS TO
VARYING DIETARY CORN GRAIN CONTENT OR LENGTH OF
FEEDING PERIOD PREPARTUM

presented by
Douglas G. Mashek

has been accepted towards fulfillment
of the requirements for

M. S . degree in AnimaL Science

l ‘ i W
[Mprofessor
Date gujgfi—é I 999

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1m www.mu

PERIPARTUM RESPONSES OF LATE PREGNANT DAIRY cows To
VARYING DIETARY CORN GRAIN CONTENT OR LENGTH OF FEEDING
PERIOD PREPARTUM
By

Douglas G. Mashek

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
Department of Animal Science

1 999

ABSTRACT
PERIPARTUM RESPONSES 0F LATE PREGNANT DAIRY COWS TO
VARYING DIETARY CORN GRAIN CONTENT OR LENGTH OF FEEDING
PERIOD PREPARTUM
By

Douglas G. Mashek

The objective of this research was to study nutritional management strategies
prepartum that may improve periparturient energy status, health, milk yield and
composition, and reproduction in dairy cows. In the first experiment, 189 cows were
assigned randomly to a late dry period diet with supplemental corn grain (SC) or without
supplemental corn grain (NC) during the last 17 d prepartum. Cows fed SC had lower
plasma B-hydroxybutyrate and tended to have increased insulin concentrations
prepartum. Treatment had no effect on milk yield or composition, health, or
reproduction, but several interactions involving parity showed that SC was more
beneficial to parity 3+ cows. In the second experiment, 189 cows in two farms were
assigned randomly to the late dry period for < 26 d (S), or 2 26 d (L). Cows in L gained
more body condition prepartum, tended to have lower plasma non-esterified fatty acid
and higher insulin concentrations postpartum, and lost less body condition during the first
3 wk postpartum. Cows in L had lower milk yields, increased incidences of metritis,
increased days open and somatic cell count in one farm, but not in the other. Correlation
analysis of dependent variables of the combined datasets grouped by parity showed that
relationships between blood variables were similar for parity 1 and 3+ cows, and

relationships involving BCS and BCS changes were similar for cows in parities 2 and 3+.

DEDICATION

To Mara, for making me the luckiest man alive.

iii

ACKNOWLEDGEMENTS

I would like to thank Dr. Beede for his guidance, advice, and friendship throughout
Master’s program. I thank Dr. Allen, Dr. Bucholtz, and Dr. Herdt for serving on my
graduate committee. I also appreciated the use of Dr. Tucker’s and Dr. Orth’s
laboratories for analysis of blood samples. I appreciated the help from Larry Chapin and
Dr. Chris McMahon while working in Dr. Tucker’s laboratory.

I would like to thank Jim Leisman ‘for his help with the blood assays and answering
numerous SAS questions, and Dr. Rob Templeman for enduring hours of endless
statistical questions.

I extend my thanks to Laura Bolinger for her help with data collection, and Katie Gould
and Irene Choi for their help in the laboratory. I thank Tom Pilbeam for his help with
sample collection, and his friendship and advice. I would like to thank Jill Davidson,
Sara Scheurer and Luis Rodriquez for their friendships and support.

I would like to thank the Michigan Corn Growers Association and Mr. Keith Muxlow for
partially financing these studies.

Thanks to Webster Ridge and Nobis Dairy Farms for participating in this research.

Finally, thanks to Mara for her help with every aspect of my research and for her love and

support.

iv

TABLE OF CONTENTS

LIST OF TABLES .............................................................................. vii

LIST OF FIGURES .............................................................................. x

LIST OF ABBREVIATIONS ................................................................. xii

CHAPTER 1

INTRODUCTION

CHAPTER 2

REVIEW OF LITERATURE .................................................................. 3
Aspects of Feeding High Concentrations of Grain Prepartum ...................... 3
Effects of Grain Supplementation Prepartum on Milk Production ................. 4
Effects of Grain Supplementation Prepartum on Indicators of Energy Status. . . .7
Effects of Grain Supplementation Prepartum on Health Disorders ................ 9
Effects of Grain Supplementation Prepartum on Reproduction ................... 10
Altering Length of the Late Dry Period ............................................... 11
Relationships Between Body Condition Score and Milk Production ............. 12
Relationships Between Body Condition Score and Dry Matter Intake ........... 13
Relationships Between Body Condition Score and Health Disorders ............ 14
Relationships Between Body Condition Score and Reproduction. . . . . . . . . . 16

CHAPTER 3

Peripartum responses of dairy cows to partial substitution of corn silage with corn
grain in diets fed during the late dry period
ABSTRACT .............................................................................. 17
INTRODUCTION ....................................................................... 18
MATERIALS AND METHODS ...................................................... 19
Cows and Treatments
Sample Collection and Analysis
Statistical Analysis
RESULTS AND DISCUSSION ....................................................... 23
Diet Composition
Body Condition and Udder Edema
Metabolic Variables
Health Disorders
Milk Yield, Composition, and Somatic Cell Count
Reproductive Measurements

CONCLUSIONS ......................................................................... 28

TABLES AND FIGURES ............................................................... 30
CHAPTER 4
Peripartum responses of dairy cows to altering length of the late dry period
ABSTRACT .............................................................................. 48
INTRODUCTION ........................................................................ 49
MATERIALS AND METHODS ...................................................... 50

Cows and Treatments
Sample Collection and Analysis
Statistical Analysis

RESULTS AND DISCUSSION ........................................................ 55

Diet Composition

Body Condition and Udder Edema

Metabolic Variables

Health Disorders

Milk Yield, Composition, and Somatic Cell Count
Reproductive Measurements

CONCLUSIONS ......................................................................... 64
TABLES AND FIGURES ............................................................... 65
CHAPTER 5

Associations among body condition score, body condition score changes, blood
variables, and milk yield and composition in periparturient dairy cows

ABSTRACT .............................................................................. 92
INTRODUCTION ........................................................................ 93
MATERIALS AND METHODS ...................................................... 94
RESULTS AND DISCUSSION ....................................................... 97
All Parities
Differences Among Parities
CONCLUSIONS ........................................................................ 103
TABLES AND FIGURES ............................................................ 105
CHAPTER 6
Discussion and Implications .................................................................. 145
LITERATURE CITED ........................................................................ 152

vi

LIST OF TABLES

CHAPTER 3

Table l. Formulated ingredient and analyzed chemical composition, and
particle size distribution of experimental diets fed in the late dry period ................... 30

Table 2. Formulated ingredient and analyzed chemical composition, and
particle size distribution of experimental diets fed postpartum .............................. 31

Table 3. Formulate ingredient and chemical composition of diets fed in
the early dry period ................................................................................. 32

Table 4. Least squares means and statistical significance of body condition
scores (BCS) during the periparturient period .................................................. 33

Table 5. Least squares means and statistical significance of body condition
score changes during the periparturient period ................................................. 34

Table 6. Least squares means and statistical significance of plasma NEFA
concentrations dining prepartum, postpartum or periparturient periods .................... 35

Table 7. Least squares means and statistical significance of plasma BI-IBA
concentrations during prepartum, postpartum or periparturient periods .................... 36

Table 8. Least squares means and statistical significance of plasma insulin
concentrations during prepartum, postpartum or periparturient periods .................... 37

Table 9. Incidence rates and statistical significance of health disorders, and
‘ abnormal rectal temperatures ..................................................................... 38

Table 10. Least squares means and statistical significance of milk yield
and composition through 60 DIM .......................................... 39

Table 11. Least squares means and statistical significance of milk yield and
composition through 150 DIM ................................................................... 40

Table 12. Least squares means and significance of energy-corrected milk
(ECM) and SCC through 60 or 150 DIM ....................................................... 41

Table 13. Least squares means and statistical significance of reproductive
measurements ....................................................................................... 42

vii

CHAPTER 4

Table 1. Days spent in the late dry period and allocation of cows to treatments. . . . . . ...65
Table 2. F orrnulated ingredient and analyzed chemical composition, and

particle Size distribution of diets fed in the late dry period .................................. 66
Table 3. Formulated ingredient and analyzed chemical composition, and

particle size distribution of diets fed postpartum in Farm 1 ................................. 67
Table 4. Formulated ingredient and analyzed chemical composition, and

particle size of diets fed postpartum in Farm 2 ................................................ 68
Table 5. Formulath ingredient composition of diets fed in the early dry

period ............................................................................................... 69
Table 6. Least squares means and Statistical significance of body condition

scores during the periparturient period ......................................................... 70
Table 7. Least squares means and statistical significance of body condition

score changes during the periparturient period ............................................... 71
Table 8. Least squares means of plasma NEFA concentrations for prepartum,
postpartum, and periparturient periods ........................................................ 72
Table 9. Least squares means of plasma BHBA concentrations for prepartum,
postpartum, and periparturient periods ........................................................ 73
Table 10. Least squares means of plasma insulin concentrations for prepartum,
postpartum, and periparturient periods ........................................................ 74
Table 11. Incidence rates and statistical significance of health disorders and

abnormal rectal temperatures ................................................................... 75
Table 12. Least squares means and statistical significance of milk yield and
composition through 60 DIM .................................................................. 76
Table 13. Least squares means and statistical significance of milk yield and
composition through 150 DIM ................................................................. 77
Table 14. Least squares means and statistical significance of daily milk

yields in Farm 1 .................................................................................. 78

viii

Table 15. Least squares means and statistical significance of energy-corrected

milk (ECM) yield and SCC through 60 DIM ................................................. 79
Table 16. Least squares means and statistical significance of

energy-corrected milk (ECM) yield and SCC through 150 DIM ........................... 80
Table 17. Least squares means and significance of reproductive I
measurements ...................................................................................... 81
CHAPTER 5

Table 1. Arithmetic means, standard deviations, and ranges for all variables .......... 105
Table 2. Correlations, P-values and n amongst variables pooled across parities ...... 109
Table 3. Correlations, P-values and n amongst variables in parity 1 cows ............. 118
Table 4. Correlations, P-values and n amongst variables in parity 2 cows .............. 127
Table 5. Correlations, P-values and n amongst variables in parity 3+ cows ............. 136

ix

LIST OF FIGURES

CHAPTER 3

Figure 1. Least squares means and 95% confidence intervals for the
interaction of treatment by time (P = 0.02) on plasma BHBA concentrations

in the periparturient period ....................................................................... 43
Figure 2. Least squares means and SEM for the interaction of treatment

by parity by time (P = 0.10) for milk production during the first 60 DIM ................ 44
Figure 3. Least squares means and SEM for the interaction of treatment

by parity by time (P = 0.13) for protein yield through 150 DIM ............................ 45
Figure 4. Least squares means and 95% confidence intervals for the

interaction of treatment by parity (P = 0.08) for SCC through 60 DIM ................... 46
Figure 5. Least squares means and SEM for the interaction of

treatment by parity (P = 0.08) for days open .................................................. 47
CHAPTER 4

Figure 1. Least squares means and 95% confidence intervals for the
interaction of treatment by time (P = 0.03) for plasma insulin in the
periparturient period .............................................................................. 82

Figure 2. Least squares means and 95% confidence intervals for the
interaction of treatment by parity by farm (P = 0.13) for plasma insulin
concentrations postpartum ........................................................................ 83

Figure 3. Least squares means and 95% confidence intervals for the
interaction of treatment by parity by time (P = 0.12) on plasma insulin

concentrations postpartum ....................................................................... 84
Figure 4. Least squares means and 95% confidence intervals for the

interaction (P = 0.06) for milk yield through 150 DIM ...................................... 85
Figure 5. Least squares means and SEM for the treatment by parity

interaction (P = 0.07) of milk protein content through 60 DIM ............................ 86
Figure 6. Least squares means and SEM for the treatment by time

interaction (P < 0.01) of milk protein content through 60 DIM .......... ‘ .................. 87

Figure 7. Least squares means for the interaction of parity by treatment
by time (P = 0.03) for milk protein content through 150 DIM .............................. 88

Figure 8. Least squares means and SEM for the interaction of treatment
by time (P < 0.01) for milk protein yield through 150 DIM ................................ 89

Figure 9. Least squares means and 95% confidence intervals for the
interaction of treatment by farm (P < 0.01) for SCC through 150 DIM ................... 90

Figure 10. Least squares means and SEM for the interaction of
treatment by farm (P = 0.06) on days to first service ........................................ 91

BCS
BHBA
BW
CP
DIM

VLDL

LIST OF ABBREVIATIONS

Acid detergent fiber

Body condition score
Betahydroxybutric acid
Body weight

Crude protein

Days in milk

Dry matter intake

Ether extract
Energy-corrected milk

F at-corrected milk

Neutral detergent fiber
Non-esterified fatty acids
Non-fiber carbohydrate
National Research Council
Somatic cell count
Triglyceride

Total mixed ration
Volatile fatty acids

Very low density lipoprotein

xii

CHAPTER 1

INTRODUCTION

Dairy cows undergo a host of physiological and metabolic changes during late
gestation. The growing gravid uterus metabolizes increasing amounts of nutrients and
energy throughout the dry period (Bell, 1995), and lactogenesis requires sufficient
amounts of substrates during the last week of gestation (Davis et al., 1979). Additionally,
a series of endocrine changes may be responsible partially for an accelerated decline in
feed intake during the last 2 wk before parturition (Bertics et al., 1992). Together, these
changes can result in negative energy status and mobilization of body tissue reserves in
late gestation and early lactation. Excessive mobilization of body reserves prepartum
may predispose a variety of metabolic disorders (Dyk et al., 1995).

The late dry period is defined as the time prior to parturition in which dry cows
are fed and managed differently than dry cows earlier in gestation. The energy and
nutrient composition of diets fed timing the late dry period can have profound effects on
energy status of dairy cows. Increasing the amount of dietary corn grain increases the
energy concentration of the diet and may improve energy status of cows prepartum.
Feeding increased concentrations of corn grain may adapt ruminal microbes to a more
fermentable diet and improve rumen health in early lactation when this type of diet is
typically fed (Mackie et al., 1979). In addition, fermentation of corn grain produces the
desired volatile fatty acids to stimulate growth of ruminal papillae (Dirksen et al., 1985,
Xu and Allen, 1998). Proper adaptation of rumen microbes and growth of ruminal
papillae may improve energy status and rumen fimction in early lactation. Propionate
produced fi'om fermentation of corn grain results in increased blood glucose and insulin
concentrations. Both insulin and glucose are antilipolytic and may minimize

mobilization of body stores prepartum (Grummer, 1995). Therefore, proper nutritional

management of prepartum dairy cows is critical to improve energy status and minimize
health problems that may lead to improved milk production and reproduction in early
lactation.

Therefore, the working hypotheses in this research were: 1) that partial
substitution of corn silage with corn grain in diets fed to dairy cows during the late dry
period will improve energy status, health, reproduction, and milk production, and 2) that
increasing length of the late dry period will increase body condition and improve energy
status, health, reproduction, and milk production of dairy cows.

The specific objectives were: 1) to compare the effects of partial substitution of
corn silage with corn grain in diets fed to dairy cows during the late dry period on body
condition, energy status, health, reproduction, and milk production, and 2) to compare
effects of altering length of the late dry period on body condition, energy status, health,

reproduction, and milk production of dairy cows.

CHAPTER 2

REVIEW OF LITERATURE

Aspects of Feeding High Concentrations of Grain Prepartum

Increasing the concentration of grain in diets prepartum increases the energy
density of diets and may help minimize negative energy status. The idea of
supplementing concentrate feeds in diets of late gestation cows was introduced early in
the century (Boutflour, 1928). The objectives were to build up body reserves and
accustom the rumen to rations similar in energy concentration and fermentability to those
fed typically in early lactation. Today, we still hold these beliefs to~ be true and
hypothesize that increasing grain concentrations in diets prepartum may better prepare
cows for the subsequent lactation by: l) adapting rumen microbial populations to highly
fermentable diets; 2) stimulating ruminal papillae development; and 3) supplying cows
with additional energy during a period of negative energy status.

Ruminal microbial adaptation. It takes 3 wk approximately for the ruminal
microbial population to adapt from a high forage to a high concentrate diet (Mackie et al.,
1979). If large amounts of readily fermentable carbohydrate are introduced in the rumen
without proper microbial adaptation (i.e., early lactation), the carbohydrates may be
metabolized to lactic acid, which lowers ruminal pH (Goff and Horst, 1997). Dramatic
decreases in ruminal pH can cause ruminal acidosis and has many detrimental effects on

health and performance of dairy cows (Allen and Beede, 1996).

Ruminal papillae development. The concentration and type of volatile fatty acid
(VFA) produced in the rumen is important to stimulate ruminal papillae development
(Dirksen et al., 1985). High concentrations of butyrate and, to a lesser extent, propionate
increase papillae size and absorptive surface area within the rumen (Sakata and Tamate,
197 8). Ruminal fermentation of grain increases propionate production; however, an
economically feasible feedstufl~ that yields butyrate upon fermentation has yet to be
found. Increasing absorptive surface area is important for removing VFA from the
rumen. Improved absorption of VFA helps prevent ruminal acidosis and increases
energy uptake which is critical when cows are in negative energy status (i.e., during late
gestation and early lactation [Allen and Beede, 1996]).

Mtive energy stains. Typically, cows experience approximately a 30%
reduction in dry matter intake (DMI) during the last 1 to 2 wk of gestation (Bertics et al.,
1992). They become energy deficient when energy intake fails to meet the needs of
maintenance, and increasing requirements for pregnancy and lactogenesis (Bell, 1995).
Feeding a diet with higher energy density in late gestation may improve energy status and
minimize glycogenolysis and lipolysis (Grummer, 1995). Additionally, improving
energy status around parturition also may influence immune function (Kimura et al.,
1997) and incidence of health disorders (Dyk et al., 1995).

Efl'ects on Grain Supplementation Prepartum on Milk Production

In early studies, effects of energy intake prepartum on milk production were
variable. Cows fed hay and corn silage plus 2.3 kg/d of concentrate starting 6 wk
prepartum and increased gradually to 5.5 kg/d at parturition had similar milk yields as
those fed only hay and corn silage (Greenhalgh and Gardner, 1958). Schmidt and
Schuldtz (1959) found no additional milk production by supplementing corn silage and
hay with 5.8 kg/d of concentrate during the final 8 wk of gestation. Similarly,

supplementing ad libitum hay and pasture with concentrates did not alter milk production

(Davenport and Rakes, 1969). The above mentioned studies did not record BCS which
can influence DMI, fed diet components separately, and reported low milk production.
Therefore, it is difficult to extrapolate these results to modern high producing herds fed a
total mixed ration (TMR).

Nocek et al. (1983) randomly assigned 289 cows to prepartum diets of: 1) all hay
fed ad libittun; 2) 50% hay and 50% corn silage fed adlibitum; and, 3) corn silage fed at
1% of body weight (BW) supplemented with 1.1 kg/d of a concentrates. Cows fed diet 1
produced 1.5 kg/d more milk during the first 9 wk of lactation than cows fed diets 2 and 3
(P < 0.05). However, there were no differences in fat-corrected milk (FCM) yield due to
low milk fat concentrations of cows fed diet 1. It could be theorized that the lack of
adaptation of the ruminal microbes and papillae was responsible for some degree of
acidosis and reduced fiber digestion postpartum that caused the decrease in milk fat
concentration. Daily NEL intakes prepartum were 9.9, 11.8 and 9.6 Mcal per cow for
groups 1, 2 and 3, respectively. Cows fed diet 3 lost body weight during the dry period
because of the low energy intakes, making it difficult to compare these cows to those fed
ad libitum.

Several studies showed positive responses to increasing the amount of concentrate
in the diet prepartum. Addition of concentrates, primarily corn grain, to ad libitum hay
consumption prepartum increased milk yields (Swanson and Hinton, 1962; Emery et al.,
1969). Recent research utilizing higher producing cows showed benefits of increasing
NEL intake prepartum. Johnson and Combs (1991). fed cows either 1.5 or 1.68 Mcal
NEl/kg of dietary dry matter from 70 to 10 d prepartum. The lower energy diet consisted
of 59% alfalfa silage and 41% corn silage; ground corn and soybean meal replaced 43%
of the silage mixture in the higher energy diet, dry basis. All cows were fed a medium-
energy diet (1.61 Mcal NEl/kg) the last 10 d prepartum. Cows fed the high-energy diet
produced 6 kg/d more F CM (P = 0.06), but only 6 cows were used in this study due to
other experimental objectives. Minor et al. (1996) fed cows a standard diet with 1.34

Mcal NEng and 23.5% non-fiber carbohydrate (NFC; NFC = 100 — neutral detergent
fiber - crude protein - ether extract - ash, dry basis) or a high diet of 1.63 Mcal NEL/kg
and 43.8% NFC for the last 19 d of gestation. Partially substituting corn grain and starch
for alfalfa silage, corn silage and straw altered the NFC of the diets. Cows fed the high
diet produced 2.8 kg/d more milk (P < 0.05) that was higher in protein percentage (P <
0.01), but tended to be lower in fat percentage (P < 0.10) during the first 40 wk of
lactation.

In addition to total dietary energy, the proportion of concentrates relative to
forage may also be important. Two unique experiments compared isocaloric diets
varying in forage-to-concentrate ratio (Olsson et al., 1997). The diets were fed in
different amounts to compensate for the changes in energy value of varying the forage-to-
concentrate ratio. Grass silage and hay were the forage sources and the concentrate
fraction comprised oats and barley. Concentrate feeding started at 4 wk prepartum and
gradually increased to meet the assigned ratio in both experiments at 3 d prepartum. The
forage-to-concentrate ratios for the three diets in experiment 1 were 95:5, 70:30, and
40:60 for diets 1, 2 and 3, respectively. Cows fed diet 3 produced 3.8 kg/d more F CM
during wk 2 through 4 of lactation than cows fed diet 2 despite having lower DMI
prepartum because of energy restriction (P < 0.05). Although numerically higher for
cows fed diet 3, no significant differences in milk yield were detected between the groups
during the first 2 wk or after 4 wk postpartum. In experiment 2, forage-to-concentrate
ratios of 60:40 (diet 1) and 40:60 (diet 2) were fed. Cows fed diet 2 produced more milk
than those fed diet 1 during wk 5 to 14 of lactation (P < 0.05), but no differences were
seen before and after this period or in F CM yield. Based on these studies, the type of
energy source (grain vs. fiber) may be important in determining the effectiveness of the
diet prepartum. These results support the dreary that perhaps the proper fermentation
end-products (propionate and butyrate vs. acetate) are essential to prepare the rumen by

adapting microbes and stimulating ruminal papillae development.

Effects of Grain Supplementation Prepartum on Indicators of Energy Status

Insulin. Increasing the amount of grain in diets increases propionate and glucose

 

production and subsequent insulin secretion. It is well documented that increased
concentrate feeding prepartum increases plasma insulin concentrations (Fronk et al.,
1980; Holtenuis et al., 1993; Kunz et al., 1985; Olsson et al., 1997). Increased plasma
insulin concentrations prepartum have been suggested to cause insulin resistance
postpartum; thereby, reducing the antilipolytic effects of insulin (Holtenuis, 1993).
However, high circulating concentrations of insulin also have been hypothesized to
increase hepatic glucose production and spare glycogen usage (Grummer, 1995). This
could reduce hepatic triglyceride (TG) deposition and incidences of ketosis and fatty
liver syndrome (Grummer, 1993). The significance of insulin concentration prepartum
on insulin receptor sensitivity postpartum and hepatic lipid metabolism has not been
elucidated.

Non-esterified fag acids (NEFA). NEFA are a measure of lipolysis and are
indicators of energy status. NEF A are produced in the greatest quantities during periods
of negative energy status such as late gestation and early lactation when adipose tissue is
mobilized to meet additional energy demands. The liver removes 7 to 25% of circulating
NEFA (Emery et al., 1992), but NEFA concentrations in blood regulate uptake into the
liver (Bell et al., 1980). Once in the liver, NEFA can be oxidized completely to C02 and
H20, oxidized partially to ketones, or re-esterified to TG (Bruss, 1993). The bovine liver
has a decreased ability to export TG as very low-density lipoprotein (VLDL); therefore,
increased uptake of NEFA may predispose TG deposition in hepatic tissue and may lead
to fatty liver syndrome (Grummer, 1993). Additionally, high NEFA concentrations in the
liver can exceed the mitochondrial and peroxisomal oxidative capacity and result in
ketone body production and subsequent ketosis.

The effects of concentrate feeding prepartum on NEFA concentrations in blood

vary among studies. Cows fed to meet maintenance energy requirements had higher
serum NEFA concentrations from 70 to 5 d prepartum than cows fed the same diet
supplemented with concentrates throughout the dry period (Kunz et al., 1985). However,
NEF A concentrations postpartum were higher for the cows supplemented with
concentrates prepartum. Higher DMI postpartum for the maintenance-fed group may
account for the lower NEF A concentrations. Several studies reported no effects of
prepartum energy intake on NEFA concentrations (Boisclair et al., 1986; Holtenuis,
1989; Jones and Garnsworthy, 1989), but others reported increased NEFA for cows fed
higher energy diets prepartum (Fronk et al., 1980: Nachtomi et al., 1986). Discrepancies
in the results may have arisen from the wide ranges of DMI, BCS, and milk production
among studies.

Recent research suggests that increasing concentrates prepartum may improve
energy status and decrease NEFA concentrations. Holtenuis et al. (1996) fed cows
rations in which concentrates were increased gradually into the diet starting at 4 wk
prepartum to reach levels of 10 and 50 % concentrate at 3 d prepartum. Cows fed 50%
concentrate had lower NEF A concentrations from 1 wk prepartum through 1 wk
postpartum than cows fed 10% concentrate at calving (P < 0.01). No changes were
observed before or after this 2 wk period. Similarly, Minor et al. (1998) found
numerically lower NEFA concentrations fi'om 7 d prepartum through 60 d postpartum in
cows fed 43.8% NFC diets compared with cows fed 23.5% NFC during the last 3 wk of
gestation. Cows fed 1.68 Mcal NEng of dry matter (DM) during the last 26 d of
gestation had lower NEFA concentrations in the last 7 d prepartum than cows fed 1.30
Mcal NEng of DM (V andeHaar et al., 1995). Unfortunately, higher concentrations of
protein in the high energy diet confounded clear determination of the effect of energy in
this study. F uturc research should address the role of grain supplementation and other
contributing factors such as BCS and DMI on adipose tissue mobilization.

Ketone Bodies. Incomplete oxidation of NEF A in hepatic tissue results in

production of ketone bodies (beta-hydroxybutyrate, acetoacetate, and acetone). Excess
acetyl CoA is converted to acetoacetate in hepatic mitochondria through a series of
metabolic reactions. Acetoacetate can be reduced to beta-hydroxybutyrate if the reduced-
to-oxidized ratio of nicotinamide andenine dinucleotide is sufficient. Acetone comprises
a small percentage of total ketones and is formed from a spontaneous decarboxylation of
acetoacetate. High circulating concentrations of ketones combined with low blood
glucose may predispose cows to ketosis.

Several studies reported no effect of increasing grain supplementation in diets fed
prepartum on blood ketone concentrations postpartum (Boisclair et a1, 1986; Olsson et
al., 1997; Schmidt and Schultz, 1959). Gardner (1969) observed increased blood ketone
body concentrations during the first 2 wk postpartum for cows fed increased energy
(20.52 vs. 14.88 Meal NEL/d) prepartum. Energy concentrations were adjusted by
feeding varying amounts of alfalfa hay. Minor et al. (1998) found decreased blood
ketone concentrations during early lactation in. cows fed diets with high NFC
concentrations prepartum. Additionally, cows in that study also had lower plasma NEFA
concentrations and liver TG during the periparturient period. Diets high in grain may
reduce ketone synthesis by increasing propionate and subsequent insulin production

which are both antiketogenic (Grummer, 1993).

