PAUL ANDREW HAIG. The University of Guelph. The Faculty of Graduate Studies EFFECT OF DIETARY NLTROGEN SOLUBILITY ON NITROGEN LOSSES

EFFECT OF DIETARY NLTROGEN SOLUBILITY ON NITROGEN LOSSES FROM LACTATING DAIRY COWS A Thesis Presented to The Faculty of Graduate Studies of The U...
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EFFECT OF DIETARY NLTROGEN SOLUBILITY ON NITROGEN LOSSES

FROM LACTATING DAIRY COWS

A Thesis

Presented to

The Faculty of Graduate Studies of

The University of Guelph

by

PAUL ANDREW HAIG

In partial fulnlment of requirements for the degree of Master of Science Augusî, 1999

O Paul A, Haig, 1999

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ABSTRACT

EFFECT OF DIETARY NLTROGEN SOLUBILITY ON NITROGEN LOSSES FROM LACTATING DAlRY COWS

Paul Andrew Haig University of Guelph, 1999

Advisorr Dr. B. W- McBride

The objective of this thesis was to determine the effect of dietary nitrogen

solubility on the route, amount and form of nitrogen losses from lactating dajr cows and whether the Comell Net Carbohydrate and Protein Systems (CNCPS) mode1 adequately describes the nitrogen partitioning. The arnount and form of nitrogen in the urine, feces, blood and milk were measured and compared to CNCPS predictions. The main effect of altering protein solubility was the partitioning of nitrogen between the urinary and fecal excretion routes. Urinary nitrogen excretion had a

significant (P~0.01) linear relationship with soluble nitrogen intake (~'=0.41). The CNCPS prediction for total fecal nitrogen was closely related (R' = 0.80) to observed, but the predicted fecal nitrogen fractions did not agree with the experimental values. Plasma

urea nitrogen and mïIk urea nitrogen estimates fiom the CNCPS were unrelated to the

observed.

1 would lEke to k t and foremost thank my wife Cathy, and our sons Benjamin

and Jacob, for their enduring support and patience during the long hours that took my

attention away fiom them. 1would Like to thank my advisor Brian McBride who has provided continuous

support and encouraged m e to strive towards my goal. The support and kuid words of advice of my other cornmittee members: Jack Dekkers, Jock Buchanan-Smith, Gordon

Surgeoner and John Cant, were greatiy appreciated. Appreciation must go to the members of my lab group who provided intellectual and social stimulation to make this experience more enjoyable. My special th&

to Tom

Wright, Paul Luimes, Stefano Moscardini, Jim Maas, Barbara Green, and Tim Mutsvangwa. My thanks also to my feilow graduate students, staff of the Ponsonby and Elora Research Stations, and the research technicians of the Department of Animal and Poultry Science who helped me with this project. 1 would Like also to acknowledge the financial assistance for this project fiom the

Dairy Farmers of Ontario, OMAFRA and of course my employer A g r i b d s hirina Canada Inc. who not only financiaiiy contnbuted to my research, but were very supportive of the t h e and effort required to pursue my goal.

TABLE OF CONTENTS Page

CEtAPTER 1 GENERAL INTRODUCTION .................................. I

CBAPTER 2

LITElWïURE REVIEW ........................................

4 21c o n .......................................... 4 2 2 Protein Evaluation Systems ........................ 4 2.2.1 NRC System .............................. 5 2.2.2 PD1 System .............................. 9 2 2 3 CNCPS System ........................... 12 2.3 Protein SoIubility .................................... 18 2.4 Nitrogen Excretion ...................... . . . ...... 20 2.4.1 Fecai Nitrogen ............................ 22 2.4.2 Urea Nitrogen ............................ 23 2.4.3 huine Nitrogen ........................... 25 2-5 Manure Nutrient Modeling......................... 28 2.6 Summary ............................................. 29 2.7 Objectives and Hypothesis ......................... 30

CHAPTER 3 EFFECTS OF VARYING DIETARY NITROGEN SOLUSILITY ON NITROGEN UTILIZATION AND EXCRETION INDAIRY CATTLE ............................ 31 3.1 Introduction ...........................................31 3 -2 Material and Methods .............................. -32 Experimental Design ............................32 Animds ................................ , , , , ...33 Diets ............................................... 33 Sample Collection ............................... 38 Chernical Analysis .............................- 4 0 Statistical Analysis ..............................42 3-3 Results and Discussion .............................. 43 Mode1 Inputs ..................................... 43 Diet ................................................ 43 Nitrogen Balance ................................ 47 Feces .................*................... . .. 51 Apparent Digestibility .......................... 54 Urine .............................................. 56 Blood ............................................. 61 Milk ....................... ............. 63 CNCPS Predîctions ............................. 65

CBAPTER 4 EVALUATION OF EXPERIMENTAL OBSERVATiONS mm THE CORNELL NET CARBOHYDRATE AND PROTEIN SYSTEMS MODEL PmDICTIONS ..,..,.,,.....- ..,,- - .-.- 66 -- - ..-- 66 4.1 Introduction ..-...- .,,*. ........., ,...,,-- -. 4.2 Model Evaluation ............................... .---67 Model Parameters Outputs ..................... 67 Animal Factors ..- - - .,- ...- ,,- ................. 79 Dietary Factors .................... .,......- .... 80 Blood and M i k Factors .,.,,.- - .- ..- ...,.....-.97 Feces and Urine Factors .-- .- .--. .- - - - -.,.,,-...101 4.3 S m a r y .............-.....---.--108 0,- -0-.*o.-*o.*.*

CHAPTER 5 OVERALL DISCUSSION AND CONCLUSIONS -.--. .... 1 10 5.1 General Discussion ................................. 110 5.2 Conclusions ...,.,......,.....,...,....- ,.,..- - -..-.- 1 13

APPENDIX 1 EFFECT OF HIGH AND LOW SOLUBILITY DIETS ON DRY MATTER INTAKE AND MILK PRODUCTION OF LACTATING DAIRY COWS .- - ...... 125

APPENDIX 2 INDMDUAL DATA MEASUREMENTS AM> CNCPS MODEL PREDICTIONS .............................134 APPENDIX 3 CNCPS DEFAULT VALUES FOR eNDF AND CARBOHYDRATE AND PROTEIN kd RATES USED IN THE EVALUATION OF THE EFFECT OF DIETARY NITROGEN SOLUBILITY ON NITROGEN EXCRETION ,,..c,..,....-.,...-.-.......-.-..~..,....,.140

LIST OF TABLES Table 2. 1

3.1

Page Annual nitrogen flow in a daüy cow with a total nitrogen intake of 175 kg/year .............................................................

10

Chemical analysis of forages used in diets for evaluating the effect of dietary nitrogen solubility on nitrogen losses from lactating daky catile ......................................................

35

3 -2

Composition and chernical analysis of treatment concentrate pellets used in diets for evaluating the effect of dietary nîtrogen solubiIIty on nïtrogen losses fiom lactahg dajr cattle. ............ 36

3 -3

Chemical analysis of total diets used for evaluating the effect of dietary nitrogen solubility on nitrogen losses fkom lactating

dajr caîtie ................................................................

37

Animal descriptions used as inputs for the Corneil Net Carbohydrate and Protein System mode1 evaluation ...............

44

Chernical composition of the dietary nitrogen intake and corresponding CorneII Net Carbohydrate and Protein System proteinfbctions ..........-............................................... 46 Nitrogen balance rneasurements on a g/day and percentage of dietary nitrogen intake bais ......................................... 49

Fecal Chemical Composition and corresponding Cornell Net Carbohydrate and Protein System protein fractions ................. 52 Apparent digestibilityof dietary components including the Corne11 Net Carbohydrate and Protein System protein fiactions ........... 55 Chemical composition of the urinary nitrogen fraction including urea, purine derivatives and creatinine .................

58

Blood parameter composition for the Corneil Net Carbohydrate and Protein System model evaluation ..............................

62

MiUr chemical composition and protein fiactions for the Comell Net Carbohydrate and Protein System mode1 evaluation .........

64

Cornell Net Carbohydrate and Rotein System model parameter outputs .......................................................

68

TABLE OF FIGURES Figure 2.1

Page Schematic of the Corneil Net Carbohydrate and Protein System protein fiactions and chemical composition ........................

13

Observed PUN 1eveIs based on predicted PUN levels ............... 72 Observed MUN Levels based on predicted MUN levels ............. 74 Observed MUN levels based on observed PUN levels ............... 75 Measured fecal nitrogen based on CNCPS fecd nitrogen prediction ...................................................................

77

Measured fecal C nitrogen based on predicted total fecal C nitrogen .....................................................................

78

Fecal dry matter output based on dry matter intake ................... 82 Measured fecal nitrogen output based on dry matter intake ......... 83

Urinafy purine derivative excretion based on dry matter intake ... 85 Urinary nitrogen excretion based on intake soluble protein nitrogen ....................................................................

87

Observed fecal nitrogen based on regression of UIP and D P nitrogen ..................................................................

89

CNCPS fecal nitrogen based on regression of UIP and DIP nitrogen ..................................................................

91

Miuc true protein nitrogen. NPN. and total nitrogen based on DIP-N ...................................................................

93

Millc true protein nitrogen, NPN. and total nieogen based on UIP-N ....................................................................

94

Measured PUN based on dietary SIP nitrogen .....................

96

Urine nitrogen excretion based on m e a s d PUN levels .........

99

Urinary urea nitrogen concentration based on measured PUN ...

LOO

4.17

Fecd dry matter and nitrogen based on predicted bacterid MP .... 104

4-18

Fecd dry matter and nitrogen based on predicted MP UIP .- ...- - .. LOS

4.19

Unc acid and total purine derivatives based on bacterial A Gaction - -- -...-...- - .-, ... -.-. -.- -..-- - - - - - - -- .. . ... .. ....-. L07

-

GENERAL INTRODUCTION

hiblic pressure to reduce the nitrogenous pollution impact fiom animai agriculture sources is an important issue. There is increased interest in reducing nutrient Losses in waste products, not only fiom a production efficiency viewpoint but also to protect the environment. If guideluies for manure storage, application method and timing, in conjunction with good land stewardship and nutrient management planning are not

sufficient to prevent contamination of the soil and water, then stringent legislation limiting production capacity could be dorced. Considerable research bas been cooducted investigating the role of nutrient management in reducing the environment burden from animal production, including dairy,

particularly in European countries with their small land base (see review by Tamminga, 1992). Provinces in Canada are currently developing Legislation that in the fùture may

restrict d a j r fmers according to their ability to safely manage their waste products to avoid environmental contamination (OMAF, 1994). Countries in Europe and parts of the

United States have strict Legislation which limits the allowable nitrogen and phosphorus levels applied to the soil (Van Hom et al., 1996) and ammonia losses fiom the barns (Korevaar, 1992). An accurate prediction of the nutrient content of wastes produced by different diets would be beneficial in designhg waste storage and removai systems and field

fertiher recommendations,

Nitrogen in daky cattle waste is potentially hazardous to the envüonment depending on the form, volatility and how it is stored and applied to the soil. Nitrogen in the fomi of urea can be converted to ammonia by urease cornrnonly found in the soil and farm

environment. Ammonia c m then be lost to the atmosphere via volatilization or m e r converted to either nitrate (nitrification), which is not absorbed by the soil but can be taken up by plants or leached into the ground water, or to fiee nitmgen (denitrification). These

conversions rnay cause the release of intermediates such as NO, Na,and N20, which may be harmful to the ozone Iayer. U M ~is the most variable and largest potential source of

nitrogen loss, particdariy in the readily degradable inorganic

~O~LIIS.Fecal

nitmgen is

g e n e d y bound to undigesteci cell wails in the organic component. This can be mineralized in the soil and released slowly for plant uptake-

Dairy manure production and composition is ofien estirnated fiom standardized tables such as the ASAE Standards (1991), MAFF (1991) and the Canadian Animal Waste Management Guide (Agriculture Canada, 1994). These tables are based on mean data fkom a wide range of sources with values generally reported by weight or age of the animal. The large variations in these values can be related to differences in animal performance levels, level of intake, type and quality of diet and feed management, and environmental factors affecting water and food intake (ASAE Standards, 1991, Holter

and Urban, 1992, Van Hom et al., 1994). The difference between intake aitrogen and rnik nitrogen has been used as a practical estimator @ 5 to I L%)

for m u r e nitrogen

(Bulley and Holbeck, 1982, Safley et al., 1986, Van Hom et al., 1996). Computerized feeding and milking systems aliow for quick nitrogen excretion calculations on an individual animal basis and can take hto account nitrogen fkom body weight changes.

However, this method remes assuming a fixed ratio of feces to urine production (Safley et al., 1986). This ratio is variable

40%) and particuiarly affected by factors that

influence water Ïntake (Morse et al., 1994). Ako, it does not estimate the partitioning of nitrogen between urine and feces, which effects the volatilïzatioa and availability of manure nitrogen for plant uptake. A more ngorous approach in determining nitrogen excretion is recpired to idente

the amount and type of nitrogen king excreted. 'ïhis thesis examines the effect of manipulating the form of dietary nitrogen on nitrogen utilization and exCretion- Thk wili aiiow for better characterization of potential wastes produced over various dietary regimen for dairy cattle.

