Predicting Somatic Cell Count Standard Violations Based on Herd's Bulk Tank Somatic Cell Count. Part II: Consistency Index

The present study examines the capability of 1,501 herds in the Upper Midwest and the performance of statistical process control charts and indices as a way of monitoring and controlling milk quality on the farm. For 24 mo, daily or every other day bulk tank somatic cell count (SCC) data were collec...

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Bibliographic Details
Published in:Journal of dairy science 2008-01, Vol.91 (1), p.433-441
Main Authors: Lukas, J.M., Reneau, J.K., Munoz-Zanzi, C., Kinsel, M.L.
Format: Article
Language:English
Subjects:
Animal productions
Animals
Biological and medical sciences
bulk milk
bulk tank somatic cell count
capability index
Cattle
Cell Count - methods
Cell Count - veterinary
consistency index
dairy cows
dairy herds
Dairying - methods
data analysis
decision making
detection
Female
Food industries
Fundamental and applied biological sciences. Psychology
General aspects
Methods of analysis, processing and quality control, regulation, standards
Milk - cytology
Milk - standards
milk quality
monitoring
quality control
regression analysis
Reproducibility of Results
somatic cell count
statistical analysis
statistical process control
Statistics, Nonparametric
temporal variation
Terrestrial animal productions
Vertebrates
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Summary:The present study examines the capability of 1,501 herds in the Upper Midwest and the performance of statistical process control charts and indices as a way of monitoring and controlling milk quality on the farm. For 24 mo, daily or every other day bulk tank somatic cell count (SCC) data were collected. Consistency indices for 5 different SCC standards were developed. The indices calculate the maximum variation allowed to meet a desired SCC level at a given mean bulk tank SCC and were used to identify herds not capable of meeting a specific SCC standard. Consistency index method was compared with a test identifying future bulk tank SCC standard violators based on herds’ past violations. The performance of the consistency index test and the past violation method was evaluated by logistic regression. The comparison focused on detection probability and certainty associated with a result. For the 5 SCC levels, detection probability and certainty associated with a result ranged from 51 to 98%. Detection probability of all violators and certainty associated with a negative result was greater for the consistency index across all 5 SCC levels (by 0.7 to 7.4% and 2.1 to 5.1%, respectively). Control charts were plotted and monthly consistency indices calculated for individual farms. Charts in combination with the consistency indices would warn from 66 to 80% of the herds about an upcoming violation within 30 d before it occurred. They offer a proactive approach to maintaining consistently high milk quality. By assessing process capability and distinguishing between significant changes and random variation in bulk tank SCC, tools presented in this article encourage fact-based decisions in dairy farm milk quality management.
ISSN:0022-0302
1525-3198
DOI:10.3168/jds.2007-0648