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Calcimator

Somatic Cell Count Analyzer

Analyze somatic cell count (SCC) to determine milk quality score, linear score, estimated milk loss, and revenue impact.

Inputs

× 1,000 cells/mL
× 1,000 cells/mL
lbs
$/cwt

Results

Linear Score

4

Quality Grade

Excellent

Meets ThresholdYes
Est. Daily Milk Loss per Cow2.8 lbs
Est. Annual Milk Loss per Cow854 lbs
Est. Annual Revenue Loss per Cow$170.80
How to Use This Calculator
  1. Enter the bulk tank SCC from the most recent milk test.
  2. Set herd size and average daily milk production per cow.
  3. Input the SCC threshold for your cooperative quality premium.
  4. Review estimated production loss from subclinical mastitis and potential premium at target SCC.
  5. Use the revenue impact to justify investment in mastitis prevention protocols.

How the result changes with Somatic Cell Count

Somatic Cell CountLinear ScoreQuality Grade
5095.35Fair — consider management changes
1,7577.14Poor — significant mastitis risk
3,2548.02Poor — significant mastitis risk
4,5018.49Poor — significant mastitis risk

What each input means

Somatic Cell Count
Bulk tank SCC in thousands. Enter 200 for 200,000 cells/mL. EU limit is 400; US Grade A limit is 750.
Quality Threshold
SCC threshold for premium payments or regulatory compliance.
Avg Daily Milk per Cow
Average daily milk production per cow for loss estimation.
Milk Price
Current milk price per hundredweight for revenue impact calculation.

What each result means

Linear Score
SCC converted to a linear scale. LS 0-3 is excellent; each unit above 3 doubles SCC.

How this is calculated

Worked example, using the default values

  1. Identify Input Parameters
    4 parameters
    Somatic Cell Count = 200, Quality Threshold = 400, Avg Daily Milk per Cow = 70, Milk Price = 20 = 4 input(s) provided
  2. Calculate Linear Score
    Linear Score = r
    4 = 4
  3. Calculate Quality Grade
    Excellent = Excellent
  4. Calculate Meets Threshold
    Yes = Yes
  5. Calculate Est. Daily Milk Loss per Cow
    Est. Daily Milk Loss per Cow
    2.8 = 2.8

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