2.1

Introduction

An objective of Canadian dairy producers is to maximize the amount of intake

protein converted into milk, due to the premium paid for milk protein under the multiple component pricing systern. Furtherrnore, cost-efficient producers will want to avoid excess loss of nitrogen through feces and urine, which must be stored and handed properly to prevent contamination of the environment. Dairy cattle diets must be evaluated as to their overall infiuence on animal nitrogen balance to assess the impact on whole f m nutrient management. The objective of this review is to examine the

literature relating to nitrogen utilization and excretion in dairy cattle and the potential impact on the environment.

2.2

Protein Evaluation Systems

Research on dietary protein utilization has become an important topic, not only fiom a nutritional viewpoint, but also due to the substantial impact on diet cost and waste production. Current ruminant protein evaluation systems have identified the need to characterize die-

proteh components and their potential losses h m the animal. This

has resulted in different approaches to descriie Illzninal degradation and microbial

growth, intesiinai digestion, nitrogen recychg and excretion of nitrogen denved fiom

endogenous sources (NRC, 1985). This review investigates three different protein evaluation systems that have been utilized extensively worldwide for balancing dahy cattle rations; 1) the National Research Council (NRC) AbsorbabIe Protein system, 2) the

French PD1 (protein digested in the s m d intestine) system, and 3) the Corneil Net Carbohydrate and Protein System (CNCPS)mode1 system.

2.2.1

NRC System In North America, the NRC publications for daky cattle feeding are a leading

source of nutritionai information to the industry- The sixth revised edition of the NRC nutrient requirements of dajr cattle (NRC, 1988), updated NRC (1989), introduced the concept of metabolizable or absorbable protein, the amount of protein digested in the postrurninal portion of the digestive tract, to replace total crude protein requirements used in the NRC (1978) edition, This conceptual fkmework was first described in the

publication entitled 'Xuminant Nitrogen Usage" (NRC, 1985). The absorbable protein concept m e r s nom one based on digestible protein in that absorbed ammonia, from excess protein degradation in the m e n , would be included in a digestible but not an absorbable protein system. Thus the digestible crude protein systems did not account for the potentialiy large and variable loss of nitrogen in the urine (Dewhurst and Thomas, 1992). The absorbable protein approach bases protein requirements on amino acids

absorbed fiom the smaii intestines. It was important to characterize dietary protein as being ruminally degradable intake protein @Il?)

or undegradable intake protein (üIP) to

account for amino acids denved fiom dietary escape protein or microbial protein.

Undegradability values obtained fiom in vivo and in situ research fiom numerous sources were surnmarized in NRC (1989). These values were used to calculate the reported UIP

and DIP requirements. Rumen escape protein and microbial m e proteîn are both assumed to have a true digestibility of 50% in the smail intestine. Microbial crude protein is comprised of 20% nucleic acid nitrogen and 80% true protein (NRC, 1989). Nucleic acids are assumed to be 100% digestible, but are completely excreted. Microbiai growth in the m e n (g N/day) is estimated fiom energy intake (-3093 + I 1.45 NE3 (NRC,1989). This

linear regression equation has a negative intercept, which leads to low microbial yield estimates at low dry matter intakes. The equation assumes there is unlimited rumen available nitrogen in relation to rumen available energy. Microbial growth in the rumen

requires nitrogen fiom either DIP or a net influx of endogenous or recycleci urea fiom saliva or across the rumen wall (NRC, 1985). The NRC system back-calcdates the requîrement for UIP and DIP by estimating the microbial growth fiom the available energy, and then calculating the amount of DIP needed to generate this growth. The diffierence between the animal's requirement for absorbable protein and that provided by the microbial protein must then be supplied nom the UIP portion. The accurate estimation of microbial growth is a crucial component of a protein system because 30 to 100% of the animal's rnetabolizable amho acids can be suppiied fiom rnicrobid tnie

protein (NRC, 1985). A major consideration of any protein system is how it handles the aspect of

endogenous nitrogen. There are several approaches used in different protein systems, with varying leveis of complexity, which attempt to account for the loss of endogenous

nitrogen (Waldo and Glenn, 1982, NRC, 1985). Endogenous nitrogen lost through the

feces is commody called metabolic fecal nitrogen. This c m include nitrogen entering the

gastrointestiual tract fiom urea, bile, mucous, enzymes and sloughed epithelial cells fiom the gastrointestinal Lining (Swanson, 1982). Measuring endogenous nitrogen is difficult

due to the continuous secretion and absorption dong the gastrointestinai tract and the bacterial action in the rumen and cecum (Swanson, 1982). In the NRC (1989) system, the fecal metabolic nitrogen requirement was separateci from the other maintenance

cornponents. This was to facilitate the use of indigestible dry matter as a fûnction for fecal metabolic nitrogen, rather than body weight

0,which is used for the

urinary

endogenous protein and scurf protein requirements. An equation of 0.09 multiplied by the indigestible dry matter (IDM) was proposed with the assumption that average diet indigestibility is 33%. Endogenous urinary protein is caiculated as the nitrogen loss on a nitrogen fiee diet (Swanson, 1977) and expressed as 2.75

woJ(g/day).

Scurf protein loss

is composed rnainly of skin secretions, haïr and scurf. Swanson (1977) summanzed calorimeter experiments to derive the equation to express scurf protein as 0.2 (g/day). The quantification of these nitrogen losses is important for deriving protein

requirements that accurately account for the metabolic processes in the animal. A fecal metabolic protein fraction is necessary for incorporation into predictions of fecai nitrogen

excretion to correspond to observed data, and to avoid underestimating crude protein requirements (NRC, 1985). Another important source of nitrogen in a protein evaluation system is recycled nitrogen. Recycled urea nitrogen rnay be a significant source of rumina1 nitrogen input, particularly when rumen ammonia is deficient (Kenaedy and Milligan, 1980). Nitrogen

can be recycled via the saliva and transfer across the rumen epithelium and intestinal

tracts in the form of urea, and by the capture of endogenous nitrogen (NRC, 1985). Factors that may affect the amount of recycled nitrogen include concentration of blood urea nitrogen (BUN), rumen ammoaia concentration, and rumen available energy Level for microbial production (Kennedy and Milligan, 1980). NRC (1 989) assumes recycied

nitrogen can be as much as 70% of the nitrogen entering the m e n when protein intake is low, and that when intake is high, the contriiution of recycied nitrogen decreases. The NRC niminant nitrogen subcommittee (NRC, 1985) reporteci an equation of Y = 121.7 12.0 1 X + 0.3235

x2;Y is urea oitrogen recycled as a percentage of nitrogen intake and X

is crude protein intake as a percent of diet dry matter- This regression equation was developed fiom data with sheep (Kennedy and Milligan, 1980), and may not reflect the situation of a lactating dairy cow where mille synthesis can act as a nitrogen si&, reducing urea synthesis and PUN and decreasing nitrogen recycled back to the m e n (NRC, 1985). Thus the Nutrient Requirements for Dairy Cattle (NRC, 1989) maintained

the equation for recycled protein as 15% of intake protein. This demonstrates the need to M e r investigate the sources of variability around nitrogen recycling to and leaving fiom the rumen. Reductions in nitrogen lost nom the rumen, due to the incomplete capture of microbial degradation products for synthesis, through dietary manipulation and feeding management have been reviewed (Tamminga and Verstegen, 1991, Sniffen and Robinson, 1987). Rumen nitrogen loss can be reduced by i o w e ~ g the dietary nitrogen Level, by reducing nimen degradation or by improving microbial protein synthesis efficiency fiom degradable protein (Tamminga, 1992). The rate of protein degradation in the rumen does not always match the rate of microbial nitrogen capture. This results in

accumulation of ammonia ui the rumen, therefore synchronizing carbohydrate, the eoergy source for microbes, and protein degradation in the rumen will maxunize microbial production (Hoover and Stokes, 1991). Tamminga (1992) descnbed the flow of nitrogen in a dairy cow producing 6250 kg of mik per year (Table 2.1) and stated that 10 to 15%

of the total nitrogen intake is lost through inefficiency of amino acid utilization at the tissue level. A functional protein evaluation system must represent the impact of dietary factors such as degradability and undegradability on the nimen environment and the flow of nitrogen throughout an animal.

2.2.2

PD1 System The French PD1 system (Vérité et al., 1979) also characterizes dietary protein as

being degraded in the rumen by microbes or bypassed to the small intestines. This information is used to estirnate the amount of utilizable amino acid absorbed fiom the small intestine. Rumen degradability is based on measurements of protein solubility in mineral buffer, and in some cases, ammonia production in vitro, which is then related to data on nitrogen flows fkom cannuiated animals (Vérité et al., 1979, NRC, 1985). Protein

solubility was found to be not as good an indicator of protein degradability as in vitro incubation with rumen fluid. Protein solubility was considered more suitable for routine testing and gave satisfactory agreement with in vitro techniques across most ingredients (NEC, 1985). Solubility provided lower degradability estimates for cereal grains, beet puip, and soybean products and higher estimates for beans and peas thus corrected

solubility estimates have been used.

Table 2-1 AnnuaI Nitrogen Flow in a Daky Cow with a total Nitrogen Intake of 175 kglyear

I

NLTROGEN(kg Iyear)

URINE

FECES

UNDIGESTED

25

ENDOGENOUS

25

15

NUCLEIC ACID

15

MAIMENANCE

6

1

1

24

1

1

33

3

GROWTH

TOTAL

TISSUE

25

RUMEN LOSS

1-

MILK

50

Adapted fiom Tamminga, 1992

88

1 3

33

4

Protein degradability, on average, was considered to include afl of the dietary soluble crude protein and 35% of the insoluble cnide protein (ME, 1985). The esthate of digestible microbial protein based on m e n available nitrogen (PDMN) is compared with the estimate based on rumen available energy (PDIME) to decide wfüch is limiting

microbial growth. When the digestible microbial protein estimate is known, it is added to the digestible U I P portion (PDIA) to determine the total amino acids available at the

small intestines. This is then compared with the animai's predicted requirements. Thus the PD1 system has more of a forward calculation of protein avaiiability, nom dietary

inputs to amino acids absorbed in the intestines, than does the NRC system. The PD1 system assumes microbial protein is 80% true protein and 20% nucleic acids, as does the

NRC system, however the digestibility of the microbial true protein is calculated as 70% and an average of 78% digestibllity is used for UIP protein (NRC, 1985). This estimation of microbial production compares well to other protein system predictions (Waldo and Glenn, 1984) and overcomes the problem of overestimating microbial production during

a rumen nitrogen deficiency. The PD1 system specifies the equation for fecal metabolic protein or the

endogenous contribution to be 0.057 gram of fecal metabolic protein per gram of indigestible organic matter (Vérité et al., 1979). This equation is based on data fkom sheep rather than cattle, and has an R~ = 0.74. The NRC (1985) suggests that fecal metabolic protein is more highly correlated to dry matter intake than indigestible organic matter intake, and this causes discrepancies between the NRC and PD1 prediction of fecal excretion. The PD1 system does not provide a value for endogenous urinary protein, but compensates for this by using a higher value of 3.25 W." for scurf protein (Waldo and

Glenn, 1982). Recycled nitrogen is accounted for indirectly in the PD1 system by having an 11% higher efficiency of microbial protein synthesis than other systems with the same microbial true protein content (Ganesh, 1991). These different approaches to allocating sources of nitrogen losses demonstrate the lack of knowledge regarding the actual mechanisms and the large variability that surrounds these values.

2.2.3

CNCPS System Another approach for evaluating protein in daîry cattle rations is proposed in the

CNCPS mode1 which is extensively described in the set of papers by Sniffen et al. (1992), Russell et al. (1992), and Fox et al. (1992) and is the bais for the level two model of the recent Nutrient Requirements of Beef Cattle, 7th Revised Edition (NRC, 1996). The CNCPS model contains a series of sub-models which describe inputs (animal,

environmental, management and feed), calculate digestion and rnicrobial growth in the rumen, and nutrient metabolism of energy, protein and essential amino acids.

Protein is divided into three chemically characterized defmitions representing Fraction A: non-protein nitrogen (NPN), Fraction B: true protein and Fraction C: bound

or unavailable nitrogen. The true protein is M e r divided into three subhctions (Bi,Bz

Bp)based on their rate of nunuial degradation and passage (Sniffen et al., 1992) (Figure 2.1). Fraction A and BI are soluble in b a e r and measured as the soluble intake protein

(SIP). Fraction A, the water soluble NPN containhg primarily urea, ammonia, nitrates, amines and fiee amino acids, is trichloroacetic acid (TCA) soluble. This fiaction is assurned to be completely depded in the rumen. Fraction Bi, the soluble true protein portion, is determineci as the TCA precipitable fiaction or caiculated as SIP minus the

Figure 2.1 Schematic of the Cornell Net Carbohydrate and Rotein System Rotein Fractions and Chetnical Composition

"BI " Fraction (SlP - NPN)

"A" Fraction

1

1

Insoluble Protein (IP - SIP)

1

1

I

I

1

"82"Fraction (By difference)

"B3" Fraction (NDICP - ADICP)

"C" Fraction (ADICP)

Legend

JI?

