Newspaper Page Text
A34-Lancaster Farming, Saturday, June 5, 1993
Make Mastitis Records
C. WILLIAM HEALD
PSU Dairy Extension
STATE COLLEGE (Centre
Co.) Simple patterns in somatic
cell score help to identify causes
of mastitis. Looking at somatic
cell score arranged by days-in
milk and lactation number often
yields recognizable patterns. If
cows with 10-40 days-in-milk
have higher average somatic cell
score than cows with 41-100 days,
and the average somatic cell score
is greater for older cows in similar
stages of lactation, this signifies
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environmental mastitis shortly
before or shortly after calving. If
the pattern is similar for first and
second or third lactation animals,
dirty conditions in dry cow hous
ing and freshening pens is
Continuing to evaluate the data
across the lactations, if the aver
age somatic cell score increases
with days-in-milk after peak lacta
tion and is greater for older cows,
chronic mastitis is suspected.
Contagious bacteria, often Strep,
ag. or Staph, aureus, are probably
being passed at milking time as a
result of improper hygiene or
milking equipment operation.
Graphing the monthly somatic cell
score by lactation number over 10
to 12 sample periods can refine
this evaluation. Look for points
above 3.0 in most herds. Some
times it helps to draw a line at this
level on the graph as the threshold.
A more powerful technique.
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although more difficult to assem
ble, is to use new infections as the
criteria in a table. Determine the
first time each cow’s somatic cell
score is greater than 3.9. List these
by month (January through
December), days-in-milk, or tests
one through 10, by lactation num
ber (1 through 3+), and/or group
number. Then list number of cows
greater than 4 for approximately
the last 24 months. With these
data, look for patterns of when
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cows became infected and identify
management conditions that could
contribute to an increased inci
dence of elevated somatic cell
score. Simply look for the month,
days-in-milk, and lactation num
ber with the most cows greater
than 4. This suggests when cows
first became infected. Design
changes in management to lower
infection rates then monitor the
success. Re-evaluate the results
periodically, set goals, and make
new plans as required.
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