Three-Year Summary of Preconditioning Effects on Pre- and Postshipment Performance of Feeder Calves

Production efficiencies associated with preconditioning feeder calves have been evaluated using 600 calves obtained from four ranches over a 3-year period. Nonpreconditioned calves remained with their dams during preconditioning and all calves were shipped to a research feedlot on the same dates each year. Average daily gains of nonpreconditioned calves for 28 days prior to shipment were variable over years and related t o range conditions. ADG of nonpreconditioned calves during each year were 1.39, .2 and 2.12 b and differed (P\u3c .001) from preconditioned c a l f gains of 2.18, 1.81 and .91 lb for the 39 days prior to shipment. Preconditioning responses interacted with ranch and year, indicating ranch conditions will have a significant impact on results. By weaning 30 days earlier, dams of preconditioned calves lost less weight during this same period. This effect was more pronounced when range conditions were poor. Preconditioning did not affect feed lot morbidity or mortality. During the initial 56 days in the feedlot, preconditioned calves consumed more dry matter each year but gains were similar. There was no effect of preshipment management on ADG after 56 days on feed and in the initial 2 years feed efficiency was better for nonpreconditioned calves. This advantage in feed efficiency carried through to slaughter at about 240 days

Effects of Preconditioning on Pre- and Postshipment Performance and Health of Feeder Steers

Four hundred steer calves were used to determine the effect of preconditioning on performance and health of calves fed either a high or low energy diet. In each of 2 years, 200 steer calves were selected from four western South Dakota ranches to participate in the study. Preconditioned (PC) calves were treated according to the South Dakota Beef Cattle Improvement Association and Cooperative Extension Service\u27s guidelines for the Green Tag program. Preconditioning and implanting with zeranol produced a heavier calf at market time. No difference in weight loss during transit was noted between the PC and control treatments (CO), but implanted calves lost more weight than those not implanted (5.51 vs 4.92%). Preconditioned calves gained faster (3.04 vs 2.68 lb/head/day) and consumed more dry matter (13.94 vs 11.98 lb/head/day) the first 28 days in the feed lot than CO. Implanted calves had improved average daily gain (ADG) (2.27 vs 1.98 lb/head/day) and feed efficiency (F/G; 5.76 vs 6.55) over nonimplanted calves during this time. By completion of the feeding period. CO calves were more efficient. Feeding a high energy diet (HE 60% concentrate) resulted in increased dry matter intake (DMI; 13.84 vs 12.09 lb/head/day) and F/G (5.18 vs 4.62) during the initial 28 days and improved ADG (3.16 vs 2.94 lb/head/day) and F/G (6.15 vs 6.53) overall compared to calves fed the low energy diet (LE)

Genetic diversity within and genetic differentiation between blooms of a microalgal species

The field of genetic diversity in protists, particularly phytoplankton, is under expansion. However, little is known regarding variation in genetic diversity within populations over time. The aim of our study was to investigate intrapopulation genetic diversity and genetic differentiation in the freshwater bloom-forming microalga Gonyostomum semen (Raphidophyceae). The study covered a 2-year period including all phases of the bloom. Amplified fragment length polymorphism (AFLP) was used to determine the genetic structure and diversity of the population. Our results showed a significant differentiation between samples collected during the two blooms from consecutive years. Also, an increase of gene diversity and a loss of differentiation among sampling dates were observed over time within a single bloom. The latter observations may reflect the continuous germination of cysts from the sediment. The life cycle characteristics of G. semen, particularly reproduction and recruitment, most likely explain a high proportion of the observed variation. This study highlights the importance of the life cycle for the intraspecific genetic diversity of microbial species, which alternates between sexual and asexual reproduction.Postprin

Infrared activity of hydrogen molecules trapped in Si

The rovibrational-translational states of a hydrogen molecule moving in a cage site in Si, when subjected to an electrical field arising from its surroundings, are investigated. The wave functions are expressed in terms of basis functions consisting of the eigenfunctions of the molecule confined to move in the cavity and rovibrational states of the free molecule. The energy levels, intensities of infrared and Raman transitions, effects of uniaxial stress, and a neighboring oxygen defect are found and compared with existing experimental data

Can microsatellite data allow identification of oleaster Plio-Pleistocene refuge zones in the Mediterranean Basin?