-Intake protein SI. - SoIubie intake protein M>N -Non-protein nitrogen NDICP -Neutra1 detergent insoluble protein ADICP -Acid detergent insoluble protein

NPN portion. The bound or C h c t i o n is the protein that is insoluble in acid detergent (ADIN) and assumed to be completely mavailable in the rumen. This may be protein that

is associated with Lignïn, tannins or Maillard-reaction type of products. Fraction B3 is insoluble in neutral detergent (NDIN) but soluble in acid detergent and detemiined as NDIN minus ADIN- Fraction B2 is a calculated value determined as the Merence of al1

other fiactions from the total protein. The B hctions have a constant degradation constant applied to each but a variable percentage of digestion in the m e n dependhg on the rate of passage (Sniffen et al., 1992).

Protein supply to the rumen for microbial degradation is the sum of dietary protein and recycled nitrogen (Russeil et al., 1992). Recycled nitrogen is calculated in CNCPS

using the NRC (1985) equation stated earlier. This equation uses only dietary crude protein, and does not capitalize on the protein fractionation and carbohydrate information that the rest of the sub-m&s

incorporate. In partîcular, information regarding the

nitrogen components which would likely increase ammonia concentration in the rumen and energy available for the ammonia-using bacteria codd improve this estimation

(Luirnes, 1998).

In the CNCPS nimen microbes are divided into two groups, one group that ferments structural carbohydrates (SC) and the other that ferments non-structural carbohydrates (NSC). The SC bactena use ammonia as their primary nitrogen source and ferment cellulose and hemiceliuiose. The NSC bacteria ferment sugars, starch and soluble fiber bectins and B-glucans). They can use either ammonia or peptides and amino acids (true protein) as nitmgen sources, and can produce ammonia if there is iosufficient energy

available.

Factors that affect the yield of microbial production include the growth rate, maintenance requirement, and maximal growth yield and rumen pH. The CNCPS assumes the growth rate of both groups is directly proportional to the rate of carbohydrate digestion as long as the appropriate nitrogen source is available (Russell et al., 1992). Fiber is fermented slower than NSC so SC bacteria grow slower than NSC bacteria. The

CNCPS model adjusts microbial yield, as a fùnction of growth rate, using the t h e dependent equation from Pirt (1965) for bacterial maintenance and theoreticai maximum yield (Russell et al., 1992). Russell et al. (1992) admits there are little data available on rumen microbial maintenance requirements or maximal growth yields. The maintenance requirements assigned by the model are different between the two groups, with the NSC

and SC bacteria having 0.150 and 0.05 grams of carbohydrate per gram of bacteria per hour, respectively (Russeil et al., 1992).

Protozoa and yeast are considered to have a negligible effect and are not accounted for in the CNCPS model (Russeli et al., 1992) except that protozoal predation is assumed to decrease the theoretical maximum bacterial growth yield by IO%, fkom

50% to 40%, or 0.4 grarns of celi dry weight per gram of carbohydrate. The yield of NSC

bactena can be increased by as much as 18.7% as the ratio of peptides to NSC plus peptides increases nom O to 14%. Above 14% there is no M e r hprovement in yield. However, the model does not adjust for an ammonia deficit in microbial yield prediction. Microbial yield is affected by low niminal pH by decreasing maximum growth yield of both SC and NSC when ration effective NDF is less than 20% (Russell et al., 1992). Rumen digestibility of an ingredient is defined as RD = Kd / (Kd + Kp) where Kd

is the rate of digestion (%/hr) and Kp is the rate of passage ( Y b )(Sniffen et al., 1992).

Ruminal escape is defined as RE = Kp I (Kd+ Kp). The extent of digestion is calculated by applying the RD percentages to the different protein and carbohydrate pools. Passage

rates c m be affected by particle size, density, hydration and dry matter intake (Sniffen et al., 1992). In the CNCPS,passage rates are calculated as a function of dry matter intake, body weight, and percentage of forage in the diet, which is then modified by the effective

NDF as an indicator of particle size. Digestion rates are assigned for each ingredient, and

c m be manuaily changed or lefi as the defanlt. These values were obtained by in vitro techniques and curve-peeling mathematics. These digestion rates are not routinely

measurable and the impact of factors such as ingredient storage (e-g. siiage), processing (grinding, pelleting, extrusion) and îngredient interactions have not been M y elucidated.

Microbial nitrogen is assumed to be comprised of 15% nucleic acids (A fraction),

60% true protein (B1 hction) and 25% protein that is associated with the ce11 wail (C

fraction) (Russell et al., 1992). Intestinal digestibility of the protein fiactions leaving the rumen is calculated by a static coefficient. Fractions A, B1 and B2 have an intestinal digestibility of 100%, B3 is 80% and C is 0%. The microbial A hction or nucleic acids are assumed to be completely digested, but do not contribute any metabolizable protein

(Sniffen et al., 1992). In the CNCPS model there is no allowance for any salvage or recycling of nucleic acids and the loss of nitrogen is not accounted for. Ruminal ammonia levels need to be estimated accurately to account for nitrogen that is caphired by bacteria, transferred across the rumen to be excreted in the urine or rnilk, or recycled to the rumen via the saliva. Predicting microbial uti1i;ration of nunen nitrogen is a critical component

of the CNCPS model for utilization in a nutrient management system because of the significant impact on the route of nitrogen excretin.

The 3.0 version of the CNCPS model does not contain any description of urinary

excretion of aitrogen to allow for a total nitrogen balance analysis. Total fecal dry matter is caiculated as the s u m of undigested feed and microbial protein, carbohydrate, fat and ash plus endogenous protein, fat and ash from the excretion of mucous, bile salts,

sloughed cells, and keratinized tissue (Van Soest, 1994). Endogenous contnïutions to fecal protein are calculated as 0.09 multiplied by the indigestible dry matter (NRC, 1989). This endogenous fecal protein is assamed to be completely unavailable (Van Soest, 1994), and added to the C hction of the fecal composition dong with the feed and microbial conanbutionsRecent research in nutrient management planning (Tylutki and Fox, 1997) has recognized the need to mod*

the model to include a nitrogen balance sheet, with

estimates for urinary, fecal, milk and tissue nitrogen fluxes, to analyze whole f m scenarios. The next proposed version of the model wili contain equations to predict anoual nutrient excretion levels, with total urine and feces production, that have been

m f m (Tylutki and Fox, 1997). An accurate evaluated with data fiom a 500-cow d accounting for niminal ammonia Loss, degradation of excess metaboluable protein and inefficiency of amino acid utiiization will be needed for irnproved prediction equations. An effective protein evaluation system must incorporate information regarding

rumen ammonia dynamics, microbial nitrogen utilization in the rumen and large intestine, impact of recycled nitrogen, and quantfication of endogenous niûrogen. The method of determinhg degradability in any system will affect the estimated quantity of microbial protein produced and the resulting amounts and routes of nitrogen loss. These systems

need inputs that are easily obtainable and provide solutions that c m be compared to production data to allow for adoption at the fàrm level.

2.3 Protein Solubiiity

Solubility of crude protein is ofien used as a criterion for evaluating ruminant diets (NRC, 1985). However, the literature is not conclusive and does not show agreement between sources on the actual importance and validity of using solubility in predicting rumen degradation of proteia Protein solubility varies with the solvent used because of differences in pH, ionic strength and extraction procedures (Wohit et al., 1973, Crooker et al., 1978,Waido and Goering, 1979). The solvents that have been investigated

in the past include Burrough's buffer (IO%),

NaCl solutions, dilute NaOH, hot water and

autoclaved m e n fluid (Brodenck, 1982). The CNCPS system is currently based on a borate-phosphate b a e r procedure established by Knshnamoorthy et al. (1983). The method of analysis is a significant variable when cornparhg data fiom various sources and must be criticaliy reviewed before deterxnining values used in evaluating diets.

Proteins in the rumen are degraded by extracellular enymes. These enzymes were believed to corne in contact with proteins through interactions involving water. Therefore

if proteins entered into solution quickly the rate of enzymatic degradation would increase. However some feed proteins can be hydrolyzed directly nom the solid state without going into the niminal solution (Tamminga, 1979). Hendrickx and Martin (1963) reported that soluble proteins are generally more subject to proteolysis than insoluble proteins. Miller

(1982) later commented that the work of Hendrickx and Martin (1963) did not

comprehensively equate solubility with degradability- Vérité et al. (1979) based degradability in the French PD1 system on solubility and used a value of 65% of the insoluble protein as the undegradable portion of protein. Pichard and Van Soest (1977) used a combination of solubility and proteolysis to establish and test the three chemically derived fiactions now used in the CNCPS model. The current utilization of protein solubility in protein systems such as the French PDI and the CNCPS model underlines the importance of understanding the effect solubility has on rumen function and nitrogen utilization. Other research has not determined relationships between solubility9degradability, and microbial production. Stem and Hoover (1978) offered four isonitrogenous diets

containing different levels of urea and protein solubility and found no significant effect

on microbial production. Little et al. (1963) found no dennite relationship between nitrogen solubility and rate of m e n ammonia production. Satter and Roffler (1975) reported that m e n ammonia levels greater than 5 mg/dl were ineffective in increasing microbial production. Stem and Satter (1984) compared values of nitrogen solubility in mineral buffer (Burroughs IO%), rumen dacron bag nitrogen disappearance and in vivo degradabiiity measurements for diets with various nitrogen sources. They found a high correlation between the solubility and dacron bag results for short durations, with a decreasing correlation as the duration of incubation increased. Correlation between solubility and in vivo degradability was low, indicating that solubility is a poor predictor of degradability without including passage rate. Mahadevan et al. (1980) concluded that the solubility of a protein is not by itself an indication of the protein's resistance to bacteria hydrolysis in

the rumen. Structurai characteristics of the proteins, such as disulfide bonds and

crosslinkages are EeIy determining factors. These fïndings suggest that the complexities of interactions in the m e n are not completely modeled with any one single assay and the iimitations of predictions based on these analyses should be recognized. Solubility is suitable for predicting the portion of the feed that wili be rapidly solubilized in the rumen but may have Little relationship to degradability of true protein.

2.4

Nitrogen Excretion

In ruminants there are various reports on the distribution of nitrogen between the feces and urine. Smith (1973) summarized the percentage of total nitrogen found in feces and urine. The ratios for various classes of livestock are: beef cattie & sheep 50% nitrogen in feces: 50% nitrogen in urine, daky cattie were 60% feces: 40% urine, swine

were 33% feces: 67% urine, and pouitry were 25% feces: 75% urine. Main components of fecal nitrogen are endogenous or metabolic fecal nitrogen, indigestible feed nitrogen and

indigestible microbial nitrogen. Endogenous fecal losses consist of enzymes, mucus, epithelial cellular debris, bile and urea and appear related to the level of intake (Bruchem et al., 1989) and digestibility of the diet (NRC, 1989). Metabolic fecal nitrogen can

contribute up to 57% of the total protein in the feces (MC, 1985). The amount of fecal nitrogen excreted is related to the level of UIP in the diet, amount of apparently digested organic matter and the amount of dry matter excreted in the feces (NRC, 1985). Microbial fermentation in the hindgut can shift the partitionhg of nîtrogen excreted between feces and the urine (Tamminga, 1992). Metabolic fixai nitrogen c m be

digested by microbes and absorbed as ammonia across the hindgut to be excreted in the urine, or captured as microbial nitrogen and excreted in the feces. AIso, excess urea

aitrogen in the blood can cross into the hindgut and be incorporated by the microbes. The amount of hindgut microbial production depends on the availability of fermentable carbohydrates and protein (Orskov et al., 1970) that reach the large intestines. Diets that have slower m e n degradability of carbohydrates or faster passage rates will provide

more of these materiais to the hmdgut. The difference in u ~ a r nitrogen y losses between animals fed N-fiee diets and those fed with infragastric infusions are attrïïuted to a flux of nitrogen to the hindgut, captured as microbial protein and excreted as metabolic fecal

nitrogen (NRC, 1985). This can account for some overestimation of metabolic fecal nitrogen in the NRC (1989) protein system. The French PD1 system prediction of total fecal nitrogen was calculated as the s u m of three sources, dietary, microbiai and endogenous. The dietary hction was

estimated as 0.143 times the insoluble nitrogen intake, the microbial fraction as 0.004 times the digestible organic matter and the endogenous fecal nïtrogen as 0.09 times the

indigestible dry matter (Vérité et al., 1979).

Urinary nitrogen consists mainly of endogenous urinary nitrogen? excess rumen arnmoaia not incorporated uito microbial protein, microbial nucleic acid metabolites, metaboluable protein nitrogen in excess of production requirements, and nitrogen fiom the inefficient utilization of absorbed amino acids for maintenance and m i k and tissue

synthesis (Dewhurst and Thomas, 1992, NRC, 1985). Endogenous urinary protein components include creatinine, creatine, hippuric acid, allantoin, uric acid, xanthine, hypoxanthine, urea, ammonia, and some fiee amino acids (NRC,1985). Urea is generally

the dominant form of nitrogen, but can range fiom 25 to 95% of the total urinary nitrogen

(Bristow et al., 1992). Bristow et al. (1992) summarized other nitrogenous components that exist in significant proportions- These are 1) hippurïc acid, a conjugate compound of glycine with benzoic acid, which nonnally ranges from 2 to 8%, 2) purines, mainly allantoin (2 to 22%), uric acid (c2%), xanthine and hypoxanthine (< 1%) 3) creatinine and creatine (1 to

6%) and 4) ftee amino acids (trace amounts). Most mine samples contain less than 1% of the total nitrogen as ammonia if the proper collection procedures are followed to avoid urea degradation.