Effects of Grain Supplementation Prepartum on. Health Disorders

Because large numbers of animals are needed, few studies have been able to
detect statistically significant differences in effects of prepartum diet on incidences of
health disorders. Much early research focused on the effects of concentrate feeding
prepartum on udder edema. Generally, primiparous cows have more udder edema than
multiparous cows (Greenhalgh and Gardner, 1958; Zamet et al., 1979). Emery et al.
(1969) reported increased udder edema of primiparous cows fed up to 7 kg/d of grain

during the last 3 wk of gestation compared with cows not receiving supplemental grain.
The effects of concentrate feeding prepartum on udder edema in multiparous cows are
less well documented. Cows fed 12 or 46.5% of dietary DM as high moisture corn for 30
d prepartum had more edema than cows fed all hay (Johnson and Otterby, 1981).
However, most studies showed no effect of concentrate feeding prepartum on udder
edema regardless of parity (Greenhalgh and Gardner, 1958; Schmidt and Schultz, 1959;
Fountaine et al., 1949; Hathaway et al., 1957). Other factors such as dietary mineral
element concentrations may influence udder edema more than prepartum concentrate
feeding.

Incidences of other health disorders to varying amounts of grain fed prepartum are
not consistent across studies. Many studies with small numbers of cows report no
changes on incidence of disorders (Boisclair et al., 1987; Johnson and Otterby, 1981;
Schmidt and Schultz, 1959). However, Emery et al. (1969) observed significant
increases in the incidence of mastitis and milk fever of 148 cows fed up to 7 kg/d of grain
compared with cows fed ad libittun hay prepartum. However, increasing energy
requirements above NRC (1989) recommendations during the last 3 wk of gestation
decreased the incidence of health disorders in 1374 cows in 31 herds (Curtis et al., 1985).

Efl'ects of Grain Supplementation Prepartum on Reproduction

Similar to health disorders, reproductive measurements require large numbers of
cows to detect significant differences. Not only did. many studies fail to measure
reproductive traits, but those that did had insufficient replications. Typically, the
variables measured to indicate reproductive efficiency are days open, days to first estrus,
days to first artificial insemination, conception rate and percent of cows pregnant by a
given date. Several studies utilizing only small numbers of cows (11 < 30) reported no
differences in any of the above mentioned measurements (I-Iolter et al., 1990; Keys et al.,

1984; Olsson et al., 1997). Nocek et al. (1983) reported the only study with reproductive

10

responses and large sample sizes (n > 90). Cows were fed all hay (9.9 Mcal NEL/d), 50%
hay and 50% corn silage (11.8 Mcal NEL/d), or corn silage at 1% of BW plus 1.1 kg/d of
concentrates (9.6 Meal NEl/d). Cows fed all hay had more days open than cows fed the
corn silage and hay mix (P < 0.05). As previously mentioned, the study is confounded by
the limited energy intakes of less than 10 Mcal NEljd.

Altering Length of the Late Dry Period

There could be two potential benefits of feeding a diet with higher grain content
for longer than the traditional 2 to 3 wk prepartrun. The first is to promote body
condition gain of dry cows. The current recommendation is for dry cows to maintain
BCS during the dry period (NRC, 1989). This recommendation is based partially on the
contention that cows deposit energy more efficiently during lactation than while dry
(Moe and Tyrell, 1972). However, replenishment of body reserves of high producing
cows during late lactation has become increasingly difficult and cows may need to
replenish body reserves during the dry period to reach an optimal BCS at parturition.
Indeed, higher producing cows dry-off with lower BCS than less productive cows
(Wildman et al., 1982).

Generally, cows can not gain sufficient amounts of body reserves during the last 2
to 3 wk prepartum when higher energy diets are more typically fed. In order to increase
BCS during the dry period, cows may need to be fed higher energy diets for longer than 3
wk. No studies have evaluated effects of altering the length of time of feeding a higher
energy diet prepartum. .

Secondly, feeding a high grain diet for a longer period of time prepartum may be
an effective method of promoting ruminal papillae development. As previously
mentioned, ruminal papillae size influences absorptive capacity of the rumen. However,
papillae may require 4 to 6 wk of increasing grain concentration to reach maximum

absorptive capacity (Dirksen et al., 1985). In support of this concept, recent research

11

from Michigan State University showed increased papillae development of non-pregnant,
non-lactating dairy cows fed 43.5% ground corn (Xu and Allen, 1998). Interestingly, the
surface area of ruminal papillae increased proportionally to time on treatment (28 (1).
Therefore, cows may benefit from higher grain diets for longer than the traditional 2 to 3
wk prepartum to achieve maximum ruminal papillae size and absorptive surface capacity
at parturition. .

Feeding higher grain diets for longer than 3 wk prepartum may improve papillae
development, VFA absorption and energy status as well as increase BCS during late
gestation. Future research should determine the length of time a more fermentable diet
needs to be fed prepartum for proper ruminal adaptation and maximal papillae growth.
Additionally, future research should investigate how BCS changes during the dry period

and BCS at parturition can influence postpartum performance.

Relationship Between BCS and Milk Production

Several field studies used regression analysis to evaluate relationships between
milk production and BCS changes during the dry period. Domecq et al. (1997) showed
an increase of 545 kg of milk in the first 120 d of lactation for cows increasing BCS by 1
unit during the dry period. The BCS cows in this study averaged 2.77 (1.0 to 5.0 scale) at
the beginning of the dry period and produced an average of 38 kg/d of milk through 120
d in milk (DIM).

The efi‘ects of BCS change during the dry period in controlled studies in not well
documented. Boisclair et al. (1986) randomly assigned cows to one of the following
dietary treatment groups: 1) all forage diet (54% alfalfa silage, 44% corn silage; 1.44
Mcal NEdkg) during the last 90 d of lactation and fed to requirements (1.5 Mcal NEljkg)
dming the dry period; 2) all forage diet during the last 90 d of lactation and ad libitum
feeding of a high energy TMR (1.64 Mcal NEL/kg) during the dry period; 3) ad libitum
feeding of a high energy TMR (1.64 Meal NEL/kg) during the last 90 d of lactation and

12

restricted energy intake (70% of energy requirement) during the dry period; and 4) ad
libitum high energy diet (1.64 Mcal NEl/kg) during late lactation and the dry period.
High moisture corn replaced alfalfa silage and corn silage in the TMR to increase energy
density of diets. BCS changes during the dry period for the four groups were -.24, .45, -
.58 and .22 for dietary treatments 1, 2, 3 and 4, respectively. BCS at parturition were
3.19, 3.95, 3.26 and 3.99 (1.0 to 5.0 scale) for dietary treatments 1, 2, 3 and 4,
respectively. Feeding diets 2 and 4 increased BCS and subsequent milk production
compared with cows fed diets 1 and 3 (35.9 and 35.3 vs. 33.1 and 32.7 kg/d; P < 0.05).
A series of studies examined feeding cows starting at 12 wk prepartum to adjust BCS to
either thin (2.0 to 2.3) or fat (3.2 to 3.5) on a 1.0 to 4.0 scale (Garnsworthy and Huggett,
1992; Gamsworthy and Jones, 1987; Jones and Garrrsworthy, 1989). There were no
changes in DMI, or milk composition and yield. Although BCS were recorded at
parturition, initial BCS and BW were not measured. Therefore, BW or BCS change
during the dry period could not be calculated. Increasing BCS from 3.0 to 3.8 (1.0 to 5.0
scale) during the dry period by liberal grain feeding with corn silage resulted in similar
milk yields (F ronk et al., 1980). Other studies have tried to change BCS substantially
throughout the dry period, but failed due to inadequate dietary energy concentrations or
because cows were fed higher energy diets for only a short period of time (Gardner,
1969; Grum et al., 1996; Nocek et al., 1983; Nocek et al., 1986). Overall, it appears that
cows entering the dry period with inadequate BCS may benefit from replenishment of

body reserves.

Relationship Between BCS and DMI

The negative relationship between BCS at parturition and DMI is becoming more
evident with more recent research. Generally, it is accepted in the field that cows calving
with excessive BCS have compromised DMI. However, past research does not fully

support this claim. Two often cited studies reported lower peak DMI in cows with high

13

BCS, although no significant differences were reported (Garnsworthy and Topps, 1982;
Treacher et al., 1986). Additionally, many studies reported no changes in DMI as it
relates to BCS at parturition (Boisclair et al., 1986; Erb et al., 1982; Holter et al., 1990;
Smith et al., 1997). In contrast, several studies have reported effects of BCS on DMI.
One study involving three groups of eight cows varying in BCS showed a longer interval
to peak DMI in the group with the highest BCS (Garnsworthy and Topps, 1982). Perkins
(1982) showed that both cows with high BCS at calving and cows that had accelerated
BCS loss during the first 2 wk postpartum had depressed DMI. Roseler et al. (1997)
showed that BCS accounted for approximately 6% of the variation in a linear model used
to predict DMI. It should be noted that of the 241 eows used in this study none with a
BCS of greater than 4.0 (1.0 to 5.0 scale) were included in the model. BCS was a
significant factor when predicting DMI of transition cows (Hayirli et al., 1998). This
study utilized 299 cows in various research projects from three universities. The authors
also noted that BCS affected the shape of the DMI curve around parturition. The
prepartum DMI depression in thin cows (BCS < 3.0) began later, but rate of depression
was much more severe during the last 3 (1 prior to parturition. This area requires further
research to elucidate the effects of BCS on DMI in the periparturient period. Research
should investigate the effects of different diets postpartum as well as BCS at partm'ition
on the potential depression of DMI and time required for cows to reach peak DMI in

early lactation.

Relationship Between BCS at Parturition on Health Disorders '

The efi‘ects of BCS at parturition on incidences of health disorders postpartum are
not well understood. Treacher et al. (1986) showed higher total incidences of health
disorders for cows that were over-conditioned at parturition, but only 18 cows were
included in this study. Others suggested increased problems postpartum, but differences
were not statistically significant (F ronk et al., 1980; Keys et al., 1983; Perkins, 1982).

14

However, several studies utilizing cows at different milk production levels showed no
relationship between BCS at parturition on health disorders in early lactation (Boisclair et
al., 1986; Gamsworthy and Topps, 1982; Gearheart et al., 1990; Ruegg and Milton,
1995). Morrow (1976) suggested that feeding high amounts of corn silage during the dry
period and thus increasing the energy of the diet may predispose cows to health disorders
postpartum. However, often BCS of cows at dry-off were not considered. Morrow et al.
(1979) investigated a herd with a high incidences of fatty liver syndrome. Cows were fed
diets high in corn silage during the dry period and throughout lactation. Reducing corn
silage consumption during the dry period decreased the incidence of fatty liver syndrome
and other health disorders associated with it. Although BCS were not reported, the
authors stated that cows reached dry-off with excessive body condition. Feeding high
amounts of corn silage promoted further, unneeded weight gain during the dry period
resulting in obese cows at parturition. This study does not represent modern, high-
producing cows which may have more difficulty replacing body condition than becoming
over-conditioned during late lactation. Benefits from increasing grain supplementation
during late gestation may be compromised if cows are gaining to achieve BCS in excess
of those recommended (3.5 to 3.75) (Michigan State University Dairy Programs Group,
1995). Recent research involving 1556 cows in 95 Michigan dairy farms Showed cows
calving with BCS greater than 4.0 had an increased risk of ketosis and abomasal
displacement (Dyk, 1995).

Decreasing BCS during the dry period in an attempt to reach the recommended
BCS at parturition is not recommended. Lowering BCS during the dry period caused
increased incidences of health disorders in early lactation (Gearheart et al., 1990; Zamet
et al., 1979). Other factors such as diet composition, DMI, and rate of acceleration to
peak DMI, immune function and parity Should be considered when evaluating the role of

BCS at parturition on health disorders.

15

Relationship Between BCS at Parturition on Reproduction

Several studies have evaluated the effects of BCS at parturition to reproductive
performance. Research shows that reproductive variables are not affected by BCS at
parturition (Garnsworthy and Topps, 1982; Gearheart et al., 1990; Pedron et al., 1993;
Reugg and Milton, 1995; Treacher et al., 1986; Waltner et al., 1993). The severity of
negative energy status in early lactation appears to be a major determinant of
reproductive function (Butler and Smith, 1989;Nebe1 and McGilliard, 1993; Staples et
al., 1990). Cows that lost BCS rapidly in early lactation had more days open and days to
first estrus (Perkins, 1982). Additionally, cows with a BCS of 4.2 at parturition lost 57%
more BW during the first 4 d of lactation compared with cows with a BCS of 3.5 (Smith
etal., 1997). These findings suggest that obese cows that lose more BCS in early
lactation may have reduced reproductive efficiency compared with cows that have
moderate BCS. Future research efforts should investigate the effects BCS at parturition
on severity and extent of BCS loss in early lactation, and how BCS changes in early

lactation influence reproductive performance.

16

CHAPTER 3

PERIPARTUM RESPONSES OF DAIRY COWS TO PARTIAL SUBSTITUION
OF CORN SILAGE WITH CORN GRAIN IN DIETS FED DURING THE LATE

DRY PERIOD

ABSTRACT

One hundred eighty-nine cows in a commercial dairy farm were assigned
randomly to either a diet with supplemental corn grain (SC) or without supplemental corn
grain (NC) approximately 17 d before parturition. Diets were formulated to be similar

with the exception that dry ground corn replaced 21% of the corn silage in the SC diet,
dry basis. The SC diet reduced plasma betahydroxybutyrate and tended to increase
plasma insulin concentrations prepartum compared with the NC diet. Effects of
treatment on production responses were highly dependent upon parity as indicated by
parity by treatment by time interactions for milk and protein yields. Primiparous cows
fed the SC diet had reduced milk protein yield, increased somatic cell count and days
open compared with cows of the same parity fed the NC diet. The SC diet resulted in
lower milk yields in early lactation and increased sOmatic cell count and days Open for
cows in their second parity. However, cows in their third parity or greater fed the SC diet
yielded more milk and protein in early lactation, and had decreased somatic cell count
and days open. Increasing the corn grain concentration of diets fed prepartum was
advantageous to third and greater parity cows in this experiment, but showed no benefits

during lactation for cows in first or second parities.

l7

INTRODUCTION

Dairy cows undergo a host of physiological and metabolic changes during late
gestation. The growing gravid uterus metabolizes increasing amounts of nutrients
throughout the dry period (Bell, 1995) and lactogenesis requires sufficient amounts of
substrates during the last week of gestation (Davis et al., 1979). In addition, a series of
endocrine changes may be responsible partially for an accelerated decline in feed intake
during the last 2 wk before parturition (Bertics et al., 1992). Together these changes can
result in negative energy status and mobilization of body tissue reserves in late gestation
and early lactation. Excess mobilization of body reserves prepartum may predispose a
variety of health disorders (Dyk et al., 1995).

The late dry period is the time prior to calving when ofien dairy cows are fed and
managed differently than cows earlier in the dry period. Feeding increased amounts of
corn grain to cows in the late dry period may be advantageous for several reasons.
Increasing corn grain may acclirnatize rmninal microbes to higher energy diets fed
typically in early lactation (Mackie et al., 1979). Increased propionate production from
ruminal fermentation of corn grain may stimulate ruminal papillae development (Dirksen
et al., 1985, Xu and Allen, 1998). The additional energy supplied by the corn grain may
help offset the negative energy status prior to parturition. In addition, fermentation of
corn grain results in increased concentrations of propionate and subsequently glucose
(Olsson et al., 1997). Improving the carbohydrate status of periparturient cows may
promote glycogenesis and improve hepatic function (Grummer, 1995).

Both propionate and glucose promote secretion of insulin, an antilipolytic

l8

hormone. Therefore, increased corn grain potentially could improve lipid metabolism
and energy status of periparturient dairy cows by reducing plasma NEFA concentrations
and improving hepatic NEFA metabolism.

The objective of this experiment was to determine the effects of partially
replacing corn silage with corn grain in a diet fed during the late dry period on body

condition, health, energy status, milk production, and reproduction of dairy cows.

MATERIALS AND METHODS

Cows and Treatments

One hundred eighty-nine cows in. a commercial dairy farm were completely
randomized and assigned to be fed a diet with supplemental corn grain corn grain (SC) or
without supplemental corn grain (NC) approximately 3 wk before their expected calving
date (Table 1). There were 50 parity 1, 58 parity 2, and 81 parity 3+ cows in the
experiment. Cows were co-mingled and fed the same diet during the first 2 to 3 wk
postpartum (early lactation diet; Table 2). Subsequently, primi- or multiparous cows

were grouped separately, and fed different diets (Table 2).

Sample Collection and Analysis

Silage dry matter content was determined weekly using a Koster Tester (Koster
Crop Tester, Inc., Medina, OH) and adjustments were made to maintain the same dietary
composition on a dry basis. TMR were sampled weekly prepartum through 150 d
postpartum and dried at 55° C for 72 h for future analysis. Particle size distribution of

TMR samples, as-fed basis, was determined using the Penn State Particle Separator

l9

(Nasco, Fort Atkinson, WI; Lammers et al., 1996). Feed samples were ground through a
Wiley mill (1 mm screen, Authur H. Thomas, Philadelphia , PA) and composited
monthly. Samples were analyzed for NDF, ADF, CP, ether extract (EE), ash, ammonia,
and minerals (Northeast DHI Forage Laboratory, Ithaca, NY).

One evaluator scored cows for BCS [five-point scale where l = thin to 5 = fat;
(Wildman et al., 1982)] weekly prepartum, at calving, and 3 and 6 wk postpartum.
Additionally, one evaluator assigned udders edema scores (0 = none , 1 = mild, 2 =
moderate, and 3 = severe) within 3 (1 following parturition.

Blood samples were collected in evacuated test tubes containing sodium heparin
(V acutainer; Becton Dickson Vacutainer Systems USA, Rutherford, NJ) from the
eoccygeal vessels twice weekly prior to parturition, within 3 d following parturition, and
1 and 2 wk postpartum. Blood samples were collected approximately 7 to 8 h after
feeding. Samples were stored on ice during transport to the laboratory. Upon arrival
they were centrifuged, and plasma was harvested and stored at -4 C until later analysis
of NEFA (NEFA-C kit, Waco Chemicals USA, Richmond, VA) with modifications
(Johnson and Peters, 1993), insulin (Coat-A-Count, Diagnostic Products Corporation,
Los Angeles, CA), and BHBA (310-A, Sigma Diagnostics, St. Louis, MO). All reagents
in the BHBA assay except beta-hydroxybutyrate dehydrogenase were reduced
proportionally to fit into 350 ul wells of cell culture plates. Beta-hydroxybutyrate
dehydrogenase was added at twice the reduced dose to shorten the incubation time. Inter-
assay and intra-assay coefficients of variation for BHBA, NEFA and insulin were 5.6 and
7.0, 6.9 and 8.0, and 4.3 and 6.6, respectively.

Herdspersons and veterinarians were responsible for recording incidences of

20

health disorders and reproductive performance data throughout the experiment. Health
disorders are defined as the following: displaced abomasum was an abnormal location of
the abomasum as diagnosed by percussion that required corrective surgery; ketosis was a
positive urine ketone test of moderate or greater (Ketostix; Bayer Corp., Elkhart, IN);
mastitis was abnormal stripping or inflammation that required treatment; and, retained
placenta was fetal membranes retained longer than 24 h after parturition.

The farm that participated in this study had an intensive milk fever prevention
protocol. All third parity cows received a bottle of CMPK (10.8g Ca, 75g dextrose; Jice
Pharmaceuticals Co., Lowell, MI) orally immediately following parturition. All fourth or
greater parity cows, or any cows having twins, received a bottle of CMPK orally plus 500
ml of Calnate (10.7g Ca; The Butler Co., Columbus, OH) subcutaneously. In addition,
rectal temperatures of all cows were monitored daily through 12 DIM. For analysis,
cows having a rectal temperature above 394°C for at least 1 (1 during the first 12 DIM
were considered abnormal. Individual milk weights were recorded every 2 wk and
samples were analyzed for fat, protein and SCC monthly (Michigan DHIA). Energy-
corrected milk (ECM) was calculated by the equation ECM (lb) = 0.3246 x milk yield
(lb) + 12.86 x fat yield (lb) + 7.04 x protein yield (lb)(Dairy Herd Improvement Glossary,
Fact sheet A-4, 1999). Over 60% of the cows in each treatment received bST injections
(Monsanto Co., St. Louis, MO) during the sampling period. The voluntary waiting
period for bST administration was 63 and 90 d for multiparous and prirrriparous cows,
respectively. Cows received bST unless BCS was less than 2.5 or milk yield was greater
than 40 kg/d for primiparous cows and 50 kg/d for multiparous cows.

Days open, days to first service, pregnancy rate and percentage of cows pregnant

21

by 150 DIM were recorded. All analyses of reproductive variables were based on cows
that were confirmed pregnant by 200 DIM. The Ovsynch® protocol (Pursley et al., 1996)

was used to synchronize breeding for all cows at 70 DIM.

Statistical Analysis

All blood measurements and SCC data were log transformed to correct for
heterogeniety of variance. Milk production, BCS and blood measurements were
analyzed as repeated measures using the PROC MIXED procedure of SAS [version 6.1;
SAS, (1989)]. The statistical model included the fixed effects of treatment, parity, time,
two- and three-way interaction terms of all fixed effects, the random effect of cow nested
within treatment, and residual error. Blood measurements were analyzed and reported for
the prepartum and postpartum periods separately, or across both periods (periparturient
period). For all models, non-significant interaction terms (P > 0.15) were removed in a
backwards stepwise manner. Udder edema and reproduction data were analyzed using
PROC MIXED with main effects of farm, parity and treatment, and all two- and three-
way interaction terms. Incidences of health disorders and percentage of cows pregnant
by 150 DIM were analyzed using the PROC GENMOD procedure of SAS [version 6.1;
SAS, (1989)] and differences were determined by Chi-Square tests. Differences between
treatments were determined by F-test. Least squares means and standard error of the
means are reported for all data except blood and SCC measurements. Because of the
transformations to remove heterogeneity, 95% confidence intervals are reported instead
of standard error of the means for blood and SCC data. Statistical significance was

declared at P < 0.05, and tendency towards significance at P > 0.05 to P < 0.15.

22

RESULTS AND DISCUSSION

Diet Composition

Cows were fed treatment diets for 17 i 6 d prepartum (mean 1- standard
deviation). Ingredient and chemical compositions of the treatment diets are presented in
Table 1. The only differences in ingredient compositions between the diets were the
concentration of corn grain and corn silage. As expected, diets were similar in CP, EE
and mineral concentrations. The SC diet had higher DM content and smaller particle size
because of the replacement of corn silage with dry ground corn. The NFC concentrations
of the diet were more similar than expected. Diets fed from parturition to 150 DIM are
shown in Table 2. Ingredient composition of diets differed slightly, but chemical
compositions among diets were similar. Additionally, formulated ingredient and
chemical composition of the diet fed during the early dry period prior to the treatment

diets is shown in Table 3.

Body Condition and Udder Edema

Body condition scores of cows throughout the periparturient period are shown in
Table 4. Treatment had no effect on BCS when analyzed as repeated measures across
time (P = 0.16). BCS changes during the periparturient period are shown in Table 5.
Effect of treatment on BCS changes tended to vary among cows of different parities
(treatment by parity interaction; P = 0.09; Table 5). Cows of parity 1 fed the NC diet

gained BCS in the late dry period, but cows of the same parity fed the SC diet lost BCS in

23

the late dry period. However, cows of parity 2 fed the NC diet lost BCS, whereas parity
2 cows fed the SC diet gained BCS in the late dry period. Both treatments promoted BCS
gain of parity 3+ cows. It is doubtful that the small changes observed in BCS changes
prepartum among parities and treatment have biological significance. There were no
effects of treatment on BCS changes from parturition to 3 or 6 wk postpartum, or from 3
to 6 wk postpartum (Table 5). Therefore, treatment had no effect on rate or extent of
BCS loss in early lactation.

Udder edema scores were not affected by treatment (P = 0.24; data not shown),
but were influenced by parity (P < 0.01). Primiparous cows had higher udder edema
scores compared with multiparous cows (1.9, 1.3, and 1.4, respectively). Feeding higher
amounts of concentrates prior to parturition caused increased udder edema in some
studies (Emery et al., 1969; Johnson and Otterby, 1981), but not in others (Greenlaugh
and Gardner, 1958; Hathaway et a1, 1957; Schmidt and Schultz, 1959). It is common for
primiparous cows to have more udder edema at calving compared with multiparous cows

(Greenhalgh andGardner, 1958; Zamet et al., 1979).

Metabolic Variables

Plasma NEFA concentrations for the prepartum, postpartum and periparturient
periods (both pre- and postpartum) are shown in Table 6. Treatment did not affect
plasma NEFA concentrations during any period. Plasma NEFA increased as parturition
approached and peaked at 7 d postpartum. The similar plasma NEFA concentrations in
cows between treatments suggest that both treatment groups were in similar energy status

in the periparturient period.

24

Cows fed the SC diet had lower plasma BHBA concentrations prepartum
compared with cows fed the NC diet (P < 0.01; Table 7). There were no differences
observed in the postpartum period, but the SC diet tended to reduce plasma BHBA across
the entire periparturient period (P = 0.07). There was a significant treatment by time
interaction for plasma BHBA in the periparturient period (P = 0.02). Plasma BHBA
concentrations were higher prepartum for cows fed the NC diet, but were lower
posparturn compared with cows fed the SC diet (Figure 1). Contrary to these results,
feeding a higher energy diet prepartum decreased plasma NEF A concentrations
(Holtenius et al., 1996; Minor et al, 1998; VandeHaar et al., 1995), but had no effect on
ketone production (Boisclair et al., 1986; Minor et a1, 1998; Olsson et al., 1997; Schmidt
and Schultz, 1959) prior to parturition.

Plasma insulin concentrations are shown in Table 8. Cows fed the SC diet tended
to have higher plasma insulin concentrations prior to parturition compared with cows fed
the NC diet (14.17 vs. 12.63 uIU/ml; P = 0.07). Treatment had no effect on plasma
insulin concentrations postpartum or during the periparturient period. Insulin has both
antilipolytic and antiketogenic properties (Grummer, 1993; Holtenhuis, 1993). A
reduction in lipolysis elicited by insulin reduces the substrates available for ketogenesis.
Increasing the amount of corn grain in the diet may promote propionate and glucose
production and subsequently, insulin secretion. Indeed, cows fed the SC diet tended to
have higher insan concentrations prepartum, probably a result of increased propionate
and glucose production. However, no reduction in lipolysis, as measured by plasma
NEFA concentration, was observed in this study. A metabolite of propionate, succinyl-

CoA, directly inhibits ketogenesis (Lowe and Tubbs, 1985). Therefore, improved

25

carbohydrate supply and subsequently reduced ketogenesis in cows fed the SC diet may
have caused the decrease in plasma BHBA as opposed to a decrease in NEFA

concentrations.

