Use and Limitations of Profiles in Assessing Health or Nutritional Status of Dairy Herds 1 R. S. ADAMS, W. L. STOUT, D, C. KRADEL, S. B, GUSS, Jr., B. L. MOSER, and G. A. JUNG College of Agriculture The Pennsylvania State University University Park 16802
routine dairy herd management. Some of these may be overcome in the future while others are inherent.
ABSTRACT
A number of factors limit the usefulness of blood or metabolic profiles. These include sampling problems, low correlations with nutrient intake, inconsistent patterns in disease, and difficulties in interpretation. Despite these limitations, profiles properly used may serve as an adjunct to more conventional technology in alleviating some dairy herd problems. Their use appears justified when feed analysis, ration evaluation, disease testing, and checks on management do not alleviate herd problems. Considerable potential for misuse of profiles exists due to the complexities of interpretation.
Sampling Problems
Sampling problems have been presented in detail by others (9, 13, 21). Differences exist among sites of blood sampling. Serum from blood removed at the mammary vein may be higher in phosphorus but lower in calcium and magnesium than jugular samples (23). Tail blood may be higher in inorganic phosphorus and potassium but lower in calcium, magnesium, packed cell volume, and hemoglobin than jugular samples (14). Choice of animals to be sampled also has not been resolved. Many workers follow schemes similar to those of English workers (3, 17, 19).
INTRODUCTION
Our experience with blood or metabolic profiles dates from 1968 when a limited program was initiated by the Large Animal Diagnostic Laboratory of The Pennsylvania State University. Since that time certain blood chemistries and hematological tests have been run on samples from approximately 750 problem dairy herds. In addition a 2-yr study has heen made of some blood parameters, health, and reproduction as well as soil, water, and feed analysis in 15 high-producing herds with a history of good health and reproductive performance (23). This research has provided a basis for the development of expected values for use in the interpretation of blood profiles (1). Various aspects of the program have been published in (7). LIMITATIONS
A number of factors limit the usefulness of blood profiles in either problem situations or Received October 3, 1977. 1Scientific Journal Series Paper No. 5540, Pennsylvania Agricultural Experiment Station. 1978 J Dairy Sci 61:1671--1679
Low Correlations with Nutrient Intake
Considerable emphasis has been placed by some on the use of profiles in assessing nutritional status (3, 16, 17, 18, 21). Homeostatic mechanisms and various nutrient interrelationships could be expected to limit their usefulness in this regard. Others have indicated that other animal tissue tests, feed analysis, and, in some cases, soil tests may be better indicators of ration adequacy than blood tests (4, 10). Based on estimated intakes obtained under farm conditions in Pennsylvania, some significant but low correlations may exist between some blood measures and nutrient intake (2). Contributions of both feed and water were included in this study of normal herds. Some of these relationships are in Tables 1 and 2. English workers (15) also have found some significant but low correlations between blood parameters and nutrient intake. These researchers cautioned that blood contents do not show cconsistent relationship with nutrient balance. Blood profiles are sufficiently sensitive to
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TABLE 1. Correlation of some blood measures with estimated nutrient intake. Estimated intake expression Correction a
Total
% Dry matter
Hemoglobin with crude protein Total protein with crude protein Albumin with crude protein Globulin with crude protein Calcium with ration Ca Phosphorus with ration P Magnesium with ration Mg Potassium with ration K Iron with ration Fe Copper with ration Cu
-.22
...
a
.
.
...
% NRC b +.18
+.07
+.08
-.07 -.06 +.10 +.19
... +.06
+.07 . .
"-:1"9
...
+:06 +.14 +:09 .
.
.
.
.
Significance at 5%: .06.
bIntake expressed as a percent of National Research Council requirements, as given in
Nutrient Requirements
of Dairy Cattle, 1971. National Academy of Sciences, Washington, DC.
TABLE 2. Influence of nutrient interrelationships on selected blood measures. Estimated intake expression % Dry matter
% NRC
Correlation a
Total
Serum calcium with ration: Calcium Phosphorus Magnesium Iron Zinc Crude protein Estimated TDN
-.19 -.21 -. 19 -.29 -.24 -. 15 -.21
"-:09
"-:11 -.24 -.10 -.13 ...
Serum magnesium with ration: Magnesium Potassium Copper
+.08 -. 13 +.11
+.19 -.09 +.15
+.14 -. 12 +.12
Serum copper with ration: Copper Estimated TDN Magnesium Phosphorus
+.06 +. 12 +.08 +.12
... ...
Hemoglobin with ration: Crude protein Estimated TDN Iron Copper Zinc
-.22 -. 39 -.23 -.24 -.30
a
.
.
.
Sxgmflcance at 5%: .06.
Journal of Dairy Science Vol. 61, No. 11, 1978
-.06 -.14 -. 11 -.23 -.19
+.06
+:07
"-:06 ... ...
"-:08 -.12 -.15 -.23
+.18 +.11 -.12 -.15 -.22
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TABLE 3. Mean blood contents in herds with a high incidence of various problems. Milk fever
Parameter Packed cell volume, % Hemoglobin, g/dl Red blood cells, M/mm 3 White blood ceils, T/ram 3 Serum inorganic P, mg/dl Serum Ca, mg/dl Serum Mg, mg/dl Serum K, meq/l Serum Cu, ppm Serum Fe, ppm Total protein, g/dl No. samples
31.8 10.7 5.9 9.0 5.7 9.1 2.3 7.0 .84 1.99 7.9 813
Tetany syndrome
Infertility
27.0 10.3 5.8 8.1 5.9 8.8 2.1 7.5 1.05 2.14 8.3 79
31.2 10.4 5.9 9.0 5.8 9.5 2.4 6.4 .91 1.99 7.7 858
Expected a 32.3 10.8 6.2 9.4 6.0 9.3 2.2 5.1 .85 1.72 7.6 2290
aReference (23).
i n d i c a t e wide d e p a r t u r e s f r o m r e c o m m e n d e d i n t a k e in s o m e cases. P r e l i m i n a r y d a t a f r o m a s t u d y u n d e r c o n t r o l l e d c o n d i t i o n s at t h e P e n n s y l v a n i a s t a t i o n suggest t h a t u r e a n i t r o g e n in b l o o d was a l m o s t 50% less o n a r a t i o n c o n t a i n i n g 12.7% vs. 17% c r u d e p r o t e i n o n a d r y m a t t e r basis. B l o o d glucose values a p p e a r e d t o be r e d u c e d o n l y 8% w h e n cows were fed forage a l o n e a f t e r r e a c h i n g m i l k p r o d u c t i o n o f 18.2 kg daily. B l o o d c o n t e n t s have b e e n in r e a s o n a b l y close a g r e e m e n t w i t h e s t i m a t e d i n t a k e s f r o m r a t i o n e v a l u a t i o n in s o m e p r o b l e m herds. T h e r e l a t i o n s h i p , h o w e v e r , is n o t suffic i e n t l y c o n s i s t e n t to e n a b l e use o f profiles as a sole m e a n s o f assessing n u t r i t i o n a l s t a t u s or nutrient intake.
Inconsistent Patterns in Disease
A wide variety o f a b n o r m a l i t i e s in profile m a y o c c u r in a n y t y p e of p r o d u c t i o n disease.
