Article,

Environmental effects on conception rates of Holsteins in New York and Georgia

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Journal of Dairy Science, 91 (2): 818 - 825 (2008)
DOI: http://dx.doi.org/10.3168/jds.2007-0306

Abstract

The purpose of this study was to investigate the compounded impact on conception rates (CR) of the effects of milk production, service month, and days in milk (DIM) by using recent artificial insemination records of Holsteins in New York (NY) and Georgia (GA). Dairy Herd Improvement records were obtained from Dairy Records Management Systems in Raleigh, North Carolina. After removing records with lactations >1 and uncertain and extreme records (records without a calving or birth date, with days to service after calving of <21 or >250, and without the next calving date), the final data set comprised 298,015 service records for 160,879 cows and 23,366 service records for 12,184 cows in \NY\ and GA, respectively, from 2000 to 2003. The analytical model included \DIM\ class, milk-production level, service month, the covariate of cow's age at calving, and all 2-way interactions. The 2 states were analyzed separately. In general across the 2 states, \CR\ declined as milk production increased, and \CR\ declined during the hottest months. Conception rate was similar in \NY\ and GA, at approximately 55% from December to April. In NY, \CR\ declined by approximately 10% in May and June and mostly recovered by July. In GA, the \CR\ started declining in May, bottomed at 31% in September, and did not recover until December. The difference in \CR\ between high- and low-producing cows was 7% in \NY\ and 6% in GA. That difference was the strongest from June to July in \GA\ (15%) and was more uniform in NY. The increase in \CR\ with increasing \DIM\ varied across service season. The \CR\ was nearly flat from 50 to 125 \DIM\ in \NY\ for all seasons, except for a large increasing trend in spring. In GA, there was also an increasing trend in fall. Conception rates were similar in \NY\ and \GA\ between December and May, and were strongly influenced by heat stress in \GA\ from June to November. A decline in \CR\ for reasons other than heat stress was present in both states in late spring. High production resulted in a faster decline of the \CR\ in \GA\ under heat stress. Models analyzing service records should include the \DIM\ × season × region interaction.

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