In this thesis, the investigation focused on three main fonns of nitrogen excretion: 1) fecal nitrogen 2) urea nitrogen excreted in urine and milk and 3) purine derivatives

excreted in urine. These forms are important quantitatively and have different potential rates of nitrogen loss to the environment due to storage, soil incorporation, and plant uptake.

2.4.1

FecaL Nitrogen Fecal composition has been extensively investigated to estimate tnie digestibility

of feed proteins and to identify amounts of endogenous losses. Fecal nitrogen has been reported to consist of 45 to 65 % amino nitrogen, 5 % nucleic acid nitrogen, and 3%

ammonia nitrogen, with the remainder being derived fiom bacteria cell walls, glycoprotehs and fiber bound nitrogen W C , 1985). Further separation of the feces has suggested that the source of the fecal nitrogen can be distriiuted as 7 to 28% fkom

undigested dietary nitrogen, 16 to 59% water-soluble nitrogen and 38 to 74% bacterial

and endogenous debris nitrogen, which is mainly bacteriai cell walls (NRC, 1985). hcreased availability of energy in the large intestines has been found to increase fecal nitrogen and decreases uruiary nitrogen excretion, partly because of a . increase in microbial protein and pady because of an increase in the soluble nitrogen fiaction of the feces (Mason et al-, 1977)- Generally more nitrogen enters the large intestines fiom the smaU intestines and urea transfer h m the blood, than leaves in the feces, This is

dependent on diet, intake level, and several other physiologicai factors (LNRC, 1985). Whitehead and Raistrkk (1993) analyzed the changes to fecal nitrogen during short-term storage and reported that the largest differences were in the soluble nitrogen forms. During the three-week storage they concluded that the portion of organic nitrogen that was mineralized to ammonium was already present in a distinct readily minedkable

hction. Thus the fonn of nitrogen excreted in the feces influences the changes that occur

during storage.

2.4.2

Urea Nitrogen Urea is a small water-soluble molecule that permeates al1 ceils and tissues in the

body. It is the metabolic end-product of protein catabolism (Butler et al., 1995). Urea is the dominant inorganic form of excreted nitrogen in the urine (Bristow et al., 1992). The

level of urea in the urine versus the other orgaaic nitrogen sources is important in relation to the potential polluting capacity of excreted urine (Srnits et al. 1995). High urea levels could be lost to ammonia volatilization while the organk nitrogen compounds are more slowly

degraded (Bristow et ai., 1992). Ammonia volatilized k m urea c m increase by 2.5 fold

with the presence of hippuric acid in urine (Whitehead et al., 1989). Thus there are

interactions between the nitrogen sources that also must be taken into account.

Urinary urea nitrogen excretïon is related to blood urea nitrogen (BUN), m i k urea nitrogen (MUN) and rumen ammonia levels (Kertz et al., 1970, Ciszuk and Gebregziabher, 1994, Gonda and Lindberg, 1994, Jonker et al., 1998). Urea can be measured fiom the bloodstream in either the plasma (PUN)or senun (SUN) fiactions or refmeci to as blood urea nitrogen (BUN)and can be considerd synonymous (Butler et al., 1995). The BUN is produced in the lïver fiom ammonia in the blood that cornes from the gastrointestind

tract (Kennedy and Milligan, 1980) or fkom deamination and metabolisrn of amino acids (Reynolds, 1992).

The amount of urea excreted in the urine is directiy proportionai to the concentration of urea in the blood (Ciszuk and Gebregziabher, 1994). High correlations between MUN and BUN (Baker et al., 1995, Roseler et al. 1993) and between MUN and

rumen ammonia concentrations (Gustafsson and Palmquist, 1993) suggests the use of milk urea as an indicator of rumen nitrogen balance and U1 particular excess rumen degradable nibogen. Roseler et al. (1993) developed prediction equations for PUN and

MUN that are used in the CNCPS model. Multiple regression analysis determined a positive relationship between both degradable and undegradable intake protein with PUN and MUN and a negative relationship with energy intake. Jonker et al. (1998) developed

model equations to predict nitrogen excretion fkom MUN and used hterahue values to evaluate the regressions. They found the majority of unexplained model error was associated with variation among animds. The measurement of MUN is simple and

noninvasive and is considered a practicaf method to evaluate diet utilization (Butler et al., 1995, Jonker et al,, 1998)-

2.4.3

Purine Nitrogen Nucleic acid cataboiites that can onginate nom the feed, m e n microorganisms,

and endogenous tissue turnover are another large source of excreted nitrogen in the urine (Puchala and Kulasek, 1992). Nucleic acid purines are degraded and excreted in the mine as their derivatives- hypoxanthine, xanthine, uric acid and allantoh. Eariy work by Topps

and Elliot (1965) reported a highly significant correlation between the ruminal concentration of nucIeic acids and the excretion of purine denvattives- Smith and McAUan (197 1) and McAllan and Smith (1973) detennined that the nucleic acids flowing to the

small intestines are essentiaily of rumen microbiai ongin. Feed nucleic acids are highly soluble in the rumen and are extensively degraded by m e n microorganisms (Djouvinov et al. 1998) and thus do not contribute significantly to purines in the urine. There has been

considerable interest over the years in ushg purines as a non-invasive indicator of microbial production (Fujihara et al., 1987, Lindberg, 1989, Chen et al., 1990b, Verbic et al., 1990, Balceus et al., 1991, Susmel et al., 1993, Giesecke et al., 1994, Dewhurst et al.,

1996, Gonda and Lindberg, 1997, Vagnoni et al., 1997). There are advantages because of the non-invasiveness of the techniques, but limitations in the knowledge regardhg

endogenous contributions, recycling and salvaging, and rate of excretion in the urine. The contribution to the total nitrogen output in the urine wïll depend on the microbiai production, glomedar filtration rate, and endogenous loss (Chen et al., 1990b).

Microbial nucleic acids leaving the rumen are extensively degraded to purine nucleotides and fiee bases in the s m d intestines. In the intestinal mucosa there is a high activity of xanthine oxidase which converts absorbed purines into uric acid (Chen et al., 1990a). Once converted to urïc acid it is not available for incorporation or salvage into tissue nucleic acids. There is also a high activity of xanthine oxidase in other tissues, such as blood and kidneys, resultuig in uric acid and ailantoin being the major purines that are excreted. The typical proportion of ailautoin to urÏc acid in the purine derivatives is 85% to 15% (Chen et al., 1WOb, Dewhurst and Thomas, 1992).

Endogenous purines excreted in the urine are accounted as part of endogenous urinary nitrogen (NRC, 1985). Measurements of the amount of endogenous excretion have been made using the intragastric infusion technique (Chen et ai., 1992a). When comparing the literature there is a large merence between the endogenous levels found

in sheep and cattie. Chen et al. (1990a) related this to the higher level of xanthine oxidase in cattle tissue and blood. Sheep can salvage more nucleic acids than cattle which makes calculation of endogenous purines difficult. In cattle an endogenous concnbution is taken

as a constant at 0.385 mmoVkg f17'per &y because of the low level of salvaging (Chen and Gomes, 1992).

Purine derivatives (PD) entering the blood are cleared rapidly. The primary route of excretion is through the urine. Urinary excretion is a b c t i o n of the plasma

concentration and glomeru1ar filtration rate (Chen et al., 1991). Some of the purine derivatives can be disposed of by secretion into the rumen via saliva or across the gut wall, and by secretion into the milk (Chen et al., 1990~).Once secreted in the gut PD are degraded by microbes in the rumen. The partitionhg between rend and non-renal

excretion is poshilated to be a b c t i o n of plasma concentration with a 85~15distribution (Chen et al., 199Oc, Gonda and Lindberg, 1997). Chen and Gomes (1992) proposed the foliowing equation to describe the quantitative relationship for cattle between absorption of microbial purines (X mmoWday) and the excretion of PD in the urine (Y mmol/day): Y= 0.85X + (0.385 W0-75). Once the

urinary PD are measured and the absorbed microbial purines are calculateci, an estimate of the intestinal flow of microbial nitrogen can be determiaed using the equation: Microbial nitrogen supply (g/day) = X (mmoi/day) x 70 / (0.83 x 0.1 16 x 1000) or 0.727

x X (mrnoVday) (Chen and Gomes, 1992). The 0.83 factor represents the assumed digestibility of microbial purines, 70 is the nitrogen content of purines per mm01 and the

0.1 16 factor descnbes the ratio of p u ~ nitrogen e to total nitrogen in mixed m e n microbes (Chen and Gomes, 1992). The resulting value is expressed as grams of microbial nitrogen per day. The assumption on the ratio of purine nitrogen to total nitrogen in mixed m e n microbes is that this is unchanged by dietary treatment, which

may not be valid. Dewhurst et al. (1988) used a similar approach, but they measured values of 0.1 12 for the purine nihogen to total nitrogen ratio, that 85% of the microbial purines are digested and 80% of the absorbed purines are excreted in the urine. They did not provide an estimate for endogenous contribution. Antoniewicz et al. (198 1) and Chen et al. (1992b) proposed using a ratio of allantoin N to creatînine N as the indicator of microbial production. However, this resulted in larger standard errors than obtained fiom total collection. Faichney et al.

(1 995) reported a large variation between animals in creatinine excretion and suggested that using the creatinine coefficient could result in prediction errors between diets greater

than 10%. There is a significant contribution of microbial nitrogen in both fecal and

urinary excretion routes and the purine derivative approach appears to provide a method to not only rneasure one source of degradable nitrogen in the urine, but also to monitor the impact of diet on microbial growth.

2.5

Manure Nutrient Modeling

Accurate prediction of the dietary impact on animai performance and waste nutrient production will ailow for improved estimations of manure quality for whole farm nutrient management (Van Hom et al., 1996, Wilkerson et al., 1997). Farm and balance trials provide similar values of overall manure production, but different estimates of nitrogen excretion and loss. Balance trials are designed to be more accurate than farm level trials in quantimg al1 the nitrogen in the system. This is an important consideration

because Muck and Richards (1983) found that about half of the nitrogen in manure is lost before it reaches the storage area. Environmental factors such as barn temperature, hurnidity and wînd speeds a l l have an influence on losses afier excretion by the animal.

Research in manure storage, application, soi1 microbiology and plant nutrient uptake have investigated the dynamics of nitrogen flues. This research relies on models to predict and interpret r e d t s from designed experiments. Models such as the Centwy

Soil Organic Matter Mode1 (Parton et al., 1987) simulate the flow of nitrogen, carbon, phosphorus, and sulfur through the different inorganic and organic pools in the soi1 and

into plant utilization. Soil mode1 input parameters of inorganic N (urea and ammonia), organic N (protein bound to fiber fractions) and lignin c m be obtained fiom nutritional

mode1 predictions and storage factors- The relative levels of these nutrknts will inauence the availability of nitrogen for imrnediate or delayed absorption by plants, and the

potential leachuig or volatilization fiom the soil. This combination of modeling efforts can help identify the critical control points and areas of greatest potential loss in an

environmental protection plan.

2.6

Summary

There are many current approaches to evaluating protein in lactating daïry cow diets. They all recognize the need to determine if the protein will be used for microbial

production or will be bypassed to the lower intestines. How that is determined can vary significantly. There is still a lack of knowledge around dietary interactions and effects on the microbiai population- The major diffIculty is in i d e n m g and quantifying al1 the

variables that could affect nitrogen partitionùig. There is Little information on impact of dietary changes on endogenous fecal and urinary losses, hindgut fermentation and their role in changing the route of h g e n excretion, and the extent of nitrogen recycling and the mechanisms that control i t Research has generally focused on how dietary nitrogen

affects productive outputs such as milk and meat, and less on the impact on waste products such as urine and feces. With the increasing pressure from govemments and the public for environmental protection, fiiture research will be needed to support the knowledge of overall nitrogen utilization and excretion. This will enable the producer to make intelligent decisions on aspects of the business when balancing diets for the

lactating daky cow.

Objectives and Hypothesis

2.7

This research was desîgned to investigate the nuii hypothesîs that altering the protein solubility in the diet of lactating cows would have no effect on the amount, route and f o m of excreted nitrogen and that the CNCPS mode1 adequately describes nitrogen

partitionhg in the lactating daky cow. The objectives developed to test this hypothesis

were: 1) To formulate diets of eqyd crude protein but with v-g

levels of protein solubility,

degradability and undegradability.

2) To carry out a nitrogen balance trial on lactating cows fed diets of varying protein solubility to determine the route and amounts of nitrogen loss. 3) To analyze the feces, urine and milk to determine the forms of niaogen that are excreted. 4) To evaluate the individual animal responses versus the predicted values fkom the

CNCPS mode1 for the variables under investigation.

EFFECTS O F VARYING DIETARY NITROGEN SOLUBILITY ON MTROGEN

UTILIZATION AND EXCRETION IN DAIRY CATTLE

3.1

Introduction

Early experiments investigating the impact of protein nutrition on nitrogen

contamination of the environment by dairy cattle generaiiy focused on changing the crude protein level of the diet to maximize production and minimïze waste (Tarmninga, 1992, W, 1985). Later studies iovestigated different undegradable intake protein (UIP) to

degradable intake protein (DIP) ratios to optimize nitrogen utilization and avoid any excesses (Dewhurst and Thomas, 1992, Baker et al., 1995, Wright et al., 1998). There is however, Little information available to assess the effect of soluble intake protein (SIP) level, at a fixed crude protein level, on route of excretion and nitrogen utilization for miik and tissue production.