A b n o r m a l i t i e s are n o t striking or c o n s i s t e n t a m o n g h e r d s suffering f r o m a h i g h i n c i d e n c e o f a p a r t i c u l a r disorder. B o t h a b n o r m a l l y high a n d l o w values for a given p a r a m e t e r m a y b e f o u n d a m o n g afflicted herds. This s i t u a t i o n is indic a t e d b y t h e lack o f large d i f f e r e n c e s in m e a n b l o o d values in samples f r o m P e n n s y l v a n i a h e r d s w i t h a high i n c i d e n c e o f various h e a l t h p r o b l e m s . T h e s e are in T a b l e 3. B o t h high a n d low calcium in s e r u m are e n c o u n t e r e d in h e r d s w i t h a high i n c i d e n c e o f m i l k fever or d o w n e r c o w s y n d r o m e . L o w s e r u m c a l c i u m m a y be associated w i t h e i t h e r a n excessive or i n a d e q u a t e i n t a k e o f this e l e m e n t . F u r t h e r , n o r m a l calcium a c c o m p a n i e d b y o t h e r a b n o r m a l i t i e s m a y b e in profiles~ f r o m o t h e r h e r d s w i t h this disorder. T h i s is i l l u s t r a t e d in T a b l e 4 w i t h d a t a f r o m selected h e r d profiles. A n e m i a m a y b e in m a n y profiles f r o m h e r d s with infertility problems, but not consistently. T h e a p p a r e n t effects o f a n e m i a o n r e p r o d u c t i o n
TABLE 4. Mean serum minerals in herds with a high incidence of milk fever and downer cows. Herd Ex-
Serum
A
B
C
D
Inorganic P, mg/dl Ca, mg/dl Mg, mg/dl K, meq/l
4.7 7.6 1.1 6.0
4.4 9.4 2.2 7.8
6.2 10.9 2.6 ...
7.6 11.0 2.3 6.1
pected a 6.0 9.3 2.2 5.1
abased on data obtained in normal herds (23). Journal of Dairy Science V ol. 61, No. 11, 1978
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TABLE 5. Reproductive performance of dairy cows grouped according to hemoglobin content,a Mean
hemoglobin
Services
Days open
per conception
119 113 75
2.7 1.6 1.5 1.3
(g/dl) 9.1 9.7
10.2 10.7
77
aReference (12). in some problem herds were summarized by Morrow (12). These are in Table 5. Days open and services per conception decrease appreciably as hemoglobins for individual animals in these herds approach an expected of 10.8 g/dl. Anemia was not related to conception in one study (15), but others have reported that anemia may affect reproduction adversely (5, 16, 24). While low serum inorganic phosphorus may be encountered in some infertility herds, high values may be found in others. The diversity in profiles from herds with infertility is indicated by the examples in Table 6. Low calcium in serum frequently is noted in herds with low production. Sometimes packed cell volume may be considerably higher than expected in herds with a production problem. Often this has been associated with inadequate water intake in such herds. Example profiles from herds with low production are in Table 7. Depressed calcium in serum has been a fairly consistent finding in herds with grass and
winter tetany or sudden dealth problems. Low magnesium values are not always present. Several findings suggest that copper may be involved in this syndrome. Cows in such herds may be anemic. Data from normal herds indicate interrelationships between serum and ration concentrations of copper and magnesium. In addition copper content was low in liver samples from necropsied animals submitted from tetany herds in Pennsylvania. The value of soil tests in some problem situations is illustrated by a grass tetany problem. Beef cattle grazing certain fields had a high incidence of tetany while others grazing fields in another area of the same farm had no cases. Differences were not appreciable in forage analysis. However, blood profiles in the two groups differed appreciably. Cattle grazing the tetany-prone area had less hemoglobin and depressed packed cell volume. Magnesium in serum of the tetany group was less than 50% of that for cattle grazing in the nontetany area. Soils from fields in the tetany area averaged 112 kg Mg per hectare compared to 157 kg for the nontetany area. The wide range of abnormalities that may occur in any type of problem make it difficult to use profiles in predicting the susceptibility of a herd to individual problems. It appears that an outbreak of clinical problems may be more likely to occur when the number of abnormalities or the severity of the abnormality reaches a breaking point. As indicated later, problem herds usually have a higher incidence of profile abnormalities. Thus, profiling in a general way may indicate the presence of a potential problem.
TABLE 6. Selected mean blood contents in herds with a high incidence of infertility problems. Herd Ex-
Parameter
A
B
C
pected a
Packed cell volume, % Hemoglobin, g/dl Red blood cells, M/mm3 White blood cells, T/ram 3 Serum inorganic P, mg/dl
23 8.6 4.9 4.6 6.6
27 9.2 4.8 8.4 7.2
34 11.5 6.5 7.0 5.3
32 10.8 6.2 9.4 6.0
aReference (23). Journal of Dairy Science Vol. 61, No. 11, 1978
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TABLE 7. Selected mean blood contents in herds afflicted with low production. Herd Ex-
Parameter
A
B
pected a
Packed cell volume, % Hemoglobin, g/dl Serum inorganic P, mg/dl Serum Ca, mg/dl
36 12.2 6.8 8.5
23 8.6 7.6 8.6
32 10.8 6.0 9.3
aReference (23).
Other Interpretation Problems
One of the most basic items relating to interpretation is the selection of so-called normal or expectancy values. Values established by laboratories in widely separated areas differ considerably for some parameters (11, 19, 22, 23). These discrepancies may reflect differences in general feeding and farming practices, as well as variations in climate, sample handling, and laboratory methods, among other possibilities. It appears preferable that normal values be established for given areas or populations, if not for individual laboratories. Once basic data have been obtained, normal or expected ranges must be established that are reasonable from a number of standpoints. Regardless of confidence limits or other statistical methods, normal ranges should not encompass values which have been associated closely with health or other problems by controlled research, adequate clinical studies, or long experience. For example, it is unreasonable to set a normal range for hemoglobin that includes values under 9.6 g/dl when such levels have been associated closely with reproductive problems under our conditions. Considerable data are available in the literature which may be used in helping to set tentative and later final expectancies. There has been a tendency to set normal or expected ranges of two standard deviations or 95% confidence limits as in the Compton profile (19). For some parameters this may result in normal ranges that are too wide to discriminate between normal and problem situations. In addition, they may include levels associated with disorders. This is especially true for magnesium. Based on our experiences since 1968 as well
as data from our study or normal herds and the literature, we feel that the ranges for most parameters should use 1.3 standard deviations from mean or 80% confidence. This is what we have used for most tests (1). Hemoglobin range, however, was established with one standard deviation. The range of magnesium was based primarily on literature values and data from herds with magnesium-related problems. Our range for potassium was established with two standard deviations due to the greater influence of sample handling on results. Others have found it more meaningful to use one standard deviation in establishing normal ranges (20). Statistical and other approaches to interpretation have been presented by others (3, 13, 17, 19). Whatever methods are employed, a relatively high incidence of problems may exist in apparently normal herds. Only 30% of the good-producing herds, which we considered for use in our study of normal herds, could meet practical criteria for herd health, reproduction, and cow-turnover for 2 yr prior to selection. Significant production, stage of lactation, seasonal, yearly, and age effects have been reported for some parameters by several groups (17, 19, 21, 23). These differences, while significant, are not of the magnitude that will interfere with careful interpretation. This is especially true if values for dry cows and those with various production are summarized separately. Another important aspect of interpretation is related to what criteria are used to label values as abnormal. We consider noteworthy means for a herd or group that fall outside of expected range, or those that closely approach doing so. In addition, tests for which over 19% Journal of Dairy Science Vol. 61, No. 11, 1978
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TABLE 8. Incidence of noteworthy findings in blood profile, a
Item Tests with means beyond normal herds Tests with over 19% abnormal animals
Problem herds
Normal herds
1.64
.14
5.64
1.93
aprofiles with 11 to 13 parameters.