Health Disorders

Incidence rates of health disorders and the occurrence of rectal temperatures
above 394°C are shown in Table 9. Incidence rates of mastitis are not reported because
of the low incidence rate (1.6%). There were no significant effects of treatment on
incidence rates of any health disorders. However, incidence rates of displaced abomasrun
and ketosis were numerically higher for cows fed the SC diet compared with cows fed the
NC diet. Several studies and reviews have reported that feeding higher energy diets prior
to parturition may lead to an increased risk of displaced abomasrun (Cameron et al.,
1998; Shaver, 1997). Contrary to these findings, Curtis et a1, (1985) reported that
decreased incidences of left displaced abomasum and dystocia were associated with

higher than average dietary energy intake during the last 3 wk prepartum.

Milk Yield, Composition and Somatic Cell Count

There were no differences in milk yields through 60 or 150 DIM between
treatments (Tables 10 and l 1). During the first 60 DIM there was a tendency towards a
treatment by parity by time interaction (P = 0.10; Figure 2). The interaction was evident
only in parity 2 and 3+ cows. Parity 2 cows fed the SC diet had lower milk yields during
the first 15 d of lactation compared with parity 2 cows fed the NC diet (33.7 vs. 38.0

kg/d). In contrast, cows of parity 3+ fed the SC diet yielded more milk during the first 15

26

d of lactation compared with cows of the same parity fed the NC diet (44.2 vs. 37.4 kg/d).
Additionally, cows of parity 3+ fed the SC diet tended to have slightly higher milk yields
throughout the first 60 DIM compared with parity 3+ cows fed the NC diet (45.2 vs. 42.6
kg/d). Prirrriparous cows fed the SC diet had consistently lower milk yields through 60
DIM although the differences were small. No differences were observed in milk fat yield
or content through 60 or 150 DIM (Tables 10 and 11). The differences in milk yield may
have been a result of differences in DMI in early lactation. Because of experimental
conditions, DMI was not measured in this study.

Treatment had no effect on milk protein content through either 60 or 150 DIM
(Table 10 and 11). No treatment differences were observed for protein yield through 60
DIM, but there was a tendency for a treatment by parity by time interaction through 150
DIM (P = 0.13; Figure 3). Additionally, parity 3+ cows fed the SC diet had higher
protein yields during the first 15 DIM compared with parity 3+ cows fed the NC diet.
Cows of parity 1 fed the NC had higher protein yields through 150 DIM compared with
parity 1 cows fed the SC diet (0.98 vs. 0.91 kg/d). The higher milk protein yield in parity
3+ cows during the first 15 d postpartum follows the trend in milk production. However,
it is unclear why primiparous cows fed the NC diet tended to have consistently higher
protein yields. Feeding more energy-dense diets toprimiparous cows for the last 170 d of
gestation had no effects on milk yield or composition (Grummer et al., 1995). Research
evaluating the effects of prepartum diets on primiparous cows is scanty and deserves
further attention.

There were no effects of treatment on ECM yields through 60 or 150 DIM (Table

12). There was no main effect of treatment on SCC, but there was a treatment by parity

27

interaction through 60 d (P = 0.01; Table 12 and Figure 4) and 150 d (P = 0.08; Table
12). The SCC of cows fed the SC diet decreased, and the SCC of cows fed the NC diet
increased as parity increased. High concentrations of somatic cells in the mammary gland
do not necessarily lead to increased incidences of mastitis (Erskine et al., 1988).

Therefore, it is difficult to interpret these findings.

Reproduction

Several cows were selected not to re-breed (n=12), or were culled (n=26) and not
included in analysis of reproductive measurements. Reproductive measurements are
shown in Table 13. Treatment had no effect on days to first service or pregnancy rate.
As mentioned, all cows were synchronized using Ovsynch® and targeted to breed at 70
DIM. Therefore, the similarity in days to first service is not surprising. There was no .
main effect of treatment on days open, but a treatment by parity interaction tended
towards significance (P = 0.08; Figure 5). Cows in their first and second parities fed the
SC diet had increased days open compared with cows of the same parities fed the NC
diet. Contrary to this, parity 3+ cows fed the SC diet had decreased days open compared
with parity 3+ cows fed the NC diet. It is unknown why treatment affected days open
differently between parities. However, the number of replications used to compare

interactions in reproductive measurements may be too low to draw conclusions.

CONCLUSIONS

With the exception of plasma concentrations of BHBA and insulin prepartum, the

effect of treatment was dependent upon parity. The SC diet tended to benefit cows in

28

their third or greater parity, but had no or negative effects on production responses of first
or second parity cows compared with the NC diet. Based on this study, parity should be
considered when recommending feeding programs for late gestation dairy cows.
However, interactions between parity and diets fed prepartum require further research

before specific recommendations can be derived.

29

TABLES AND FIGURES

Table 1. Formulath ingredient and analyzed chemical composition, and
particle size distribution of experimental diets fed in the late dry period.

 

 

Item NC1 SCr
Ingredient, % of DM

Corn silage 45.5 24.2
Alfalfa-grass mixed hay 16.6 16.6
Beet pulp, dehydrated 13.4 13.4
Corn, dry ground - 21.2
Custom mix2 15.4 15.4
Soybean meal 9.1 9.2
Chemical composition, %

DM 49.3 61.1
CP 15.8 16.2
ADF 26.2 22.6
NDF 39.3 34.9
BR 2.9 3.0
Ash 9.32 9.73
CP equivalent fi'om ammonia 2.43 2.15
NFC3 35.2 38.3
Ca 1.43 1.66

P 0.36 0.41
Mg 0.40 0.42
K 1.42 1.35
Na 0.18 0.22
Particle size4 (%)

> 19.0 mm 7.13:4.1 6.4i3.6
8.0 to 19.0 mm 47.6:57 32.5i4.9
< 8.0 mm 45.3:39 61.1;t3.9

 

—rT‘reatrnents: NC = no supplemental corn grain, SC = supplemental corn grain.
2Contained 19.9% CP, 2.8% fat, 7.21% Ca, 0.54% P, 1.4% Mg, 0.82% K, 0.67% Na,
5.9% CI, 2.6% S, 3.6% Se, 53 KIU/kg of Vitamin A, 11 KIU/kg of Vitamin D, and
528 IU/kg of Vitamin E, dry basis; mix included wheat middlings and soyhulls as
earners.
3NFC = 100 - % NDF - % CP + % CP equivalent from ammonia - % EE - % ash.
4Particle size determined by the Penn State Particle Separator (Lammers et al., 1996),

as-fed basis; mean 1: SD.

30

Table 2. Formulated ingredient and analyzed chemical composition, and particle
size distribution of diets fed postpartum.

 

 

Item Early lactationr Primiparous Multiparous
Corn silage 23.9 27.6 29.4
Alfalfa silage 8.9 9.6 9.6
Corn, high moisture 18.3 20.0 17.9
Corn grain 8.8 10.9 9.2
Corn distillers dried grains 5.9 11.3 11.0
Soybean meal 12.7 9.6 10.6
Custom mix2 5.6 5.7 5.2
Beet pulp, dehydrated 4.8 3.5 5.6
Alfalfa-grass mixed hay 8.8 - -
Wheat straw 2.3 1.9 1.6

Chemical composition, %

DM 56.7 52.4 51.6
CP 18.7 18.0 18.2
ADF 19.7 18.4 19.1
NDF 30.4 29.3 28.9
EE 3.4 3.9 4.0
Ash 8.1 8.5 8.0
CP equivalent from ammonia 0.93 1.05 1.06
NFC3 40.3 41.4 42.0
Ca 1.15 1.22 1.13
P 0.56 0.61 0.59
Mg 0.37 0.38 0.37
K 1.46 1.43 1.40
Na 0.65 0.66 0.56

Particle size‘ (%)
> 19.0 m 51:27 3.4i1.9 3.0:I:1.4
8.0 to 19.0 mm 36.5:3.1 39.0i3.4 41.3:t3.9
< 8.0 mm 58.4:2.6 57.6:t3.2 55.7:35

 

 

ICows of all parities were fed this diet for the first 17 DIM, approximately.
2Contained 23.3% CP, 0.5% fat, 12.4% Ca, 2.9% P, 2.8% Mg, 0.4% K, 8.9% Na,
11.0% CI, 1.7% S, 3 ppm of Co, 254 ppm of Cu, 1270 ppm of Fe, 13 ppm of I, 1016
ppm of Mn, 6 ppm Se, 152 KIU/kg of Vitamin A, 25 KIU/kg of Vitamin D, and 484
IU/kg of Vitamin E.

3NFC = 100 - % NDF - % CP + % CP equivalent from ammonia - % EE - % ash.
4Particle size determined by the Penn State Particle Separator (Lammers et al., 1996),
as fed basis; mean :I: SD.

31

Table 3. Formulated ingredient and chemical
composition of the diet fed in the early dry period.

 

 

Ingredient % of DM
Corn silage 35.0
Alfalfa silage 41.9
Beet pulp, dehydrated 20.7
Mineral mixl 2.4

Chemical composition, %

DM 40.9
CP 15.6
ADF 28.7

NDF' 43.2
EE 2.8
Ash 6.8
NPC2 31.7
Ca ' 1.03
P 0.32
Mg 0.34
K 1.52
Na 0.11

 

rContained 15.0% CP, 2.0% BR, 2.0% Ca, 0.2% P, 1.4 ppm of
Se, 14 KIU/kg of Vitamin A, 3.1 KIU/kg of Vitamin D, and
195 KIU/kg of Vitamin E.
2NFC=100-%NDF-%CP-%EE-%ash.

32

Table 4. Least squares means and statistical
significance of body condition scores (BCS)

 

 

during the periparturient period.

Variable BCS SEM
NCl 3.13 0.05
SC1 3.22 0.05
Parity 1 3.27 0.07
Parity 2 3.11 0.06
Parity 3+ 3.14 0.05

Time, d relative to

Parturition
-14 3.56 0.04
-7 3.55 0.04
2 3.38 0.04
21 2.69 0.04
42 2.69 0.04

P-value
Treatment 0.16
Parity 0.18
Time < 0.01
Parity‘time < 0.01

 

1Treatments: NC = no supplemental corn grain,
SC = supplemental corn grain.

33

Table 5. Least squares means and statistical significance of body condition score changes
during the periparturient period.

 

 

 

Weeks postpartum
Variable Prepartum SEM O to 6 SEM 0 to 3 SEM 3 to 6 SEM
NCl 0.03 0.03 -0.84 0.06 -0.84 0.05 0.01 0.04
SC1 0.00 0.03 -0.88 0.06 -0.90 0.05 0.03 0.04
Parity 1 -0.01 0.04 -0.92 0.08 -0.90 0.08 -0.02 0.06
Parity 2 .4101 0.03 -0.63 0.07 -0.74 0.07 0.14 0.05
Parity 3+ 0.06 0.03 -1.03 0.06 -0.97 0.06 -0.06 0.04
NC*parity l 0.06 0.05
NC*parity 2 -0.05 0.05
NC*parity 3+ 0.08 0.04
SC*parity 1 -0.08 0.06
SC*parity 2 0.03 0.05
SC*parity 3+ 0.03 0.04
P-value2
Treatment (Trt) 0.40 0.60 0.38 0.85
Parity 0.22 < 0.01 0.04 0.01
Trt*parity 0.09 RM2 RM RM

 

lTreatments: NC = no supplemental corn grain; SC = supplemental corn grain.
2Independent variables were removed (RM) from the statistical model if P > 0.15.

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40

Table 12. Least squares means and significance of energy-corrected milk
(ECM) and SCC through 60 or 150 DIM.

 

 

 

 

ECM 95% confidence
yield SCC interval
Variable (kg/d) SEM (cells/ml) Lower Upper
0 to 60 DIM
NCl 42.6 1.3 104,708 79,674 137,613
sc‘ 43.6 1.3 93,517 70,983 123,204
Parity 1 30.5 1.8 96,929 65,736 142,929
Parity 2 47.9 1.6 93,591 67,501 129,768
Parity 3+ 50.9 1.4 106,810 80,330 142,017
Time, d
relative to
parturition
15 39.4 1.6 184,702 131,268 259,886
30 44.6 1.2 99,983 73,109 136,735
45 44.5 1.1 72,558 53,982 97,529
60 43.8 1.1 71,557 52,607 97,334
P-value2
Treatment (Trt) 0.59 0.57
Parity < 0.01 0.82
Time < 0.01 < 0.01
Trt*parity RM3 0.014
0 to 150 DIM
NC 42.8 0.9 79,348 63,380 99,340
SC 42.9 0.9 80,465 64,094 101,023
Parity 1 33.8 1.4 76,672 55,843 105,272
Parity2 45.2 1.2 77,304 59,101 101,114
Parity 3+ 49.5 1.0 86,074 68,125 108,749
Time5
P-value
Trt 0.96 0.93
Parity < 0.01 0.78
Time < 0.01 < 0.01
Trt‘parity RM 0.08
Parity*time . < 0.01 RM

 

lTreatments: NC = no supplemental corn grain; SC = supplemental corn grain.
2All 2- and 3-way interactions not shown were removed from the statistical

model (P > 0.15).
3 Independent variables were removed (RM) from the statistical model if P > 0.15.

4See Figure 4.
5Time not show

41

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11- [INC
10. .80 1

 

BHBA (mg/(ll)
\l

   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-14 -11 -8 -5 -2 2
Days relative to parturition

Figure 1. Least squares means and 95% confidence intervals for the interaction of
treatment by time (P = 0.02) on plasma BHBA concentrations in the periparturient
period. Other significant variables in the model included: treatment (P = 0.07), parity (P

14

=0.07), time (P < 0.01), and parity by time (P < 0.01). Treatments: NC = no

supplemental corn grain; SC = supplemental corn grain.

43

 

 

—C1—Parity 1 (NC) -n— Parity 1 (SC)

 

 

 

 

 

 

 

  

 

 

 

—<>— Parity 2 (NC) — 4 — Parity 2 (SC)
—A—— Parity 3+ (NC) - ~A — Parity 3+ (SC)
50
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c
E 35 .1.
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g 30 4.. “““““““““
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25 -- Pooled SEM = 1.9
20 T f I
15 30 45 60
Days postpartum

Figure 2. Least squares means and standard error of the means for the interaction of
treatment by parity by time (P = 0.10) for milk production during the first 60 DIM. Other
significant variables in the model included: Parity (P < 0.01), time (P < 0.01), and parity
by time (P = 0.03). Days postpartum on the x-axis represent an average of the previous
15 d. Treatments: NC = no supplemental corn grain; SC = supplemental corn grain.

 

—Cl—Parity 1 (NC) - a -Parity 1 (SC)
+ Parity 2 (NC) - -o - ~ Parity 2 (SC)
—<>— Parity 3+ (NC) — -& — Parity 3+ (SC)

 

 

 

 

 

 

 

 

3

E

.2

>‘o

.E

8

O

i-

n.
0.7 , .3” Pooled SEM=0.05
0.6 . . . . . T r I I I

15 30 45 60 75 90 105 120 135 150
Days postpartum

Figure 3. Least squares means and standard error of the means for the interaction of
treatment by parity by time (P = 0.13) for protein yield through 150 DIM. Other
significant variables in the model included: parity (P < 0.01), time (P < 0.01), and parity
by time (P < 0.01). Days postpartum on the x-axis represent an average of the previous
15 d. Treatments: NC = no supplemental corn grain; SC = supplemental corn grain.

45

275,000
250,000 1 -- UNC
225,000 . I
200,000 . 1'
175,000 4
150,000 .
125,000 4 "
100,000 .
75,000 .
50,000 .
25,000

 

 

 

 

 

 

SCC (cells/ml)

 

 

 

 

 

 

 

 

 

   

 

 

 

 

 

1 2
Parity

Figure 4. Least squares means and 95% confidence intervals for the interaction of .
treatment by parity (P = 0.01) for somatic cell count through 60 DIM. The only other
significant variable in the model was time (P < 0.01). Treatments: NC = no supplemental
corn grain; SC = supplemental corn grain.

46

130

 

 

DNC

120 _
.SC

 

 

 

110 -
100 _
90 .

Days open

804
70.

 

 

 

 

 

 

60

 

 

Parity

Figure 5. Least squares means and standard error of the means for interaction of
treatment by parity (P = 0.08) on days open. There were no other Significant effects in
the model. Treatments: NC = no supplemental corn grain; SC = supplemental corn grain.

47

CHAPTER 4

PERIPARTUM RESPONSES OF DAIRY COWS TO ALTERING LENGTH OF

THE LATE DRY PERIOD

ABSTRACT

One hundred eighty-nine cows in two commercial dairy farms were assigned
randomly to enter the late dry period at either 3 or 6 wk prepartum. During this time,
cows were fed diets with increased nutrient and energy densities compared with diets fed
earlier in the dry period. Cows in the late dry period S 26 d were designated Short late
dry period (S) and those in the late dry period > 26 d were the long late dry period (L).
Cows in L tended to gain more body condition during the late dry period. Treatment L
improved energy status of cows during the first 2 wk postpartum as indicated by a trend
towards lower plasma non-esterified fatty acid and higher insulin concentrations
postpartum, and reduced BCS loss during the first 3 wk postpartum. Cows in L had
higher milk protein content through 60 DIM, but tended to have lower milk fat content
and yield through 150 DIM. In Farm 1, cows in L lost more body condition from 3 to 6
wk postpartum, had a higher incidence rate of metritis and a longer interval to first
service. Additionally, cows in L in Farm 1 produced less milk and had higher somatic
cell counts through 150 DIM. Increasing the length of time cows were in the late dry
group elicited profound changes in Farm 1, but had little effect in Farm 2. Based on
these results, the L treatment may improve energy status immediately postpartum, but

long-term efl‘ects varied between farms, likely due to management differences.

48

INTRODUCTION

The late dry period is the time prior to calving when often dairy cows are fed and
managed differently than cows earlier in the dry period. It is common for cows to be fed
diets with increased concentrations of energy, protein, and certain vitamins and minerals
during the late dry period. The purpose of feeding dry cows differently during the last
few weeks of gestation is to help meet the physiological changes occurring at this time.
During the last few weeks of gestation, an accelerated decrease in DMI (Bertics et al.,
1992) coincides with increasing energy requirements for conceptus growth (Bell, 1995)
and lactogenesis (Davis et al., 1979). Cows may mobilize body stores during the late dry
period in an attempt to compensate for the inadequate energy intake. Excess mobilization
of body stores prepartum may predispose cows to several health disorders (Dyk et al.,
1995)

The practice of partially substituting concentrates for lower energy forages is a
method to increase energy density of diets and help minimize declining or negative
energy status of dairy cows in the late dry period. Additionally, increased amounts of
concentrates help ruminal microbial populations adapt to a more fermentable diet that is
typically fed in early lactation, and promotes ruminal papillae development (Goff and
Horst, 1998). Dirksen et al. (1985) showed that feeding increasing amounts of grain to
cows increased ruminal papillae growth and VFA absorption. However, ruminal
papillae did not reach maximum size until 5 to 6 wk after initiation of the high energy
diet. In support of this concept, recent research showed that feeding a diet containing
43.5% corn grain to non-pregnant, non-lactating dairy cows caused ruminal papillae to

grow (Xu and Allen, 1998). The size of ruminal papillae increased linearly over the 28 d

49

cows were sampled. Therefore, cows may benefit from a higher energy diet for longer
than the traditional 2 to 3 wk late dry period to achieve maximal papillae size and to
improve energy status at parturition and early lactation.

Feeding a higher energy diet to dry cows for a longer period of time also may
promote body condition gain. Higher producing cows have more difficulty replenishing
body reserves in late gestation than lower producing cows (Wildman et al., 1982). If
body condition is inadequate at dry-off, increasing body condition to recommendations
during the dry period may improve postpartum performance. Increasing body condition
during the dry period has resulted in improved milk yields (Boisclair et al., 1986). Yet,
other studies showed no benefits of promoting body condition gain during the dry period
(Jones and Gamsworthy, 1989; Gamsworthy and Huggett, 1992; Gamsworthy and Jones,
1987). However, these experiments evaluated the effects of over-conditioning dry cows.
No studies have evaluated the optimal length of time the late dry diet should be fed.

The objective of this experiment was to determine the effects of altering the
length of the late dry period on body condition, periparturient health and energy status,

and postpartum production and reproduction of dairy cows.

MATERIALS AND METHODS
Cows and Treatments
One hundred eighty-nine cows in two commercial dairy farms were completely
randomized and assigned to enter the late dry period at either 3 or 6 wk prepartum.
Retrospectively, cows were assigned to treatment based on how many days they spent in

the late dry period (Table 1). Cows in the late dry period 5 26 d were designated short

50

late dry period (S) and cows in the late dry group longer than 26 d were designated long
late dry period (L). Means and standard deviations for days spent in the late dry group
were calculated for each treatment group and seven cows lying outside two standard
deviations were removed from the study. There were 43 first parity, 63 second parity,
and 83 third or greater parity cows in the experiment (Table 1). All cows within farms
were housed together and were fed the same diets prepartum (Table 2) and were grouped
as primiparous or multiparous after calving and fed accordingly (Tables 3 and 4).
Additionally, cows in Farm 2 were grouped and fed separately during the first 2 to 3 wk

of lactation (early lactation group; Table 4).

Sample Collection and Analysis

Silage dry matter was determined weekly using a Koster Tester (Koster Crop
Tester, Inc., Medina, OH) and adjustments were made to maintain the same diet
composition, dry basis. TMR were sampled weekly through 150 DIM and dried at 550 C
for 72 h for future analysis. Particle size distribution of TMR samples, as-fed basis, was
determined using the Penn State Particle Separator (Nasco, Fort Atkinson, WI; Lammers
et al., 1996). Feed samples were ground through a Wiley mill (1 mm screen, Authur H.
Thomas, Philadelphia , PA) and composited monthly. Samples were analyzed for NDF,
ADF, CP, ether extract (EE), ash, ammonia and minerals (Northeast DHI Forage
Laboratory, Ithaca, NY).

One evaluator scored cows for BCS [five-point scale where 1 = thin to 5 = fat;

(Wildman et al., 1982)] weekly prepartum, at calving, and 3 and 6 wk postpartum.

51

Additionally, one evaluator assigned udder edema scores (0 = none , 1 = mild, 2 =
moderate, and 3 = severe) within 3 d following parturition.

Blood samples were collected in evacuated test tubes containing sodium heparin
(V acutainer; Becton Dickson Vacutainer Systems USA, Rutherford, NJ) from the
eoccygeal vessels twice weekly prior to parturition, within 3 d following parturition, and
1 and 2 wk postpartum. Blood samples were collected at approximately 20 h after
feeding in Farm 1 and about 7 h after feeding in Farm 2. Samples were stored on ice
during transport to the laboratory. Upon arrival they were centrifuged and plasma was
stored at -4°C until later analysis of NEFA (NEFA-C kit, Waco Chemicals USA,
Richmond, VA) with modifications (Johnson and Peters, 1993), insulin (Coat-A-Count,
Diagnostic Products Corporation, Los Angeles, CA), and BHBA (310-A, Sigma
Diagnostics, St. Louis, MO). All reagents in the BHBA assay except beta-
hydroxybutyrate dehydrogenase were reduced proportionally to fit into 350 ul wells of
cell culture plates. Beta-hydroxybutyrate dehydrogenase was added at twice the reduced
dose to shorten the incubation time. Inter-assay and intra-assay coefficients of variation
for BHBA, NEFA and insulin were 5.9 and 7.1, 6.9 and 8.4, and 4.4 and 7.0,
respectively.

Herdspersons and veterinarians were responsible for recording incidences of
health disorders and reproductive measurements throughout the experiment. Health
disorders are defined as the following: displaced abomasum was an abnormal location of
the abomasum diagnosed by percussion that required corrective surgery;
ketosis was a positive urine ketone body test of moderate or greater (Ketostix; Bayer

Corp., Elkhart, IN); mastitis was an abnormal stripping or inflammation of the udder

52

which required treatment; retained placenta was fetal membranes retained for greater than
24 h after parturition; and, metritis was diagnosed as an uterine infection which required
treatment.

Farm 2 had an intensive milk fever prevention protocol. All third parity cows
received an oral bottle of CMPK (10.8 g Ca, 75 g dextrose; Jice Pharmaceuticals Co.,
Lowell, MI) immediately following parturition. All fourth parity cows, or any cows
having twins, received a bottle of CMPK orally plus 500 ml of Calnate (10.7 g Ca; The
Butler Co., Columbus, OH) subcutaneously. In addition, Farm 2 measured rectal
temperatures on all cows daily through 12 DIM. For analysis, cows having a rectal
temperature above 39.4° C for at least 1 d during the first 12 DIM were considered
abnormal. In Farm 1, milk weights were collected monthly and were analyzed for fat and
protein content and SCC every three months (Michigan DHIA). Daily milk weights
through 150 DIM also were recorded on Farm 1. In Farm 2, individual milk weights
were recorded every 2 wk and samples were analyzed for fat and protein content and
SCC monthly (Michigan DHIA). Energy-corrected milk was calculated from the
equation ECM (lb) = 0.3246 x milk yield (lb) + 12.86 x fat yield (lb) + 7.04 x protein
yield (lb; Dairy Herd Improvement Glossary, Fact Sheet A-4, 1999). Both farms used
bST (Monsanto Co., St. Louis, MO) during the experiment. All cows received bST at
100 DIM in Farm 1 and remained on bST throughout the sampling periods. The
voluritary waiting period for bST administration on Farm 2 was 63 and 90 d for
multiparous and primiparous cows, respectively. Cows received bST unless BCS was

less than 2.5 or milk yield was greater than 40 kg/d for primiparous cows and 50 kg/d for

53

multiparous cows. Over 60% of the cows in each treatment in Farm 2 received bST
during the sampling periods.

Days open, days to first service, pregnancy rate and percentage of cows pregnant
by 200 DIM were recorded in each farm. All analyses of reproductive variables were
based on cows that had been confirmed pregnant by 200 DIM. The voluntary waiting
period was 55 d on Farm 1 and 70 days on Farm 2. Farm 2 used the Ovsynch® protocol
(Pursley et al., 1996)'to synchronize breeding for all cows on the experiment. Several
cows in Farm 1 were exposed to a bull for natural service and were removed from '

analysis of reproductive measurements.

Statistical Analysis

All blood and SCC data were log transformed to correct for heterogeneity of
variance. Milk production data fiom DHIA in both farms were reduced to monthly
means for analysis. Additionally, in Farm 1, daily milk weights were available for
analysis. These data were reduced to weekly means for subsequent analysis. Milk
production and blood measurements were analde as repeated measures using the PROC
MIXED procedure of SAS [version 6.1; SAS (1989)]. The statistical model for milk and
blood data included the fixed effects of treatment, parity, farm, time, two- and three-way
interaction terms of all fixed effects, the random effect of cow nested within treatment
and farm, and the residual error. Blood measurements were analyzed and reported for the
prepartum or postpartum periods separately, or across both periods (periparturient
period). Udder edema, BCS changes, days open, days to first service, and pregnancy rate

were analyzed using PROC MIXED procedure of SAS [version 6.1; SAS (1989)] with

54

farm, parity, treatment and all two- and three-way interaction terms, and the residual
error. Incidences of health disorders and percentage of cows pregnant by 200 DIM were
analyzed using the PROC GENMOD procedure of SAS [version 6.1; SAS (1989)] and
differences were determined by chi-square tests. For all models, non-significant
variables (P > 0.15) were removed in a backwards stepwise manner. Least squares
means could not be generated for BCS if treatment was in the model because treatment
was confounded in time. For cows in L, BCS were recorded before 3 wk prepartum.
However, cows in S only had BCS data during the last 3 wk prepartum and had no values
prior to this time. Therefore, a separate model was used for analysis each treatment to
generate least squares means. The model included the fixed main effects of farm, parity,
time, the random effect of cow, and the residual error. Differences between treatments
for all models were determined by F-test. Least squares means and standard error of the
means are reported for all data except blood and SCC measurements. Because of the
transformations to remove heterogeneity, 95 % confidence intervals are reported instead
of standard error of the means for blood and SCC data. Statistical significance was

declared at P < 0.05, and tendency towards significance at P > 0.05 to P < 0.15.