Soluble protein is the portion of DIP that is immediately available for microbial utilization. The rate at which DIP is degraded in the rumen can affect the amount of

ammonia which escapes microbial capture, depending upon the availability of carbohydmte sources to support microbial growth m w v e r and Stokes, 1991). If there is insufficient rumen-available energy or the degradation rates of protein and carbohydrates are not synchronized, then excess ammonia will be absorbai md transported to the liver to be converted to urea and excreted via the urine (Nocek and Russell, 1988).

The objective of this trial was to detemiine the amount, form and route of nieogen loss when levels of die-

nitrogen solubility were altered while maintaining constant

crude protein, energy and degradable carbohydrate levels.

3.2

Materials and Methods

Experimental Design

Eighteen animals were assigned randomly to one of three dietary treatments that differed in soluble intake protein (SIP) level (high, medium and low). To facilitate coliection in the Physiology Wing at the Elora Daky Cattle Research Station, the experiment was split into three penods using six animals, 2 per treatment for a total of 6 animals per treatment over three experimental periods. Each experimental period was 2 1days in length, starting one week apart. During the first ten days of the period, cows were

adapted to the treatment diets offered ad Libitum (to provide at least 10% orts) in their usual stalls. Animals were then moved to the collection room for adaptation and intakes were restncted to 95% of the average feed consumption calcdated fiom the previous ten days. Total nitrogen balance collections were made during the last five days of the experimental period.

Animals

The experiment was conducted with eighteen mature lactating Holstein cows

fiom the herd at the Elora Dairy Cattie Research Station. The cows (2.9 51.0 lactations) had an average body weight of 685

+46 kg and were 170 + 12.5 days in milk at the start

of the experirnental period. Cows were rnilked daily at 0530 and 1600 h and fed in two equal amounts at 0500 and 1500 h.

Diets

Diets were formuiated to follow the NRC (1989) recommendations for post-peak cows producing 25

- 30 kg of milk per day for crude protein,

energy, minerals and

vitamins. Treatments were balanced differently for the amount of soluble, degradable and undegradable intake protein. The medium treatment was balanced for 100% of the NRC recommended level for UIP and DIP, while the hi& treatment had 85% and 1IS%, and the low treatment had 115% and 85% respectively. Soluble protein level was designed to

increase fkom 30% of total crude protein (50% of DIP) on the low, 36% (55% of DIP) on the medium, to 48% (65% of DIP) on the high diet. Animals bad access to water at all

times. Diets were developed with a forage to concentrate ratio of60:40 on a dry matter basis. Each diet contained a common forage mixture of corn silage, alfafa haylage and

dry alfalfa hay mixed on an as-fed basis of 45.7%, 45.7% and 8.6% respectively. The

chernical analyses of the forages are lïsted in Table 3.1. Treatment differences were

achieved through addition of thme separate pelleteci (5132 inch diameter) concentrates

nom Agribrands Purina Canada Inc. (Woodstock, Ont), compositions and chemical analyses are descnied in Table 3.2. Concentrates were formulated using varying levels of urea, soybean meal, blood meal and fish meal to attain the required levels of soluble, degradable and undegradable protein. Feed grade urea, a cornmon source for NPN, provided the major addition of soluble protein. Soybean meal provides a less soluble but still degradable protein source while the blood and fish meals were sources of undegradable proteh. The pellets were top-dressed on the forage miaure and completely

mixed together prior to feeding- Peiieting the concentrate reduced the chance of

separation and selection of individual components by the cows and improved mïxi.ngwith the forages. The same production batch of diets was used for each of the three periods to

avoid compositional ingredient variation.

The chemical analyses of the total diets are shown in Table 3.3. The actual analyzed values for total dietary crude protein percentage vernis those formulated were higher

(+ 1.7

% units) and correspondingly protein solubility had increased as a

percentage of cmde protein (+ 12 % unîts).

Table 3 -1 Chernical Analysis of Forages used in Diets for Evaluating the Effect of Dietary Nitrogen Solubiiity on Nitrogen Losses nom Lactating Daîry Cattle. % Dry Matter

Haylage

+ 0.16

Corn SïIage

+ 0-15 8.12 + 0.07 5.03 + 0.12

Dry Maiter

33.45

Cnide Protein (CP)

2 1-762 0.08

Soluble Protein (SIP)

15-134 0.09

SIP ( % of CP)

69.53 5 0.06

6 1.95 2 0.09

ADF CP

2-15 f:0.09

0.37 + 0.04

NDF CP

3.32 2 0.16

1-08f:0.06

Non-protein Nitrogen (NPN) (%CP)

14.74 2 0.10

4.50 2 O. 13

Acid Detergent Fibre (ADF)

43.03 2 0.35

23.73 2 0.4 1

Neutrai Detergent Fibre (NDF)

53.63 2 1.O0

37.67 2 0.27

Lignin

9-075 0.13

2.3 12 0.08

Starch

0.00 5 0.00

32.90 _+ 0.70

11.77 2 1.05

47.93 2 0.54

2-60 5 0.06

3 -20 2 0.06

10.23 5 0.03

3.47 f:0.15

Calcium

1.25 5 0.15

0.20 f:0.0 1

Phosphorus

0.29

Sodium

0.15 5 0.01

0.05

Magnesium

0.22 2 0.03

O. 17 2 0.00

Potassium

2.5 1 1+ 0.26

0.64 5 0.03

Non-structurai Carbohydrate (NSC) Cnide Fat Ash

Values are means

SE of 3 replicates

-+ 0.04

37.99

0.23 + 0.0 I

+ 0.00

Table 3.2 Composition and Chernicd Aoalysis of Treatment Concentrate PeUets used in Diets for Evaluating the E f f i t of Dietary Nitrogen Solubility on Nitrogen Losses nom Lactating D a j r Catîle% As Fed Medium Component Low N SolubiIity N Solubility N Solubility 66-8 Yellow Corn 54.8 52-4 22.9 29.6 21-4 Wheat Shorts 12.7 Soybean MeaI 1.3 Blood Meal 2.7 7.5 Fish Meal 3-3 0.5 Urea 2-0 Molasses 1.23 Salt 1.83 Limestone 0.69 Dicalcium Phosphate O. 12 Magnesium oxide 0.47 Mag-Pot-Sulfate 0.08 TMNit ~remix' % Dry Matter 86.34 _+ O. 18 Dry Matter 2 1-922 0.08 Crude Protein (CP) 6.67 2 0.15 Soluble Protein (SIP) 5 0-10 30.43 SIP ( % of CP) 0.60 2 0-02 ADF CF 1.O8 2 0.02 NDF CP 5.88 2 O. 14 Non-protein Nitrogen (NPN) (CP%) 5.83 2 0.15 Acid Detergent Fibre (ADF) 15. 10 2 0.29 Neutra1 Detergent Fibre (NDF) 1.2 1 k 0.07 Lignin 39.70 2 1.10 Starch 51.63 2 0.20 Non-structural Carbohydrate (NSC) 3.50 2 0.00 Cnide Fat 7.83 2 0.48 Ash 1-142 0.03 Calcium 0.74 2 0.01 Phosphorus 0.59 5 0.02 Sodium 0.41 5 0.02 Magnesium Potassium 0.82 f0.01 0.98 2 0.0 1 0.68 _t 0.05 Values are means 2 SE of 3 repiicates ' Prernix supplied added values per kilogramof concentrate :11,000 IU Vitamin A, 3,300 Iü Vitamin D3,45 KJ Vitamin E, 0.3 mg Cobalt, 30 mg Copper, 50 mg Iron, 1.9 mg Iodioe, 95 mg Manganese, 95 mg Zinc, 0.52 mg Selenium ( A g n h d s Purina Canada Inc., Woodstock, Ont.)

Table 3.3 Chernical Analysis of Total Diets used for Evaluating the Effêct of Dietary Nitrogen Solubili~on Nitrogen Losses f?om Lactahg ~ a k ~attle. y % Dry Matter

'

Low N SoIubility 5l.04 50.16

Medium N Solubility 50.95 + O. 19

17.63 _t 0.03

17-74_t 0.03

7.40 2 0.06 42.00 t 0.02

+ 47-96+ 0.02

ADF CP

1.O0 2 0-02

1-052 0.02

NDF CP

2-17 & 0.02

1-83 0.03

7.16 2 0.05

8-17+ 0.04

Acid Detergent Fibre (ADF)

23.22 2 0.11

23.3 1 + 0.14

Neutra1 Detergent Fibre W F )

35.38 + 0.20

34.39 t 0.20

Dry Matter

Cnide Protein (CP) Soluble Protein (SE)

SIP ( % of CP)

Non-protein Nitrogen

(CP%)

8.5 1 0.05

+

Lignin

4.2 1 0.05

4-13

+ 0-06

Starch

24.47 2 0.24

24.40

+ 0.28

Non-structural Carbohydrate (NSC)

36.58 +0.17

37.47 4 0-18

+

+ 0-01

NE1 (McaVkg)

1.61 20.01

1.62

Cnide Fat

3.18 20.02

3-04 5 0.02

Ash

7.28 2 0.02

7.35 2 0.09

Calcium

0.94 2 0.03

0-91 + 0.03

Phosphorus

0.45 2 0.01

0.45 + 0-02

Sodium

0.27

+ 0.01

Magnesium

0.27 + 0.02

+ 0-01 0.28 + 0-01

Potassium

1.33 2 0.05

1.39 2 0-06

0.29

Values are means 5 SE of 3 replicates TMNitamin premix supplied average added values/cow/day of: 102,300 IU Vitamin A, 30,690 IIJ Vitamin D3,420 N Vitamin E, 2.8 mg Cobalt, 280 m g Copper, 465 m g Iron, 17.7 mg Iodine, 885 mg Manganese, 885 mg Zinc, 4.85 mg Selenium

Sample CoUection

The complete input variable data set required for the CNCPS mode1 includùig ail

animal, management and environmental inputs, were recorded for each animal and period (Appendix 2). Temperatures were collected daily and averaged over the t h e period Weights and body condition scores were measured on day 1, 7, 14 and 2 1 of the

experimental period. Body condiilon was scored on a scde of 1 to 5, 1 being thin to 5 being overconditioned (Patton et al., 1988). Scores were taken by two different observers, who were in close agreement, and the values averaged. Feed intakes were recorded riaily for each animal. In the collection area, there were stall partitions to prevent any cross contamination with any other animals. During the collection phase when animals were restrîcted to 95% of ad Liiitum intake, any orts present were weighed back before the morning feeding and a representative sample taken and stored at -20 O C. Feed sarnples were collected d d y during the collection phase for the cornmon TMR, individual forage

components, and treatment pellets. Samples were composited within each week and stored at -20 " C. Blood samples were taken at 0830 h on days 1 and 21 of the experimental period. Blood was collected fiom the coccygeal vein of each of the animais using 20 gauge, 2.5 cm needles into 10 ml serum vacuum tubes (Beckton Dickinson, Rutherford, NI) and placed on ice. Sarnples were allowed to dot for 60 minutes then centrifuged at 2500 rpm

for 15 minutes. Serum aiiquots (1 ml) were transferred from the vacuum tubes into storage tubes by disposable pipets for immediate fkeezhg at -70' C.

Milk production was recorded daiiy for each animal. A daily composite milk sample fiom the morning and aftemoon millàngs was taken during the colIection phase.

Fresh subsamples were analyzed daily for compositional data and subsamples were also frozen at -20' C for fiirther anaiysis.

Urine was collected using an urethral catheter (Bardex Foley catheter, size 26 Fr., with a 75 ml capacity balioon; CA. Bard Inc.,Covington, GA, USA.) connected to a polyethylene collection bottle for each animal (Crutchneld, L968). Catheters were inserted the day before the collection phase was to begh to d o w anirnaIs t h e to adapt. An average of 60 ml of distilled water was used to innate the catheter balloons. Urine was

acidified by the daily addition of 200 ml concentratecl sulfuric acid (Fisher Scientific, Toronto, ON) to the empty polyethylene collection botties, to prevent nitrogen losses and

bactena growth. Urine production was recorded and a 5% subsample raken daily, to be composited at the end of the collection phase. Urine samples were also taken daily, diluted with distilied water 5 t h e s and fiozen at -20° C, to be used for individual &y

analysis.

Feces were collected in steel trays positioned in the gutter behind each animal. Trays were put into place right afier the urine catheters were connected. Fecal samples

were collected daily, weighed and mixed thoroughly. A representative subsample was taken and frozen at -20GC. The feces were proportioned on a daily dry matter basis to make a composite sample to be used for further a d y s i s .

Feed and fecal samples were fieeze-dned to determine dry matter and ground

through a 1 mm screen using a Christy-Nomk miil. Feed and fecal samples were andyzed for dry matter (AOAC 930.15, l99O), cmde protein (AOAC 99O.O3,l99O), crude fat

(AOAC 920.39,l 99O), ash (AOAC 942.05, IggO), soluble protein (Chalupa et al., 199l),

non-protein nitrogen (AOAC 967.07,1990), acid detergent and neutral detergent insoluble nitrogen (Van Soest et al. 199l), acid detergent fibre (AOAC 973.18, 1990), neutral detergent fibre (Van Soest et al. 199l), Lignin (AOAC 973.18, IggO), starch (AOAC 920.40, 1990) and minerals (calcium, phosphorus, magnesium, potassium, and sodium) by inductively coupled plasma spectroscopy at a commercial Iaboratory (Centrai Laboratory SeMce, Strathroy ON). The CNCPS mode1 default values were used for

effective neutrai detergent fibre (eNDF), amino acid composition, and the degradation rates (kd) of the carbohydrate and protein fiactions for each individual ingredient

(Appendix 3). Blood samples were analyzed on a Coulter Dacos Biochemistry Analyzer

(Hideah, FL) at the Department of Clinical Pathology, Ontario Veterinary College. Sarnples were tested for total protein (Dart total protein , Codter kit #7#75O6 l), urea nitrogen @art urea nitrogen, Codter kit #7546773), P-hydroxybutyrate (Sigma P-HBA, Sigma kit #3 I O-UV)and glucose @art glucose, Codter kit #7546860).