International audienc

Structurama: Bayesian Inference of Population Structure

Structurama is a program for inferring population structure. Specifically, the program calculates the posterior probability of assigning individuals to different populations. The program takes as input a file containing the allelic information at some number of loci sampled from a collection of individuals. After reading a data file into computer memory, Structurama uses a Gibbs algorithm to sample assignments of individuals to populations. The program implements four different models: The number of populations can be considered fixed or a random variable with a Dirichlet process prior; moreover, the genotypes of the individuals in the analysis can be considered to come from a single population (no admixture) or as coming from several different populations (admixture). The output is a file of partitions of individuals to populations that were sampled by the Markov chain Monte Carlo algorithm. The partitions are sampled in proportion to their posterior probabilities. The program implements a number of ways to summarize the sampled partitions, including calculation of the ‘mean’ partition—a partition of the individuals to populations that minimizes the squared distance to the sampled partitions

Non-linear regression models for Approximate Bayesian Computation

Approximate Bayesian inference on the basis of summary statistics is well-suited to complex problems for which the likelihood is either mathematically or computationally intractable. However the methods that use rejection suffer from the curse of dimensionality when the number of summary statistics is increased. Here we propose a machine-learning approach to the estimation of the posterior density by introducing two innovations. The new method fits a nonlinear conditional heteroscedastic regression of the parameter on the summary statistics, and then adaptively improves estimation using importance sampling. The new algorithm is compared to the state-of-the-art approximate Bayesian methods, and achieves considerable reduction of the computational burden in two examples of inference in statistical genetics and in a queueing model.Comment: 4 figures; version 3 minor changes; to appear in Statistics and Computin

Interacting Multiple Try Algorithms with Different Proposal Distributions

We propose a new class of interacting Markov chain Monte Carlo (MCMC) algorithms designed for increasing the efficiency of a modified multiple-try Metropolis (MTM) algorithm. The extension with respect to the existing MCMC literature is twofold. The sampler proposed extends the basic MTM algorithm by allowing different proposal distributions in the multiple-try generation step. We exploit the structure of the MTM algorithm with different proposal distributions to naturally introduce an interacting MTM mechanism (IMTM) that expands the class of population Monte Carlo methods. We show the validity of the algorithm and discuss the choice of the selection weights and of the different proposals. We provide numerical studies which show that the new algorithm can perform better than the basic MTM algorithm and that the interaction mechanism allows the IMTM to efficiently explore the state space

A Distinct Genetic Cluster in Cultivated Chickpea as Revealed by Genome-wide Marker Discovery and Genotyping

The accurate description of plant biodiversity is of utmost importance to efficiently address efforts in conservation genetics and breeding. Herein, we report the successful application of a genotyping-by-sequencing (GBS) approach in chickpea ( L.), resulting in the characterization of a cultivated germplasm collection with 3187 high-quality single nucleotide polymorphism (SNP) markers. Genetic structure inference, principal component analysis, and hierarchical clustering all indicated the identification of a genetic cluster corresponding to black-seeded genotypes traditionally cultivated in Southern Italy. Remarkably, this cluster was clearly distinct at both genetic and phenotypic levels from germplasm groups reflecting commercial chickpea classification into and seed types. Fixation index estimates for individual polymorphisms pointed out loci and genomic regions that might be of significance for the diversification of agronomic and commercial traits. Overall, our findings provide information on genetic relationships within cultivated chickpea and highlight a gene pool of great interest for the scientific community and chickpea breeding, which is limited by the low genetic diversity available in the primary gene pool

Association Mapping Reveals Novel Stem Rust Resistance Loci in Durum Wheat at the Seedling Stage

Wheat stem rust rapidly evolves new virulence to resistance genes. Recently emerged races in East Africa, such as TTKSK (or Ug99), possess broad virulence to durum cultivars, and only a limited number of genes provide resistance. An association mapping (AM) study conducted on 183 durum wheat accessions has allowed us to identify 41 quantitative trait loci (QTLs; determination coefficient [R2] values from 1.1 to 23.1%) for seedling resistance to one or more of four highly virulent stem rust races: TRTTF, TTTTF, TTKSK (Ug99), and JRCQC, two of which (TRTTF and JRCQC) were isolated from Ethiopia. Among these loci, 24 are novel, while the remaining 17 overlapped with loci previously shown to provide field resistance in Ethiopia and/or chromosome regions known to harbor designated stem rust resistance designated loci (Sr). The identified loci were either effective against multiple races or race specific, particularly for race JRCQC. Our results highlight that stem rust resistance in durum wheat is governed in part by loci for resistance across multiple races, and in part by race-specific ones (23 and 18, respectively). Collectively, these results provide useful information to improve the effectiveness of marker-assisted selection towards the release of durum wheat cultivars with durable stem rust resistance