of t h e a n i m a l s fall o u t s i d e o f n o r m a l range are n o t e w o r t h y . T h e d i s t r i b u t i o n o f values f o r a given p a r a m e t e r also is observed. F o r e x a m p l e , average c a l c i u m in s e r u m m a y b e close t o expected, and the percentage of abnormal a n i m a l s m a y be low. However, i n d i v i d u a l values m a y b e clustered at t h e high a n d l o w e n d s o f n o r m a l range. This o f t e n m a y h a p p e n in a h e r d o n excessive calcium i n t a k e f o r a p e r i o d o f i n t e r m e d i a t e length. Using this a p p r o a c h we find c o n s i d e r a b l y m o r e a b n o r m a l i t i e s or n o t e w o r t h y f i n d i n g s in problem herds than ones with no overt problems. This is s h o w n in T a b l e 8, w h i c h is b a s e d o n d a t a f r o m 14 profiles each f r o m n o r m a l a n d p r o b l e m h e r d s selected at r a n d o m f r o m o u r files. T h e average n u m b e r o f m e a n s falling o u t s i d e o f n o r m a l range was 10 t i m e s as high f o r p r o b l e m c o m p a r e d t o n o r m a l herds. Profiles f r o m p r o b l e m h e r d s h a d a l m o s t t h r e e t i m e s as m a n y p a r a m e t e r s w i t h 20% or m o r e o f t h e animals o u t s i d e o f n o r m a l range. As i n d i c a t e d in T a b l e 9, a l m o s t 86% o f t h e n o r m a l h e r d s h a d profiles w i t h n o m e a n s o u t s i d e o f e x p e c t e d range c o m p a r e d t o 29% f o r p r o b l e m herds. No n o r m a l h e r d in t h i s l i m i t e d sample h a d m o r e t h a n o n e test w i t h a m e a n value t h a t was o u t s i d e o f n o r m a l range. T h e f r e q u e n c y o f tests w i t h over 19% o f t h e a n i m a l s o u t s i d e o f n o r m a l range are in T a b l e 10. Over 20% o f t h e profiles for n o r m a l h e r d s c o n t a i n e d n o tests w i t h over 19% a b n o r m a l animals. In c o n t r a s t , profiles f r o m p r o b l e m h e r d s h a d at least f o u r tests w i t h over 19% a b n o r m a l animals. S o m e 43% of t h e p r o b l e m h e r d s h a d profiles with five t e s t s w i t h a n o t e w o r t h y p r o p o r t i o n o f a b n o r m a l animals, a n d 29% o f t h e m h a d 7 t o 8 s u c h tests. O n l y 21% o f t h e n o r m a l profiles h a d over t h r e e t e s t s w i t h a Journal of Dairy Science Vol. 61, No. 11, 1978
TABLE 9. Frequency of blood tests with means beyond normal range, a Frequency Abnormal means in profile
Problem herds
Normal herds (%)
0 1 2 3 4 5
28.6 21.5 28.6 7.1 7.1 7.1
85.8 14.2 .0 .0 .0 .0
aprofiles with 11 to 13 parameters.
noteworthy percent of animals outside of e x p e c t e d range. It a p p e a r s t h a t a h e r d profile w i t h m o r e t h a n t w o m e a n s o u t s i d e o f n o r m a l r a n g e a n d / o r over 3 to 4 te~ts w i t h 20% or m o r e o f t h e a n i m a l s b e y o n d e?~pected range m i g h t b e a p o t e n t i a l p r o b l e m herd. E x t r a o b s e r v a t i o n a n d c h e c k i n g o f f e e d i n g a n d m a n a g e m e n t p r a c t i c e s m a y b e in o r d e r for such a herd. While such a n a p p r o a c h t o a s s e s s m e n t o f h e a l t h s t a t u s c o u l d n o t give c o n s i s t e n t l y g o o d results, we c o r r e c t l y h a v e p r e d i c t e d b r e a k s in h e a l t h f o r s o m e h e r d s w i t h n o k n o w n p r o b l e m s at sampling. In several cases it was p r e d i c t e d c o r r e c t l y t h a t s o m e d e a t h s m i g h t be e x p e c t e d d u e t o u n u s u a l l y l o w
TABLE 10. Frequency of blood tests with over 19% of the animals beyond normal range, a No. tests with over 19% abnormal animals
Problem herds
Frequency
0 1 2 3 4 5 6 7 8
.0 .0 .0 .0 14.2 42.9 14.2 21.6 7.1
Normal herds (%)
aprofiles with 11 to 13 parameters.
21.4 28.6 14.3 14.3 14.3 7.1 .0 .0 .0
OUR INDUSTRY TODAY mineral in serum. Upon checking with the herd owner, we found that deaths had occurred within several days after sampling. The importance of interpretation is illustrated in our experience with a herd problem of alert downer cows and sudden deaths. Another laboratory ran and interpreted a metabolic profile. Their interpretation, however, was based primarily on two standard deviations from mean. As a result they failed to detect the low inorganic phosphorus in serum which our program found in 48% of the cows. Magnesium levels were not deemed remarkable by the initial laboratory but were critically low in 33% of the c o w s by our scheme of interpretation. Both laboratories noted that urea nitrogens in blood were higher for the lower producing group. Further investigation revealed that the herd was being fed an abnormally large amount of soluble nitrogen via nonprotein-nitrogen (NPN) treated corn silage, haylage, and freechoice liquid protein supplement. The grain mixture was deficient in calcium, phosphorus, magnesium, and sulfur. It also contained more protein than necessary. Dry cows were not fed concentrate but had NPN-corn silage and liquid protein supplement available free-choice.
O P E R A T I O N A L ASPECTS
An important consideration in profiling is choice of parameters to be included. A canonical analysis (6, 8) of Pennsylvania data obtained from 13 normal and 13 herds with milk fever and/or infertility problems indicated that the variables which discriminated best between normal and problem herds were, in descending order of importance: red blood cell count, serum magnesium, serum copper, ration iron, globulin, ration phosphorus, packed cell volume, serum potassium, ration calcium, hemoglobin, and ration phosphorus. All ration variables were expressed as percent of NRC (National Research Council) requirement. After reviewing our program during the past year, we now offer profiling on a fee basis to recover partial costs. The standard profile includes packed cell volume, hemoglobin, red and white blood cell counts, serum calcium, inorganic phosphorus, magnesium, potassium, total protein, albumin, globulin, and blood urea nitrogen. Two optional tests are available at added fees, serum copper and iron, and gluta-
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thione peroxidase on whole blood. Considerable study during the past year has indicated that glutathione peroxidase as determined on whole blood in cattle is highly correlated with selenium in blood and selenium intake. Further, numerous problem herds have been deficient in selenium by both glutathione peroxidase and selenium tests. Strong consideration is being given to adding one or more tests that m a y be reasonably indicative of liver function. German workers (20) successfully have used SGOT and cholesterol. Parameters which may give a reasonable indication of acid-base balance and rumen acidosis also are being considered. Practitioners are urged to sample 10 to 21 cows. The fee schedule has been set to encourage the larger number. Forage testing and ration evaluation are recommended. Such information is available on most herds involved. Submittal forms request detailed but concise histories. Various computer programs and manuals have been developed to help the practitioner and others with interpretation (18, 19). It is difficult to justify these unless a large number of profiles are processed. Further, they may fail to discern problems, may oversimplify interpretation, and sometimes may lead to errors regarding possible causative factors and corrective measures. Our approach is to provide a simple summary of the profile and comments. This is done on a group and herd basis. The summary includes the mean a n d range for each measure. In addition, the percentage of animals outside of expected range for each test and the direction of the abnormality are indicated. Comments provided are developed by one or more specialists after review of the profile, herd history and, in most cases, the feeding program. Serological tests for diseases sometimes are done on samples and are available for evaluation of the problem. Infections as well as metabolic problems are in numerous herds. Water analysis and intakes sometimes are obtained. Usually the profiles, other information, and recommendations are reviewed by an extension veterinarian, dairy specialist, and veterinary pathologist. Raw results are sent to the practitiener as soon as available. Complete profile reports may require an additional 4 to 10 days. Obvious situations and recommendations may Journal of Dairy Science Vol. 61, No. 11, 1978
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ADAMS ET AL.