MiIk was adyzed dady for protein, fat, lactose and solids-non-fat on fiesh samples using a near infra-red analyzer (Foss System 4000, Hillerod, Denmark) at the Central Milk Test Laboratory (University of Guelph Laboratory Senrices, Guelph, On).

40

Frozen samples were thawed in a 38" C water-bath and mixed (AOAC 925.2 1, 1990) prior to determination of total nitrogen (AOAC 9921.20, 1990), tme protein (AOAC 991.23, 1991) and nonprotein nitrogen (AOAC 991.21, 1991). Urea nitrogen was

determined on the fütrate fiom the nonprotein nitrogen determination using a kit based on the Fearon reaction nom Sigma Diagnostics (Procedure #535).

Urine was analyzed for nitrogen using the macro-Kjeldahl procedure (AOAC 984.13,1990).

Urine urea nitrogen was determineci using a kit based on an

ureaselBerthelot reaction nom Sigma Diagnostics (Procedure #640). This kit was aiso attempted for miik analysis but the tricldoracetic acid solution used in the nonprotein nitrogen determination interfered with the urease activity. Urine was also anaiyzed for creatinine by a Jaffe-color based kit nom Sigma Diagnostics (Procedure #555) and uric acid by an e~lzymatickit fiom Sigma Diagnostics (Procedure #686). Allantoin was determined using a procedure fiom Chen and Gomes (1992), which is a modification of the colorimetric method of Young and Conway (1942) based on the

Rimini-Schryver reaction. This pmcedure required close attention to the timing and temperature of reactions. First, the diluted urine samples were m e r diluted five t h e s

with distilled water. The aliantoin in the sample was hydrolyzed to dantoic acid by the

addition of sodium hydroxide (0.5 M) and placement in a boiling water bath (100 C) for seven minutes. Atter cooling in cold water (-5 O C), allantoic acid was further degraded to wea and glyoxylic acid with the addition of hydrochlonc acid (0.5 M). The pH of the

solution after acid addition was verifid to be in the range of 2 to 3. The glyoxylic acid was then reacted with phenylhydrazine hydrochloride (0.023 M) to produce glyoxylate phenyihydrazone by placement in the boiling water bath (100 O C) again for exactly seven

minutes. This was a modification h m the original Young and Conway (1942) procedure to optirnize the recovery rate of allantoin (Munro and Fleck, 1969). To ensure the process stops and side reactions with the phenylhydrazone are inhi'bited, immeciiately after the seven minutes the samples were removed fiom the boiling water and plunged into an icy isopropyl alcohol bath at -20 O C. An ice water bath was attempted but adequate coohg was not obtained. A red-coloured unstable chromophore was created by the quick &g

in of concentrated hydrochlork acid (11.4 N) cooled at -20 O C and potassium femcyanide (0.05 M). After exactly 20 minutes, the absorbance was read on a spectrophotometer at

522 nm, ensuring standards and samples were read over the shortest time-span possible

since the optical density decreases with tirne.

Statistical Anaiysis

The objective of the trial was to obtain individual animal values for input and

output parameters to be used in evaluating the CNCPS model. Treatment ranges and

means with standard ermrs were ody reported to demonstrate animal response to the different diets. Differences between variables were detected by the T-test procedure of Statistica (StatSoft Inc., 1993). Statistical signincance in all cases was taken as P c 0.05. Multiple regression procedures of Statistica (StatSoft Inc., 1993) were used to analyze input and output parameter values of the CNCPS model versus observed and predicted resuits. When more than one independent variable was selected, a forward stepwise regression process was utilized to determine the optimal regression model (StatSofi Inc., 1993).

3.3

Results and Discussion

Mode1 Inputs

The means and ranges of the animal descriptions used as inputs for the CNCPS model are reported in Table 3.4. The treatment means were not signincaotly different, except for body condition score of the low solubility group which was lower (P < 0.05). This would have only affect& the expected energy reqirement calculation in the model and did not impact on any învestigated variable. The envir0lmenta.i and management

inputs were kept constant across ail treatments and periods. The current and previous temperature was set as 14' C with 3 km wind speed, thin hide and 1.5 cm hair length. There were no feed additives and a TMR feeding method was selected as an input variable. The uniformity of the ranges in the animal, environmental and management

variables allowed the main variable of interest in the &el,

diet, to be expressed,

Diet

The daify intakes of nitrogen fictions are reported in Table 3.5. The A, B 1, B2,

B3 and C fiactions were calculated as dehed in Russeii et ai. (1992). As noted earlier, the actual total level of protein was 10% higher than was f o d a t e d to balance for NRC

requirements. A U treatments had an excess of dietary nitrogen intake which may have impacted on the ability to observe clifferences between treatments. Any stated conclusions are in the context of a dietary nitrogen excess. The increase in protein was also accompanied by an increase in protein solubility across ail treatments, with the relative differences between the treatments remaining as designed. This resulted in a

43

Table 3.4 Animal Descriptions used as inputs for the Comeïi Net Carbohydrate and Protein System Mode1 Evaluation. SolubilityLevel Body Weight (kg)

Low

Medium

Hkh

6575 19 a (610 -725)

Body Condition Score Number of Lactations Days in Milk Days Pregnant

2.420.1 a

(2.0 - 3 .O)

2-750.3 a (2-0- 4-0) 18054 a (168 - 196) 5 8 2 16 a (21 - 104)

Values are means & SE of n = 6. Values in brackets are ranges. a,b,c Means within a row having a different Letter are statistically different at (P < 0.05)

proportionaüy higher protein solubility for the low treatment by 41%, medium treatment by 34%, and the high treatment by 25%. Thus the low treatment ended up with a protein solubility higher than the NRC (1989) recommen&tion, consequently nunen available

nitrogen was always in excess in relation to the provided energy level. Dry matter intake was not signincantly different between treatments (Table 3.5).

During the experimental periods, the 95% restriction on intake was sufficient to ensure that there were no orts to collect. The high levels of solubïlity did not appear to affect thc

palatability of diets, as shown in a preliminary study (Appendk L), as the intake as percent of body weight fell within expected ranges for cows at this stage of lactation (NRC, 1989) of high 2.9%, medium 3.2% and low 3.2%.

Diet crude proteh percentage levels and total nitrogen intakes were not

significantly different between treatments, as per design. Degradable and soluble protein, as a percentage of dietary crude protein, were significautly different (Table 3.5). These

values fa11 within the ranges found in a study of dairy herds across Ontario, where there

was a mean crude protein (% of DM) of 17.5 + 1.9, DIP (% of CP) of 65.5 of CP)of 37.8

+ 4.1, SIP (%

+ 7.7 and a dry matter intake of 23.1 + 2.0 (Godden, 1998).

The percentage of degradable protein that was soluble, was also significantly different and represented the increased inclusion of urea in the treatment pellets (Table

3.2). This was also shown by a significant krease in the level of non-protein nitrogen

(NPN) and A fiaction (Table 3.5) which related to an average urea intake of 240, 50 and O g / day on the high, medium and low treatments, respectiveIy-

Table 3 -5 Chernical Composition ofthe Dietary Nitrogen Intake and Corresponding Comell Net Carbohvdrate and Protein Svstem Protein Fractions, Solubility Level (kg/da~) Cnide Protein (%)

DIP (% of CP)' SIP (% o f CP)

SIP (% of DIP)

Medium

Low 20.8 50.6 (19.0 -23 -3) 17.6+0,0 (1 7.5 - 17.7) 60.4+0,1 (60.2 -60-7) 42.0+0.2 (41 -5 -42.5) 69.5+0.1 (69.0 -70.0)

a

a

a a a

Intake N SIP-N NPN

NDF-N ADF-N A Fraction

B 1 Fraction B2 Fraction

B3 Fraction C Fraction

DIP' Calculated fÏom NRC (1989) Values are means + SE of n = 6. Values in brackets are ranges. a,b,c Means within a row having a different letter are statisti~all~ different at (P < 0-05)

The percentage of SIP comuig fiom NPN was 95.0%, 93.1%, and 93.4% on the

high, medium and low treatments respectively, reflecting the low amount of soluble tme

protein (B 1 fraction) found in cornmon silage based diets (Van Soest, 1994). The medium diet has a significantly higher level of BI, supplied by the soybean meal in the pellet. Soybean meal has been reported to provide peptides for microbial production (Chen et al. 1987). The intermediate degradable B2 portion was signiscantly lower on the high diet

due to the level of NPN. The slowly degradable B3 portîon showed a higher level in the Iow treatment due to the inclusion of bypass ingredients such as blood and fish. The

indigestible C fraction or the portion bound in the ADF hction was similar across al1 treatments and came mostly fiom the forage portion. The diets were designed to provide animals varying intake nitrogen fiactions to

elicit different responses in utilization and excretion patterns to allow for cornparisons against mode1 predictions. The observed ranges of intake nitrogen kctions supports that this was achieved, even if the absolute amount of nitrogen was higher than intended.

Nitrogen Balance

The overall nitrogen balance (Table 3.6) indicated that there was a significant difference in the route of nitrogen excretion across the treatment diets. The level of nitrogen excreted in the miik and retained in the tissue were not different, thus productive nitrogen was unaffected by treatment level. However, the power of the t-test may not have been sufficient to ailow the detection ofa significant différence between treatments, and producing a type II error. The level of intake nitrogen that was captured as milk nitrogen feil within the ranges reported by Tamminga (1992) of 15 to 25%. However this

was lower than data fiom Chalupa and Ferguson (1995) where they were achieving values of 30 to 35% by balancing the diet to maximize microbial capture of rumen ctmfnonSa and increasing metabolizable protein nom U[P sources. They reported that constraining the

m e n ammonia balance to 100% of requirement reduced nitrogen excretion by 15% (Chalupa and Ferguson, 1995). AU diets in this experiment were in excess rumen ammonia balance and demonstrate the associated increased aitrogen loss. Differences were found in the route of nitmgen excreîion. The high solubility diet's main route of excretion was through the urine (Table 3.6), which was significantly greater than in the low solubility treatment, while fecal nitrogen was significantly lower.

The medium diet tended (P < 0.1) to have a higher nitrogen intake, which produced

.

higher gram per day values than the other treatments for aU variables. By analyzhg the mean data on a percent of nitrogen intake basis, the level of fecal (37.2%) and

LU~EUY

(38.5%) excretion appeared to be equally balanced (Table 3-6).Similar results were found in a study by Buchanan-Smith (1994), where raising protein degradability of the diet had

a greater impact on excretion route than overail protein level. Similady, Susmel (1995) fed an additional 290 g per day of urea and observed that 47% of the extra NPN was lost in the urine, 20 % was utilized in the milk and 33% was retained in the body. The

conclusion reached was that what nitrogen was not captured for microbial production was lost immediately in the urine. Lines and Weiss (1996) also reported that nitrogen balance was unaffected by urea addition but with an increase in urinary nitrogen. These results,

and those observed in this trial, suggest that balancing the diet to minimize excess rumen ammonia has a direct impact on urinary nitrogen excretion (Ferguson and Chalupa, 1994)

and an important aspect for incorporation into a nutrient management model.

Table 3.6 Nitrogen Balance Measurements on a gMay and Percentage of Dietary Nitrogen intake Basis.

Solubility Level

Medium

Low

+

Intake N

587.8 16.9 (537.7 - 652.0) 221.3 5 11.7 (197.0 - 270.6) 179.85 7-9 ( 1 55.8 - L98.8) 119.6% 4.6 (101.4 - 128.9) 67-1f: 17.3 (4.6 - 114.1) 186.7 5 17.3 (133.6 237.1)

Fecd N Urine N Milk N Retained N Productive N

-

Hi&

a a a

a

a a

Fecai N

Urine N Milk N Retained N

+

Values are means SE of n = 6. Vaiues in brackets are rangesa,b,c Means within a row having a different letter are statistically different at (P C 0.05)

The fecal :urine nitrogen ratio aiso demonstrated this effect of solubility on the nitrogen balance. The differences between the treatment mean ratios were significant (P c 0.05) with the low treatment fecal : urine nitrogen ratio of 55.2:44.8,

medium of

49.4:50.6, and high of 45.1549. As solubility increased from low to high , the ratio

switched by 10% fiom higher fecal nitrogen to higher urine nitrogen ,while the medium diet induced an intermediate response. This was important in the context of the

assurnptions that were made for predicting manure quant@ and composition for storage and fertilization recommendations (Builey and Holbeck, 1982, Safley et ai., 1986, Van

Hom et al., 1996). The assumption made by ASAE (199 1) and Van Hom et al. (1 994) was that manure nitmgen was approximately 50% in the fomi of urea and ammonia, mainly fiom urine. This established the level of nitrogen volatihation that was calculated to occur. A shift in the contniution of urinary nitrogen would affect the leve1 of predicted

nitrogen left in the manure at time of incorporation into the soil. The individual animal nitrogen balance values provided a wide range of responses to the treatment diets to be used for mode1 evaluation. The principal conclusion of this

trial was that altering protein solubility, degradability and undegradability affected the proportion of nitrogen excreted in either the feces or urine. This is critical for detemiining

nutrient availability at point of storage and for balancing rations to minïmize environmental losses when using on-fgnn ingredients such as silage which can vary tremendously in protein solubility.

