Help predict individual cow risk for ketosis

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The University of Minnesota has developed a model that uses body condition score and colostrum yield to predict cows at risk for subclinical ketosis.

Using 200 cows, the university's "Pre-K" model accurately identified 80 percent of cows that developed subclinical ketosis. University of Minnesota researchers found that cows with high body condition score have greater potential for body fat mobilization after calving.

Work shows that a good early predictor of energy demands is colostrum yield, as cows with high colostrum yield appear to produce more milk in early lactation.

Cows with a body condition score over 3.5 and colostrum yield greater than 16 pounds were found to be at risk for subclinical ketosis.  Researchers note that identifying and treating at risk cows for subclinical ketosis after calving may increase milk yield and decrease ketosis risk.



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