RESULTS AND DISCUSSION

Diet Composition

Chemical compositions of diets fed pre- and postpartum in both farms are
presented in Tables 2, 3, and 4. The diets fed prepartum varied in ingredient composition
between farms, but the analyzed chemical compositions were similar. Overall, particle

size was larger in the diet fed prepartum in Farm 1 because of a larger inclusion of hay

55

and the corn fed in Farm 2 was finely ground. Chemical composition of diets fed
postpartum was similar between primi- and multiparous groups within and between farms
(Tables 3 and 4). The exception is the inclusion of whole cottonseed that increased the
EB concentration of diets in Farm 1. Additionally, the ingredient composition of the diets
fed during the early dry period prior to the treatment diets is shown in Table 5. Diets fed
during this time could potentially affect papillae development and ruminal microbial
adaptation. However, diets fed during the early dry period were similar in chemical

composition.

Body Condition and Udder Edema

Cows entered the late dry group with similar BCS regardless of treatment (Table
6). Cows in S and L gained 0.08 and 0.14 BCS units, respectively in the late dry group
(Table 7). An objective of this study was to determine if lengthening the late dry period
would increase BCS. The difference of body condition gain in the late dry group
between treatments of 0.06 BCS units tended towards significance (P = 0.14). Parity had
a strong influence on body condition gain (Table 7). Cows entering their second lactation
gained more body condition during the late dry period than cows of parity 1 or 3+. Cows
entering their third or greater parity did not gain substantial BCS during the late dry
period (0.01 and 0.02 BCS units in Farm 1 and 2, respectively). Cows of parity 2 entered
the late dry period with the lowest BCS of any parity (3.70, 3.40, 3.60 for parity 1, 2 and
3+, respectively; data not shown). A review of several studies measuring DMI of
periparturient cows reported increased DMI of cows with lower BCS (Hayirli, 1998).

This may partially explain the differences in BCS gain observed in the late dry period.

56

There were no significant differences between treatments in total BCS loss during
the first 6 wk of lactation (Table 7). However, cows in S lost more BCS during the first 3
wk postpartum compared with cows in L (-1.15 vs. —0.95; P < 0.01). In contrast, cows in
L tended to lose more BCS from 3 to 6 wk postpartum compared with cows in S (-0.13
vs. -0.27; P = 0.06). A tendency towards a farm by treatment interaction (P = 0.13) for
BCS change from 3 to 6 wk was observed. In Farm 1, cows in L lost more BCS from 3
to 6 wk postpartum than cows in S (-0.33 vs. -0.08). Treatment had no effect on BCS
change in Farm 2 (-0.18 vs.-0.21 for S and L, respectively). Based on BCS changes,
cows in S appeared to be in poorer energy status during the first 3 wk postpartum in both
farms. At 6 wk postpartum, cows in S appeared to be closer to positive energy status
compared with cows in L in Farm 1 or in similar energy status with L in Farm 2 as
indicated by BCS changes from 3 to 6 wk (Table 7). Several studies have shown
increased BCS losses in early lactation if BCS is high at parturition ( Gamsworthy and
Jones, 1987; Gamsworthy and Topps, 1982; Pedron et al., 1993; Smith et al., 1997;
Treacher et al., 1986).

There were no treatment effects on udder edema scores (P = 0.70; data not
shown). Parity did influence the severity of udder edema. Cows in their first parity had
higher udder edema scores (1.6; P = 0.05) than cows in their second parity (1.4) or third

and greater parities (1.3).

Metabolic Variables
Plasma NEF A concentrations for the prepartum, postpartum and periparturient

‘ (both pre- and postpartum) periods are shown in Table 8. There were no treatment

57

differences in plasma NEFA concentrations during the prepartum or periparturient
periods. Plasma NEFA concentrations in the postpartum period tended to be higher for
cows in S compared with cows in L (542.4 vs. 487.1 qu/L; P = 0.15). Plasma NEFA
concentrations coincide with BCS data that showed a reduced BCS loss of cows in L
during the first 3 wk posparturn. One hypothesis of this experiment was that increasing
the time spent in the late dry group may improve energy status in early lactation. This
hypothesis is supported partially by the lower BCS loss and tendency toward lower
plasma NEF A of cows in L during the first 3 wk of lactation compared with cows in S.
For both treatments, plasma NEFA concentrations showed an accelerated increase as
parturition approached, peaked at 2 (1 (629.4 qu/L) and slowly declined at 7 and 14 d
postpartum-

There was no effect of treatment on plasma BHBA concentrations during the I
prepartum, postpartum or periparturient periods (Table 9). Concentrations of BHBA
increased gradually to peak values (9.24 mg/dl) at 7 d postpartum and declined by 14 d.
Similar plasma BHBA concentrations between treatments suggest that treatment had no
effect on hepatic lipid metabolism during the periparturient period.

Plasma insulin concentrations are shown in Table 10. There was a significant
treatment by time interaction (P = 0.03) on plasma insulin across the periparturient period
(Figure l). Insulin concentrations of cows in L were lower prepartum and higher
postpartum compared with cows in S. Although plasma insulin concentrations were
numerically different between S and L (11.66 vs. 10.48 uIU/ml, respectively) in the
prepartum period they were not significantly different (P = 0.28). Large variations in the

insulin concentrations prepartum may have precluded detecting a statistical difference.

58

However, there was a tendency for a treatment by parity by farm interaction during the
prepartum period (P = 0.13; Figure 2). In parity 1, L increased plasma insulin
concentrations in farm 1, but decreased insulin in farm 2. L decreased insulin in cows of
parities 2 and 3+ in a similar manor compared with S. Cows in L tended to have higher
plasma insulin concentrations postpartum compared with cows in S (7.19 vs. 6.46
uIU/ml; P = 0.12). Additionally, a parity by treatment by time interaction tended toward
significance (P = 0.07) in the postpartum period (Figure 3). Plasma insulin
concentrations of primiparous cows in S decreased over the first 2 wk postpartum, but
plasma insulin of primiparous cows in L increased during the same period. Plasma
insulin concentrations of cows in parities 2 and 3+ followed similar patterns during the
first 2 wk postpartum for both treatments. Lower plasma insulin concentrations
postpartum for cows in S coincide with increased BCS losses during the first 3 wk and
the tendency for higher plasma NEFA during the first 2 wk after parturition compared
with cows in L. Feeding high concentrations of energy prepartum has been hypothesized
to induce insulin resistance postpartum, thereby elevating plasma insulin (Holtenius,
1993). Feeding a higher energy diet for a longer period of time prepartum could firrther
exacerbate insulin resistance. Cows in L were fed a higher energy diet for an additional
17 d on average compared with cows in S and potentially could be at an increased risk of
insulin resistance. Yet, adipose tissue of cows in L may have been more sensitive to

insulin as noted by the reduction in plasma NEFA concentrations.

Health Disorders

59

Incidence rates of health disorders are shown in Table 11. The incidence rate of
milk fever was recorded, but not reported because of the low incidence rate. Farm 1
reported two cases and Farm 2 had no clinical cases of milk fever. Cases of metritis were
not recorded in Farm 2. In addition, Farm 1 did not measure rectal temperatures. The
only significant effect of treatment was on metritis incidence in Farm 1. Cows in L had
an increased incidence rate (12.9 vs. 6.3; P = 0.06) of metritis compared with cows in S.
Ten cases of metritis were reported for L and only two for S. It is surprising that cows in
apparently more negative energy status (i.e., treatment S) during the first few weeks
postpartum had a lower incidence. rate of metritis. Several studies have reported non-j
significant increases in the incidence of health disorders when cows gained appreciable
BCS during the dry period (Fronk et al., 1980; Keys et al., 1983; Treacher et al., 1986).
However, these studies reported effects of gaining body condition well in excess of the

present study.

Milk Yield, Composition and Somatic Cell Count

Milk yield and composition for 60 and 150 DIM are shown in Tables 12 and 13,
respectively. Treatment had no effect on milk production during the first 60 DIM.
Through 150 DIM, cows in the S tended to produce more milk compared with cows in L
(41.4 vs. 39.2 kg/d; P = 0.06). However, effects of treatment are only evident in Farm 1
as indicated by the tendency towards a farm by treatment interaction (P = 0.06; Figure 4).
Cows in Farm 1 in S produced 43.2 kg/d, whereas cows in L produced only 38.8 kg/d. In
Farm 2, there was no difference in milk yield between treatments with both groups

producing 39.5 kg/d through 150 DIM. The daily milk yields reported in Farm 1 also

60

support the effect of treatment on milk production (Table 14). Cows in S in Farm 1
tended to have greater milk yields through 56 DIM compared with cows in L (P = 0.12).
Through 150 DIM, milk yields were greater for cows in S in Farm 1 compared with cows
in L (42.0 vs. 36.6 kg/d; P = 0.03). Differences in management practices between farms
may have influenced effects of treatment on milk production.

Treatment had no significant effect on milk fat content through 60 d (P = 0.47;
Table 12), but milk fat content of cows in S tended to be higher compared with cows in L
through 150 DIM (P = 0.15; Table 13). Because of higher milk production and
numerically higher milk fat content, cows in S tended to have higher fat yields through
150 DIM than cows in S (1.62 vs. 1.52 kg/d; P = 0.11). No differences in fat yield
between treatments were detected during the first 60 DIM. NEFA can be used as
substrates for endogenous fatty acids synthesis in the mammary gland. Cows in S had
higher plasma NEFA concentrations during the first 2 wk of lactation compared with
cows in L. NEFA were measured only during the first 2 wk postpartum, but higher
plasma NEF A concentrations may have persisted into lactation for cows in S and caused
the higher milk fat content and yield.

Cows in L had higher protein content compared with cows in S through 60 DIM
(P < 0.01), but not through 150 DIM. Parity by treatment (P = 0.07) and treatment by
time (P < 0.01) interactions for the analysis for milk protein content through 60 DIM are
shown in Figures 5 and 6, respectively. These interactions Show that L increased milk
protein content the most in cows of parities 1 and 2, and in the first month of lactation.
Additionally, there was a parity by treatment by time interaction on milk protein

percentage through 150 DIM (P = 0.03; Figure 7). Cows of all parities in S followed

61

similar patterns of milk protein percentages through 150 DIM. In the first test month,
protein percentages were higher for all parities in L compared with those in S. Within the
L treatment, cows in parity 3+ had lower protein content compared with parity 1 and 2
cows through 5 mo of lactation with the exception of month 4. Although protein
percentage was lower for all cows in month 4, the decline was less severe for cows of
parity 3+. There was a significant interaction of treatment by time on milk protein yield
through 150 DIM (P‘< 0.01; Figure 8). The pattern of milk protein yield over time
mirrored that of milk protein percentage. Cows in L had appreciably higher protein
yields during the first month and lower yields during mo 4 than cows in S. Interestingly,
cows in L had higher protein content during the first month of lactation compared with
cows in S. In addition, the tendency towards higher insulin and lower NEFA in early
lactation for cows in L indicates improved energy status. Improved energy status may
reduce the amount of amino acids used for glucogenesis thereby allowing more substrate
to be available for milk protein synthesis in the first month postpartum (McGuire et al.,
1995). Furthermore, consuming a higher energy diet for a longer time may have better
prepared the rumen environment for the early lactation ration and thus, maximized
microbial protein yield.

There were no significant effects of treatment on ECM yield through 60 or 150
DIM (Tables 15 and 16). Treatment had no effect on SCC through 60 DIM, but cows in
S had lower SCC (49,258 vs. 80,505 cells/ml; P = 0.04) compared with cows in L
through 150 DIM (Table 16). Figure 9 illustrates the treatment by farm interaction (P <
0.01) for SCC analyzed through 150 DIM. In Farm 1, cows in S had greatly reduced

SCC compared with cows in L (29,790 vs. 96,586 cells/ml). In Farm 2, cows in S had

62

slightly higher SCC than cows in L (81,479 vs. 67,119 cells/ml). Although the number of
mastitis incidences were low and not significantly different, 5 cases of mastitis were

reported for cows in L in Farm 1 compared with only 2 cases for cows in S in Farm 1.

Reproduction

Several cows were sold or died (11 = 26), selected not to rebreed (n = 10) or were
exposed to a bull (n = 21; Farm 1 only) and therefore were removed from the analysis of
reproductive measurements. There were 99 cows remaining for analysis plus and
additional 33 which were not pregnant by 200 DIM.

All reproductive measurements are shown in Table 17. Cows in S had fewer days
to first service than cows in L (73 vs. 66; P = 0.04). However, the trend towards an
interaction of farm by treatment indicated that the effect of treatment was only in Farm
1(P = 0.06; Figure 10). In Farm 1, cows in L had longer days to first service than cows in
S (74 vs. 61 d). No differences due to treatment were detected in Farm 2 (71 vs. 71 d). It
is not surprising that no changes in days to first service were found in Farm 2 because all
cows were synchronized and bred using the Ovsynch® protocol. Again, DMI could be
postulated to affect days to first service in Farm 1. Cows in more negative energy status
or cows in negative energy status for a longer time have delayed return to ovarian activity
and estrous cycles (Butler and Smith, 1989; Staples et al., 1990). The shorter days to first
service for cows in S in F arm 1 would agree with the theory that reduced BCS losses
fiom 3 to 6 wk pospartum and increased milk yields are a result of improved DMI. There
were no significant effects of treatment on days open, pregnancy rate, or percentage of

cows pregnant by 200 DIM.

63

CONCLUSIONS

Extending the time spent in the late dry group slightly improved BCS of late
gestation dairy cows, but did not promote the large changes observed in previous
research. Cows may have gained BCS more readily if BCS at dry-off were lower than
the current study. In agreement with the hypothesis, cows in L apparently had improved
energy status postpartum as indicated by a tendency towards lower plasma NEFA and
higher insulin concentrations and a less severe BCS loss from parturition to 3 wk
postpartum. However, effects on production, health, and reproduction were dependent
upon farm. Cows in Farm 1 had lower milk yields, poorer health and reproduction, but
treatment had no effect on the same variables measured in Farm 2. Differences in
management between farms, or nutrition at other stages of the production cycle need to

be considered when evaluating effects of diets fed in the late dry period.

TABLES AND FIGURES

Table 1. Days spent in the late dry group
and allocation of cows to treatments.

 

 

S1 L'
Days
Mean 17.5 36.6
SD 4.1 6.9
Minimum 6 27
Maximum 26 60
n
Farm 1 23 54
Parity 1 9 9
Parity 2 6 19
Parity 3+ 8 26
Farm 2 70 42
Parity 1 15 10
Parity 2 26 12
Parity 3+ 29 20
Total 93 96

 

ITreatments: S = short late dry period; L =
long late dry period.

65

Table 2. Formulated ingredient and analyzed chemical composition, and particle size
distribution of diets fed in the late dry period.

 

 

Item Farm 1 Farm 2
Ingredient, % of DM

Corn silage 22.1 32.5
Alfalfa silage 8.5 -
Alfalfa-grass mixed hay 14.9 9.3
Beet pulp, dehydrated - 13.4
Corn, high moisture 21.3 -
Corn, dry ground - 18.6
Corn distillers grains 2.2 -
Cottonseed, whole 6.2 -
Soybean meal - 9.8
Mineral mix 24.31 16.42
Chemical composition, %

DM 50.6 55.2
CP 17.4 16.7
ADF 18.8 20.4
NDF 29.3 32.0
BE 4.8 2.6
Ash 7.9 8.6
CP equivalent fiom ammonia 1.7 1.9
NFC3 42.4 42.0
Ca 1.13 1.60

P 0.47 0.37
Mg 0.36 0.45
K 1.17 1.14
Na 0.13 0.21
Particle size4 (%)

> 19.0 m 80:66 3.15:1.7
8.0 to 19.0 mm 47.1:t8.1 36.8:t4.0
< 8.0 mm 44.9:t12.5 60.8143

 

IContained 27.0% CP, 3.7% lipid, 2.47% Ca, 0.51% P, 0.79% Mg, 0.75% K, 0.26% Na,
1.8% CI, 1.07% S, 1 ppm Co, 144 ppm Cu, 449 ppm Fe, 5 ppm I, 360 ppm Mn, 3 ppm
Se, 360 ppm Zn, 38 KIU/kg of Vitamin A, 7 KlU/kg of Vitamin D, and 308 IU/kg of
Vitamin E, dry basis.

2Contained 13.7% CP, 2.6% lipid, 3.31% Ca, 0.51% P, 0.40% Mg, 0.69% K, 0.51% Na,
.31% CI, 2.4% S, 1 ppm Co, 40 ppm Cu, 201 ppm Fe, 2 ppm 1, 161 ppm Mn, 2 ppm Se,
161 ppm Zn, 10 KIU/kg of Vitamin A, 2 KIU/kg of Vitamin D, and 110 IU/kg of
Vitamin E, dry basis.

3NFC = 100 - % NDF - % CP + % CP equivalent from ammonia - % BE - % ash.
,4Particle size determined by the Penn State Particle Separator (Lammers et al., 1996), as-
fed basis; mean i SD.

66

Table 3. Formulated ingredient and analyzed chemical composition, and particle size
distribution of diets fed postpartum in Farm 1.

 

 

Item Primiparous Multiparous
Ingredient, % of DM

Corn silage 22.0 23.7
Alfalfa silage 5.9 4.8
Corn, high moisture 29.0 28.9
Corn distillers grains, dry 10.9 10.6
Custom mixl 10.6 10.3
Alfalfa hay 6.6 5.4
Soybean meal 5.5 6.3
Cottonseed, whole 7.8 7.8
Chemical composition, %

DM 54.3 54.4
CP 18.8 18.8
ADF 18.8 18.4
NDF 30.8 29.2
EE 6.0 5.5
Ash 7.7 7.4
CP equivalent from ammonia 0.87 0.88
NFC2 37.6 40.0
Ca 1.11 1.10

P 0.56 0.58
Mg 0.30 0.31

K 1.33 1.30
Na 0.42 0.40
Particle size3 (%)

> 19.0 m 83:42 7.1:1-25
8.0 to 19.0 mm 42313.1 44032.9
< 8.0 mm 49.3:38 48.9:33

 

IContained 36.2% CP, 10.2% lipid, 5.60% Ca, 1.48% P, 0.89% Mg, 1.21% K, 3.06% Na,
1.55% Cl, 0.60% S, 1.76 ppm Co, 97 ppm Cu, 809 ppm Fe, 5.6 ppm 1, 398 ppm Mn, 3.5
ppm Se, 444 ppm Zn, 25 KIU/kg of Vitamin A, 5 KIU/kg of Vitamin D, and 161 IU/kg
of Vitamin E, dry basis.

2NFC = 100 - % NDF - % CP + % CP equivalent from ammonia - % EE - % ash.

3 Particle size determined by the Penn State Particle Separator (Lammers et al., 1996), as-
fed basis; means 3: SD.

67

Table 4. Formulated ingredient and analyzed nutrient composition, and particle size of
diets fed postpartum in Farm 2.

 

 

Item Early lactationI Primiparous Multiparous
Ingredient, % of DM

Corn silage 23.9 27.6 29.4
Alfalfa silage 8.9 9.6 9.6
Alfalfa-grass mixed hay 8.8 - -
Corn, high moisture 18.3 20.0 17.9
Corn, dry ground 8.8 10.9 9.2
Corn distillers grains 5.9 11.3 11.0
Soybean meal 12.7 9.6 10.6
Custom mix2 . 5.6 5.7 5.5
Beet pulp, dehydrated 4.8 3.5 5.6
Wheat straw 2.3 1.9 1.6
Chemical composition, %

DM 55.7 49.2 50.9
CP - 18.7 18.0 18.2
ADF 19.7 18.4 19.1
NDF 30.4 29.3 28.9
EE 3.4 3.9 4.0
Ash 8.1 8.5 8.0
CP equivalent from ammonia 0.93 1.05 1.06
NFC3 40.3 41.4 42.0
Ca 1.15 1.22 1.13

P 0.56 , 0.61 0.59
Mg 0.37 0.38 0.37
K 1.46 1.43 1.40
Na 0.58 0.66 0.56
Particle size‘(%)

> 19.0 m 70:43 3.0i1.8 3.13:1.9
8.0 to 19.0 mm 34.4i4.7 39.7+.4.0 41.6i4.0
< 8.0 mm 58.6i3.3 57.3:t4.2 55414.0

 

 

ICows of all parities were fed this diet for the first 17 DIM approximately.

2Contained 23.3% CP, 0.5% fat, 12.4% Ca, 2.9% P, 2.8% Mg, 0.4% K, 8.9% Na,

11.0% C1, 1.7% S, 3 ppm of Co, 254 ppm of Cu, 1270 ppm of Fe, 13 ppm of I, 1016 ppm
of Mn, 6 ppm Se, 152 KIU/kg of Vitamin A, 25 KIU/kg of Vitamin D, and 484 IU/kg of
Vitamin E.

3NFC = 100 - % NDF - % CP + % CP equivalent from ammonia - % EE - % ash.
4Particle size determined by the Penn State Particle Separator (Lammers et al., 1996), as-

fed basis; meansiSD.

68

Table 5. Formulated ingredient composition of diets fed in the
early dry period.

 

 

Item Farm 1 Farm 2
Ingredient, % of DM

Corn silage 72.0 35.0
Alfalfa silage 18.5 41.9
Beet pulp, dehydrated - 20.7
Soybean meal 7.3 -
Mineral mix 2.21 2.42
Chemical composition, %

DM 34.4 40.9
CF 15.0 15.6
ADF 25.1 28.7
NDF 42.7 43.2
EE 2.9 2.8
Ash 6.9 6.8
NFC3 32.4 31.7
Ca 0.65 1.03
P 0.36 0.32
Mg 0.29 0.34
K 1.30 1.52
Na 0.05 0.1 1

 

IContained 2.5 KIU/kg of Vitamin E and 2 ppm of Se.
2Contained 15.0% CP, 2.0% EE, 2.0% Ca, 0.2% P, 1.4 ppm of
Se, 14 KIU/kg of Vitamin A, 3.1 KIU/kg of Vitamin D, and
195 KIU/kg of Vitamin E.
3NFC=100-%NDF-%CP-%EE-%ash.

69

Table 6. Least squares means and statistical significance
of body condition scores during the periparturient period.

 

 

Variable Sl SEM Ll SEM
Farm 1 3.11 0.04 3.27 0.05
Farm 2 3.27 0.03 3.50 0.05
Parity 1 3.29 0.04 3.58 0.06
Parity 2 3.11 0.04 3.31 0.05 ‘
Parity 3+ 3.17 0.04 3.27 0.05
Time, d relative
to parturition
~42 ' - - 3.52 0.11
-35 - - 3.52 0.07
-28 - - 3.65 0.05
-21 3.49 0.12 3.65 0.05
-14 3.52 0.05 3.69 0.05
-7 3.60 0.05 3.68 0.05
2 3.30 0.05 3.41 0.05
21 2.50 0.05 2.69 0.05
42 2.36 0.05 2.43 0.05
P-value
Parity < 0.01 - < 0.01 -
Farm < 0.01 - < 0.01 -
Time < 0.01 - < 0.01 -

 

ITreatments: S = short late dry period; L = long late dry period.

70

Table 7. Least squares means and statistical significance of body condition score changes

during the periparturient period.

 

 

 

Weeks postpartum

Variable Prepartum SEM 0 to 6 SEM 0 to 3 SEM 3 to 6 SEM
s ' 0.08 0.03 -1.30 0.06 -115 0.06 -0.13 0.06
L' 0.14 0.03 -121 0.06 -0.95 0.05 -027 0.05
Parity 1 0.11 0.04 -1.08 0.08 -0.99 0.07 +0.07 0.07
Parity 2 0.20 0.03 -1.21 0.07 -0.96 0.06 -0.23 0.06
Parity 3+ 0.01 0.03 -1.46 0.06 -1.21 0.06 -0.31 0.06
Farm 1 0.16 0.03 -135 0.07 -1.14 0.06 -0.19 0.06
Farm 2 0.05 0.03 —1.15 0.05 -0.96 0.05 -0.21 70.06
S*farm 1 -0.08 0.10
L*fa.rm 1 -0.33 0.07
S*farm 2 -0.18 0.05
L*far'm 2 -0.21 0.07
P-value2

Treatment (Trt) 0.14 0.30 < 0.01 0.06

Parity < 0.01 < 0.01 < 0.01 0.03

Farm < 0.01 0.02 0.03 0.83
Trt*farm RM RM RM 0.13
Parity*farm 0.08 RM3 RM 0.14

 

'Treatments: S = short late dry period; L = long late dry period.
All 2- and 3-way interaction terms not listed were removed from the statistical model

because P > 0.15.

3 Independent variables were removed (RM) from the statistical model if P > 0.15.

71

Table 8. Least squares means of plasma NEF A concentrations for prepartum,
postpartum, and periparturient periods.

95% confidence intervals

 

 

NEF A (qu/L) (lower limit/upper limit)
Pre- Post- Peripart Pre- Post- Peripart-
Variable partum partum -urientl partum partum urient
Sz 171.7 542.4 270.2 1502/1964 4847/6070 240.8/303.1
L2 178.9 487.1 260.7 1579/2027 4444/5339 2366/2872
Parity 1 211.7 480.5 298.8 1768/2536 4210/5485 2601/3432
Parity 2 120.4 469.8 204.0 103.9/ 139.5 418.4/527.6 181.1/229.8
Parity 3+ 211.3 601.5 306.6 1855/2406 5393/6708 2763/3403
Farm 1 208.7. 543.7 305.3 180.6/241.1 4832/6118 2708/3443
Farm 2 147.2 485.9 230.7 131.0/ 165.4 4470/5283 2108/2524
Time, d
relative to
parturition
-14 129.6 135.0 107.8/ 155.7 109.6/ 166.4
-11 133.5 142.3 115.5/14.3 1231/1645
-8 151.5 149.2 133.6/171.7 1320/1688
-5 199.8 198.8 177.8/224.6 ”7.3/222.9
-2 316.0 313.6 2825/3535 2820/3488
2 628.1 629.4 5735/6879 5697/6953
7 550.8 554.0 501.1/605.3 4997/6142
14 392.6 394.6 356.7/431.9 3556/4380
P-value3
Trt 0.66 0.15 0.65
Parity < 0.01 < 0.01 < 0.01
Farm <0.01 0.13 <0.01
Time < 0.01 < 0.01 < 0.01
Trt‘parity RM4 0.32 0.28
Trt*farm RM 0.86 0.86
Trt*time RM 0.37 0.16
Parity*farm 0.06 < 0.01 < 0.01
Parity*time RM 0.08 < 0.01
Farm‘time RM 0.14 0.03
ffntwfm RM 0.07 0.15
tlme

 

lPeriparturient period = combined pre- and postpartum periods.
2'1‘ reatrnents: S = short late dry period; L = long late dry period.
3All 2- and 3-way interaction terms not listed were removed from the statistical model
P > 0.15).
SIndependent variables were removed (RM) from the statistical model if P > 0.15.

