Use of Dairy Herd Improvement Variables to Predict Lifetime Profitability,

Abstract

This study was to determine if relative profitability of cows could be predicted accurately from variables available through Dairy Herd Improvement. Lifetime income was calculated from sales of milk and fat, calves produced, and salvage value; lifetime expenses were initial value of the animal, feed, mastitis treatment, breeding, and fixed costs. Methods to estimate total profit and profit per day were relative net income function, calculated from lifetime milk and fat production, age at first calving, number of freshenings, and days of herd life; and best fit regression models with one to four variables. The best fit regression models with one to four variables for predicting total profit from relative net income function variables had squared multiple correlations .76, .94, .95, and .96 compared to .95 for relative net income. The best fit regression models of one to three variables for predicting profit per day yielded .69, .83, and .86 compared to .85 for relative net income per day. The relative net income function was successful for accounting for most differences among cows for profit but was less successful for predicting profit per day. The relative net income function appears to be useful for estimating lifetime profitability for establishing the relative importance of traits measured early in the animal's lifetime. © 1984, American Dairy Science Association. All rights reserved.