Feces

Fecal production (kg DM / &y) was highest on the medium solubiiity diet (Table 3.7), which also was numencaliy higher in Qy matter intake (Table 3.5) than the other

treatments. There was little Merence in the composition of the feces between treatments other than the crude protein level in the low diet, the one with the highest inclusion of

UIP ingredients, being slightly eIevated. The A and B1 fractions appear to be a major component in the feces of ail the treatments (Table 3.7). These levels are higher than expected since Van Soest (1994) reported that most of the oitrogen in feces is fiom the indigestible portion of the diet and undigesteci microbial celi wds. Urea in the feces would be expected to be lost by volatilization to ammonia. A possible explanation would

be the degradation of protein in the excreted feces into it's soluble f o m by microbes or

naturally occurring enzymes during the t h e p e n d between collections. This degradation would be breaking down protein fÎom the B2 and B3 fiactions into urea and small peptides or soluble tnie protein. However, analysis of rectal grab samples of feces that

were Unmediately fiozen in liquid nitrogen (unpublished data), revealed an average protein solubility of 28

+ 1.5 % of the crude protein. Comparing this with the mean

observed value of 38 % suggested that a large portion of the soluble hction was present at the tirne of excretion, although some post excretion degradation had occurred. This has

a direct effect on the assumptions that are made of fecal nitrogen stability and susceptibility to volatilization in manure storage models. The possibility that greater than 25% of the nitrogen in the feces codd be quickly lost to ammonia by volati1ization must be considered for incorporation into the cdcdations of nutrient management systems.

Table 3.7 Fecd Chemical Composition and Correspondhg Cornell Net Carbohydrate and Protein System Protein Fractions. Solubility Level Low Amount (kg DM/day)

Cnide Protein (%)

ADF (%) NDF (%) Lignin (%) Fat (%) Ash (%)

Total N Soiuble N + NPN ADF-N NDF-N A + B 1 Fraction

B2 Fraction

B3 Fraction C Fraction

Endogenous N' Endogenous N' -calcuiated from NRC (1989) Values are means + SE of n = 6. Values in brackets are ranges. a,b,c Means withina row having a different letter are statisticaily different at (P c 0.05)

Microbial fermentation in the lower intestines contriautes to the amount of potentially digestible nitrogen in the feces (NRC, 1989). The level of microbial production depends upon the availability of carbohydrate and protein (Tarnminga, 1992). In the treatment diets there wodd be sufficient nitcogen fiom c i r c u l a ~ gurea and NDF

bound nitrogen available for microbial prgduction. Also there was available NDF for structural bacteria growth. As corn was the major source of energy in these diets there would be the opportunity, according to the CNCPS model, that starch avoided digestion in the rumen and small intestines and was available for large intestine fermentation, due

to a slower rumen degradation rate and lower postnunùial digestibility (Sniffen et al., 1992). An increase in hindgut microbial production can decrease urea excretion in the

urine and increase fecal nitrogen excretion. However, hindgut microbial production can also digest endogenous protein into ammonia which c m be absorbed across the large

intestine and be excreted as urea in the urine. Endogenous fecal N was calculated using the NRC (1989) equation of 9% of indigestible dry matter (Table 3.7). The CNCPS

model also uses this equation to calculate endogenous fecal N which is then added directly to the C portion of the fecal total. This ïmpiies that the CNCPS model considers endogenous protein indigestible and to consist of sloughed animal tells, mucous and keratinized tissue (Sniffen et al., 1992). This does not agree with the observed nitrogen fractions which appear to be related to the feed C hction only (Table 3.5). Also it does not fit the description of endogenous protein provided by NRC (1985) which reported a range of 16 - 59% water soluble nitrogen. The CNCPS model overestimated the amount of fecal nitrogen bound in the C fraction and ignores the possibility that any fecal nitrogen

could be in the A, B 1 and B2 fiactions by assuming 100% digestibility. This calculation

approach would lead to incorrect assumptions in nitmgen stability in manure storage and soi1 utilization by not taking into account the potential of volatilkation loss fiom the fecd portion of manure nitrogen. The observed results, as weil as the large range, indicate a need to improve the estimation of endogenous nitrogen in the rnodel. Further information on fecal nitrogen hctionation is necessary to reflect the potential for hindgut microbial production to alter the excretion pattern,

Apparent Digestibility The high solubility diet had a significantly higher apparent digestibility for nitrogen than both the low and medium diets (Table 33).This is similar to the finding of Buchanan-Smith (L996) where he found protein degradability impacted nitrogen digestibility. The high SIP diet was also sigaificantly higher than the medium diet for dry

matter apparent digestibility. This may be an impact of the slightly higher intake level of the medium diet increasing passage rates and thereby decreasing overall digestibility (NRC, 1985). The fat and ash digestibility were consistent across al1 diets (Table 3.8). In

the CNCPS model, fat is calculated as 95% digestible and ash is 50% (Sniffen et al, 1992). The observed ssh digestibility agreed with the value used in the CNCPS, but the

determined fat digestibility was 11 to 13% lower than that used in the model. This would negatively affect the calculated energy available to the animal (Sniffen et al., 1992)The apparent digestibility values of the protein fiactions A+B 1, B2, B3 and C are dependent on whether the chernical analysis done on the samples t d y represent that of fiesh fecal matter. The C hction, representing the bound fiaction would not be affected

Table 3.8 Apparent Digestibility of Dietary Components incIuding the Corneil Net

5 Solubility Level

Low

Dry Matter Nitrogen

ADF NDF Fat Ash A + B 1 Fraction

B2 Fraction B3 Fraction C Fraction

Values are means 2 SE of n = 6. Values in brackets are ranges. a,b,c Means within a row having a different letter are sipnificantly different at (P < 0.05)

by any degradation over the collection period. This hction is generally considered

indigestible and the CNCPS uses a value of 0% for it's calcdation. The srnaii values obtained here could be representative of errors in samphg, analysis and the overd nitrogen balance procedure and are not signincantly different from zero. The A+B1 fiaction was measured as soluble nitrogen and considered 100% absorbed in the m e n by the model. The determined apparent digestibility therefore does not relate directly to the

feed, but rather to either a reabsorption of urea in the large intesrines or an artifact of post defecation digestion. The B2 and B3 hctions are given digestibility values of 100% and

80% respectively in the CNCPS model. The underestimation of digestibility of these fiactions observed in this trial versus the model may be a resuit of hindgut fermentation

(NRC, 1985) and the decision in the model to put all endogenous losses in the C fraction of the feces. The apparent digestibility results reinforce the requirement for an improved evaluation of how postnuninal fermentation influences urea recychg and excretion in the

model-

Urine Urine volumes were impacted by dietary treatment, with the ciifference between the low and other two groups being significant (Table 3.9). This was due to the higher

amounts of urea that was being excreted by the kidneys in the high and medium diet groups vernis the low diet group, which is in agreement with Morse et al. (1994). Total

urùiary nitrogen, as described in the nitrogen balance, indicated the ciifference between the high and low treatment's main route of excretion. Concentrations found here (9.4 to

10.1 g Nfitre) are consistent with the range reported by Bristow et al (1 992) for cattle of

2 to 20 g Nfitre. The level of urea nitrogen in the urine followed the same pattern as total

nitrogen (Table 3.9). Urinary urea has been used as an indicator of protein utilkation and balance in nuniLlants (Gonda and Lindberg, 1994, Wilkerson et al, 1997). The percentage

of the total urinary nitrogen that is urea nitrogen is consistent across diets and thus lends itself for mode1 cornparison purposes. This percentage f d s within the range found by Bristow et ai. (1992) of 68% to 93%. Overd184 - 90 % of the total urioary nitrogen was identified as urea, ailantoin, uric acid and creatinine. The remaining nitrogen could be in compounds çuch as hippuric acid, creatine, xanthine and hypoxanthine and fiee amino acids (Bristow et al., 1992).

Urine was also analyzed for purine derivatives, specificaiiy ailautoin and uric acid, due to their important contribution to nitrogen excretion and the potential of using

them as an indicator of microbial protein production (Chen and Gomes, 1992). Xanthine and hypoxanthine were not anaiyzed as they nomaiLy occur in cattle urine at very low

levels (Bristow et al ,1992). This has been attnbuted to a high activity of xanthine oxidase

in cattle tissues which oxidizes these compounds to uric acid (Chen et al., 1990a). There was no significant cifierence between the treatments in aiiantoin and uric acid when

analyzed separately. Again, the power of the t-test may not have been sufficient to detect a true difference. ALthough when the purine derivatives were considered as a whole, the

medium diet was higher (P~0.05)on a mmoVday and gcam/day nitrogen basis (Table 3.9). This approach has also been reported by Stefanon et aL(1996) who suggested that

the sum of the two purine derivatives was the most reliable Uidicator of microbial protein. These results would support the conclusion that the rumen requirement for protein was best baianced on the medium diet which contained soybean meal, a source of

----

-

Table 3.9 Chemical Composition of the Urinary Nitrogen Fraction includùig Urea, Punne Derivatives and Creatinine. Solubility Level

Low

Medium

Amount (kg /&y)

Total N (g/day) Urea N (g/day) Urea N (% of Total N) Allantoin (mrnoYday)

Uric Acid (mm0Wday)

'

PD (rnmol/day) Allantoin (% of PD)

PD - N Wday)

PD - N (% of Total N) Creatinine (mg/dl) Creatinine - N (*y) PD' - Purine derivatives - calculated as allantoh plus uric acid Values are means _t SE of n = 6. Values in brackets are ranges. a,b,c Means within a row having a different letter are significantly different at (P < 0.05)

peptides for the NSC bacteria (Russell et ai, 1992). AUantoin has been reported to be the

main form of purine derivatives excreted in cattle urine (Chen et a1.,1990b, Balcelis et al 1991, Susmel et al 1994) with mit acid comprising most of the remainder. This was in agreement with the results of this study. The percentage of purine derivatives that was allantoin was consistent across ail diets (Table 3.9) and was in agreement with the value of 85% found by Chen et a1.(1990c) and Dewhurst and Thomas (1992). Also the level of total nitrogen that was supplied nom putines was in the range reported by Bristow et al (1992) and Ettala and Kreula (1976) on cows fed urea as the sole nitrogen source. Dietary

purine contribution to urhmy purine excretion was net considered to be significant, even on the low SIP diet contahïng fish and blood med, following the reports of Moscardini et al. (1998) and Calsamigilia et al. (1996) that found negligible contributon on diets

with higher inclusion rates of CTIP ingredients. The contribution of purine derivative nitrogen to total uruiary nîtrogen excretion suggests that purine derivatives should be considered an important variable to determine when rneasuriog urinary oitrogen bctions. Mode1 parameters need to be estabLished to reflect this contribution to the total nitrogen excretion and the impact on urine nitrogen volatility. Bristow et al. (1992) reported that eventually uricase enzyme in the environment wiU break down purine derivatives to urea and then ammonia but with a longer t h e lag than if excreted in the urea form. This has implications on potential ammonia loss rates before storage and thus the quatltity of nitrogen available for fertilization. The CNCPS version 3.0 does not make any predictions on urine nitrogen amounts or hctiom but implied in the calculations is that

aU microbial nucleic acids or microbial A hction nitrogen is digesteci but excreted in the Unne.

Creatinuie was also analyzed in the urine, with the Iow diet group having a significantly higher concentration than the other diet groups. When the creatinine analysis was reported on a g/day nitrogen basis there was no merence between treatments due to

lower urine volume in the low diet. Research has investigated using creatinine as an interna1 marker of excretion rates to make quantitative predictions of metabolic processes and it's relationship to Lveweight (Brody, 1945). These data have been utilized in purine research to observe whether spot samples of urine could be used instead of total

collections, which would have benefit in pasture and practical applications. ALso, Chen et

al. (1996) reported that the calculated relationship of excreted urinary purine derivatives with plasma purine derivatives and microbial protein production was affected by a change

in the kidney filtration rate. The observed d o r m i t y in creatiniae nitrogen and purine derivatives nitrogen suggests there were no dietary treatment effects on the glomerular mtration rate and that this could be removed as a possible variable. The treatments were designed to provide different levels of rumen degradable nitrogen for microbial production while maintainhg a constant level of carbohydrate fractions. This was expected to manipulate the amount of microbial protein king produced, which would be detected by the purine derivatives. It was evident fiom the lack

of any significant merences between treatments in purine derivatives (Table 39), that with the level of nitrogen solubility fed there was no deficiency of available nitrogen in

the rumen and microbial production was M t e d only by carbohydrate availability.

Blood There were no significant ciifferences between treatments in any of the measured blood parameters (Table 3.10). Again, the power of the t-test may not have been sufficient to detect a true difference. AU observed levels fell within reference ranges reported by Topps and Thompson (1984). The values of plasma urea nitmgen (PUN) tended, non-significantiy (PHLOS), to increase from the low SIP diet to the high SIP diet, but so did the variability (Table 3.10).