72

Table 9. Least squares means and statistical significance of plasma beta-
hydroxybutyric acid (BHBA) concentrations for prepartum, postpartum, and
periparturient periods.

 

 

 

95% confidence intervals
BHBA (mg/d1) (lower limit/upper limit)
Pre- Post- Peri art- Peri art-
Variable Partu partum urifntl Pre-partum Post-partum ufignt
S‘ 4.15 7.42 5.17 385/448 666/827 4.80/5.57
L2 4.27 7.41 5.20 398/4.59 6.72/8.17 4.86/5.57
Parity 1 4.12 7.07 4.95 3.70/4.S9 6.12/8.16 4.47/5.50
Parity 2 4.04 6.69 4.94 3.70/4.41 593/754 454/538
Parity 3 4.48 8.63 5.70 4.16/4.83 7.73/9.63 5.30/6.14
Farm 1 3.92 6.92 4.83 3.61/4.26 6.15/7.79 444/5.24
Farm 2 4.52 7.94 5.58 422/484 727/869 5.22/5.96
Time, (1
relative to
-14 3.93 3.83 3.52/4.39 3.31/4.42
-11 3.82 3.86 3.50/4.17 3.45/4.32
-8 3.94 3.94 3.66/4.24 3.58/4.34
-5 4.29 4.26 400/460 390/465
-2 5.22 5.23 4.89/5.56 482/568
2 6.36 6.39 581/696 581/696 592/689
7 9.31 9.24 8.49/ 10.22 8.49/ 10.22 8.54/ 10.0
14 6.86 6.86 627/756 627/756 6.33/7.42
P-value3
Trt 0.58 0.98 0.91
Parity 0.16 0.01 0.02
Farm < 0.01 0.07 < 0.01
Time < 0.01 < 0.01 < 0.01
Parity*farm 0.02 0.09 0.05
Parity‘time 0.1 1 0.05 0.02
Farm*time < 0.01 0.15 0.05

 

1Periparturient period = combined pre- and postpartum periods.
2Treatments: S = short late dry period; L = long late dry period.
3All 2- and 3-way interaction terms not listed were removed (P > 0.15).

73

Table 10. Least squares means and statistical significance of plasma insulin
concentrations for prepartum, postpartum and periparturient periods.
95% confidence intervals

 

 

Insulin (uIU/ml) (lower limit/upper limit)
Variable Pre- Post- Periparlt- Pre- Post- Peripart-
partum partum urient partum partum urient

8‘ 11.66 6.46 9.21 10.0/13.5 5.5/7.2 8.3/10.3

L2 10.48 7.19 8.96 9.2/11.8 6.6/7.8 8.2/9.8

Parity 1 12.05 9.29 11.05 10.1/14.4 8.2/10.5 9.7/12.6

Parity 2 12.42 6.56 9.53 105/14.7 5.97.3 8.5/10.7

Parity 3+ 9.02 5.19 7.12 7.8/10.4 4.75.7 6.5/7.8

Farm 1 . 9.83 6.68 8.25 8.4/11.2 6.0/7.5 7.4/9.2

Farm 2 12.43 6.95 10.01 11.1/14.0 6.4/7.5 9.2/10.9

Time, d relative

to parturition
-14 13.21 13.28 112/156 114/155
-11 12.50 12.45 11.0/14.3 11.0/14.0
-8 11.18 10.68 10.0/12.6 9.6/11.9
-5 10.37 10.16 9.3/11.6 9.2/11.2
-2 8.60 8.44 7.7/9.6 7.7/9.3
2 6.72 6.71 6.2/7.3 6.2/7.3
7 6.64 6.55 6.1/7.2 ’ 6.0/7.2
14 7.08 6.98 6.5/7.7 6.4/7.7

P-value3

Trt 0.28 0.12 0.70

Parity < 0.01 < 0.01 < 0.01

Farm 0.01 0.57 < 0.01

Time < 0.01 0.29 < 0.01

Trt*parity 0.40 0.87 RM

Trt*farm 0.24 0.24 0.13

Trt‘time 0.87 0.59 0.035

Parity*farm 0.02 0.15 < 0.01

Parity*time 0.01 0.20 < 0.01

Farm*time 0.85 0.71 0.03

Trt*parity*farm 013‘5 RM RM

Trt*parity*time RM 0.077 RM

 

1Pfieriparturient period = combined pre- and postpartum periods.

2Treatments: S = short late dry period; L = long late dry period.

3All 2-, 3-way interaction terms not listed were removed from the statistical model (P
> 0.15).

4Independent variables were removed (RM) from the statistical model if P > 0.15.
5See Figure 1.

6See Figure 2.

7See Figure 3.

74

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77

Table 14. Least squares means and statistical
significance of daily milk yields in Farm 1.

 

 

 

Milk yield
Variable (kg/d) SEM
0 to 56 DIM
s1 38.4 2.2
L1 34.2 1.5
Parity 1 25.9 2.4
Parity 2 42.7 2.1
Parity 3+ 40.4 2.1
Time, mo postpartum
1 26.0 1.5
2 30.2 1.4
3 34.3 1.5
4 37.0 1.5
5 39.4 1.5
6 40.2 1.5
7 41.5 1.5
8 41.9 1.5
P-value2
Treatment (Trt) 0.12
Parity < 0.01
Time < 0.01
0 to 150 DIM
S 42.0 2.0
L 36.6 1.3
Parity 1 32.2 2.1
Parity 2 43.2 1.8
Parity 3+ 42.4 1.9
Time3
P-value
Trt 0.03
Parity < 0.01
Time < 0.01
Parity*time < 0.01

 

'Treatments: S = short late dry period, L = long late dry period

2All 2- and 3-way interaction terms not listed were removed from the
statistical model because P > 0.15.

3 Time not shown.

78

Table 15. Least squares means and statistical significance of
energy-corrected milk (ECM) yield and SCC through 60 DIM.

 

 

 

53:1 S C C 95% confidence intervals

Variable (kg/d) SEM (cells/ml) Lower Upper
SI 41.3 2.0 94,051 59,213 149,388
L1 41.5 1.7 70,597 46,831 106,425
Parity 1 28.7 2.5 126,355 71,396 223,619
Parity 2 47.0 1.9 56,846 36,450 88,654
Parity 3+ 48.4 1.9 75,325 48,098 117,960
Farm 1 36.3 2.9 107,621 52,923 218,841
Farm 2 46.5 1.1 61,696 48,441 75,582
Time, mo '
postpartum

1 41.4 1.6 90,744 60,018 137,201
2 41.4 1.6 73,171 48,977 109,316
P-value2
Treatment 0.92 0.22
Parity < 0.01 0.03
Farm < 0.01 0.15
Time 0.96 0.20

 

lTreatments: S = short late dry period; L = long late dry period.
2All 2- and 3-way interaction terms not listed were removed from the statistical
model because P > 0.15.

79

Table 16. Least squares means and statistical significance of energy-corrected milk
(ECM) yield and SCC through 150 DIM.

 

 

 

5.3:: S C C 95% confidence intervals
Variable (kg) SEM (cells/ml) Lower Upper
S1 42.9 1.0 49,258 34,068 71,218
L1 41.3 0.9 80,515 60,895 106,468
Parity 1 32.7 1.4 70,885 48,137 104,391
Parity 2 45.7 1.1 48,204 34,839 66,696
Parity 3+ 47.8 1.1 73,096 53,407 100,047
Farm 1 38.8 1.4 53,630 35,355 81,349
Farm 2 45.3 0.8 73,951 60,162 90,899
Time, mo '
postpartum
1 42.9 1.1 59,418 43,019 82,068
2 42.8 1 .0 47,452 34,403 65,447
3 42.4 0.9 52,505 39,755 69,342
4 42.6 1.0 87,444 63,557 120,307
5 39.5 1.0 76,520 55,938 104,673
P-value2
Treatment (Trt) 0.22 0.04
Parity < 0.01 0.09
Farm < 0.01 0.17
Time < 0.01 < 0.01
Trt*farm RM3 < 0.014
Parity*time <0.02 0.02

 

ITreatments: S = short late dry period; L = long late dry period.

2All 2- and 3-way interaction terms not listed were removed from the statistical model

because P > 0.15.

3 Independent variables were removed (RM) from the statistical model if P > 0.15.

4See Figure 9.

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.S
L
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E
E 15 -
S;
.E
E 10 -
.E.
5 J
O .J L , 1 L
-14 -11 -8 -5 -2 2 7 14

Days relative to parturition

Figure 1. Least squares means and 95% confidence intervals for the interaction of
treatment by time (P = 0.03) for plasma insulin in the periparturient period. Other
significant effects in the model for the periparturient period included: parity (P <
0.01), farm (P < 0.01), time (P < 0.01), treatment by farm (P = 0.13), parity by farm
(P < 0.01), parity by time (P < 0.01), farm by time (P = 0.03). Treatments: S = short
late dry period; L = long late dry period.

82

Parity 1 Parity 2 Parity 3+

 

 

 

 

 

 

 

 

 

 

 

 

 

 

   

 

 

 

 

 

 

 

 

 

 

r: I S

3 i
v
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'.-.'-'.

m J

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1 2 1 2 1 2
Farm Farm Farm

Figure 2. Least squares means and 95% confidence intervals for the interaction of
treatment by parity by farm (P = 0.13) on plasma insulin concentrations prepartum.
Other significant efi‘ects in the model included: parity (P < 0.01), farm (P < 0.01),
time (P < 0.01), parity by farm (P = 0.02), and parity by time (P = 0.01). Treatments:
S = short late dry period; L = long late dry period.

83

Parityl Parity2 Parity3+

 

    
   

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Insulin (u IU/ml)

 

 

 

 

 

 

 

2 7 l4 2 7 l4 2 7 14
Days postpartum Days postpartum Days postpartum

Figure 3. Least squares means and 95% confidence intervals for the interaction of
treatment by parity by time (P = 0.17) on plasma insulin concentrations postpartum.
Other significant effects in the model included: treatment (P = 0.12), parity (P <
0.01), and parity by farm (P = 0.15). Treatments: S = short late dry period; L = long
late dry period.

84

46
45 -
44 4
43 .
42 -

 

IS
bl

Milk yield (kg/d)

 

 

   

 

 

 

Farm

Figure 4. Least squares means and SEM for the treatment by farm interaction (P =
0.06) for milk yield through 150 DIM. Other significant effects in the model include:
treatment (P = 0.06), parity (P < 0.01), time (P < 0.01), and farm by time (P = 0.12).
Treatments: S = short late dry period; L = long late dry period.

85

 

 

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3'"
A
l .

 

5"
U
1

Protein (%)

 

 

 

 

 

 

 

 

 

 

3.1
3.0 -.
2.9 4.
2.8 A .
1 2
Parity

Figure 5. Least squares means and SEM for the treatment by parity interaction (P =
0.07) of milk protein content through 60 DIM. Other significant effects in the model
include: treatment (P < 0.01), farm (P < 0.01), parity (P < 0.05), time (P < 0.01),
treatment by time (P < 0.01), and parity by farm (P = 0.08). Treatments: S = short late
dry period; L = long late dry period.

86

 

 

 

 

Protein (%)

 

 

 

 

 

 

 

 

 

Month postpartum

Figure 6. Least squares means and SEM for the treatment by time interaction (P <
0.01) of milk protein content through 60 DIM. Other significant effects in the model
include: treatment (P < 0.01), farm (P < 0.01), parity (P < 0.05), time (P < 0.01),
treatment by parity (P = 0.07), and parity by farm (P = 0.08). Treatments: S = short
late dry period; L = long late dry period.

87

3.6

 

 

 

 

 

 

 

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A 3.3 . +Parity2(S)
6
i 3.2 . +Parity3+(8)
.3 31 -fl-.Parityl(L)
E ' __A._.Parity2(L)
3 “ ll -.o-.Parity 3+ (L) l
.l J
2.9 - I
l
2.8 4 i
2.7 . . . r I

 

 

1 2 3 4 5
Month postpartum

Figure 7. Least squares means for the interaction of parity by treatment by time (P =
0.03) on milk protein percentage through 150 DIM. Other significant effects in the
model through 150 DIM were: farm (P < 0.01), parity (P = 0.09), time (P < 0.01),
farm by time (P < 0.01), and treatment by time (P < 0.01). Significant effects of the
model through 60 DIM were: farm (P < 0.01), parity (P = 0.05), treatment (P < 0.01),
time (P < 0.01), farm by parity (P = 0.08), parity by treatment (P = 0.07) and
treatment by time (P < 0.01). Treatments: S = short late dry period; L = long late dry
period.

1.5
1.4 1
1.3 .
1.2 -
1.1 _
1 _
0.9 -
0.8 -
0.7 4

0.6 . I . ,
1 2 3 4 5

Month postpartum

 

 

 

 

 

 

Milk protien (kg/d)

 

 

 

Figure 8. Least squares means and standard error of the means for the interaction of
treatment by time (P < 0.01) on milk protein yield through 150 DIM. Other
significant effects in the model include: farm (P = 0.05), parity (P < 0.01), time (P =
0.02), farm by time (P < 0.01), and parity by time (P < 0.01). Treatments: S = short
late dry period; L = long late dry period.

89

 

160,000
140,000 . " .8
120,000 - UL
100,000 . -
80,000 _
60,000 _
40,000 .
20,000 1
0 _

 

 

 

 

 

 

 

 

SCC (cells/ml)

 

 

 

 

 

 

 

 

 

Farm

Figure 9. Least squares means and 95% confidence intervals for the interaction of
treatment by farm (P < 0.01) for SCC through 150 DIM. Other significant variables
in the model included: treatment (P = 0.04), parity (P = 0.09), time (P < 0.01) and
parity by month (P = 0.02). Treatments: S = short late dry period; L = long late dry
period.

80
75 _
70 a
65 .

 

 

Days to first service

 

 

 

 

 

 

 

Farm 1 Farm 2

Figure 10. Least squares means and standard error of the means for the interaction of
treatment by farm (P = 0.06) on days to first service. The only other significant
variable in the model was treatment (P = 0.04). Treatments: S = short late dry period;
L = long late dry period.

91

CHAPTER 5

ASSOCIATIONS AMONG BODY CONDITION SCORES, BODY CONDITION
SCORE CHANGES, BLOOD VARIABLES AND MILK YIELD AND

COMPOSITION IN PERIPARTURIENT DAIRY COWS

ABSTRACT

The objective of this study was to compare the relationships among body
condition scores (BCS), BCS changes, and blood variables during the periparturient
period, and milk yield and composition of early lactation dairy cows. Data from 378
cows from two previous research projects were pooled and correlation coefficients were
generated among variables. Days spent in the late dry period consuming a higher energy
diet compared with conventional early dry period diets, and BCS changes during this
time were not strongly correlated with any other variables. Increased BCS at parturition
were associated with increased plasma insulin concentrations prepartum, non-esterified
fatty acid (NEFA) concentrations at 2 d postpartum, and BCS losses in early lactation.
Cows with greater BCS losses in early lactation had higher postpartum NEF A
concentrations and milk, fat, protein, and energy-corrected milk (ECM) yields. In early
lactation, plasma NEFA concentrations were correlated positively with plasma beta-
hydroxybutyrate (BHBA) concentrations and BCS losses, and negatively with plasma
insulin concentrations. Plasma insulin concentrations were associated negatively with
BHBA postpartum and with milk, fat, protein, and ECM yields. Additionally, correlation

coefficients for all variables were calculated for parity categories 1, 2, and 3+, separately.

92

 

Days spent in the late dry period and BCS changes in the late dry period were correlated
with BCS at parturition only in cows of parity 2. BCS at parturition were associated with
increased BCS losses in early lactation in parity 2 and 3+ cows. In cows of parity 3+,
BCS at parturition were correlated positively to milk, fat, and ECM yields, and fat and
protein contents. Increased BCS losses in early lactation were associated with increased
milk, fat, protein, and ECM yields in cows of parities 2 and 3+. In parities 1 and 3+ only, '
cows with higher plasma BHBA postpartum had increased plasma NEFA concentrations
and BCS losses in early lactation and lower plasma insulin concentrations. Plasma insulin
concentrations postpartum were correlated negatively with milk, fat, protein and ECM
yields in parity 2 cows. Overall, correlations among variables differed depending upon
parity. In this dataset, relationships between blood variables were similar in parity 1 and
3+ cows, and relationships involving BCS and BCS changes were similar in cows of

parities 2 and 3+.
INTRODUCTION

Many factors during the periparturient period can influence milk yield and
composition of dairy cows in early lactation. One such factor is the energy status of cows
both pre- and postpartum. A common, practical method of measuring energy status is
assigning body condition scores (BCS) to cows based on visual appraisal (Wildman et al.,
1982). This method helps dairy producers monitor changes in body condition over
several weeks or months. The relationships between BCS at parturition and BCS changes

during lactation have been the focus of much research. Many controlled studies have

93

 

adjusted BCS at parturition by feeding a diet higher or lower in energy density during the
dry period or late lactation (Boisclair et al., 1986; Fronk et al., 1980; Gamsworthy and
Huggett, 1992; Holter et al., 1990; Gamsworthy and Jones, 1987; Jones and
Gamsworthy, 1989; Nachtomi et al., 1986). Other studies measured BCS and BCS
changes as they occurred naturally in commercial dairy farms (Domecq et al., 1997; Gallo
et al., 1996; Gearheart and Curtis, 1990; Pedron et al.,1992; Rueeg et al., 1992). A more
definitive method of measuring energy status may be analysis of certain blood
metabolites and hormones known to reflect energy status. BCS at a point in time do not
indicate the current energy status of cows. BCS need to be monitored over weeks or
months to determine changes in BCS that can be related to energy status. However,
certain blood variables can define current energy status more accurately compared with
BCS. Few studies comparing BCS and milk yield have included analysis of blood
variables. Therefore, the objective of this analysis was to evaluate the relationships
among BCS, BCS changes and blood variables in the periparturient period, and milk

yield and composition in early lactation.
MATERIALS AND METHODS

Three hundred and seventy-eight cows in two commercial dairy farms were
studied in two previous experiments. In the first experiment, one hundred eight-nine
cows in a commercial dairy farm were fed either one of two treatments that varied in corn
grain concentration during the last 17 d prepartum (Chapter 3, Table 1). In the second

experiment, one hundred eighty-nine cows in two commercial dairy farms were assigned

94

 

randomly to one of two treatments that varied in length of time cows were in the late dry
period (LDP; Chapter 4, Table 2). Data from both experiments were combined for the
current analysis.

One evaluator scored cows for BCS [five-point scale where 1 = thin to 5 = fat;
(Wildman et al., 1982)] within the first week after cows entered the LDP, weekly
prepartum, and 3 and 6 wk postpartum. BCS changes used in the analysis were defined
as: LDP BCS change = -1 wk BCS (taken within 1 wk prior to parturition) — BCS taken
within 1 wk afier cows entered the late dry group; and, early lactation BCS change = 6
wk BCS — -lwk BCS. Therefore, a negative value for BCS change would indicate BCS
loss. Additionally, days spent in the LDP when cows are fed a more nutrient-dense diet
compared with early dry period diets are presented.

Blood samples were collected in evacuated test tubes containing sodium heparin
(V acutainer; Becton Dickson Vacutainer Systems USA, Rutherford, NJ) fi'om the
eoccygeal vein twice weekly prior to parturition, within 3 d following parturition, and l
and 2 wk postpartum. Samples were stored on ice during transport to the laboratory.
Upon arrival they were centrifuged and plasma was stored at -4'C until later analysis for
NEFA (NEFA-C kit, Waco Chemicals USA, Richmond, VA) with modifications
(Johnson and Peters, 1993), insulin (Coat-A-Count, Diagnostic Products Corporation,
Los Angeles, CA), and BI-IBA(310-A, Sigma Diagnostics, St. Louis, MO). All reagents
in the BHBA assay except beta-hydroxybutyrate dehydrogenase were reduced
proportionally to fit into 350 ul wells of cell culture plates. Beta-hydroxybutyrate

dehydrogenase was added at twice the reduced dose to truncate the incubation time.

95

 

V1

rm

”r:

A

 

 

Inter-assay and intra-assay coefficients of variation for BHBA, NEFA and insulin were
5.8 and 7.1, 6.9 and 8.2, and 4.4 and 7.8, respectively. For this analysis, blood samples
were grouped into time periods of i 1 d from the day of sampling, because all samples
were not collected on the same day relative to calving for every cow. Time periods were
—8, -5, -2, 2, 7, and 14 d.

In Farm 1, daily milk yield data were recorded monthly, and samples for fat and

protein content, and SCC analysis were collected every 3 mo (Michigan DHIA). In Farm

 

2, individual milk yield data were recorded every 2 wk and samples were analyzed for fat
and protein content and SCC monthly (Michigan DHIA). Energy-corrected milk (ECM)
was calculated by the equation ECM (lb) = 0.3246 x milk yield (lb) + 12.86 x fat yield
(1b) + 7.04 x protein yield (lb). (Dairy Herd Improvement Glossary, F act Sheet A—4,
1999). Milk yield and composition data were reduced to one mean during the first 60
DIM. All data are presented as arithmetic means and standard deviations. Gross
correlation coefficients were calculated by the PROC CORR procedure of SAS [version
6.1; SAS (1989)]. Correlation coefficients were generated for all cows and for cows of
parities l, 2, and 3+, separately. Correlations were declared significant at P < 0.05.
Generally, correlations are discussed only if r > 0.15, P < 0.05, or if there is a trend for
several significant correlations over time for specific blood variables. If correlation
coefficients are presented and discussed for a specific blood variable over a time series,

the range of low to high coefficients are presented (i.e., r = 0.20 to 0.30).

96

RESULTS AND DISCUSSION

All purities
Arithmetic means, standard deviations and ranges for all variables are in Table 1.

Correlation coefficients for the combined analysis of all parities are shown in Table 2.

Correlations among days in the LDP, -1 wk BCS, and LDP BCS change, and with blood

variables and milk yield and compgsition. Days in LDP were not correlated with BCS
changes in the LDP or —1 wk BCS. Increasing the length of time cows were fed the late
dry period diet was correlated positively with plasma NEFA concentrations prepartum.
Correlation coefficients were significant from —8 to 2 d and ranged from 0.11 to 0.20.
Additionally, days in LDP were associated with early lactation BCS changes (r = -O.l6).
BCS at —1 wk were correlated with 3 wk BCS (r = 0.61), 6 wk BCS (r = 0.47), LDP BCS
changes (r = 0.28), and early lactation BCS changes (r = -0. 19). It is well documented
that higher BCS at calving increases BCS loss in early lactation (Garnsworthy and Topps,
1982; Treacher et al., 1986; Ruegg et al, 1992; Pedron et al., 1993). In addition, -1 wk
BCS were associated with increased plasma insulin. concentrations from — 8 (r = 0.20) to
2 d (r = 0.12) and plasma NEFA at 2 d (r = 0.18). Contrary to a previous report (Pedron et
al., 1993), there was no relationship between -1 wk BCS on plasma NEF A afier

parturition. LDP BCS changes were not correlated with any variables.

97

Correlations among 3 and 6 wk BCS and early lactation BCS change, and with blood

 

variables and milk yield and composition. As expected, BCS at 3 and 6 wk were

correlated highly with each other and with early lactation BCS changes. BCS at 3 and 6
wk were associated negatively with plasma BHBA concentrations fi'om -2 to 14 d (r = -
0.15 to —0.25). BCS at 3 and 6 wk were correlated negatively with NEF A (r = -O.13 to —
0.31) and positively with insulin (r = 0.24 to 0.41) concentrations throughout the
periparturient period, Early lactation BCS changes were correlated negatively with
plasma BHBA postpartum (r = -0.21 to —0.34) and NEFA concentration both pre- and
postpartum (r = -O.17 to -O.46).

Early lactation BCS changes were positively correlated with plasma insulin
throughout the periparturient period with the strongest correlation at 14 d (r = 0.46).
Therefore, cows with higher plasma insulin concentrations pre- and postpartum had
reduced BCS losses during the first 6 wk of lactation. Insulin is an antilipolytic hormone
that reduces plasma NEFA (Grummer, 1995), and thereby should minimize BCS loss.
Early lactation BCS changes were correlated negatively with milk yield and composition
with the exception of milk protein content (correlation coefficients ranged from —O. 16 to

—O.22). Therefore, cows with high milk yields lost more BCS in early lactation.

Correlations among blood variables prepartum, and with milk yield and composition.

Plasma NEF A concentrations prepartum were correlated positively with NEFA
concentrations postpartum (r = 0.19 to 0.42). Plasma NEFA concentrations were
associated positively with BHBA (r = 0.34 to 0.56) and negatively with insulin (r = -0.34

to ~0.50) through both pre- and postpartum periods. Cows with higher plasma NEFA

98

 

concentrations prepartum had lower milk, protein and ECM yields (r = -O.14 to -O.23).
Several studies have reported reduced plasma NEFA concentrations prepartum by
altering the diet fed during this time (Minor et al. 1998, Olsson et al., 1997). However, it
not evident if the changes in milk yield and composition can be attributed solely to a
reduction in prepartum NEFA concentrations.

Plasma BHBA concentrations at —8 and —5 d were not correlated with insulin ‘
concentrations prepartum or BHBA concentrations postpartum. Plasma BHBA
concentrations prepartum were not associated with milk yield or composition. Pre- and
postpartum concentrations of insulin were highly correlated (r = 0.23 to 0.38). However,
plasma insulin concentrations prepartum were not associated with milk yield or

composition.

Correlations among blood variables mgyartum, and with milk yield and commsition.

As previously mentioned, plasma concentrations of NEFA postpartmn were associated
positively with BHBA and negatively with insulin concentrations postpartum. NEFA at
7 d was the only postpartum sample correlated with any milk yield or composition
variables. NEF A concentrations at 7 d were correlated negatively with milk (r = -0.18),
fat (r = -0.l6), protein (r = -O.l9), and ECM (r = -O.17) yields. Plasma BHBA
concentrations postpartum were correlated negatively with insulin postpartum (r = -0. 19
to —O.31). BHBA concentrations at 7 d were correlated negatively with milk (r = -O.30),
protein (r = -0.31) and ECM (r = -0.23) yields, and fat content (r = -0.17). However, the
correlations were not consistent across the postpartum period for any of the milk yield or

composition variables. Plasma insulin concentrations postpartum were correlated

99

 

negatively with milk yield, fat content and yield, protein yield, and ECM yield.

Correlation coefficients ranged from —O. 1 5 to —0.29.

Differences Among Parities

Correlations among days in the LDP, -1 wk BCS, and LDP BCS change, and with blood
variables and milk yield and commsition. Correlation coefficients for individual parities
are shown in Tables 3, 4, and 5 for cows of parities 1, 2, and 3+, respectively. Parity 2
cows gained the most BCS during the LDP, but still calved with the lowest BCS of any
parity (Table 1). Increased DIVH for cows with lower BCS in the periparturient period has
been reported (Hayirli et al., 1998). Therefore, increased energy intake by parity 2 cows
may have accounted for the greater gain in BCS during the LDP. Days in LDP were
correlated positively with -1 wk BCS (r = 0.18) and LDP BCS changes (r = 0.24) in
parity 2 cows, but negatively with -1 wk BCS in parity 3+ cows (r = 019). BCS at —1 wk
were associated with LDP BCS changes in all parities, but were associated negatively
with early lactation BCS changes in cows of parities 2 (r = ~0.22) and 3+ (r = -0.20).
Therefore, multiparous cows with higher -1 wk BCS tended to lose more BCS in early
lactation. In parity 1 cows, the only blood variables associated with -1 wk BCS
prepartum were insulin concentrations from -—8 to —5 d (r = 0.35 to 0.45). BCS at —1 wk
were associated with NEFA in parity 2 cows from 2 to 7 d (r = 0.29 and 0.31,
respectively), and NEFA and BHBA at 14 d for parity 3+ cows (r = 0.18 for both). In
parity 3+ cows only, -1 wk BCS were correlated positively with all milk yield and

composition variables (r = 0.27 to 0.34) with the exception of protein yield.