be phoned to the practitioner or farmer upon completion of the testing. Copies of reports generally are sent to the farmer and county agent, as well as to the practitioner. V A L U E OF B L O O D P R O F I L E S
Based on our experiences during the past 9 yr, we feel that blood profiles may be best used as an adjunct to aid in the alleviation of production and health problems in dairy herds. Their value or use should not be oversold. It has been our experience that profiling may yield information that would not have been detected otherwise in only about 20% of the cases. Close observation of feeding and management practices, ration evaluation, case histories, and disease testing often provide adequate information to determine possible causative factors and recommend corrective measures without p r o filing. Since many of these steps are essential for proper interpretation of the blood profile, we recommend that they be employed before profiling is considered in most situations. In some cases, however, blood profiling should be employed as one of the initial steps in trouble-shooting. This should be considered when a health or production break occurs in a well-fed and managed herd. It also may be justified in the case of a dairyman with a herd problem who cannot be convinced of the need to evaluate rations and adopt sound practices. The psychological effects of receiving a blood profile with noteworthy findings sometimes may encourage the farmer to do the other things that are essential to assess the situation and to follow recommendations. We have seen numerous instances of the psychological or educational value of blood profiles. In one case a blood profile triggered improvements in a herd of 300 cows that increased income by over $102,000 in a year. Improvements on farms called to our attention suggest that blood profiles coupled with other necessary tools may have helped to improve income by approximately $2000 on many problem farms. It is doubtful that profiling alone could result in such improvements. Profiling and other trouble-shooting tools apparently failed to help in relatively few problem herds. It appears that most profiles will become relatively normal within 3 to 5 wk following proper changes in feeding and manJournal of Dairy Science Vol. 61, No. 11, 1978
agement. Some anemias, however, may persist despite apparently good nutrition, management, and treatment. Many are normocytic and normochromic in nature. However, some have responded well to selenium treatment. The use of a blood or metabolic profile appears justified when feed analysis, feed programming, disease testing, and checks on management do not alleviate problems. It is too early to determine the value of routine profiling as a tool in preventive programs and in assessing nutritional or health status in apparently normal herds. P O T E N T I A L FOR MISUSE
Many service-oriented technologies have built-in risks for misuse. Such has occurred unintentionally and otherwise in soil testing, forage testing, and feed programming. Due to the complexities of interpretation, blood profiling has an even greater potential for misuse. Thus, it is important that reputable people become involved in this technology. It also is imperative that farmers and people working with them be made aware of the limitations of profiles, as well as their potential value. There appears to be no justification for widespread use of profiles in dairy herd management or bovine veterinary practice. ACKNOWLEDGMENTS
The contributions of numerous concerns and individuals to the partial support of our field studies are greatly appreciated. The assistance of F. Y. Borden and B. F. Merembeck of the School of Forest Resources and R. J. Hemman, II, with statistical treatment of data is acknowledged gratefully. REFERENCES
1 Adams, R. S. 1975. A look at profiles in dairy cattle. Page 63 in Proc. Maryland Nutr. Conf. 2 Adams, R. S., W. L. Stout, D. C. Kradel, D. E. Baker, G. A. Jung, and S. B. Guss, Jr. 1977. Relationship of nutrient intake to blood profiles. Page 29 in 1977 Dairy Sci. Res. Sum., Pennsylvania State University. 3 Blowey, R. W. 1975. A practical application of metabolic profiles. Vet. Rec. 97:324. 4 Committee on Mineral Nutrition. 1973. Tracking and treating mineral disorders in dairy cattle. 2nd ed. Centre for Agr. Publ. and Doc. The Hague, Netherlands.
OUR INDUSTRY TODAY 5 Hansel, W. 1965. Why cows fail to come in heat. Page 154 in Proc. 18th Annu. Cony. Nat. Ass. Anim. Breeders. 6 Horton, I. F., J. S. Russell, and A. W. Thorpe. 1968. Multivariate-covariance and canonical analysis: A method for selecting the most effective discriminators in a multivariate situation. Biometrics 24:845. 7 Kradel, D. C., R. S. Adams, G. A. Jung, S. B. Guss, W. L. Stout, and C. G. Smiley. 1975. Blood profiling in cattle - the Pennsylvania experience. Page 327 in 19th Annu. Proc. Amer. Ass. Vet. Lab Diagnosticians. 8 Lachowsld, H. M. 1973. Canonical analysis applied to the interpretation o f multispectral scanner data. M.S. thesis, Pennsylvania State University, University Park. 9 Mia, A. S., and H. D. Kroger. 1976. Errors in blood chemistry tests. The Practicing Vet. 48:2, 13. 10 Miller, W. J. 1974. Role of biochemical measurements in diagnosing mineral deficiency problems in farm animals. Feedstuffs 16:28, 24. 11 Morrow, D. A. 1975. Vet. Clinic. Michigan State University, East Lansing. Data presented at the Annu. Meeting Amer. Vet. Med. Ass., Anaheim, CA. 12 Morrow, D. A. 1976. Effects o f nutrition on reproduction in dairy cattle. Page 15 in Proc. Agway Symp. for Vet. 13 Norman, B. B. 1976. Metabolic profile testing: Problems o f putting MPT to work. Page 12 in Anim. Nutr. Health. Jan.-Feb. 14 Parker, B. N. J., and R. W. Blowey. 1974. A comparison of blood from the jugular vein and coccygeal artery and vein o f cows. Vet. Rec. 95:1, 14.
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15 Parker, B. N. J., and R. W. Blowey. 1976. Investigations into the relationship of selected blood components to nutrition and fertility of the dairy cow under commercial farm conditions. Vet. Rec. 98:20, 394. 16 Payne, J. M., S. M. Dew, R. Manston, and M. Paules. 1970. The use of a metabolic profile test in dairy herds. Vet. Rec. 87:150. 17 Payne, J. M., G. J. Rowlands, R. Manston, and S. M. Dew. 1973. A statistical appraisal o f the results o f metabolic profile tests on 75 dairy herds. Brit. Vet. J. 129:370. 18 Payne, J. M. 1975. The Compton metabolic profile present and future. Mimeograph presented at the 67th Annu. Conf. for Vet. Cornell University, Ithaca, NY. 19 Rowlands, G. J., and R. M. Pocock. 1976. Statistical basis of the Compton metabolic profile test. Vet. Rec. 98:333. 20 Sommer, H. 1970. Bestimmung, physiologischer bereich und beurteilung des blutzuckers beim rind. Der Prakt. Tierarzt 51:5, 179. 21 Stevens, J. B. 1975. Metabolic and cellular profile testing: An aid to dairy herd health management. Page 14 in Anita. Nutr. Health. Sept.-Oct. 22 Stevens, J. B. 1977. College Vet. Med., University of Minnesota, St. Paul. Mimeographed tables presented at 72nd Annu. Meeting Amer. Dairy Sci. Ass., Ames, IA. 23 Stout, W. L., D. C. Kradel, G. A. Jung, and C. G. Smiley. 1976. Blood composition of well-managed high-producing Holstein cows in Pennsylvania. Pennsylvania Agr. Exp. Sta. Profit. Rep. 358. 24 Wagner, W. C., and W. Hansel. 1969. Reproductive physiology of the postpartum cow. I. Clinical and histological findings. J. Reprod. Fert. 18:493. -
Journal o f Dairy Science Vol. 61, No. 1 I, 1978
routine dairy herd management. Some of these may be overcome in the future while others are inherent.
