Model comparison for genetic evaluation of milk yield in crossbred Holsteins in the tropics

The objective of this study was to compare models for appropriate genetic parameter estimation for milk yield (305-day) in crossbred Holsteins in the tropics, where only records from crossbred cows were available. Eleven models with different effects of contemporary group (CG) at calving (herd-year-season or herd-year-month as fixed, and herd-year-month as random), age at calving (as linear or quadratic covariates, age-class, and age-class x lactation), and dominance were considered. On-farm records from small herds (n < 50) were included or excluded to validate the parameter estimates. Average Information Restricted Maximum Likelihood (AIREML) and Best Linear Unbiased Prediction (BLUP) were used to estimate variance components and breeding values. R-square (R2) and standard error of heritability (h2) were used to determine the appropriate model. The estimates of heritability from most models ranged from 0.18 to 0.22. CG formation of herd-year-month as a random effect slightly lowered the additive genetic variance but considerably decreased the permanent environmental variance. The model with age-class x lactation gave better R2 than other age adjustments. The models including records from smallholders gave similar estimates of heritability and a lower standard error than the models excluding them. The estimate of dominance variance as a proportion of total variance was close to zero. The low ratio of dominance to additive genetic variance suggested that the inclusion of dominance effects in the model was unjustified. In conclusion, the model including the effects of herd-year-month, age-class x lactation, as well as additive genetic, permanent environmental and residual effects, was the most appropriate for genetic evaluation in crossbred Holsteins, where records from smallholders could be included.     

Physiological adsorption of Sulfolobus acidocaldarius on coal surfaces

Summary The adsorption of Sulfolobus acidocaldarius on bituminous coal surfaces and the respiration rate during adsorption at 70° C were enhanced at pH 1.0–2.0, in comparison with those at pH 3.0–5.0. The maximum number of bacterial cells adsorbed per unit area of coal attained a maximum (1.4 × 10¹¹ cells/m²) at pH 2.0. The rate of desulphurization at pH 2.2–2.5 was higher than at other pHs tested. Micrographs of S. acidocaldarius obtained by TEM and SEM indicated that the cells were adsorbed to the coal surfaces by extracellular slime. Specific inhibitors of membrane-bound ATPase (NaF, 20 mm) and respiration (NaN₃, 1 mm; KCN, 1 mm) had pronounced effects on suppressing adsorption. The amount of S. acidocaldarius adsorbed decreased when the coal particles were leached in advance with 2.0 m HNO₃. These facts lead to the conclusion that the adsorption of S. acidocaldarius on coal surfaces requires physiological activity relatd to respiration or energy conversion. Offprint requests to: V. B. Vitaya     

Comparative Analysis of Microbial Profiles in Cow Rumen Fed with Different Dietary Fiber by Tagged 16S rRNA Gene Pyrosequencing

The ruminal microbiome of cattle plays an important role not only in animal health and productivity but also in food safety and environment. Microbial profiles of rumen fluid obtained from dairy cows fed on three different fiber/starch diet compositions were characterized. Tagged 16S rRNA gene pyrosequencing and statistical analysis revealed that the dominant ruminal bacteria shared by all three sample groups belonged to phyla Bacteroidetes, Firmicutes, and Proteobacteria. However, the relative abundance of these bacterial groups was markedly affected by diet composition. In animals fed with a high fiber diet, the fibrolytic and cellulolytic bacteria Lachnospiraceae, Ruminococcaceae, and Fibrobacteraceae were found in highest abundance compared with animals fed other diets with lower fiber content. The polysaccharide-degrading Prevotellaceae and Flavobacteriaceae bacteria were most abundant in the rumen of cows fed on diet with the highest starch content. These data highlight the ruminal microbiome’s ability to adapt to feed composition and also provide a basis for the development of feed formulation systems designed to improve livestock productivity.     

Evaluating application performance and energy consumption on hybrid CPU+GPU architecture

The High Performance Computing (HPC) community aimed for many years to increase performance regardless of energy consumption. Until the end of the decade, a next generation of HPC systems is expected to reach sustained performances of the order of exaflops. This requires many times more performance compared to the fastest supercomputers of today. Achieving this goal is unthinkable with current technology due to strict constraints on supplied power. Therefore, finding ways to improve energy efficiency become a main challenge on state-of-the-art research. The present paper investigates energy efficiency on heterogeneous CPU+GPU architectures using a scientific application from the agroforestry domain as a case-study. Differently from other works, our work evaluates how the workload of the application may affect energy efficiency on hybrid architectures. Results point out that the power supplier constraints depend also on the workload.