This Iack of ciifference between treatments is in

disagreement with seveml researchers who had found a significant impact of increased levels of DIP on PUN values (Baker et al., 1995, Roseler et al., 1993, Wright et al., 1998). These trials u d y varied crude protein intake to develop regcession equations

and did not reach the level of degradability or solubility found in this trial. Blauwiekel and Kincaid (1986) reported no effect of protein solubility on blood urea nitrogen when

crude protein was held constant, but a significant difference between protein levels. Forster et al. (1983) also saw no effect of nitrogen solubility on blood urea nitrogen of steers. It is evident fiom the analysis that ali treamients were under excess rumen ammonia conditions and would be contribuMg to the circdating PUN levels. It appears

from the mean values that the procedure of taking one sample of blood for analysis was not sufficiently sensitive to detect the differences between the treatments with increased

amounts of soluble nitrogen. There were, however, large variations found between animals and thus the results must be analyzed on an individual animal basis for mode1 evaluation. The amount of uruiary urea nitmgen was repcxted to be dependent on the level of urea in the blood and the glomenilar nitration rate (Maltz and Silanikove, 1996). With the differences found between the treatments for urine urea nitmgen (Table 3.9), it

Table 3.10 Blood Parameter Composition for the Cornell Net Carbohydrate and Protein System Mode1 Evaluation. Solubility Level Total Protein (g/L)

B H B ~(POIL) Glucose (mmoVL)

Urea N (mg/cU)

'

Medium

Low 70-05 4.2 (63 - 75) 828.7 2221-1 (598 - 1135) 3.1 20.3 (2.7 3.4) 15.5 + 0.6 (14.6 - 16.3)

-

69.3 + 3.3 (66 - 75) 1040.7 428.6 (488 - 1687) 3.0 0-4 (2.4 - 3 -7) 16.3 _t 1.1 (15.2 - 18.0)

+

+

BHB - P-hydroqbutyrate Values are means 2 SE of n = 6. Values in brackets are ranges-

would be expected there would be a detectable difference in the blood, suggesting again a lack of sensitivity due to the large variations when using mean values.

Milk There were no signincant merences between the treatments in any of the

measured mille parameters (Table 3.1 1) that we were able to detect with the power of the t-test used. The mik protein and fat analyzed by NTR were within the nomial ranges found for that herd. The nitmgen fractionation, on a g/day basis, between m e protein and

NPN did not differ between treatments but the medium diet tended (P>0.05) to have a higher output fkom an increased milk volume. The mille urea nitrogen (MUN) values found were slightly lower than values reported in a sunrey of Ontario herds of 13.9 mg/dl (Godden, 1998). These MUN values appeared to be unaffeçted by changes in the SIP,

DIP and UIP levels. This was in disagreement with Roseler et aL(1992) who found a strong relationship between UIP and MUN values. The study by Roseler et al. (1992) used diets that ranged in DIP fiom 57 to 71% of crude protein, while thïs trial had D I . levels of 7 1 to 80 %. However in that trial, crude protein was also varied which was not the case in this experiment. The large increases reported in the trial of Roseler et al.

(1992) were attributed to both degradable and undegradable protein excesses. The MUN

values in this trial displayed the same unresponsiveness as the PUN values, however with less variability around the mean. The relationship between MUN and PUN has been

demonstrated by numerous trials in the literature (Gustafsson and Palmquist, 1993, Roseler et al. 1993, Baker et al. 1995). Insensitivity of MUN to increasing protein degradability was also experienced by Rodriguez et al. (1997) in a trial where UIP was

Table 3.1 1 MiUc Chemicd Composition and Protein Fractions for the Comeil Net Carbohydrate and Protein System Mode1 Evaluation. Sohbility Level

Low

Medium

Amount (kg / &y)

25.3 f 1.4 (19.2 - 28-1)

Protein (% by NIR)

3.3 2 0.1 (2.8 - 3.6) 4-42 0.1 (4.0 4.7) 12.4 0.3 (11-5 - 13.2)

Fat (% by MR) MUN' (mg/d)

Total N NPN

True Protein -N Urea -N NPN (% of Total N)

Urea -N (% ofNPN)

+

High

26-6_+ 2.3 (20.2 -32.5)

24.3 5 1.1 (21.2 - 28.9)

3.2 2 0.2

4.3 2 0.3 (3.0 - 5.0) 12.7 2 0.3 (12-0 - 13-5)

3.2 + 0.1 (3 .O - 3 -4) 4-6 % 0.2 (4.1 - 5.3) 12.4 + 0.6 (10.5 - 14.1)

7.0 2 0.5 (5.9 - 8.9) 35.7 t 2.4 (27.5 -41.l)

7.5 0.5 (6.2 - 8.5) 35.4 2.1 (29.4 - 43-9)

(2.6 - 3.6)

119-62 4.6 (101.4 - 128.9) 8.3 5 0.6 (6.5 - 10.0) 111.3 5 4.6 (94.9 - 121.4)

3.2 2 0.2 (2.3 - 3 -6) 7.3 5 0.4 (6.0 8-6) 38.3 2 2.4 (32.5 - 46-8)

-

MUN1 - milk urea nitrogen Values are means + SE of n = 6. Values in brackets are ranges-

+

+

increased fiom 29 to 40% and protein was kept constant. The totai amount of intake nitrogen, rather than the form, appears to be the major influence on urea excretion Ieveis (Gonda and Lindberg, 1994)The percentage of total milk nitrogen coming fiom NPN (Table 3.1 1) is slightly higher than that found in the literature summarized by DePeters and Ferguson (1992) of 5% to 6% but withui the ranges reported by Baker et al. (1995) studying effects of varying

DIP levels on milk nitrogen composition. The percentage of NPN that is urea nitrogen falls within the range reporîed by DePeters and Ferguson (1992) of 35% to 48%. Roseler et al. (1993) also found a range of 20% to 44% of milk NPN as urea nitrogen. They

reported a significant relationship between UTP and DIP in the diet and the level of milk NPN that was not found in tbis trial. This relationship was not as sensitive as MUN to diet DIP and UIP changes when the diet were isonitrogenous. The insensitivîty of milk protein fiactions to changes in protein solubiiity needs to be further investigated in order to properly use EiNN as a tool for evaluating rations. Hof

et al. (1997) identified that only about 50% of the variation in milk urea nitrogen content

could be atûibuted to nitrogen losses nom the rumen. The ability to use a simple measurable index such as MUPI for model development and prediction of other nitrogen excretion levels would still be a goal for o n - f m application.

CNCPS Predîctions

The CNCPS mode1 was used with individual animal parameters to evaluate the strengths and weaknesses of the prediction equatiom and relationships with other measured variables such as the purine derivatives in the foilowing chapter.

EVALUATION OF EXPERLMENTAL OBSERVATIONS WTH THE CORNELL

NET CARBOHYDRATE AND PROTEIN SYSTEMS MODEL PREDICTIONS

4.1

Introduction

The Corne11 Net Carbohyrate and Protein System (CNCPS) model, and its derivatives such as the beef NRC (1996) and the CPM-DAIRY (CorneIl-Penn-Miner, 1W8), are currently usefùi tools used in North America for evaiuating dairy cattle rations.

Animal, environmental, management and feed inputs are entered by the user and the model generates a prediction of both the diet supplied nutrients and nutrients required by the animal for the indicated level of production. The user can then evaluate the diet

according to the differences between the supplied and required level of nutnents. The

model does not calculate a niwgen balance, since no value is provided for urinary nitrogen loss. In this experiment, environmental and management factors were maintained as a constant in the model across al1 treatments and periods, and the animal and dietary factors were treated as variables.

This chapter will cover the fourth objective of this thesis, which was to evaluate the individual animal responses veaus predicted results fkrn the CNCPS model.

Regression analysis with animal, diet, blood, mille, fecal and Unnary factors were used to determine if meanin@

relationships between measured parameters existed and how

these compared to CNCPS model's generated r e d t s . Variables not measured, such as

rumen and total nitrogen balance, but calculated in the model were hvestigated as to their application in predicting analyzed components.

4.2

Model Evaluation

Model Parameters Outputs

The CNCPS model (version 3-0 ,1994) was inputted with the measured animal, enviro~mentai,management and feed compositional data. Model outputs were compiled and analyzed on an individual animal basis (Appendix 2) with the treatment means and ranges reported in Table 4.1. The main outputs of interest in this trial were the predictions of nitrogen levels in the bacteria, rumen, feces, blood and mîlk- Cornparison of predicted venus observed values could only be done for the PUN, MUN and the fecd nitrogen fraction variables. Urine nitrogen predictions were not available in this version of

CNCPS. Dietary protein degradability was calculated in the CNCPS model as the sum of the analyzed protein fractions multiplied by their digestion rate adjusted for rate of

passage. Default values for digestion rates of component ingredients were adopted (Appendk 3). The resulting values (Table 4.1) were significantly higher (P < 0.05) in a l l

treatments than those predicted by NRC (1989) in Table 3.5, however the relative differences between treatments remained as designed. The NRC values were based on static estimates tiom a summary of in vivo and in situ research W C , 1989) and did not reflect the observed increases in protein solubility. The CNCPS prediction for degradability increased as solubility increased due to the impact of the A nitrogen fraction

Table 4.1 Comell Net Carbohydrate and Rotein System Mode1 Parameter Outputs. Medium Low Solubility Level 75.0 + 0.4 71.0+0.4 a DIP (% of CP) (74.0 - 76.0) (69.0 -72.0)

&&Y M P m MP Bacteria MP Total

MPN/htakeN(%) Bacterial Total N Bacterial "A"N Rumen N Balance

Recycled N Peptide Balance Total N BaIance PUN (mgW

M J N (mgW

730.5 & 38-7 (604-841) 1545.8 2 57.6 (1361-1701) 2276.3 + 95.7 (1965 - 2527) 57.8 + 0.5 (56.3 - 58.8) 412.2 2 15-4 (363.0 - 453.5) 61.8 22.3 (54.4 - 68.0) 126.2 5 5.4 (108.0 - 143.0) 65.8 + 2.7 (57.0 -73.O) -16.8 I2.L (-22 - -1 1) 87.5 5 10.2 (58.0 - 13 1.0) 18.3 2 0.7 (16.0 -20.0) 14.5 + 0.6 (13.O - 16.0) g+'day

Total Fecal N Fecal Feed B3 N

Total Fecal C N Fecal Feed C N

253.4+ 11.0 (2 17.8 -282.5) 4.6 + 0.2 (4.0 - 5.5) 248.8 5 10.9 (213.5 -278.3) 38.0 2 2-1 (3 1.3 -44.2)

103.0 5 3.8 (90-7- 113.4) 107.8 + 5.1 Endogenous C N (91.4- 121.5) Values are means i+ SE of n = 6, Values in brackets are ranges. a,b,c Means within a row having a different letter are significantly Merent at (P < 0.05) Fecal Microbial C N

(Table 35). This demonstrates an important merence in the protein evaluation systems responsiveness to changes in chernical analysis for calculating protein degradation in the rumen, The estimation of total metabolizable protein (MP) was calculated as the sum of digested niminal escape feed protein (MP UIP) and digested bacterial protein minus the

bacterial nucleic acids (MP bacteria) (SnEen et al., 1992). The bacterial nucleic acids were classified as the A hction in the CNCPS and were assumed to be totally digestible and completely excreted in the urine (Sniffen et al., 1992). This assumption does not take into account that nucleic acids can be salvaged and incorporated into tissue (Chen et

al.,199Oa), recycled in the saliva to the rumen for digestion (Chen et al.,1990b), or partially excreted via mille (Gonda and Lindberg, 1997). The CNCPS model predicted a significantly (P~0.05)lower UIP MP value for the high SIP diet than the other two diets as per design (Table 4.1). The model prediction of no treatment effect on MP Bacteria, total bacterial nitrogen and bactena A &action (nucleic acids) agreed with the results nom the purine denvative analysis. Total MP prediction showed the high diet was significantly lower than the other two die& (Table 4.1), mainly fiom the lower MP UIP value, although MP bacteria on the high diet tended, non-significantly, to be lower also, reflecting a predicted decrease in the ability of the microbes to capture the increase in soluble protek. This is demonstrated more clearly in the ratio of total MP nitrogen predicted versus total nitrogen intake. There were signif?cant ciifferences between ail treatments with a significant (P0.5), defhed by the equation:

O bserved PUN (mghil) = 14.7 + O.OSS(Predicted PUN (mgldl)) (It2=0.0i). The intercept and slope were significantly (Pc0.01) different fiom zero and one respectively, supporting the need to reevaiuate the prediction. W i t b the same crude

protein level as in this study, this calculation appears to be insensitive to varying protein solubility and overampensates for the contributon of the UIP portion.

In the same respect predicted milk urea nitrogen 0 values were not related to the determined values. The CNCPS mode1 predicted a decrease in MUN with the hi&

SIP diet. This was not observed in the experiment- The cornparison between the observed

and predicted MUN was not significant 0 . 5 ) and descnied by the equation: Observed MüN (mgAl) = 9.7 + 0.2O(Predicted MUN (mg/dl)) (R? = 0.09). The low R~ suggested a deficiency in the equation which was fiuther supported by the

intercept and dope being signiticantly (P

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