ABSTRACT
A number of factors limit the usefulness of blood or metabolic profiles. These include sampling problems, low correlations with nutrient intake, inconsistent patterns in disease, and difficulties in interpretation. Despite these limitations, profiles properly used may serve as an adjunct to more conventional technology in alleviating some dairy herd problems. Their use appears justified when feed analysis, ration evaluation, disease testing, and checks on management do not alleviate herd problems. Considerable potential for misuse of profiles exists due to the complexities of interpretation.
Sampling Problems
Sampling problems have been presented in detail by others (9, 13, 21). Differences exist among sites of blood sampling. Serum from blood removed at the mammary vein may be higher in phosphorus but lower in calcium and magnesium than jugular samples (23). Tail blood may be higher in inorganic phosphorus and potassium but lower in calcium, magnesium, packed cell volume, and hemoglobin than jugular samples (14). Choice of animals to be sampled also has not been resolved. Many workers follow schemes similar to those of English workers (3, 17, 19).
INTRODUCTION
Our experience with blood or metabolic profiles dates from 1968 when a limited program was initiated by the Large Animal Diagnostic Laboratory of The Pennsylvania State University. Since that time certain blood chemistries and hematological tests have been run on samples from approximately 750 problem dairy herds. In addition a 2-yr study has heen made of some blood parameters, health, and reproduction as well as soil, water, and feed analysis in 15 high-producing herds with a history of good health and reproductive performance (23). This research has provided a basis for the development of expected values for use in the interpretation of blood profiles (1). Various aspects of the program have been published in (7). LIMITATIONS
A number of factors limit the usefulness of blood profiles in either problem situations or Received October 3, 1977. 1Scientific Journal Series Paper No. 5540, Pennsylvania Agricultural Experiment Station. 1978 J Dairy Sci 61:1671--1679
Low Correlations with Nutrient Intake
Considerable emphasis has been placed by some on the use of profiles in assessing nutritional status (3, 16, 17, 18, 21). Homeostatic mechanisms and various nutrient interrelationships could be expected to limit their usefulness in this regard. Others have indicated that other animal tissue tests, feed analysis, and, in some cases, soil tests may be better indicators of ration adequacy than blood tests (4, 10). Based on estimated intakes obtained under farm conditions in Pennsylvania, some significant but low correlations may exist between some blood measures and nutrient intake (2). Contributions of both feed and water were included in this study of normal herds. Some of these relationships are in Tables 1 and 2. English workers (15) also have found some significant but low correlations between blood parameters and nutrient intake. These researchers cautioned that blood contents do not show cconsistent relationship with nutrient balance. Blood profiles are sufficiently sensitive to
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TABLE 1. Correlation of some blood measures with estimated nutrient intake. Estimated intake expression Correction a
Total
% Dry matter
Hemoglobin with crude protein Total protein with crude protein Albumin with crude protein Globulin with crude protein Calcium with ration Ca Phosphorus with ration P Magnesium with ration Mg Potassium with ration K Iron with ration Fe Copper with ration Cu
-.22
...
a
.
.
...
% NRC b +.18
+.07
+.08
-.07 -.06 +.10 +.19
... +.06
+.07 . .
"-:1"9
...
+:06 +.14 +:09 .
.
.
.
.
Significance at 5%: .06.
bIntake expressed as a percent of National Research Council requirements, as given in
Nutrient Requirements
of Dairy Cattle, 1971. National Academy of Sciences, Washington, DC.
TABLE 2. Influence of nutrient interrelationships on selected blood measures. Estimated intake expression % Dry matter
% NRC
Correlation a
Total
Serum calcium with ration: Calcium Phosphorus Magnesium Iron Zinc Crude protein Estimated TDN
-.19 -.21 -. 19 -.29 -.24 -. 15 -.21
"-:09
"-:11 -.24 -.10 -.13 ...
Serum magnesium with ration: Magnesium Potassium Copper
+.08 -. 13 +.11
+.19 -.09 +.15
+.14 -. 12 +.12
Serum copper with ration: Copper Estimated TDN Magnesium Phosphorus
+.06 +. 12 +.08 +.12
... ...
Hemoglobin with ration: Crude protein Estimated TDN Iron Copper Zinc
-.22 -. 39 -.23 -.24 -.30
a
.
.
.
Sxgmflcance at 5%: .06.
Journal of Dairy Science Vol. 61, No. 11, 1978
-.06 -.14 -. 11 -.23 -.19
+.06
+:07
"-:06 ... ...
"-:08 -.12 -.15 -.23
+.18 +.11 -.12 -.15 -.22
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TABLE 3. Mean blood contents in herds with a high incidence of various problems. Milk fever
Parameter Packed cell volume, % Hemoglobin, g/dl Red blood cells, M/mm 3 White blood ceils, T/ram 3 Serum inorganic P, mg/dl Serum Ca, mg/dl Serum Mg, mg/dl Serum K, meq/l Serum Cu, ppm Serum Fe, ppm Total protein, g/dl No. samples
31.8 10.7 5.9 9.0 5.7 9.1 2.3 7.0 .84 1.99 7.9 813
Tetany syndrome
Infertility
27.0 10.3 5.8 8.1 5.9 8.8 2.1 7.5 1.05 2.14 8.3 79
31.2 10.4 5.9 9.0 5.8 9.5 2.4 6.4 .91 1.99 7.7 858
Expected a 32.3 10.8 6.2 9.4 6.0 9.3 2.2 5.1 .85 1.72 7.6 2290
aReference (23).
i n d i c a t e wide d e p a r t u r e s f r o m r e c o m m e n d e d i n t a k e in s o m e cases. P r e l i m i n a r y d a t a f r o m a s t u d y u n d e r c o n t r o l l e d c o n d i t i o n s at t h e P e n n s y l v a n i a s t a t i o n suggest t h a t u r e a n i t r o g e n in b l o o d was a l m o s t 50% less o n a r a t i o n c o n t a i n i n g 12.7% vs. 17% c r u d e p r o t e i n o n a d r y m a t t e r basis. B l o o d glucose values a p p e a r e d t o be r e d u c e d o n l y 8% w h e n cows were fed forage a l o n e a f t e r r e a c h i n g m i l k p r o d u c t i o n o f 18.2 kg daily. B l o o d c o n t e n t s have b e e n in r e a s o n a b l y close a g r e e m e n t w i t h e s t i m a t e d i n t a k e s f r o m r a t i o n e v a l u a t i o n in s o m e p r o b l e m herds. T h e r e l a t i o n s h i p , h o w e v e r , is n o t suffic i e n t l y c o n s i s t e n t to e n a b l e use o f profiles as a sole m e a n s o f assessing n u t r i t i o n a l s t a t u s or nutrient intake.
Inconsistent Patterns in Disease
A wide variety o f a b n o r m a l i t i e s in profile m a y o c c u r in a n y t y p e of p r o d u c t i o n disease.
