Bioeconomic factors of beef heifer maturity to consider when establishing criteria to optimally select and/or retain herd replacements

Abstract

The online version of this article, along with updated information and services, is located on Cammack et al. (2009, p. 517) wrote, "Biological and economic efficiencies of cow-calf production are largely dependent on successful reproduction." The literature is replete with works about reproduction, dystocia, and maturity. Bellows et al. (1971) used ordinary least squares (OLS) regression to quantify the effect of physical size on 4 degrees of dystocia. Morrison et al. (1985) and Basarab et al. (1993) proposed using a discriminant analysis methodology. While similar to OLS, this method optimizes a different objective function giving the estimates of the coefficients an altered meaning and use. In seeking a method to optimize productivity and identify the control variables for reproduction efficiency, Greer et al. (1983) developed an "index of maturity." Their index values proved to be less than statistically significant. More recently, work by Patterson et al. (1992) using target weight (TW) has become a widely accepted method to forecast maturity and initiate heifer breeding. Using the same metric, Feuz (1991) developed a profit function. 4733 INTRODUCTIONAs Feuz (1991) recognized, the economically optimal breeding readiness of beef replacement heifers is that point of development where costs are less than or equal to expected revenues obtained by such development. Costs and revenues are dependent on both physical and economic factors used in producing beef cattle, and any model used to accurately reflect profitability/ productivity must include both. In a step toward this end, the maturity index (MI) developed by Stockton et al. (2013) ABSTRACT: Understanding the biology of heifer maturity and its relationship to calving difficulty and subsequent breeding success is a vital step in building a bioeconomic model to identify optimal production and profitability. A limited dependent variable probit model is used to quantify the responses among heifer maturities, measured by a maturity index (MI), on dystocia and second pregnancy. The MI account for heifer age, birth BW, prebreeding BW, nutrition level, and dam size and age and is found to be inversely related to dystocia occurrence. On average there is a 2.2% increase in the probability of dystocia with every 1 point drop in the MI between the MI scores of 50 and 70. Statistically, MI does not directly alter second pregnancy rate; however, dystocia does. The presence of dystocia reduced second pregnancy rates by 10.67%. Using the probability of dystocia predicted from the MI in the sample, it is found that on average, every 1 point increase in MI added 0.62% to the probability of the occurrence of second pregnancy over the range represented by the data. Relationships among MI, dystocia, and second pregnancy are nonlinear and exhibit diminishing marginal effects. These relationships indicate optimal production and profitability occur at varying maturities, which are altered by animal type, economic environment, production system, and management regime. With thes...

Efficiency in Cow-Calf Systems With Different Ages of Cow Culling

“…The increase in production cost per cow and per system, as the LT decreases, is due to the high disbursement for cultivated pastures that have elevated implantation and maintenance costs. Nevertheless, cultivated pastures are indispensable to meet the energy requirements of low LT systems and avoid culling cows due to reproductive failures or calving difficulties ( 45 , 46 ), especially for young cows. Although only 10% of the total area of LT13 consists of oat/ryegrass pasture (144 ha), this was the most representative item for this system because feed costs are among the most onerous for beef cattle production systems ( 47 – 49 ).…”