100

 

In parity 1 cows, LDP BCS changes were correlated positively with BHBA (r = -
0.24) and negatively with insulin at 14 d (r = -0.22). Parity 2 cows with higher LDP BCS
changes lost more BCS postpartum (r = -0.22). LDP BCS changes were not related to

any variables in cows of parity 3+.

Correlations among 3 and 6 ka BCS and early lactation BCS change, and with mikvield ‘
and commsition. Primiparous cows had less BCS loss through the first 6 wk of lactation
than multiparous cows which is agrees with previous research (Waltner et al, 1980; Gallo
et al., 1996). Early lactation BCS changes were correlated negatively with plasma NEFA
and positively with insulin concentrations postpartum for all parities. However, early
lactation BCS changes were only correlated with plasma BHBA concentrations
postpartum in cows of parities l (r = -0.34 to —0.52) and 3+ (r = -0.33). In parity 1, cows
with higher early lactation BCS changes yielded milk with less fat content during the first
2 mo of lactation (r = -0.29). Early lactation BCS changes were associated with decreased
milk, fat, protein, and ECM yields in parity 2 cows (r = -0.36, -0.22, -0.33, and —0.29,
respectively). Parity 3+ cows had similar associations as parity 2 cows between early

lactation BCS changes and milk, fat, protein and ECM yields.

Correlations among blood variables prepartum, and with milk yield and commsition.

Plasma concentrations of blood variables during the periparturient period for each parity
are shown in Table 1. Plasma concentrations of blood variables varied depending upon
parity. However, parity 2 cows appeared to be in more positive energy status based on

plasma NEF A and BHBA concentrations during the periparturient period. Plasma NEFA

101

 

concentrations were correlated positively with BHBA prepartum for all parities. In
addition, plasma NEFA were correlated with insulin concentrations both pre- and
postpartum for all parities. In parity 1 cows, plasma NEF A concentrations prepartum
were correlated with milk protein content (r = 0.30 to 0.51).

Plasma BHBA concentrations at —8 and -5 d were not correlated to postpartum
BHBA concentrations. Plasma BHBA concentrations prepartum were correlated
positively with NEF A concentrations prepartum for cows in parities l and 3+ only (r =
0.40 to 0.63). Contrary, plasma BHBA concentrations in parity 2 cows were correlated
positively with insulin at —8 and —5 d (r = 0.26 and 0.27, respectively), but not with
NEFA any time prepartum. Insulin concentrations at most time points prepartum were
correlated with postpartum insulin concentrations for all parities. With the exception of
plasma NEF A and milk protein content in parity 1 cows, there were no differences in
correlations between parities in plasma concentrations of blood variables prepartum and

milk yield and composition.

Correlations among blood variables mgpartum, and with milk yield and commsition.

Plasma NEFA concentrations postpartum were correlated positively with BHBA (r = 0.22
to 0.82) and negatively with insulin (r = -0.38 to —0.59) concentrations postpartum in all
parities. Plasma NEFA concentrations postpartum were correlated with milk fat content
(r = 0.27 and 0.36 for 7 and 14 d, respectively) in parity 1 cows. Plasma NEFA
concentrations at 14 d were correlated positively with milk (r = 0.38), fat (r = 0.26),
protein (r = 0.27), and ECM yields (r = 0.32) in parity 2 cows. Plasma NEFA

concentrations were not associated with any variables related to milk yield or

102

 

Ell

composition in parity 3+ cows. Increased concentrations of NEF A postpartum and
coinciding BCS loss result in increased milk fat content (Holter et al., 1990). This is
supported by positive correlations between plasma NEFA concentrations postpartum and
milk fat content in cows of parities 1 and 2, but not 3+.

Generally, plasma BHBA concentrations were correlated negatively with insulin
concentrations in the postpartum period in cows of parities 1 and 3+ (r = -0.33 to -0.66).
Plasma BHBA were associated with milk yield at 7 d (r = -0.28) in parity 1 cows and at 2
d (r = -0.26) in parity 3+ cows. At least one pospartum measurement of BHBA
concentrations were associated with fat content in all parities (r = 0.20 to 0.33). Plasma
insulin concentrations were associated with fat content at 2 and 7 d (r = -O.31 and -0.33,
respectively) in cows of parity 1. In parity 2 cows, plasma insulin concentrations
postpartum were associated with reduced yields of milk, fat, protein and ECM (r = -0.22
to -0.32). Similarly, insulin concentrations at 14 d were correlated with reduced yields of
fat, protein, and ECM in parity 3+ cows (r = —0. 1 9 to —0.27). Previous research has
shown that increased insulin concentrations partition nutrients away form the mammary

gland resulting in reduced milk fat yield and content (McGuire et al., 1995).

CONCLUSIONS

The associations among variables were influenced by parity. Relationships

among blood variables were often different for cows of parity 2 compared with cows in

 

 

parities 1 and 3+. Relationships with BCS and BCS changes in parity 1 cows were

unique to cows of parities 2 and 3+. Relationships among variables and parity effects

103

may be unique to this study. Differences observed require further investigation with a
dataset involving many farms. Future research should further define the associations

between these variables and attempt to draw cause and effect relationships.

 

 

104

TABLES

Table l. Arithmetic means, standard deviations and ranges for all variables.

 

 

 

 

 

 

 

 

 

 

 

Parity Pooled across
Variable 1 2 3 parities
Days in LDPI
Mean 22 22 24 23
SD 10.4 10.0 9.5 9.9
Range 5-60 3—55 7—54 3—60
LDP BCS change2
Mean 0.04 0.08 0.04 0.05
SD. 0.28 0.28 0.27 0.3
Range -1.5 - 0.75 -0.5 — 1.0 -l.0 — 0.75 -l.5 — 1.0
-1 wk BCS
Mean 3.70 3.49 3.60 3.59
SD 0.37 0.40 0.47 0.43
Range 2.25 - 4.25 2.5 — 4.50 2.0 — 4.50 2.0 — 4.50
3 wk BCS
Mean 2.79 2.64 2.60 2.64
SD 0.56 0.58 0.67 0.62
Range 1.25 — 3.75 1.5 — 4.00 1.0 - 4.00 1.0 — 4.00
6 wk BCS
Mean 2.75 2.60 2.41 2.54
SD 0.61 0.60 0.66 0.64
Range 1.25 — 3.75 1.25 - 4.25 1.0 - 4.00 1.0 - 4.25
Early lactation
BCS change3 Mean -0.98 -0.92 -l .21 -1.06
SD 0.55 0.55 0.59 0.58
Range -2.5 - 0.25 -2.5 - 0.0 -2.3 — 0.5 -2.5 -— 0.5
-8 d NEFA (qu/L)
Mean 207 106 215 178
SD 1 14 84 251 189
Range 66 — 486 30 — 587 27 — 1653 27 — 1653
-5 d NEFA (qu/L)
Mean 264 138 251 218
SD 153.5 119 238 196
Range 70 —— 942 44 —908 30 — 1391 30 — 1391
-2 d NEF A (qu/L)
Mean 388 207 371 321
SD 251.6 172 345 286
Range 92— 1569 38—930 46—2181 38-2181

 

105

Table 1. (cont)

 

 

 

 

 

 

 

 

 

 

 

Parity Pooled across
Variable 1 2 3 parities
2 d NEF A (qu/L)
Mean 658 488 716 629
SD 332 360 398 383
Range 158 - 2027 112 - 2074 59 — 1955 59 — 2074
7 d NEFA (qu/L)
Mean 671 458 606 573
SD 360 318 357 354
Range 133 — 1665 40 — 1662 84 — 1674 40 — 1674
14 d NEFA (qu/L)
Mean 413 345 403 386
SD 295 221 258 256
Range 84— 1555 60— 1148 77— 1541 60—1555
-8 d BHBA (mg/d1)
Mean 5.2 4.6 5.3 5.1
SD 5.7 1.5 2.2 3.2
Range 1.2 — 40.6 2.4 - 8.4 1.1 - 19.2 1.1 — 40.6
-5 d BHBA (mg/d1)
Mean 5.6 4.8 5.4 5.3
SD 5.3 1.4 2.3 3.1
Range 1.8 — 44.3 1.8 - 7.8 2.0 - 18.5 1.8 — 44.3
-2 d BHBA (mg/d1)
Mean 6.3 5.1 6.5 6.0
SD 4.3 1.3 3.8 3.4
Range 1.5 — 33.8 1.5 — 8.6 1.8 - 34.8 1.5 - 34.8
2 d BHBA (mg/d1)
Mean 8.9 6.1 8.7 7.9
SD 6.7 2.3 5.6 5.3
Range 1.7 — 39.4 1.9 - 14.0 1.6 - 49.0 1.6 - 49.0
7 d BHBA (mg/d1)
Mean 16.5 8.9 12.2 12.1
SD 14.2 6.4 9.0 10.2
Range 2.5 — 58.9 2.8 — 49.7 3.3 — 72.4 2.5 — 72.4
14 d BHBA (mg/d1)
Mean 8.6 7.5 10.0 8.8
SD 6.9 5.6 8.2 7.2
Range 1.9 - 46.3 2.9 — 52.9 2.1 - 49.7 1.9 — 52.9

 

106

 

Table 1. (cont.)

 

 

 

 

 

 

 

 

 

 

 

Parity Pooled across
Variable 1 2 3 parities
--8 d Insulin (uIU/ml)
Mean 12.3 15.8 13.3 13.9
SD 6.4 8.3 7.2 7.5
Range 3.1 — 28.9 2.6 — 44.4 1.3 - 34.5 1.3 - 44.4
-5 d Insulin (uIU/ml)
Mean 12.2 13.5 11.2 12.2
SD 5.5 7.3 7.3 7.0
Range 3.5 — 28.7 2.9 - 47.5 2.1 - 42.9 2.1 — 47.5
-2 d Insulin (uIU/ml)
Mean 11.3 12.4 9.9 11.1
SD 5.6 6.8 6.8 6.6
Range 3.3 - 30.3 1.3 — 35.4 1.3 — 42.3 1.3 — 42.3
2 d Insulin (uIU/ml)
Mean 9.6 10.3 7.8 9.3
SD 4.7 5.7 4.4 5.4
Range 4.0 — 25.4 1.3 — 35.8 1.3 - 22.7 1.3 — 35.8
7 d Insulin (uIU/ml)
Mean 9.6 8.8 7.4 8.4
SD 4.7 4.8 3.6 4.4
Range 4.0—25.4 1.3—41.0 1.7—22.3 1.3 -41.0
14 d Insulin (uIU/ml)
Mean 10.6 9.1 8.6 9.2
SD 5.0 4.0 4.4 4.5
Range 4.2 - 30.6 2.8 — 24.5 1.3 — 30.0 1.3 - 30.6
Milk yield (kg/d)
Mean 28.0 42.6 44.4 40.1
SD 6.3 6.4 8.7 9.9
Range 13.3 — 41.5 27.9 — 59.7 22.5 — 66.7 13.3 — 66.7
Fat content (%)
Mean 4.4 4.8 . 4.7
SD 0.8 1.0 1.1 1.0
Range 2.7 — 6.0 2.0 — 7.6 2.0 — 8.5 2.0 - 8.5
Fat yield (kg/d)
Mean 1.3 2.1 2.2 2.0
SD 0.4 0.6 0.8 0.7
Range 0.4 — 2.2 0.9 - 4.4 0.4 — 5.1 0.4 - 5.1

 

107

 

Table 1. (cont.)

 

 

 

 

 

Parity Pooled across
Variable 1 2 3 parities
Protein content (%)
Mean 3.1 3.1 3.0 3.1
SD 0.3 0.3 0.4 0.3
Range 2.3 — 3.8 2.4 — 3.7 2.1 — 4.2 2.1 - 4.2
Protein yield (kg/d)
Mean 0.9 1.3 1.3 1.2
SD 0.2 0.2 0.3 0.3
Range 0.4 — 1.3 0.8 - 1.8 0.5 — 2.1 0.4 - 2.1
ECM yield (kg/d)
Mean 32.1 49.9 52.4 47.0
SD 8.0 10.2 13.7 14.0
Range 13.6 - 48.0 25.2 - 88.1 13.0 — 96.2 13.0 - 96.2

 

ILDP = Late dry period.

2LDP BCS change = -1 wk BCS — BCS within 1 wk after moved into LDP.
3Early lactation BCS change = 6 wk BCS - -1 wk BCS.

108

 

 

Table 2. Correlations, P-values and n amongst variables pooled across parities.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Days in -1 wk 3 wk 6 wk LDP BCS Early lactation
Variable LDPl BCS BCS BCS Change2 BCS change3
Days in
LDP
-1 wk BCS 0.01‘
0.915
3726
3 wk BCS -0.09 0.61
0.10 < 0.01
345 344
6 wk BCS -0.14 0.47 0.79
< 0.01 < 0.01 < 0.01
343 342 340
LDP BCS 0.09 0.28 0.14 0.05
change 0.07 < 0.01 < 0.01 0.35
372 374 344 342 374
Early lactation -0.16 -0.19 0.45 0.78 -0.14
BCS change < 0.01 < 0.01 < 0.01 < 0.01 0.01
339 341 337 341 341
-8 d BHBA -0.07 -0.06 -0.13 -0.08 -0.08 -0.05
0.34 0.40 0.09 0.27 0.25 0.55
195 194 181 179 194 177
—5 d BHBA -0.15 -0.06 -0.15 -0.07 -0.07 -0.02
0.02 0.36 0.02 0.29 0.24 0.75
261 260 244 241 260 239
—2 d BHBA 0.00 -0.08 -0.21 -0.15 -0.12 -0.09
0.94 0.17 < 0.01 0.01 0.04 0.12
287 288 272 271 288 269
2 d BHBA 0.00 0.07 -0.16 -0.17 -0.10 -0.21
0.94 0.22 < 0.01 < 0.01 0.06 < 0.01
346 345 328 g 324 345 320
7 d BHBA -0.07 0.07 -0.18 -0.25 -0.06 -0.34
0.19 0.23 < 0.01 < 0.01 0.26 < 0.01
341 341 329 325 341 322
14 d BHBA -0.07 0.11 -0.05 -0.17 -0.13 -0.30
0.23 0.04 0.33 < 0.01 0.02 < 0.01
327 327 323 318 327 315

 

109

 

 

Table 2. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

Days in -1 wk 3 wk 6 wk LDP BCS Early lactation
Variable LDP BCS BCS BCS change BCS change
-8 d NEFA 0.20 -0.14 -0.26 -0.23 -0.14 -0.17
< 0.01 0.045 < 0.01 < 0.01 0.045 0.03
195 194 181 179 194 177
-5 d NEFA 0.18 0.00 -0.11 -0.13 -0.04 -0.20
< 0.01 0.99 0.09 0.04 0.49 < 0.01
261 260 244 241 260 239
-2 d NEFA 0.15 0.10 -0.21 -0.23 -0.11 -0.33
< 0.01 0.09 < 0.01 < 0.01 0.06 < 0.01

' 287 288 272 271 288 269 ,
2 d NEFA 0.11 0.18 -0.16 -0.26 0.03 -0.43
0.0336 < 0.01 < 0.01 0.01 0.56 < 0.01
346 345 328 324 345 320
7 d NEFA 0.06 0.10 -0.19 -0.31 0.02 -0.43
0.29 0.07 < 0.01 < 0.01 0.74 < 0.01
341 341 329 325 341 322
14 d NEFA 0.07 0.12 -0.17 -0.28 -0.04 -0.46
0.22 0.03 < 0.01 < 0.01 0.46 < 0.01
327 327 323 318 327 315
-8 d Insulin -0.07 0.20 0.37 0.36 0.08 0.27
0.32 < 0.01 < 0.01 < 0.01 0.25 < 0.01
193 192 179 177 192 175
-5 d Insulin -0.05 0.14 0.27 0.28 0.08 0.21
0.41 0.02 < 0.01 < 0.01 0.23 <_ 0.01
256 255 239 236 255 234
-2 d Insulin -0.04 0.12 0.34 0.31 0.11 0.25
0.49 0.05 < 0.01 < 0.01 0.07 < 0.01
285 286 270 269 286 267
2 d Insulin -0.13 0.11 0.29 0.38 0.02 0.36
0.02 0.05 < 0.01 <_ 0.01 0.78 < 0.01
340 339 323 318 339 315
7 d Insulin -0.06 0.04 0.28 0.40 0.06 0.44
0.27 0.49 < 0.01 < 0.01 0.28 < 0.01
335 335 323 319 335 316
14 d Insulin -0.13 -0.06 0.24 0.41 -0.02 0.46
0.03 0.30 < 0.01 < 0.01 0.67 < 0.01
317 317 315 310 317 307

 

 

110

 

 

Table 2. (cont.)

 

 

 

 

 

 

 

Days in -1 wk 3 wk 6 wk LDP BCS Early lactation

Variable LDP BCS BCS BCS change BCS change
Milk yield 0.02 -0.01 -0.15 -0.19 0.08 -0.20
0.68 0.85 0.01 < 0.01 0.17 < 0.01

294 293 290 291 293 288

Fat content -0.09 0.11 0.01 -0.07 -0.05 -0. 16
0.13 0.06 0.91 0.22 0.42 0.01

294 293 290 291 293 288

Fat yield -0.04 0.07 -0.08 -0. 15 0.02 -0.21
0.48 0.26 0.18 0.01 0.73 < 0.01

294 293 290 291 293 288

Protein 0.06 0.03 0.05 0.06 0.03 0.04
content 0.29 0.64 0.37 0.34 0.61 0.54
294 293 290 291 293 288

Protein 0.05 0.01 -0. 14 -0.18 0.07 -0.20
yield 0.36 0.88 0.02 < 0.01 0.24 < 0.01
294 293 290 291 293 288

ECM yield -0.02 0.05 -O.11 -0.18 0.04 -0.22
0.76 0.44 0.06 < 0.01 0.54 < 0.01

294 293 290 291 293 288

 

 

lll

 

 

Table 2. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 d
Variable BHBA BHBA BHBA BHBA BHBA BHBA
-8 d BHBA
-5 d BHBA 0.86
< 0.01
158
.2 d BHBA 0.70 0.71
< 0.01 < 0.01
' 151 208
2 d BHBA 0.40 0.44 0.50
<001 <001 <001
189 252 279
7 d BHBA 0.02 0.05 0.25 0.36
0.81 0.44 < 0.01 < 0.01
' 183 247 276 334
14 d BHBA 0.02 0.02 0.10 0.19 0.52
0.82 0.77 0.09 < 0.01 < 0.01
173 237 268 321 322
-8 a NEFA 0.34 0.30 0.22 0.29 0.10 0.07
< 0.01 < 0.01 0.01 < 0.01 0.19 0.39
196 158 151 189 183 173
-5 d NEFA 0.42 0.42 0.43 0.47 0.17 0.07
< 0.01 < 0.01 < 0.01 < 0.01 0.01 0.25
158 262 208 252 247 . 237
-2 d NEFA 0.15 0.18 0.47 0.42 0.31 0.26
0.07 0.01 < 0.01 < 0.01 < 0.01 < 0.01
151 208 289 279 276 268
2 d NEFA 0.07 0.10 0.18 0.36 0.36 0.14
0.34 0.12 < 0.01 < 0.01 < 0.01 0.01
189 252 279 348 334 321
7 d NEFA -0.01 0.04 0.20 0.20 0.56 0.31
0.93 0.50 < 0.01 < 0.01 < 0.01 < 0.01
183 247 276 334 343 322
14 d NEFA < 0.01 -0.02 0.05 0.15 0.31 0.51
0.96 0.72 0.43 0.01 < 0.01 < 0.01
173 237 268 321 322 329

 

112

 

 

 

Table 2. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 d

Variable BHBA BHBA BHBA BHBA BHBA BHBA
-8 d Insulin -0.02 -0.16 -0.21 -015 -0.16 -0.04
0.76 0.05 0.01 0.04 0.04 0.65

194 156 150 187 181 171

-5 d Insulin -0.12 -007 -0.17 -0.19 -0.18 0.03
0.13 0.28 0.02 < 0.01 0.01 0.68

156 257 205 247 242 233

-2 d Insulin -0.15 -0.12 -0.18 -0.13 -019 -0.07
0.06 0.09 < 0.01 0.03 < 0.01 0.24

' 150 206 287 277 274 267

2 d Insulin -005 -0.06 -0.11 -0.19 -0.20 -0.15
0.51 0.34 0.08 < 0.01 < 0.01 0.01

184 247 274 342 328 316

7 d Insulin 0.06 0.02 -0.10 -005 -0.31 -025
0.45 0.72 0.11 0.33 < 0.01 < 0.01

178 242 272 328 337 317

14 d Insulin -0.04 -0.03 -0.06 -012 -O.16 -023
0.59 0.67 0.37 0.04 < 0.01 < 0.01

169 230 259 311 313 319

Milk yield -0.02 -0.08 -0.15 -0.21 -0.30 -0.04
0.85 0.24 0.02 < 0.01 < 0.01 0.46

150 203 232 277 281 274

Fat content -0.02 0.07 0.03 0.12 0.06 0.20
0.84 0.34 0.66 0.05 0.34 < 0.01

150 203 232 277 281 274

Fat yield -0.02 0.02 -0.08 -0.08 -0.17 0.08
0.78 0.80 0.23 0.18 < 0.01 0.16

150 203 232 277 281 274

Protein .010 -0.02 -0.01 0.03 -004 .005
Content 0.23 0.78 0.92 0.67 0.52 0.42
150 203 232 277 281 274

Protein 007 -0.06 -0.14 -020 -0.31 -0.05
Yield 0.38 0.38 0.03 < 0.01 < 0.01 0.41
150 203 232 277 281 274

ECM yield -0.03 -0.01 -0.10 -0.13 -0.23 0.05
0.70 0.92 0.12 0.03 < 0.01 0.45

150 203 232 277 281 274

 

 

113

 

 

Table 2. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d --2 d 2 d 7 d 14 (1
Variable NEFA NEF A NEFA NEFA NEFA NEFA
-8 d NEF A
-5 d NEFA 0.61
< 0.01
158
-2 d NEFA 0.41 0.62
< 0.01 < 0.01
‘ 151 208
2 d NEFA 0.38 0.37 0.42
< 0.01 < 0.01 < 0.01
189 252 279
7 d NEF A 0.19 0.27 0.39 0.41
0.01 < 0.01 < 0.01 < 0.01
183 247 276 334
14 d NEFA 0.26 0.23 0.28 0.30 0.41
~ < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
173 237 268 321- 322
-8 d Insulin -0.43 -O.40 -0.33 -0.33 -0.18 ~0.16
< 0.01 < 0.01 < 0.01 < 0.01 0.02 0.04
194 156 150 187 181 171
-5 d Insulin -0.35 -0.41 -0.36 -0.28 -O.30 -0.15
< 0.01 < 0.01 < 0.01 < 0.01 < 0.01 0.02
156 257 205 247 242 233
-2 d Insulin -0.24 -O.30 -0.50 -0.32 -0.21 -0.11
< 0.01 < 0.01 < 0.01 < 0.01 < 0.01 0.08
150 206 287 277 274 267
2 d Insulin -0.25 -0.25 -0.28 -0.46 -0.32 -0.27
< 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
184 247 274 342 328 316
7 d Insulin -0.09 -0.12 -0.21 -0.29 -0.45 -0.30
0.26 0.07 < 0.01 < 0.01 < 0.01 < 0.01
178 242 272 328 337 317
14 d Insulin -0.19 -0.08 -0.14 -0.24 -0.26 -0.34
0.01 0.24 0.02 < 0.01 < 0.01 < 0.01
169 230 259 311 313 319

 

114

 

Table 2. (cont.)

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 (1

Variable NEF A NEF A NEFA NEFA NEFA NEF A
Milk yield -0.23 -O. l 6 -0.18 -0.06 -0.18 0.08
< 0.01 0.02 0.01 0.32 < 0.01 0.16

150 203 232 277 281 274

Fat content -0. 14 -0.07 -0.05 0.04 -0.06 0.10
0.10 0.31 0.45 0.52 0.35 0.09

150 203 232 277 281 274

Fat yield -0.23 -0. l4 -0. 14 -0.01 -0.16 O. 12
< 0.01 0.05 0.03 0.89 0.01 0.06

‘ 150 203 232 277 281 274

Protein 0.12 0.08 0.15 0.02 -0.06 -0.08
Content 0.16 0.23 0.02 0.76 0.29 0.18
150 203 232 277 281 274

Protein -0.15 -0.10 -0.09 -0.03 -0.19 0.08
Yield 0.07 0.15 0.16 0.68 < 0.01 0.17
150 203 232 277 281 274

ECM yield -0.23 -0.14 -0.14 -0.02 -0.17 0.12
< 0.01 0.05 0.03 0.75 < 0.01 0.06

150 203 232 277 281 274

 

 

115

Table 2. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 (1
Variable Insulin Insulin Insulin Insulin Insulin Insulin
-8 d Insulin
-5 d Insulin 0.62
< 0.01
154
-2 d Insulin 0.47 0.62
< 0.01 < 0.01
' 149 203
2 d Insulin 0.38 0.37 0.36
< 0.01 < 0.01 < 0.01
182 242 272
7 d Insulin 0.23 0.25 0.29 0.53
< 0.01 < 0.01 < 0.01 < 0.01
176 238 270 322
14 d Insulin 0.26 0.23 0.27 0.48 0.50
< 0.01 < 0.01 < 0.01 < 0.01 < 0.01
167 226 258 306 308
Milk yield 0.07 -0.04 -0.07 -0.17 -0. 15 -0.25
0.40 0.58 0.30 < 0.01 0.01 < 0.01
148 199 230 272 275 268
Fat content 0.08 0.17 0.03 -0.09 -0.13 -0.16
0.32 0.02 0.63 0.15 0.04 0.01
148 199 230 272 275 268
Fat yield 0.08 0.09 -0.02 -0. 15 -0.17 -0.23
0.31 0.20 0.78 0.01 0.01 < 0.01
148 199 230 272 275 268
Protein 0.01 0.21 0.06 < 0.01 0.06 -0.02
Content 0.93 < 0.01 0.35 , 0.94 0.33 0.80
148 199 230 272 275 268
Protein 0.07 0.07 -0.03 -0.19 -0.15 -0.29
Yield 0.40 0.34 0.64 < 0.01 0.01 < 0.01
148 199 230 272 275 268
ECM yield 0.08 0.06 -0.03 -0.17 -0. 17 -0.26
0.31 0.37 0.62 0.01 < 0.01 < 0.01
148 199 230 272 275 268

 

116

Table 2. (cont.)

 

 

 

 

 

 

 

 

Milk Fat Fat Protein Protein ECM
Variable yield content yield content yield yield
Milk yield
Fat content 0.30
< 0.01
295
Fat yield 0.80 0.78
< 0.01 < 0.01
‘ 295 295
Protein -0.28 ~ 0.13 -0. 14
Content < 0.01 0.02 0.02
295 295 295
Protein 0.88 0.36 0.76 0.15
Yield < 0.01 < 0.01 < 0.01 0.01
295 295 295 295
ECM yield 0.90 0.65 0.98 -0.14 0.87
< 0.01 < 0.01 < 0.01 0.01 < 0.01
295 295 295 295 295

 

lLDP = Late dry period.
2LDP BCS change = -1 wk BCS — BCS within 1 wk after moved into LDP.