A b n o r m a l i t i e s are n o t striking or c o n s i s t e n t a m o n g h e r d s suffering f r o m a h i g h i n c i d e n c e o f a p a r t i c u l a r disorder. B o t h a b n o r m a l l y high a n d l o w values for a given p a r a m e t e r m a y b e f o u n d a m o n g afflicted herds. This s i t u a t i o n is indic a t e d b y t h e lack o f large d i f f e r e n c e s in m e a n b l o o d values in samples f r o m P e n n s y l v a n i a h e r d s w i t h a high i n c i d e n c e o f various h e a l t h p r o b l e m s . T h e s e are in T a b l e 3. B o t h high a n d low calcium in s e r u m are e n c o u n t e r e d in h e r d s w i t h a high i n c i d e n c e o f m i l k fever or d o w n e r c o w s y n d r o m e . L o w s e r u m c a l c i u m m a y be associated w i t h e i t h e r a n excessive or i n a d e q u a t e i n t a k e o f this e l e m e n t . F u r t h e r , n o r m a l calcium a c c o m p a n i e d b y o t h e r a b n o r m a l i t i e s m a y b e in profiles~ f r o m o t h e r h e r d s w i t h this disorder. T h i s is i l l u s t r a t e d in T a b l e 4 w i t h d a t a f r o m selected h e r d profiles. A n e m i a m a y b e in m a n y profiles f r o m h e r d s with infertility problems, but not consistently. T h e a p p a r e n t effects o f a n e m i a o n r e p r o d u c t i o n
TABLE 4. Mean serum minerals in herds with a high incidence of milk fever and downer cows. Herd Ex-
Serum
A
B
C
D
Inorganic P, mg/dl Ca, mg/dl Mg, mg/dl K, meq/l
4.7 7.6 1.1 6.0
4.4 9.4 2.2 7.8
6.2 10.9 2.6 ...
7.6 11.0 2.3 6.1
pected a 6.0 9.3 2.2 5.1
abased on data obtained in normal herds (23). Journal of Dairy Science V ol. 61, No. 11, 1978
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ADAMS ET AL.
TABLE 5. Reproductive performance of dairy cows grouped according to hemoglobin content,a Mean
hemoglobin
Services
Days open
per conception
119 113 75
2.7 1.6 1.5 1.3
(g/dl) 9.1 9.7
10.2 10.7
77
aReference (12). in some problem herds were summarized by Morrow (12). These are in Table 5. Days open and services per conception decrease appreciably as hemoglobins for individual animals in these herds approach an expected of 10.8 g/dl. Anemia was not related to conception in one study (15), but others have reported that anemia may affect reproduction adversely (5, 16, 24). While low serum inorganic phosphorus may be encountered in some infertility herds, high values may be found in others. The diversity in profiles from herds with infertility is indicated by the examples in Table 6. Low calcium in serum frequently is noted in herds with low production. Sometimes packed cell volume may be considerably higher than expected in herds with a production problem. Often this has been associated with inadequate water intake in such herds. Example profiles from herds with low production are in Table 7. Depressed calcium in serum has been a fairly consistent finding in herds with grass and
winter tetany or sudden dealth problems. Low magnesium values are not always present. Several findings suggest that copper may be involved in this syndrome. Cows in such herds may be anemic. Data from normal herds indicate interrelationships between serum and ration concentrations of copper and magnesium. In addition copper content was low in liver samples from necropsied animals submitted from tetany herds in Pennsylvania. The value of soil tests in some problem situations is illustrated by a grass tetany problem. Beef cattle grazing certain fields had a high incidence of tetany while others grazing fields in another area of the same farm had no cases. Differences were not appreciable in forage analysis. However, blood profiles in the two groups differed appreciably. Cattle grazing the tetany-prone area had less hemoglobin and depressed packed cell volume. Magnesium in serum of the tetany group was less than 50% of that for cattle grazing in the nontetany area. Soils from fields in the tetany area averaged 112 kg Mg per hectare compared to 157 kg for the nontetany area. The wide range of abnormalities that may occur in any type of problem make it difficult to use profiles in predicting the susceptibility of a herd to individual problems. It appears that an outbreak of clinical problems may be more likely to occur when the number of abnormalities or the severity of the abnormality reaches a breaking point. As indicated later, problem herds usually have a higher incidence of profile abnormalities. Thus, profiling in a general way may indicate the presence of a potential problem.
TABLE 6. Selected mean blood contents in herds with a high incidence of infertility problems. Herd Ex-
Parameter
A
B
C
pected a
Packed cell volume, % Hemoglobin, g/dl Red blood cells, M/mm3 White blood cells, T/ram 3 Serum inorganic P, mg/dl
23 8.6 4.9 4.6 6.6
27 9.2 4.8 8.4 7.2
34 11.5 6.5 7.0 5.3
32 10.8 6.2 9.4 6.0
aReference (23). Journal of Dairy Science Vol. 61, No. 11, 1978
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TABLE 7. Selected mean blood contents in herds afflicted with low production. Herd Ex-
Parameter
A
B
pected a
Packed cell volume, % Hemoglobin, g/dl Serum inorganic P, mg/dl Serum Ca, mg/dl
36 12.2 6.8 8.5
23 8.6 7.6 8.6
32 10.8 6.0 9.3
aReference (23).
Other Interpretation Problems
One of the most basic items relating to interpretation is the selection of so-called normal or expectancy values. Values established by laboratories in widely separated areas differ considerably for some parameters (11, 19, 22, 23). These discrepancies may reflect differences in general feeding and farming practices, as well as variations in climate, sample handling, and laboratory methods, among other possibilities. It appears preferable that normal values be established for given areas or populations, if not for individual laboratories. Once basic data have been obtained, normal or expected ranges must be established that are reasonable from a number of standpoints. Regardless of confidence limits or other statistical methods, normal ranges should not encompass values which have been associated closely with health or other problems by controlled research, adequate clinical studies, or long experience. For example, it is unreasonable to set a normal range for hemoglobin that includes values under 9.6 g/dl when such levels have been associated closely with reproductive problems under our conditions. Considerable data are available in the literature which may be used in helping to set tentative and later final expectancies. There has been a tendency to set normal or expected ranges of two standard deviations or 95% confidence limits as in the Compton profile (19). For some parameters this may result in normal ranges that are too wide to discriminate between normal and problem situations. In addition, they may include levels associated with disorders. This is especially true for magnesium. Based on our experiences since 1968 as well
as data from our study or normal herds and the literature, we feel that the ranges for most parameters should use 1.3 standard deviations from mean or 80% confidence. This is what we have used for most tests (1). Hemoglobin range, however, was established with one standard deviation. The range of magnesium was based primarily on literature values and data from herds with magnesium-related problems. Our range for potassium was established with two standard deviations due to the greater influence of sample handling on results. Others have found it more meaningful to use one standard deviation in establishing normal ranges (20). Statistical and other approaches to interpretation have been presented by others (3, 13, 17, 19). Whatever methods are employed, a relatively high incidence of problems may exist in apparently normal herds. Only 30% of the good-producing herds, which we considered for use in our study of normal herds, could meet practical criteria for herd health, reproduction, and cow-turnover for 2 yr prior to selection. Significant production, stage of lactation, seasonal, yearly, and age effects have been reported for some parameters by several groups (17, 19, 21, 23). These differences, while significant, are not of the magnitude that will interfere with careful interpretation. This is especially true if values for dry cows and those with various production are summarized separately. Another important aspect of interpretation is related to what criteria are used to label values as abnormal. We consider noteworthy means for a herd or group that fall outside of expected range, or those that closely approach doing so. In addition, tests for which over 19% Journal of Dairy Science Vol. 61, No. 11, 1978
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ADAMS ET AL.
