Use of robust multivariate linear mixed models for estimation of genetic parameters for carcass traits in beef cattle

Assumptions of normality of residuals for carcass evaluation may make inferences vulnerable to the presence of outliers, but heavy-tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. We compare estimates of genetic parameters by fitting multivariate Normal (MN) or heavy-tail distributions (multivariate Student’s t and multivariate Slash, MSt and MS) for residuals in data of hot carcass weight (HCW), longissimus muscle area (REA) and 12th to 13th rib fat (FAT) traits in beef cattle using 2475 records from 2007 to 2008 from a large commercial operation in Nebraska. Model comparisons using deviance information criteria (DIC) favoured MSt over MS and MN models, respectively. The posterior means (and 95% posterior probability intervals, PPI) of v for the MSt and MS models were 5.89±0.90 (4.35, 7.86) and 2.04±0.18 (1.70, 2.41), respectively. Smaller values of posterior densities of v for MSt and MS models confirm that the assumption of normally distributed residuals is not adequate for the analysis of the data set. Posterior mean (PM) and posterior median (PD) estimates of direct genetic variances were variable with MSt having the highest mean value followed by MS and MN, respectively. Posterior inferences on genetic variance were, however, comparable among the models for FAT. Posterior inference on additive heritabilities for HCW, REA and FAT using MN, MSt and MS models indicated similar and moderate heritability comparable with the literature. Posterior means of genetic correlations for carcass traits were variable but positive except for between REA and FAT, which showed an antagonistic relationship. We have demonstrated that genetic evaluation and selection strategies will be sensitive to the assumed model for residuals

Impact of Nitrogen Fertilization and Cropping System on Carbon Sequestration in Midwestern Mollisols

Growing interest in the potential for agricultural soils to provide a sink for atmospheric C has prompted studies of effects of management on soil organic carbon (SOC) sequestration. We analyzed the impact on SOC of four N fertilization rates (0–270 kg N ha−1) and four cropping systems: continuous corn (CC) (Zea mays L.); corn–soybean [Glycine max (L.) Merr.] (CS); corn–corn–oat–alfalfa (oat, Avena sativa L.; alfalfa, Medicago sativa L.) (CCOA), and corn–oat–alfalfa–alfalfa (COAA). Soils were sampled in 2002, Years 23 and 48 of the experiments located in northeast and north-central Iowa, respectively. The experiments were conducted using a replicated split-plot design under conventional tillage. A native prairie was sampled to provide a reference (for one site only). Cropping systems that contained alfalfa had the highest SOC stocks, whereas the CS system generally had the lowest SOC stocks. Concentrations of SOC increased significantly between 1990 and 2002 in only two of the nine systems for which historical data were available, the fertilized CC and COAA systems at one site. Soil quality indices such as particulate organic carbon (POC) were influenced by cropping system, with CS \u3c CC \u3c CCOA. In the native prairie, SOC, POC, and resistant C concentrations were 2.8, 2.6, and 3.9 times, respectively, the highest values in cropped soil, indicating that cultivated soils had not recovered to precultivation conditions. Although corn yields increased with N additions, N fertilization increased SOC stocks only in the CC system at one site. Considering the C cost for N fertilizer production, N fertilization generally had a net negative effect on C sequestration