The importance of measuring feed consumption as a supplementary criterion of net performance was studied from two different sources of data: (1) random sample egg production tests conducted in the United States between 1949 and 1957 (USRST) and (2) a private test of experimental commercial strains conducted by the Goto Hatchery, Inc., Gifu City, Japan, between 1968 to 1971 (GOTO). Seven traits included in the study were net income (NI), egg rate (ER), egg weight (EW), body weight (BW), mortality (MORT), maturity (MAT) and feed consumption (FEED). Performance indexes were derived as multiple regression equations with NI dependent on the other traits. To test the value of feed consumption records, two performance indexes were compared in each data source. The first, I(6), contained all 6 independent variables, and the second, I(5), contained all variables except FEED.The correlations between NI and I(6) were 0.820 and 0.824 and between NI and I(5) were 0.818 and 0.822 in the USRST and GOTO data, respectively. The difference between the correlations with and without feed was nil in either data source. Thus, measuring FEED did not significantly improve the predictive value of a performance index when prior information was available on the other five variables.I(5) was also compared with an empirical performance index, I(E), defined as the ratio of egg mass output to the ¾ power of body weight. The latter simulates a feed efficiency index where egg mass output is an estimator of feed utilized for egg production and the ¾ power of body weight is an estimator of feed used in the maintenance of body tissues. The correlations between I(E) and net income were 0.68 ond 0.74 in the USRST and GOTO data, respectively, which were only slightly lower than the corresponding correlations between net income and I(5) when the latter was applied to the data source other than that from which it was derived. Thus, a rather simple empirical performance index of egg production efficiency, I(E), was almost as accurate in predicting net income as a multiple regression-derived performance index.
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