TABLE 8. Incidence of noteworthy findings in blood profile, a
Item Tests with means beyond normal herds Tests with over 19% abnormal animals
Problem herds
Normal herds
1.64
.14
5.64
1.93
aprofiles with 11 to 13 parameters.
of t h e a n i m a l s fall o u t s i d e o f n o r m a l range are n o t e w o r t h y . T h e d i s t r i b u t i o n o f values f o r a given p a r a m e t e r also is observed. F o r e x a m p l e , average c a l c i u m in s e r u m m a y b e close t o expected, and the percentage of abnormal a n i m a l s m a y be low. However, i n d i v i d u a l values m a y b e clustered at t h e high a n d l o w e n d s o f n o r m a l range. This o f t e n m a y h a p p e n in a h e r d o n excessive calcium i n t a k e f o r a p e r i o d o f i n t e r m e d i a t e length. Using this a p p r o a c h we find c o n s i d e r a b l y m o r e a b n o r m a l i t i e s or n o t e w o r t h y f i n d i n g s in problem herds than ones with no overt problems. This is s h o w n in T a b l e 8, w h i c h is b a s e d o n d a t a f r o m 14 profiles each f r o m n o r m a l a n d p r o b l e m h e r d s selected at r a n d o m f r o m o u r files. T h e average n u m b e r o f m e a n s falling o u t s i d e o f n o r m a l range was 10 t i m e s as high f o r p r o b l e m c o m p a r e d t o n o r m a l herds. Profiles f r o m p r o b l e m h e r d s h a d a l m o s t t h r e e t i m e s as m a n y p a r a m e t e r s w i t h 20% or m o r e o f t h e animals o u t s i d e o f n o r m a l range. As i n d i c a t e d in T a b l e 9, a l m o s t 86% o f t h e n o r m a l h e r d s h a d profiles w i t h n o m e a n s o u t s i d e o f e x p e c t e d range c o m p a r e d t o 29% f o r p r o b l e m herds. No n o r m a l h e r d in t h i s l i m i t e d sample h a d m o r e t h a n o n e test w i t h a m e a n value t h a t was o u t s i d e o f n o r m a l range. T h e f r e q u e n c y o f tests w i t h over 19% o f t h e a n i m a l s o u t s i d e o f n o r m a l range are in T a b l e 10. Over 20% o f t h e profiles for n o r m a l h e r d s c o n t a i n e d n o tests w i t h over 19% a b n o r m a l animals. In c o n t r a s t , profiles f r o m p r o b l e m h e r d s h a d at least f o u r tests w i t h over 19% a b n o r m a l animals. S o m e 43% of t h e p r o b l e m h e r d s h a d profiles with five t e s t s w i t h a n o t e w o r t h y p r o p o r t i o n o f a b n o r m a l animals, a n d 29% o f t h e m h a d 7 t o 8 s u c h tests. O n l y 21% o f t h e n o r m a l profiles h a d over t h r e e t e s t s w i t h a Journal of Dairy Science Vol. 61, No. 11, 1978
TABLE 9. Frequency of blood tests with means beyond normal range, a Frequency Abnormal means in profile
Problem herds
Normal herds (%)
0 1 2 3 4 5
28.6 21.5 28.6 7.1 7.1 7.1
85.8 14.2 .0 .0 .0 .0
aprofiles with 11 to 13 parameters.
noteworthy percent of animals outside of e x p e c t e d range. It a p p e a r s t h a t a h e r d profile w i t h m o r e t h a n t w o m e a n s o u t s i d e o f n o r m a l r a n g e a n d / o r over 3 to 4 te~ts w i t h 20% or m o r e o f t h e a n i m a l s b e y o n d e?~pected range m i g h t b e a p o t e n t i a l p r o b l e m herd. E x t r a o b s e r v a t i o n a n d c h e c k i n g o f f e e d i n g a n d m a n a g e m e n t p r a c t i c e s m a y b e in o r d e r for such a herd. While such a n a p p r o a c h t o a s s e s s m e n t o f h e a l t h s t a t u s c o u l d n o t give c o n s i s t e n t l y g o o d results, we c o r r e c t l y h a v e p r e d i c t e d b r e a k s in h e a l t h f o r s o m e h e r d s w i t h n o k n o w n p r o b l e m s at sampling. In several cases it was p r e d i c t e d c o r r e c t l y t h a t s o m e d e a t h s m i g h t be e x p e c t e d d u e t o u n u s u a l l y l o w
TABLE 10. Frequency of blood tests with over 19% of the animals beyond normal range, a No. tests with over 19% abnormal animals
Problem herds
Frequency
0 1 2 3 4 5 6 7 8
.0 .0 .0 .0 14.2 42.9 14.2 21.6 7.1
Normal herds (%)
aprofiles with 11 to 13 parameters.
21.4 28.6 14.3 14.3 14.3 7.1 .0 .0 .0
OUR INDUSTRY TODAY mineral in serum. Upon checking with the herd owner, we found that deaths had occurred within several days after sampling. The importance of interpretation is illustrated in our experience with a herd problem of alert downer cows and sudden deaths. Another laboratory ran and interpreted a metabolic profile. Their interpretation, however, was based primarily on two standard deviations from mean. As a result they failed to detect the low inorganic phosphorus in serum which our program found in 48% of the cows. Magnesium levels were not deemed remarkable by the initial laboratory but were critically low in 33% of the c o w s by our scheme of interpretation. Both laboratories noted that urea nitrogens in blood were higher for the lower producing group. Further investigation revealed that the herd was being fed an abnormally large amount of soluble nitrogen via nonprotein-nitrogen (NPN) treated corn silage, haylage, and freechoice liquid protein supplement. The grain mixture was deficient in calcium, phosphorus, magnesium, and sulfur. It also contained more protein than necessary. Dry cows were not fed concentrate but had NPN-corn silage and liquid protein supplement available free-choice.