3Early lactation BCS change = 6 wk BCS - -1 wk BCS.

‘Correlation coefficient.

’P-value.

Number of observations.

117

 

Table 3. Correlations, P-values, and n amongst variables for cows of parity 1.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Days in -1 wk 3 wk 6 wk LDP BCS Early lactation
Variable LDPl BCS BCS BCS change2 BCS change3
Days in LDP
-1 wk BCS 0.17r
0.115
91‘5
3 wk BCS -0.01 0.51
0.91 < 0.01
83 82
6 wk BCS -0.02 0.44 0.82
0.89 < 0.01 < 0.01
84 83 82
LDP BCS 0.13 0.36 0.11 0.01
change 0.23 < 0.01 0.34 0.97
91 91 82 83
Early lactation -0.11 -0.09 0.62 0.85 -0.04
BCS change 0.32 0.40 < 0.01 < 0.01 0.70
83 83 81 83 83
-8 d BHBA -0.18 -0.14 -0.37 -0.24 -0.10 -0.08
0.23 0.35 0.02 0.13 0.54 0.61
44 44 39 39 44 39
-5 d BHBA -0.13 -0.18 -0.35 -0.19 -0.11 -0.06
0.34 0.18 0.01 0.17 0.43 0.66
60 59 56 56 59 55
-2 d BHBA -0.17 -0.17 -0.38 -0.20 -0.09 -0.08
0.16 0.15 < 0.01 0.12 0.46 0.55
70 70 65 64 70 64
2 d BHBA -0.02 -0.11 -0.41 -0.39 -0.05 -0.34
0.83 0.31 < 0.01 < 0.01 0.63 < 0.01
83 82 79 79 82 78
7 d BHBA -0.12 -0.19 -0.43 -0.52 —0.12 -0.48
0.28 0.09 < 0.01 < 0.01 0.27 < 0.01
84 83 81 81 83 80
14 d BHBA -0.12 -0.14 -0.26 -0.34 -0.24 -0.43
0.28 0.23 0.02 < 0.01 0.03 < 0.01
78 77 77 76 77 75

 

118

 

 

Table 3. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

Day in -1 wk 3 wk 6 wk LDP BCS Early lactation

Variable LDP BCS BCS BCS change BCS change
-8 d NEFA -0.13 -0.06 -0.37 -0.31 -0.08 -0.24
0.42 0.70 0.02 0.05 0.59 0.13

44 44 39 39 44 39

-5 d NEFA 0.17 -0.11 -0.26 -0.10 -0.25 -0.07
0.18 0.39 0.06 0.44 0.06 0.59

60 59 56 56 59 55

-2 d NEFA 0.02 0.01 -0.19 -0.10 -0.05 -0.16
0.84 0.95 0.14 0.45 0.70 0.20

70 7O 65 64 70 64

2 d NEFA 0.11 0.06 -0.18 -0.37 0.06 -0.46
0.31 0.59 0.12 < 0.01 0.58 < 0.01

83 82 79 79 82 78

7 d NEFA -0.17 -0.10 -0.41 -0.48 -0.19 -0.51
0.12 0.36 < 0.01 < 0.01 0.08 < 0.01

84 83 81 81 83 80

14 d NEFA 0.03 -0.12 -0.38 -0.43 -0.21 -0.56
0.77 0.29 < 0.01 < 0.01 0.07 < 0.01
78 77 77 76 77 75 '

-8 d Insulin 0.06 0.45 0.38 0.36 0.19 0.07
0.72 < 0.01 0.02 0.02 0.22 0.67

44 44 39 39 44 39

-5 d Insulin 0.10 0.35 0.20 0.26 0.06 0.04
0.46 0.01 0.15 0.05 0.68 0.80

58 57 54 54 57 53

-2 d Insulin 0.03 0.19 0.29 0.23 0.14 0.11
0.82 0.1 l 0.02 0.07 0.25 0.38

70 70 65 64 70 64

2 d Insulin 0.01 0.16 0.21 0.36 -0.06 0.32
0.92 0.17 0.07 < 0.01 0.59 < 0.01

81 80 77 77 80 76

7 d Insulin 0.14 0.09 0.31 0.37 0.13 0.37
0.21 0.45 0.01 < 0.01 0.23 < 0.01

82 81 79 79 81 78

14 d Insulin -0.06 -0.14 0.13 0.41 -0.22 0.40
0.64 0.24 0.28 < 0.01 0.06 < 0.01

75 74 74 73 74 72

 

 

119

Table 3. (cont.)

 

 

 

 

 

 

 

Days in -1 wk 3 wk 6 wk LDP BCS Early lactation

Variable LDP BCS BCS BCS change BCS change
Milk yield 0.12 0.13 0.06 0.02 0.01 -0.04
0.35 0.31 0.63 0.88 0.98 0.73

66 65 64 65 65 64

Fat content -0.15 -0.07 -0.21 -0.29 -0.18 -0.26
0.24 0.59 0.10 0.02 0.16 0.04

66 65 64 65 65 64

Fat yield -0.02 0.05 -0.04 -0. 12 -0. 12 -0. 14
0.90 0.69 0.74 0.34 0.35 0.26

‘ 66 65 64 65 65 64

Protein 0.05 -0.01 0.10 0.18 -0.07 0.20
content 0.72 0.96 0.43 0.15 0.56 0.12
66 65 64 65 65 64

Protein 0.17 0.13 0.11 0.09 -0.07 0.04
yield 0.17 0.30 0.38 0.46 0.58 0.77
66 65 64 65 65 64

ECM yield 0.06 0.08 0.01 -0.06 -0.09 -0.09
0.65 0.51 0.96 0.66 0.47 0.46

66 65 64 65 65 64

 

 

120

Table 3. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 (1
Variable BHBA BHBA BHBA BHBA BHBA BHBA
-8 d BHBA
-5 d BHBA 0.97
< 0.01
34
-2 d BHBA 0.91 0.89
< 0.01 < 0.01
' 36 46
2 d BHBA 0.56 0.61 0.69
< 0.01 < 0.01 < 0.01
42 56 67
7 d BHBA -0.01 0.03 0.16 0.40
0.93 0.80 0.19 < 0.01
40 57 66 81
14 d BHBA -0.13 -0.04 0.01 0.13 0.47
0.47 0.76 0.93 0.28 < 0.01
35 53 62 75 77
-8 D NEF A 0.44 0.48 0.51 0.58 0.29 0.10
< 0.01 < 0.01 < 0.01 < 0.01 0.07 0.58
44 34 36 42 40 35
-5 d NEFA 0.64 0.62 0.69 0.50 0.10 -0.08
-' < 0.01 < 0.01 < 0.01 < 0.01 0.47 0.59
34 60 46 56 57 53
-2 d NEF A 0.12 0.19 0.40 0.32 0.25 0.04
0.50 0.20 < 0.01 0.01 0.04 0.77
36 46 70 67 66 62
2 d NEF A 0.09 0.12 0.17 0.57 0.44 0.14
0.57 0.39 0.16 < 0.01 < 0.01 0.23
42 56 67 83 81 75
7 d NEFA 0.09 0.09 0.18 0.25 0.75 0.39
0.58 0.50 0.14 0.02 < 0.01 < 0.01
40 57 66 81 84 77
14 d NEF A -0.05 0.01 0.03 0.17 0.34 0.83
0.76 0.93 0.80 0.14 < 0.01 < 0.01
35 53 62 75 77 78

 

121

Table 3. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 (1

Variable BHBA BHBA BHBA BHBA BHBA BHBA
Insulin -8 -0.19 -0.23 -0.29 -0.21 -0.14 -0.16
0.23 0.19 0.09 0.18 0.40 0.35

44 34 36 42 40 35

Insulin -5 -O.29 -0.22 -0.24 -0.32 -0.25 0.19
0.10 0.09 0.12 0.02 0.06 0.18

33 58 45 54 55 52

Insulin -2 -0.26 -0.28 -0.39 -0.29 -0.28 0.04
0.12 0.06 < 0.01 0.02 0.03 0.73

' 36 46 70 67 66 62

2 d Insulin -0.07 -0.16 -0.12 -0.35 -0.28 -0.14
0.68 0.25 0.33 < 0.01 0.01 0.22

40 54 65 81 79 74

7 d Insulin 0.01 0.02 -0. 14 -0.13 -0.51 -0.32
0.99 0.86 - 0.28 0.24 < 0.01 0.01

38 55 65 79 82 76

14 d Insulin -O. 12 -0.1 1 -0.14 -0.22 -0. 1 7 -0. l 7
0.48 0.44 0.28 0.07 0.14 0.16

34 51 59 72 74 75

Milk yield 0.23 0.09 -0.16 -0. 14 -0.28 -0.04
0.20 0.56 0.27 0.28 0.03 0.74

32 45 48 62 64 60

Fat content -0.18 0.13 0.23 0.33 0.30 0.21
0.32 0.40 0.12 0.01 0.02 0.11

32 45 48 62 64 60

Fat yield -0.02 0.1 1 0.03 0.06 -0.04 0.07
0.90 0.48 0.86 0.63 0.77 0.60

32 45 48 62 64 60

Protein -0.26 0.1 1 0.22 0.10 -0.10 -0.29
Content 0.15 0.48 0.13 0.42 0.43 0.02
32 45 48 62 64 60

Protein 0.05 0.1 l -0.02 -0.08 -0.30 -0.17
Yield 0.81 0.49 0.88 0.53 0.02 0.19
32 45 48 62 64 60

ECM yield 0.05 0.10 -0.02 0.01 -0. 14 0.01
0.77 0.50 0.91 0.98 0.26 0.98

32 45 48 62 64 60

 

 

122

Table 3. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d —5 d —2 d 2 d 7 d 14 (1
Variable NEF A NEF A NEFA NEFA NEFA NEF A
-8 d NEF A
-5 d NEFA 0.58
< 0.01
34
-2 d NEF A 0.46 0.58
< 0.01 < 0.01
‘ 36 46
2 d NEFA 0.31 0.22 0.33
0.05 0.10 0.01
42 56 67
7 d NEFA 0.27 0.20 0.30 0.38
0.09 0.14 0.01 < 0.01
40 57 66 81
14 d NEFA 0.25 0.10 0.09 0.24 0.41
0.15 0.48 0.47 0.04 < 0.01
35 53 62 75 77
-8 d Insulin -0.45 -0.36 -0.29 -0.09 -0.14 -0.19
< 0.01 0.04 0.09 0.57 0.39 0.26
44 34 36 42 40 35
-5 d Insulin -0.31 -0.29 -0.20 -0.15 -0.30 0.01
0.08 0.03 0.19 0.26 0.02 0.96
33 58 45 54 55 52
-2 d Insulin -0.35 -0.41 -O.46 -0.15 -0.27 0.15
0.03 < 0.01 < 0.01 0.22 0.03 0.25
36 46 70 67 66 62
2 d Insulin -0.30 -0.25 -0.36 -0.51 -0.35 -O.l6
0.06 0.07 < 0.01 < 0.01 < 0.01 0.19
40 54 65 81 79 74
7 d Insulin -0.31 -0.06 -0.14 . -0.20 -0.59 -0.25
0.06 0.68 0.28 0.08 < 0.01 0.03
38 55 65 79 82 76
14 d Insulin -0.44 0.10 0.05 -0.23 -O.20 -0.17
0.01 0.51 0.72 0.05 ‘ 0.09 0.15
34 51 59 72 74 75

 

123

Table 3. (cont.)

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 d

Variable NEFA NEFA NEFA NEFA NEFA NEFA
Milk yield -0.09 0.01 -0.19 -0. 19 -0.13 0.01
0.61 0.96 0.19 0.15 0.29 0.91

32 45 48 62 64 60

Fat content 0.26 0.09 0.17 0.21 0.36 0.27
0.16 0.55 0.25 0.10 < 0.01 0.04

32 45 48 62 64 60

Fat yield 0.10 0.09 -0.04 0.03 0.14 0.17
0.60 0.54 0.81 0.83 0.29 0.19

‘ 32 45 48 62 64 60

Protein 0.30 0.43 0.51 -0.06 -0.04 -0. 16
Content 0.09 < 0.01 < 0.01 0.66 0.76 0.22
32 45 48 62 64 60

Protein 0.08 0.28 0.04 -0.12 -0.08 0.01
Yield 0.65 0.06 0.79 0.34 0.52 0.99
32 45 48 62 64 60

ECM yield 0.06 0.12 -0.06 -0.04 0.05 0.12
0.74 0.43 0.67 0.78 0.72 0.36

32 45 48 62 64 60

 

 

124

 

Table 3. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 d
Variable Insulin Insulin Insulin Insulin Insulin Insulin
-8 d Insulin
-5 d Insan 0.66
< 0.01
33
-2 d Insulin 0.43 0.46
0.01 < 0.01
36 45
2 d Insulin 0.46 0.35 0.41
< 0.01 0.01 < 0.01
40 52 65
7 d Insulin 0.18 0.28 0.38 0.49
0.29 0.04 < 0.01 < 0.01
38 54 65 77
14 d Insulin 0.30 0.12 0.26 0.42 0.51
0.09 0.40 0.05 < 0.01 < 0.01
34 50 59 71 73
Milk yield 0.05 -0.09 , -0.05 0.03 0.04 -0.25
0.80 0.54 0.75 0.83 0.75 0.06
32 44 48 61 62 57
Fat content -0.09 -0.12 -0.22 -0.20 -0.31 -0.33
0.64 0.43 0.14 0.12 0.01 0.01
32 44 48 61 62 57
Fat yield -0.03 -0.14 -0. 12 -0.10 -0.14 -0.31
0.88 0.37 0.42 0.43 0.27 0.02
32 44 48 61 62 57
Protein 0.01 0.12 -0. 15 -0.11 0.08 0.12
Content 0.97 0.44 0.30 0.41 0.53 0.37
32 44 48 61 62 57
Protein 0.08 -0.03 -0.15 -0.05 0.04 -0.21
Yield 0.65 0.85 0.32 0.72 0.74 0.1 1
32 44 48 61 62 57
ECM yield 0.01 -0.12 -0. 12 -0.07 -0.07 -0.29
0.97 0.42 0.44 0.60 0.57 0.03
32 44 48 61 62 57

 

125

 

Table 3. (cont.)

 

 

 

 

 

 

 

 

Milk Fat Fat Protein Protein ECM
Variable yield content yield content yield Yield
Milk yield
Fat content 0.25
0.04
66
Fat yield 0.82 0.72
< 0.01 < 0.01
' 66 66
Protein -0.22 0.16 -0.08
Content 0.07 0.19 0.54
66 66 66
Protein 0.86 0.29 0.78 0.22
Yield < 0.01 0.02 < 0.01 0.07
66 66 66 66
ECM yield 0.91 0.56 0.97 -0.07 0.89
< 0.01 < 0.01 < 0.01 0.57 < 0.01
66 66 66 66 66

 

lLDP = Late dry period.
2LDP BCS change = -1 wk BCS - BCS within 1 wk after moved into LDP.
3Early lactation BCS change = 6 wk BCS - -1 wk BCS.
‘Correlation coefficient.

sP-value.

Number of observations.

126

 

Table 4. Correlations, P-values and n amongst variable for parity 2 cows.

 

 

 

 

 

 

 

 

 

 

 

 

 

Days in -1 wk 3 wk 6 wk LDP BCS Early lactation
Variable LDPl BCS BCS BCS change2 BCS change3
Days in LDP
-1 wk BCS 0.18‘
0.055
1206
3 wk BCS 0.01 0.68
0.91 < 0.01
115 114
6 wk BCS -0.12 0.48 0.75
0.21 < 0.01 < 0.01
115 114 113
LDP BCS 0.24 0.32 0.14 0.02
change
0.01 < 0.01 0.14 0.79
120 120 114 114
Early lactation -0.24 -0.22 0.33 0.76 -0.22
BCS change 0.01 0.02 < 0.01 < 0.01 0.02
1 13 1 13 1 12 1 13 l 13
-8 d BHBA -0.14 0.05 0.20 0.18 -0.34 0.20
0.26 0.70 0.13 0.16 0.01 0.13
64 63 62 61 63 60
-5 d BHBA -0.18 0.10 0.19 0.11 -0.11 0.05
0.1 1 0.37 0.09 0.33 0.31 0.63
83 83 80 79 83 79
-2 d BHBA -0.17 0.01 0.01 -0.05 -0.12 -0.05
0.10 0.98 0.93 0.63 0.26 0.63
95 94 92 94 94 92
2 d BHBA 0.02 0.06 -0.08 -0.11 -0.08 -0.16
0.86 0.52 0.43 0.28 0.40 0.10
112 111 107 107 111 105
7 d BHBA 0.17 0.17 0.01 -0.07 0.13 -0.22
0.08 0.07 0.90 0.45 0.18 0.02
113 112 108 108 112 106
14 d BHBA 0.01 0.12 0.07 0.02 -0.13 -0.06
1.00 0.23 0.49 0.83 0.18 0.54
110 109 108 108 109 106

 

 

127

 

 

Table 4. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

Days in -1 wk 3 wk 6 wk LDP BCS Early lactation

Variable LDP BCS BCS BCS change BCS change
-8 d NEFA -0.03 -0.25 -0.22 -0.12 -0.06 0.06
0.81 0.04 0.08 0.37 0.63 0.63

64 63 62 61 63 60

-5 d NEFA 0.14 0.13 < 0.01 -0.18 0.06 -0.29
0.22 0.24 ' 0.99 0.12 0.62 0.01

83 83 80 79 83 79

-2 d NEFA 0.29 0.13 -0.15 -0.32 0.03 -0.45
< 0.01 0.22 0.14 < 0.01 0.75 < 0.01

' 95 94 92 94 94 92

2 d NEFA 0.24 0.31 -0.03 -0.14 0.10 -0.38
0.01 < 0.01 0.73 0.15 0.30 < 0.01

112 111 107 107 111 105

7 d NEFA 0.20 0.29 0.01 -0.21 0.20 -0.46
0.03 < 0.01 0.98 0.03 0.03 < 0.01

113 112 108 108 112 106

14 d NEFA 0.20 0.16 -0.14 -0.27 0.07 -0.42
0.03 0.11 0.16 < 0.01 0.48 < 0.01

110 109 108 108 109 106

-8 d Insulin -0.06 0.07 0.33 0.32 -0.03 0.31
0.65 0.59 0.01 0.01 0.85 0.02

63 62 61 60 62 59

-5 d Insulin -0.05 0.10 0.26 0.26 0.04 0.24
0.66 0.38 0.02 0.02 0.69 0.04

82 82 79 78 82 78

-2 d Insulin -0.09 0.06 0.32 0.25 0.02 0.23
0.38 0.59 < 0.01 0.02 0.82 0.03

94 93 91 93 93 91

2 d Insulin -O.20 -0.04 0.17 0.29 -0.01 0.35
0.04 0.67 0.07 < 0.01 0.92 < 0.01

109 108 105 104 108 103

7 d Insulin -0.22 -0.06 0.18 0.39 -0.03 0.48
0.02 0.53 0.06 < 0.01 0.77 < 0.01

113 112 108 108 112 106

14 d Insulin -0.26 -0.02 0.22 0.38 0.01 0.44
0.01 0.84 0.02 < 0.01 0.98 < 0.01

108 107 106 106 107 104

 

 

128

 

Table 4. (cont.)

 

 

 

 

 

 

 

Days in -1 wk 3 wk 6 wk LDP BCS Early lactation

Variable LDP BCS BCS BCS change BCS change
Milk yield 0.10 -0.08 -0.29 -0.36 -0.06 -0.34
0.34 0.41 < 0.01 < 0.01 0.56 < 0.01

102 101 99 100 101 98

Fat content -0.03 0.04 0.04 -0.06 -0.16 -0.11
0.76 0.68 0.67 0.55 0.10 0.29

102 101 99 100 101 98

Fat yield 0.02 0.01 -0.10 -0.22 -0.14 -0.26
0.84 1.00 0.33 0.03 0.18 0.01

' 102 101 99 100 101 98

Protein -0.01 0.18 0.14 0.09 0.11 -0.06
content 0.89 0.08 0.18 0.39 0.26 0.55
102 101 99 100 101 98

Protein 0.10 0.03 -0.21 -0.33 0.01 -0.41
yield 0.34 0.73 0.04 < 0.01 0.92 < 0.01
102 101 99 100 101 98

ECM yield ' 0.05 -0.01 -0.16 -0.29 -0.12 —0.32
0.63 0.90 0.11 < 0.01 0.24 < 0.01

102 101 99 100 101 98

 

 

129

Table 4. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 (1
Variable BHBA BHBA BHBA BHBA BHBA BHBA
-8 d BHBA
-5 d BHBA 0.40
< 0.01
52
-2 d BHBA 0.34 0.36
0.02 < 0.01
50 68
2 d BHBA 0.27 0.21 0.27
0.04 0.06 0.01
61 80 91
7 d BHBA 0.01 -0.01 0.18 0.16
0.93 0.92 0.08 0.1 1
62 80 92 109
14 d BHBA 0.20 0.08 0.25 0.17 0.70
0.13 0.47 0.02 0.08 < 0.01
60 77 92 107 107
o8 d NEFA -0.05 0.10 -0.12 0.44 -0.03 -0.03
0.70 0.48 0.41 < 0.01 0.81 0.80
64 52 50 61 62 60
-5 d NEFA -0.06 -0.07 -0.05 0.30 0.38 0.21
0.66 0.50 0.67 0.01 < 0.01 0.07
52 83 68 80 80 77
-2 d NEF A 0.32 0.01 0.01 0.27 0.23 0.21
0.02 0.94 0.94 0.01 0.03 0.05
50 68 95 91 92 92
2 d NEFA 0.05 -0.13 0.07 0.35 0.35 0.17
0.69 0.24 0.53 < 0.01 < 0.01 0.08
61 80 91 1 12 109 107
7 d NEFA -0.26 -0.18 0.11 0.03 0.54 0.27
0.04 0.10 0.28 0.77 < 0.01 0.01
62 80 92 109 1 13 107
14 d NEF A -0.08 -0.29 -0.01 0.17 0.26 0.25
0.53 0.01 0.94 0.09 0.01 0.01
60 77 92 107 107 1 10

 

 

130

Table 4. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 1!
Variable BHBA BHBA BHBA BHBA BHBA BHBA
-8 d Insulin 0.26 -0.01 -0.03 -0.22 -0.07 0.12
0.04 0.97 0.85 0.08 0.60 0.37
63 51 50 60 61 59
-5 d Insulin 0.05 0.27 -0.03 -0.15 -0.21 -0.07
0.70 0.01 0.81 0.19 0.07 0.56
52 82 67 79 79 76
-2 d Insulin -0.12 -0.05 0.08 -0.26 -0.17 -0.11
0.40 0.69 0.45 0.02 0.10 0.29
‘ 50 67 94 90 91 91

2 d Insulin -0.16 0.02 -0.07 -0.05 -0.25 -0.14 '
0.22 0.86 0.53 0.61 0.01 0.15
59 78 89 109 106 104
. 7 d Insulin 0.25 0.21 -0.03 0.12 -0.17 -0.10
0.05 0.07 0.81 0.20 0.07 0.30
62 80 92 109 113 107
14 d Insulin -0.02 0.03 -0.12 -0.1 l -0.23 -0.09
0.88 0.80 0.26 0.25 0.02 0.37
59 76 90 105 105 108
Milk yield -O.14 -0.22 -0.19 -0.13 -0.04 -0.04
0.30 0.08 0.08 0.22 0.71 0.68
53 66 83 95 97 96
Fat content 0.04 0.11 -0.13 0.03 0.07 0.20
0.78 0.39 0.25 0.75 0.50 0.05
53 66 83 95 97 96
Fat yield -0.02 0.01 -0. 17 -0.05 0.01 0.14
0.87 0.98 0.12 0.66 0.92 0.19
53 66 83 95 97 96
Protein 0.23 0.14 -0.02 0.03 0.02 0.10
Content 0.10 0.27 0.88 0.75 0.81 0.34
53 66 83 95 97 96
Protein 0.06 -0.12 -0.15 -0.13 -0.04 0.03
Yield 0.66 0.35 0.18 0.22 0.67 0.76
53 66 83 95 97 96
ECM yield -0.03 -0.06 -0.18 -0.08 ~0.01 0.11
0.80 0.64 0.10 0.45 0.95 0.30
53 66 83 95 97 96

 

131

 

Table 4. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 (1
Variable NEF A NEFA NEFA NEFA NEFA NEFA
-8 d NEFA
-5 d NEFA 0.58
< 0.01
52
-2 d NEFA 0.08 0.57
0.59 < 0.01
50 68
2 d NEF A 0.31 0.46 0.47
0.02 < 0.01 < 0.01
61 80 91
7 d NEF A 0.01 0.36 0.28 0.37
0.97 < 0.01 0.01 < 0.01
62 80 92 109
14 d NEFA -0.02 0.16 0.29 0.36 0.43
0.89 0.17 0.01 < 0.01 < 0.01
60 77 92 107 107
-8 d Insulin -0.36 -0.27 -0.10 -0.21 -0.03 0.02
< 0.01 0.05 0.49 0.11 0.80 0.86
63 51 50 60 61 59
-5 d Insulin -0.29 -0.38 -0.26 -0.30 -0.25 -0.25
0.03 < 0.01 0.04 0.01 0.03 0.03
52 82 67 79 79 76
-2 d Insulin -0.16 -0.29 -0.51 -0.35 -0.06 -0.22
0.28 0.02 < 0.01 < 0.01 0.59 0.03
50 67 94 90 91 91
2 d Insulin -0.18 -0.22 -0.34 -0.41 -0.34 -0.34
0.18 0.05 < 0.01 < 0.01 < 0.01 < 0.01
59 78 89 109 106 104
7 d Insulin 0.04 -0.21 -0.24 -0.27 -0.44 -0.37
0.73 0.06 0.02 < 0.01 < 0.01 < 0.01
62 80 92 109 l 13 107
14 d Insulin -0.09 -0.12 -0.16 -0.25 -0.28 -0.53
0.50 0.32 0.14 0.01 < 0.01 < 0.01
59 76 90 105 105 108

 

132

 

Table 4. (cont.)