O P E R A T I O N A L ASPECTS
An important consideration in profiling is choice of parameters to be included. A canonical analysis (6, 8) of Pennsylvania data obtained from 13 normal and 13 herds with milk fever and/or infertility problems indicated that the variables which discriminated best between normal and problem herds were, in descending order of importance: red blood cell count, serum magnesium, serum copper, ration iron, globulin, ration phosphorus, packed cell volume, serum potassium, ration calcium, hemoglobin, and ration phosphorus. All ration variables were expressed as percent of NRC (National Research Council) requirement. After reviewing our program during the past year, we now offer profiling on a fee basis to recover partial costs. The standard profile includes packed cell volume, hemoglobin, red and white blood cell counts, serum calcium, inorganic phosphorus, magnesium, potassium, total protein, albumin, globulin, and blood urea nitrogen. Two optional tests are available at added fees, serum copper and iron, and gluta-
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thione peroxidase on whole blood. Considerable study during the past year has indicated that glutathione peroxidase as determined on whole blood in cattle is highly correlated with selenium in blood and selenium intake. Further, numerous problem herds have been deficient in selenium by both glutathione peroxidase and selenium tests. Strong consideration is being given to adding one or more tests that m a y be reasonably indicative of liver function. German workers (20) successfully have used SGOT and cholesterol. Parameters which may give a reasonable indication of acid-base balance and rumen acidosis also are being considered. Practitioners are urged to sample 10 to 21 cows. The fee schedule has been set to encourage the larger number. Forage testing and ration evaluation are recommended. Such information is available on most herds involved. Submittal forms request detailed but concise histories. Various computer programs and manuals have been developed to help the practitioner and others with interpretation (18, 19). It is difficult to justify these unless a large number of profiles are processed. Further, they may fail to discern problems, may oversimplify interpretation, and sometimes may lead to errors regarding possible causative factors and corrective measures. Our approach is to provide a simple summary of the profile and comments. This is done on a group and herd basis. The summary includes the mean a n d range for each measure. In addition, the percentage of animals outside of expected range for each test and the direction of the abnormality are indicated. Comments provided are developed by one or more specialists after review of the profile, herd history and, in most cases, the feeding program. Serological tests for diseases sometimes are done on samples and are available for evaluation of the problem. Infections as well as metabolic problems are in numerous herds. Water analysis and intakes sometimes are obtained. Usually the profiles, other information, and recommendations are reviewed by an extension veterinarian, dairy specialist, and veterinary pathologist. Raw results are sent to the practitiener as soon as available. Complete profile reports may require an additional 4 to 10 days. Obvious situations and recommendations may Journal of Dairy Science Vol. 61, No. 11, 1978
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be phoned to the practitioner or farmer upon completion of the testing. Copies of reports generally are sent to the farmer and county agent, as well as to the practitioner. V A L U E OF B L O O D P R O F I L E S
Based on our experiences during the past 9 yr, we feel that blood profiles may be best used as an adjunct to aid in the alleviation of production and health problems in dairy herds. Their value or use should not be oversold. It has been our experience that profiling may yield information that would not have been detected otherwise in only about 20% of the cases. Close observation of feeding and management practices, ration evaluation, case histories, and disease testing often provide adequate information to determine possible causative factors and recommend corrective measures without p r o filing. Since many of these steps are essential for proper interpretation of the blood profile, we recommend that they be employed before profiling is considered in most situations. In some cases, however, blood profiling should be employed as one of the initial steps in trouble-shooting. This should be considered when a health or production break occurs in a well-fed and managed herd. It also may be justified in the case of a dairyman with a herd problem who cannot be convinced of the need to evaluate rations and adopt sound practices. The psychological effects of receiving a blood profile with noteworthy findings sometimes may encourage the farmer to do the other things that are essential to assess the situation and to follow recommendations. We have seen numerous instances of the psychological or educational value of blood profiles. In one case a blood profile triggered improvements in a herd of 300 cows that increased income by over $102,000 in a year. Improvements on farms called to our attention suggest that blood profiles coupled with other necessary tools may have helped to improve income by approximately $2000 on many problem farms. It is doubtful that profiling alone could result in such improvements. Profiling and other trouble-shooting tools apparently failed to help in relatively few problem herds. It appears that most profiles will become relatively normal within 3 to 5 wk following proper changes in feeding and manJournal of Dairy Science Vol. 61, No. 11, 1978
agement. Some anemias, however, may persist despite apparently good nutrition, management, and treatment. Many are normocytic and normochromic in nature. However, some have responded well to selenium treatment. The use of a blood or metabolic profile appears justified when feed analysis, feed programming, disease testing, and checks on management do not alleviate problems. It is too early to determine the value of routine profiling as a tool in preventive programs and in assessing nutritional or health status in apparently normal herds. P O T E N T I A L FOR MISUSE
Many service-oriented technologies have built-in risks for misuse. Such has occurred unintentionally and otherwise in soil testing, forage testing, and feed programming. Due to the complexities of interpretation, blood profiling has an even greater potential for misuse. Thus, it is important that reputable people become involved in this technology. It also is imperative that farmers and people working with them be made aware of the limitations of profiles, as well as their potential value. There appears to be no justification for widespread use of profiles in dairy herd management or bovine veterinary practice. ACKNOWLEDGMENTS
The contributions of numerous concerns and individuals to the partial support of our field studies are greatly appreciated. The assistance of F. Y. Borden and B. F. Merembeck of the School of Forest Resources and R. J. Hemman, II, with statistical treatment of data is acknowledged gratefully. REFERENCES
1 Adams, R. S. 1975. A look at profiles in dairy cattle. Page 63 in Proc. Maryland Nutr. Conf. 2 Adams, R. S., W. L. Stout, D. C. Kradel, D. E. Baker, G. A. Jung, and S. B. Guss, Jr. 1977. Relationship of nutrient intake to blood profiles. Page 29 in 1977 Dairy Sci. Res. Sum., Pennsylvania State University. 3 Blowey, R. W. 1975. A practical application of metabolic profiles. Vet. Rec. 97:324. 4 Committee on Mineral Nutrition. 1973. Tracking and treating mineral disorders in dairy cattle. 2nd ed. Centre for Agr. Publ. and Doc. The Hague, Netherlands.
OUR INDUSTRY TODAY 5 Hansel, W. 1965. Why cows fail to come in heat. Page 154 in Proc. 18th Annu. Cony. Nat. Ass. Anim. Breeders. 6 Horton, I. F., J. S. Russell, and A. W. Thorpe. 1968. Multivariate-covariance and canonical analysis: A method for selecting the most effective discriminators in a multivariate situation. Biometrics 24:845. 7 Kradel, D. C., R. S. Adams, G. A. Jung, S. B. Guss, W. L. Stout, and C. G. Smiley. 1975. Blood profiling in cattle - the Pennsylvania experience. Page 327 in 19th Annu. Proc. Amer. Ass. Vet. Lab Diagnosticians. 8 Lachowsld, H. M. 1973. Canonical analysis applied to the interpretation o f multispectral scanner data. M.S. thesis, Pennsylvania State University, University Park. 9 Mia, A. S., and H. D. Kroger. 1976. Errors in blood chemistry tests. The Practicing Vet. 48:2, 13. 10 Miller, W. J. 1974. Role of biochemical measurements in diagnosing mineral deficiency problems in farm animals. Feedstuffs 16:28, 24. 11 Morrow, D. A. 1975. Vet. Clinic. Michigan State University, East Lansing. Data presented at the Annu. Meeting Amer. Vet. Med. Ass., Anaheim, CA. 12 Morrow, D. A. 1976. Effects o f nutrition on reproduction in dairy cattle. Page 15 in Proc. Agway Symp. for Vet. 13 Norman, B. B. 1976. Metabolic profile testing: Problems o f putting MPT to work. Page 12 in Anim. Nutr. Health. Jan.-Feb. 14 Parker, B. N. J., and R. W. Blowey. 1974. A comparison of blood from the jugular vein and coccygeal artery and vein o f cows. Vet. Rec. 95:1, 14.
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15 Parker, B. N. J., and R. W. Blowey. 1976. Investigations into the relationship of selected blood components to nutrition and fertility of the dairy cow under commercial farm conditions. Vet. Rec. 98:20, 394. 16 Payne, J. M., S. M. Dew, R. Manston, and M. Paules. 1970. The use of a metabolic profile test in dairy herds. Vet. Rec. 87:150. 17 Payne, J. M., G. J. Rowlands, R. Manston, and S. M. Dew. 1973. A statistical appraisal o f the results o f metabolic profile tests on 75 dairy herds. Brit. Vet. J. 129:370. 18 Payne, J. M. 1975. The Compton metabolic profile present and future. Mimeograph presented at the 67th Annu. Conf. for Vet. Cornell University, Ithaca, NY. 19 Rowlands, G. J., and R. M. Pocock. 1976. Statistical basis of the Compton metabolic profile test. Vet. Rec. 98:333. 20 Sommer, H. 1970. Bestimmung, physiologischer bereich und beurteilung des blutzuckers beim rind. Der Prakt. Tierarzt 51:5, 179. 21 Stevens, J. B. 1975. Metabolic and cellular profile testing: An aid to dairy herd health management. Page 14 in Anita. Nutr. Health. Sept.-Oct. 22 Stevens, J. B. 1977. College Vet. Med., University of Minnesota, St. Paul. Mimeographed tables presented at 72nd Annu. Meeting Amer. Dairy Sci. Ass., Ames, IA. 23 Stout, W. L., D. C. Kradel, G. A. Jung, and C. G. Smiley. 1976. Blood composition of well-managed high-producing Holstein cows in Pennsylvania. Pennsylvania Agr. Exp. Sta. Profit. Rep. 358. 24 Wagner, W. C., and W. Hansel. 1969. Reproductive physiology of the postpartum cow. I. Clinical and histological findings. J. Reprod. Fert. 18:493. -
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