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 d

Variable NEFA NEFA NEFA NEFA NEFA NEF A
Milk yield -0.01 0.16 0.01 -0.02 0.11 0.38
0.94 0.19 0.95 0.87 0.28 < 0.01

53 66 83 95 97 96

Fat content -0. 14 0.07 -0.06 0.03 -0.07 0.10
0.32 0.59 0.57 0.78 0.51 0.33

53 66 83 95 97 96

Fat yield -0.18 0.10 -0.04 0.01 -0.01 0.26
0.20 0.42 0.70 0.91 0.93 0.01

‘ 53 66 83 95 97 96

Protein 0.02 0.07 0.02 0.04 -0.15 -0. 19
Content 0.87 0.56 0.85 0.67 0.14 0.06
53 66 83 95 97 96

Protein -0.03 0.20 0.02 -0.01 0.03 0.27
Yield 0.83 0.10 0.86 0.95 0.78 0.01
53 66 83 95 97 96

ECM yield -0. l 6 0.14 -0.03 0.01 0.02 0.31
0.26 0.26 0.80 0.98 0.83 < 0.01

53 66 83 95 97 96

 

 

133

 

Table 4. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 (1
Variable Insulin Insulin Insulin Insulin Insulin Insulin
-8 d Insulin
-5 d Insulin 0.55
< 0.01
51
-2 d Insulin 0.59 0.55
< 0.01 < 0.01
50 66
2 d Insulin 0.26 0.30 0.30
0.04 0.01 < 0.01
58 77 88
7 d Insulin 0.38 0.28 0.20 0.62
< 0.01 0.01 0.05 < 0.01
61 79 91 106
14 d Insulin 0.29 0.22 0.23 0.49 0.44
0.03 0.06 0.03 < 0.01 < 0.01
58 75 89 102 105
Milk yield -0. l 3 -0.18 -0.14 -0. 13 -0.26 -0.25
0.36 0.15 0.22 0.20 0.01 0.02
52 ’ 65 82 92 97 94
Fat content 0.01 0.01 -0.08 -0.12 -0.17 -0.05
0.92 0.96 0.47 0.27 0.10 0.65
52 65 82 92 97 94
Fat yield -0.03 -0.05 -0.1 l -0.13 -0.24 -0. 15
0.82 0.69 0.35 0.21 0.02 0.14
52 65 82 92 97 94
Protein 0.03 0.26 0.08 -0.02 0.03 -0.05
Content 0.83 0.04 0.49 0.84 0.75 0.61
52 65 82 92 97 94
Protein -0.08 0.02 -0.04 -0.17 -0.25 -0.32
Yield 0.57 0.89 0.75 0.11 0.01 < 0.01
52 65 82 92 97 94
ECM yield -0.06 -0.07 -0.1 l -0.15 -0.27 -0.21
0.67 0.58 0.33 0.14 0.01 0.04
52 65 82 92 97 94

 

134

 

Table 4. (cont.)

 

 

 

 

 

 

 

 

Milk Fat Fat Protein Protein ECM
Variable yield content yield content yield yield
Milk yield
Fat content 0.15
0.12
102
Fat yield 0.60 0.87
< 0.01 < 0.01
102 102
Protein -0.36 0.13 -0.08
Content < 0.01 0.18 0.45
102 102 102
Protein 0.80 0.23 0.57 0.23
Yield < 0.01 0.02 < 0.01 0.02
102 102 102 102
ECM yield 0.77 0.72 0.97 -0.11 0.74
< 0.01 < 0.01 < 0.01 0.27 < 0.01
102 102 102 102 102

 

ILDP = Late dry period.
2LDP BCS change = -1 wk BCS — BCS within 1 wk afier moved into LDP.

3Early lactation BCS change = 6 wk BCS - -1 wk BCS.

‘Correlation coefficient.

’P-value.

“Number of observations.

135

 

Table 5. Correlations, P-values and n amongst variables in parity 3+ cows.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Days in -1 wk 3 wk 6 wk LDP BCS Early lactation
Variable LDPI BCS BCS BCS change BCS change
Days in LDP
-1 wk BCS -0.192
0.023
161‘
3 wk BCS -0.20 0.61
0.01 < 0.01
147 148
6 wk BCS -0.25 0.49 0.80
< 0.01 < 0.01 < 0.01
144 145 145
LDP BCS -0.04 0.26 0.16 0.07
change 0.65 < 0.01 0.06 0.39
161 163 148 145
Early lactation -0. 13 -0.20 0.45 0.76 -0.1 7
BCS change 0.12 0.02 < 0.01 < 0.01 0.04
143 145 144 145 145
-8 d BHBA 0.11 -0.07 -0.05 -0.06 0.08 -0.08
0.32 0.51 0.65 0.59 0.47 0.47
87 87 80 79 87 78
-5 d BHBA -0.19 -0.04 -0.16 -0.05 -0.01 0.01
0.04 0.66 0.10 0.61 0.94 0.88
118 118 108 106 118 105
-2 d BHBA 0.15 -0.10 -0.19 -0.16 -0.13 -0.08
0.10 0.27 0.04 0.09 0.14 0.42
122 124 115 113 124 113
2 d BHBA -0.01 0.11 -0.07 -0.07 -0.13 -0.12
0.92 0.17 0.43 0.44 0.1 1 0.18
151 152 142 . 138 152 137
7 d BHBA -0.17 0.09 -0.16 -0.25 -0.08 -0.33
0.04 0.30 0.06 < 0.01 0.36 < 0.01
144 146 140 136 146 136
14 d BHBA -0.09 0.18 -0.01 -0.17 -0.06 -0.33
0.28 0.04 0.90 0.05 0.49 < 0.01
139 141 138 134 141 134

 

136

 

Table 5. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

Days in -1 wk 3 wk 6 wk LDP BCS Early lactation

Variable LDP BCS BCS BCS change BCS change
-8 d NEFA 0.38 -0.23 -0.31 -0.29 -0.17 -0.19
< 0.01 0.03 0.01 0.01 0.12 0.10

87 87 80 79 ‘87 78

-5 d NEFA 0.25 -0.05 -0.13 -0.15 0.03 -0.20
0.01 0.60 0.17 0.11 0.72 0.04

118 118 108 106 118 105

-2 d NEFA 0.17 0.07 -0.25 -0.26 -0.16 -0.31
0.07 0.41 0.01 < 0.01 0.07 < 0.01

'122 124 115 113 124 113

2 d NEF A 0.01 0.12 -0.21 -0.28 0.01 -0.40
0.90 0.13 0.01 < 0.01 0.91 < 0.01

151 152 142 138 152 137

7 d NEFA 0.11 -0.01 -0.24 -0.35 0.06 -0.37
0.17 0.90 < 0.01 < 0.01 0.47 < 0.01

144 146 140 136 146 136

14 d NEFA -0.01 0.18 -0.10 -0.22 0.02 -0.43
0.89 0.03 0.23 0.01 0.80 < 0.01

139 141 138 134 141 134

-8 d Insulin -0.15 0.26 0.45 0.44 0.08 0.33
0.18 0.02 < 0.01 < 0.01 0.45 < 0.01

86 86 79 78 86 77

-5 d Insulin -0.11 0.13 0.29 0.30 0.09 0.22
0.25 0.17 < 0.01 < 0.01 0.32 0.02

116 116 106 104 116 103

-2 d Insulin -0.01 0.15 0.36 0.37 0.13 0.28
0.88 0.10 < 0.01 < 0.01 0.16 < 0.01

121 123 114 112 123 112

2 d Insulin -0.15 0.19 0.39 0.41 0.10 0.32
0.07 0.02 < 0.01 < 0.01 0.23 < 0.01

150 151 141 137 151 136

7 d Insulin -0.01 0.10 0.31 0.39 0.09 0.41
0.87 0.25 < 0.01 < 0.01 0.30 < 0.01

140 142 136 132 142 132

14 d Insulin -0.06 -0.09 0.26 0.39 0.10 0.50
0.48 0.31 < 0.01 < 0.01 0.25 < 0.01

134 136 135 131 136 131

 

 

137

 

Table 5. (cont.)

 

 

 

 

 

 

 

 

Day in -1 wk 3 wk 6 wk LDP BCS Early lactation

Variable LDP BCS BCS BCS change BCS change
Milk yield -0.11 0.31 0.04 0.01 0.18 -0.24
0.24 < 0.01 0.67 0.96 0.05 0.01

126 127 127 126 127 126

Fat content -0.13 0.27 0.10 0.05 0.06 -0.15
0.15 < 0.01 0.25 0.59 0.50 0.09

126 127 127 126 127 126

' Fat yield -0.15 0.33 0.08 0.02 0.11 -0.23
0.09 < 0.01 0.38 0.83 0.21 0.01

126 127 127 126 127 126

Protein 0.15 -0.02 -0.03 -0.04 0.02 -0.03
content 0.09 0.80 0.78 0.65 0.84 0.74
126 127 127 126 127 126

Protein -0.03 0.30 0.01 -0.03 0.13 -0.26
yield 0.70 < 0.01 0.93 0.73 0.15 < 0.01
126 127 127 126 127 126

ECM yield -0.15 0.34 0.06 0.01 0.12 -0.25
0.10 < 0.01 0.49 0.93 0.16 0.01

126 127 127 126 127 126

 

138

 

 

Table 5. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -S d -2 d 2 d 7 d 14 (1
Variable BHBA BHBA , BHBA BHBA BHBA BHBA
-8 d BHBA
-5 d BHBA 0.63 -
< 0.01
72
-2 d BHBA 0.30 0.41
0.01 < 0.01
‘ 65 94
2 d BHBA 0.22 0.26 0.36
0.04 < 0.01 < 0.01
86 116 121
7 d BHBA -0.01 0.02 0.31 0.27
0.96 0.85 < 0.01 < 0.01
81 110 118 144
14 d BHBA 0.07 0.04 0.10 0.19 0.54
0.57 0.70 0.30 0.02 < 0.01
78 107 114 139 138
-8 d NEFA 0.51 0.35 0.13 0.16 -0.04 < 0.01
< 0.01 < 0.01 0.29 0.15 0.75 0.97
88 72 65 86 81 78
-S d NEFA 0.48 0.50 0.38 0.47 0.04 0.03
< 0.01 < 0.01 < 0.01 < 0.01 0.70 0.72
72 119 94 116 110 107
-2 d NEFA 0.14 0.25 0.53 0.44 0.32 0.33
0.28 0.01 < 0.01 < 0.01 < 0.01 < 0.01
65 94 124 121 118 114
2 d NEFA 0.02 0.16 0.17 0.22 0.29 0.07
0.86 0.09 0.06 0.01 < 0.01 0.39
86 116 121 153 144 139
7 d NEFA -0.08 0.02 0.20 0.14 0.38 0.27
0.45 0.86 0.03 0.10 < 0.01 < 0.01
81 110 118 144 146 138
14 d NEFA 0.09 -0.03 0.04 0.10 0.27 0.45
0.42 0.74 0.66 0.23 < 0.01 < 0.01
78 107 114 139 138 141

 

 

139

 

Table 5. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

—8 d -5 d -2 d 2 d 7 d 14 11

Variable BHBA BHBA BHBA BHBA BHBA BHBA
Insulin —8 0.04 -0.18 -0.20 -0.04 -0.15 0.01
0.70 0.13 0.11 0.69 0.19 0.98

87 71 64 85 80 77

Insulin —5 -0.04 -0.08 -0.19 -0.15 -0.12 0.06
0.74 0.38 0.07 0.12 0.23 0.53

71 117 93 114 108 105

Insulin -2 -0.11 -0.03 -0.14 0.01 -0.14 -0.06
0.40 0.79 0.14 0.92 0.13 0.51

' 64 93 123 120 117 114

2 d Insulin 0.06 0.04 -0.09 -0.12 -0.19 -0.11
0.62 0.68 0.35 0.13 0.02 0.21

85 115 120 152 143 138

7 d Insulin 0.05 -0.05 -0.09 -0.06 -0.36 -0.30
0.64 0.63 0.32 0.48 < 0.01 < 0.01

78 107 115 140 142 134

14 d Insulin 0.03 0.03 0.01 -0.08 -0.26 -0.33
0.82 0.80 0.98 0.38 < 0.01 < 0.01

76 103 110 134 134 136

Milk yield -0.16 -0.22 -0.19 -0.26 -0.18 -0.09
0.22 0.03 0.06 < 0.01 0.05 0.36

65 92 101 120 120 118

Fat content -0.05 0.03 0.06 0.12 0.05 0.21
0.72 0.76 0.57 0.18 0.62 0.02

65 92 101 120 120 118

Fat yield -0. 12 -0.04 -0.08 -0.08 -0.08 0.08
0.33 0.70 0.43 0.38 0.38 0.41

65 92 101 120 120 118

Protein -0.22 -0.09 -0.07 0.02 0.01 -0.01
Content 0.08 0.39 0.49 0.86 0.96 0.94
65 92 101 120 120 118

Protein -0.31 -0.19 -0.21 -0.24 -0.17 -0.08
Yield 0.01 0.06 0.03 0.01 0.07 0.42
65 92 101 120 120 118

ECM yield -0.17 -0.08 -0.12 -0. 14 -0.1 l 0.04
0.18 0.43 0.24 0.13 0.24 0.70

65 92 101 120 120 118

 

 

140

 

Table 5. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 (1
Variable NEFA NEF A NEF A NEFA NEF A NEFA
-8 d NEF A
-5 d NEF A 0.58
< 0.01
72
-2 d NEFA 0.40 0.62
< 0.01 < 0.01
‘ 65 94
2 d NEFA 0.41 0.34 0.38
< 0.01 < 0.01 < 0.01
86 116 121
7 d NEFA 0.16 0.19 0.41 0.40
0.15 0.05 < 0.01 < 0.01
81 110 118 144
14 d NEF A 0.34 0.27 0.33 0.28 0.37
< 0.01 < 0.01 < 0.01 < 0.01 < 0.01
78 107 114 139 138
-8 d Insulin -0.48 -0.47 -0.42 -0.48 -0.24 -0.24
< 0.01 < 0.01 < 0.01 < 0.01 0.03 0.04
87 71 64 85 80 77
-5 d Insulin -0.40 -0.45 -0.44 -0.26 -0.32 -0.15
< 0.01 < 0.01 < 0.01 0.01 < 0.01 0.12
71 117 93 l 14 108 105
-2 d Insulin -0.24 -0.25 -0.52 -0.33 -0.25 -0.14
0.06 0.01 < 0.01 < 0.01 0.01 0.15
64 93 123 120 117 114
2 d Insulin -0.33 -0.28 -0.28 -0.46 -0.33 -0.33
< 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
85 115 120 152 143 138
7 d Insulin -0.10 -0.13 -0.28 -0.34 -0.42 -0.32
0.40 0.18 < 0.01 < 0.01 < 0.01 < 0.01
78 107 115 140 142 134
14 d Insulin -0.22 -0.18 -0.28 -0.26 -0.38 -0.38
0.05 0.07 < 0.01 < 0.01 < 0.01 < 0.01
76 103 110 134 134 136

 

141

Table 5. (cont.)

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 (1

Variable NEFA NEFA NEFA NEFA NEFA NEFA
Milk yield -0.15 -0.20 -0.13 0.04 -0.08 0.13
0.22 0.05 0.18 0.64 0.37 0.15

65 92 101 120 120 1 18

Fat content -0.20 -0.10 -0.03 0.03 -0.13 0.08
0.10 0.34 0.74 0.74 0.16 0.41

65 92 101 120 120 l 18

Fat yield -O.21 -0. 16 -0. 10 0.04 -0. 14 0.13
0.09 0.12 0.32 0.63 0.13 0.15

' 65 92 101 120 120 118

Protein 0.17 0.05 0.13 0.08 -0.01 0.03
Content 0.17 0.61 0.18 0.38 0.89 0.74
65 92 101 120 120 1 18

Protein 0.02 -0.1 l 0.01 0.13 -0.07 0.20
Yield 0.85 0.29 0.92 0.15 0.42 0.03
65 92 101 120 120 1 18

ECM yield -0.18 -0. 17 -0.08 0.06 -0.12 0.16
0.16 0.10 0.41 0.50 0.18 0.09

65 92 101 120 120 1 18

 

 

142

Table 5. (cont.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-8 d -5 d -2 d 2 d 7 d 14 d
Variable Insulin Insulin Insulin Insulin Insulin Insulin
-8 d Insulin
-5 d Insulin 0.69
< 0.01
70
-2 d Insulin 0.37 0.71
< 0.01 < 0.01
‘ 63 92
2 d Insulin 0.48 0.42 0.37
< 0.01 < 0.01 < 0.01
84 113 119
7 d Insulin 0.21 0.20 0.29 0.38
0.06 0.04 < 0.01 < 0.01
77 105 114 139
14 d Insulin 0.34 0.29 0.32 0.49 0.54
< 0.01 < 0.01 < 0.01 < 0.01 < 0.01
75 101 110 133 130
Milk yield 0.06 0.03 -0.07 -0. l 3 -0.06 -0. 18
0.66 0.76 0.46 0.17 0.53 0.06
64 90 100 119 116 117
Fat content 0.17 0.35 0.16 0.05 0.03 -0.13
0.18 < 0.01 0.11 0.60 0.73 0.17
64 90 100 119 116 117
Fat yield 0.10 0.25 0.05 -0.04 -0.03 -0.19
0.41 0.02 0.65 0.68 0.72 0.04
64 90 100 119 116 117
Protein 006 0.17 0.08 0.01 0.03 -0.09
Content 0.65 0.1 1 0.41. 1.00 0.78 0.35
64 90 100 119 116 117
Protein -0.01 0.15 —0.04 -0.15 -0.08 -0.27
Yield 0.92 0.17 0.71 0.11 0.39 < 0.01
64 90 100 119 116 117
ECM yield 0.08 0.22 0.01 -0.07 -0.06 -0.22
0.52 0.04 0.92 0.42 0.55 0.02
64 90 100 119 116 117

 

143

Table 5. (cont.)

 

 

 

 

 

 

 

Milk Fat Fat Protein Protein ECM
Variable yield content yield content yield yield
Milk yield
Fat content 0.31
< 0.01
127
Fat yield 0.77 0.82
< 0.01 < 0.01
‘ 127 127
Protein -0.38 0.14 -0.18
Content < 0.01 0.12 0.04
127 127 127
Protein 0.78 0.39 0.69 0.21
Yield < 0.01 < 0.01 < 0.01 0.02
127 127 127 127
ECM yield 0.86 0.70 0.98 -0.19 0.81
< 0.01 < 0.01 < 0.01 0.03 < 0.01
127 127 127 127 127

 

 

lLDP = Late dry period.
2LDP BCS change = -1 wk BCS - BCS within 1 wk after moved into LDP.
3Early lactation BCS change = 6 wk BCS - -1 wk BCS.
‘Correlation coefficient.

’P-value.

6Number of observations.

144

 

CHAPTER 6

DISCUSSION AND IMPLICATIONS

Corn Grain Supplementation in the Late Dry Period

The main hypothesis of partially replacing corn silage with corn grain was that it
would improve energy status of periparturient dairy cows. The SC diet reduced plasma
BHBA concentrations and tended to increase insulin concentrations prepartum.
However, there was no change in plasma NEFA concentrations during the same time.
Plasma NEF A are substrates for ketone body synthesis. NEFA are extracted from the
blood by the liver at a rate proportional to plasma NEFA concentrations (Bruss et a1.
1993). If ketone body synthesis was less in cows fed the SC diet, what happened to the
additional NEFA in cows fed the SC diet? In hepatic tissue, NEFA can be oxidized
completely to C02 and H20, partially to ketones or re-esterified as TG (Bruss, 1993). TG
can either be exported as VLDL or stored in hepatic tissue. Excess storage of TG in
hepatic tissue can result in fatty liver and reduced hepatic function (Strang et al., 1998).
The other possible alternative is that plasma NEF A were not extracted from blood by the
liver at equal rates between treatments. However, no research supports this possibility. If
complete oxidization accounted for the remaining NEFA in cows fed the SC diet, then
the decrease in ketones may have been beneficial to cows. However, if remaining NEFA
were re-esterified to TG and stored in the liver, then the reduction in ketone production

may have been detrimental to hepatic function.

145

 

 

This study identified several interactions involving parity. In general, it appeared
that parity 3+ cows benefited from the SC diet, whereas the SC diet had no or negative
effects on parity land 2 cows. It is possible that parity 3+ cows benefited the most from
the SC diet because they had the largest metabolic demands in early lactation. In general
and in this experiment, cows of parity 3+ yielded more milk than those of parities l and 2
and therefore, likely had increased energy requirements. Generally, DMI increases to
help satisfy nutritional demands, but DMI in early lactation may be compromised.
Therefore, improving energy status of more mature, higher yielding cows may show
more benefits than for less mature, lower yielding cows. However, the data does not
fully support this interpretation. If plasma NEF A concentrations postpartum are used to
indicate metabolic demands and energy status, then parity 1 cows were in more negative
energy status in early lactation. Dyk (1995) also reported that parity 1 cows had higher
plasma NEF A concentrations prepartum compared with any other parity. Interestingly,
NEF A concentrations in cows of parity 2 and 3+ peaked at 2 (1, whereas plasma NEFA of
parity 1 cows peaked at 7 (1. Furthermore, parity 1 cows had increased BHBA
concentrations in early lactation compared with parities 2 and 3+. Although liver
tryglyceride were not measured, it would have been interesting to know how parities
differed in TO accumulation in hepatic tissue. The cause of differences observed in
treatment effects on parity is not evident, but cows of different parities appear to be in
different physiological states during the periparturient period.

The results of this experiment do not fully support the original hypothesis of
improving energy status by supplementing corn grain in the late dry period. One reason

could be the smaller than expected differences observed in chemical composition of diets.

146

 

 

Diets were formulated to be substantially different in NFC and energy contents, but
analysis of TMR samples taken weekly throughout the experiment showed that diets were
more similar than originally formulated. Perhaps, treatment effects would have been
more evident if corn grain replaced a larger percentage of corn silage in the SC diet.
Results also showed that the effects of treatment varied depending upon parity. Most
nutritional studies involving late pregnant dry cows have not considered or addressed
differences in parities. Future research should characterize these differences and the
possible mechanisms causing the differences.

Implications of this research are that increasing the dietary corn grain content
during the late dry period will benefit cows of parity 3+. However, increasing the corn
grain content fed to cows of parity 1 and 2 during the late dry period may not be
advantageous. However, differing responses of parity to treatment may only apply to

cows in the farm studied.

Altering Length of the Late Dry Period

One hypothesis for increasing the length of the late dry period was that cows
would gain more body condition during this time. Cows in L tended to have greater
gains in BCS in the late dry period compared with cows in S. However, the differences
observed in BCS changes prepartum were small (0.08 and 0.14 for S and L, respectively).
It is unlikely that the small BCS changes observed between treatments had any
physiological impact on postpartum energy status, health, or production. It was surprising
that feeding a diet with higher energy and nutrient densities for longer than 26 d

prepartum did not result in greater BCS changes prepartum. Several studies have

147

reported large increases in BCS changes prepartmn when cows are fed a higher energy
diet during the entire dry period (Boisclair et al., 1986, Fronk et al., 1980). Perhaps cows
needed to be fed the higher energy diet during the entire dry period to promote
appreciable body condition change. Additionally, cows with lower BCS upon entering
the late dry period may have gained BCS more readily. BCS prepartum averaged 3.80,
3.57, and 3.63 in cows of parity 1, 2 and 3+, respectively. BCS gains in the late dry
period were 0.11, 0.20, and 0.01 in cows of parity 1, 2, and 3+, respectively. Indeed,
parity 2 cows gained the most BCS prepartum, but parity 1 cows had greater increases in
BCS compared with parity 3+ cows.

A second hypothesis was that increasing length of the late dry period would
improve energy status in the periparturient period. DMI was not measured and therefore,
energy intake and balance could not be calculated in this study. However, the
combination of blood variables, as proxies for energy status, and BCS change postpartum
can be used as indicators of energy status. Cows in L tended to have lower plasma NEF A
and higher insulin concentrations postpartum, and reduced BCS loss from parturition to 3
wk postpartum compared with cows in S. This suggests that lipolysis was reduced (as
measured by plasma NEFA) in cows in L, perhaps a result of increased plasma insulin
concentrations. Ruminal papillae may have been more developed and allowed for
increased VFA absorption in early lactation and improved energy status. As mentioned in
Chapter 3, improvements in energy status in early lactation may spare amino acids
needed for glucogenesis, thereby supplying the mammary gland with additional
substrates for protein synthesis. Increased VFA removal fi'om the rumen also may have

improved yields of microbial protein that could have contributed to amino acid

148

availability to the mammary gland. Indeed, cows in L had higher milk protein content
during the first 60 DIM compared with cows in S.

The differences observed between farms in milk production, health, and
reproduction are likely caused by the differences in management between farms.
Although just speculation, differences in DMI both pre- and postpartum could have
contributed to the observed discrepancies between farms. The diets fed pre- and
postpartum were similar in ingredient composition and chemical analysis, but of course
these values do not account for feed bunk management and DMI which may have varied
between farms. Additionally, the diets fed during the early dry period or during late
lactation could have influenced our findings. However, the diets fed during the early dry
period (i.e., prior to treatment diets) were similar in chemical composition. Therefore, it
is unlikely that diets fed during the early dry period biased the results of this study.

Further research should measure DMI and investigate changes in hepatic
metabolism of energy substrates. Changing the length of time cows are fed a higher
energy diet could influence enzymes and receptors in both hepatic and adipose tissue.
More basic research should try to identify these mechanisms and the time it takes to
modify or regulate the specific enzymes or receptors.

The implications of this research are that feeding more nutrient-dense diets during
the late dry period may improve energy balance in early lactation. However, several
studies have shown detrimental effects of excessive BCS at parturition. Therefore, BCS
should be considered before feeding to promote gains in body condition during the dry
period. For example, cows entering the dry period with BCS below 3.25 may benefit

from body condition gain during the dry period. The negative effects of lengthening the

149

late dry period observed in Farm 1 are probably a result of management and are unlikely
to occur on all farms; similar effects were not detected in Farm 2. Manipulation of
management or nutritional strategies prepartum will elicit effects that should be most
evident in early lactation. Therefore, the present study showed that increasing the length
of the late dry period was more advantageous than late dry periods of the traditional 2 to

3 wk in length.

Correlations Among Variables

Increased BCS at parturition was correlated positively with milk yield and
composition in parity 3+ cows only. This suggests that cows of parity 3+ rely more
heavily upon adipose tissue reserves as an energy source in early lactation compared with
cows of parities 1 and 2. Indeed, parity 3+ cows had higher plasma NEFA concentrations
postpartum compared with parity 2 cows, but had lower NEFA concentrations compared
with parity 1 cows. The underlying question is what happened to the NEFA in parityl
cows if they were not being used for milk or milk fat production? Future research should
answer this question and identify these mechanisms.

The other surprising correlation was with plasma BHBA in parity 2 cows. Unlike
parity 1 and 3+ cows, plasma BHBA concentrations prepartum were not correlated with
NEFA concentrations prepartum. In addition, plasma concentrations of insulin and
BHBA postpartum were not correlated in cows of parity 2, but were correlated negatively
in parity 1 and 3+ cows. NEFA can be used as substrates for ketone synthesis.
Therefore, increased NEFA concentrations should result in higher plasma BHBA

concentrations. Indeed, plasma NEFA concentrations were correlated positively with

150

 

BHBA concentrations throughout the periparturient period in parity 1 and 3+ cows.
Perhaps, parity 2 cows had increased hepatic capabilities to oxidize NEFA or export them
as VLDL. This might explain the lower plasma BHBA concentrations postpartum in
cows of parity 2. However, parity 2 cows also had lower plasma NEFA concentrations
during the periparturient period. Maybe the plasma NEFA concentrations were low
enough so that the liver and extra-hepatic tissue could metabolize them without resorting
to ketone synthesis. This also may explain why plasma insulin concentrations had no
antagonistic effects on plasma BHBA concentrations postpartum. Reducing plasma
NEFA concentrations via insulin would not cause reductions in BHBA if a substantial
amount of NEFA are not being metabolized to BHBA. Future research needs to identify
the exact mechanisms causing the differences in energy metabolism among parities.

The implications of this analysis are that cows of different parities are in different
metabolic states during the periparturient period, and need to be managed and fed
accordingly. Unfortunately, the exact optimal ways of feeding and managing cows based

on differences in metabolism have not been elucidated fully.

151

 

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