Effect of dietary crude protein on ammonia-N emission measured by herd nitrogen mass balance in a freestall dairy barn managed under farm-like conditions.

The main objective of this experiment was to monitor the impact of barn side and dietary crude protein (CP) on production performance, manure production and composition, and ammonia nitrogen (N) emission from a lactating dairy herd housed in a free-stall barn and managed under farm-like conditions throughout a number of months in each season of the year. The 78-cow lactating herd of the University of Wisconsin-Platteville (USA) was halved and each group was allocated to either the north or south side of the barn and either a recommended (REC) diet with 16.7 ± 1.3% CP dry matter basis (DM) or an excess (EXC) CP diet containing 1.5 units of CP above the REC diet (18.2 ± 1.5%). In 7 months between February 2004 and January 2005, total manure collection was conducted by manual scraping of the alleys and ammonia-N emission was calculated as intake N + bedding N - milk N - scraped manure N. Side of the barn (northern v. southern exposure) did not influence measurements and there was no effect of dietary CP on dry matter intake (DMI), milk, milk fat, and milk protein production, but a lower manure N concentration was observed for the group of cows fed the REC diet compared with the EXC diet (3.43% v. 3.66% of DM). Nitrogen intake was 63 g/day lower (643 v. 706 g/day), milk N was unaffected (157 g/day), manure N was 32 g/day lower (391 v. 423 g/day), and ammonia-N emission was 34 g/day lower (93 v. 127 g/day) for the group consuming the REC diet compared with the group consuming the EXC diet. There were larger variations in measured responses among months of the year than between level of dietary CP. Wet and dry manure excretions tended to be higher, but manure pH was reduced when corn silage became unavailable and the diet included additional corn grain and alfalfa silage as the only forage source. Prediction of manure N excretion for a group of cow determined as N intake - N milk was 9% higher than current prediction equations of the American Society of Agricultural Engineers. Ammonia-N loss averaged 110 g/day per lactating cow, but ranged from 64 g/day to 178 g/day with no clear seasonal pattern. There was no clear association between barn temperature, manure temperature or manure pH and ammonia-N emission; however, intake N explained 61% of the variation in ammonia-N emission.

Short communication: effectiveness of sample duplication to control error in ruminant digestion studies.

Eight ruminally cannulated lactating dairy cows from a study on the effect of dietary rumen-degraded protein on production and digestion of nutrients were used to assess using sample duplication to control day-to-day variation within animals and errors associated with sampling and laboratory analyses. Two consecutive pooled omasal samples, each representing a feeding cycle, were obtained from each cow in each period. The effectiveness of sample duplication in error control was tested by comparing the variance of the difference in treatment means when taking 2 samples from each cow in each period to the variance when taking only one sample. Compared with no duplication, sample duplication improved precision by reducing variance by 50, 40, 31, 23, 23, and 9% for, respectively, rumen-undegraded protein flows, ruminal neutral detergent fiber digestibility, microbial nonammonia N flow, microbial efficiency, organic matter flow, and organic matter truly digested in the rumen. For these same variables, reductions in the standard errors of the difference between treatment means due to sample duplication represented 100, 87, 73, 59, 58, and 27% of the predicted reductions resulting from doubling the number of experimental units without sample duplication. Sample duplication can substantially reduce experimental error originating from day-to-day variation within cows, sample collection, and laboratory analyses, thus improving statistical power in ruminant digestion studies.

High genetic diversity, phenotypic uniformity, and evidence of outcrossing in sclerotinia sclerotiorum in the columbia basin of washington state.

ABSTRACT Sclerotinia sclerotiorum, the causal agent of potato stem rot, is prevalent and poorly managed on potatoes in the Columbia Basin of Washington. Because of the ubiquitous nature of the fungus and high crop diversity within the Columbia Basin, understanding the population structure and the potential for outcrossing of the pathogen would be helpful in developing disease management strategies. The population structure of S. sclerotiorum in the Columbia Basin from potato was examined using microsatellite markers and mycelial compatibility. Analysis of molecular variance revealed that 92% of the variability among 167 isolates was found within subpopulations, with limited, yet statistically significant impact of the collection date, but not the year or location of collection. Linkage disequilibrium and index of association analyses noted a potential for outcrossing in two locations, which was substantiated by the discovery of recombinant ascospores in three field-generated apothecia from the 12 apothecia examined. Microsatellite haplotypes were not correlated with mycelial compatibility groups. This high haplotypic diversity did not seem to impact pathologically important phenotypes. Greenhouse inoculations of potato plants exhibited no significant differences in aggressiveness on potato stems. Moreover, in vitro studies of response to fungicides and temperature stimuli yielded no significant differences among studied isolates. These findings illustrate the potential for outcrossing in warm temperate regions of North America, where a diversity of crops are planted simultaneously and in neighboring fields. This study also indicates that the unsatisfactory management of potato stem rot is likely not directly attributable to genetic factors, but to gaps in agricultural practices.

Statistical analysis of DOE EML QAP data from 1982 to 1998.

The historical database from the Environmental Measurements Laboratory's Quality Assessment Program from 1982 to 1998 has been analyzed to determine control limits for future performance evaluations of the different laboratories contracted to the U.S. Department of Energy. Seventy-three radionuclides in four different matrices (air filter, soil, vegetation, and water) were analyzed. The evaluation criteria were established based on a z-score calculation.

A Bayesian framework for the analysis of cospeciation.

Information on the history of cospeciation and host switching for a group of host and parasite species is contained in the DNA sequences sampled from each. Here, we develop a Bayesian framework for the analysis of cospeciation. We suggest a simple model of host switching by a parasite on a host phylogeny in which host switching events are assumed to occur at a constant rate over the entire evolutionary history of associated hosts and parasites. The posterior probability density of the parameters of the model of host switching are evaluated numerically using Markov chain Monte Carlo. In particular, the method generates the probability density of the number of host switches and of the host switching rate. Moreover, the method provides information on the probability that an event of host switching is associated with a particular pair of branches. A Bayesian approach has several advantages over other methods for the analysis of cospeciation. In particular, it does not assume that the host or parasite phylogenies are known without error; many alternative phylogenies are sampled in proportion to their probability of being correct.

A compound poisson process for relaxing the molecular clock.

The molecular clock hypothesis remains an important conceptual and analytical tool in evolutionary biology despite the repeated observation that the clock hypothesis does not perfectly explain observed DNA sequence variation. We introduce a parametric model that relaxes the molecular clock by allowing rates to vary across lineages according to a compound Poisson process. Events of substitution rate change are placed onto a phylogenetic tree according to a Poisson process. When an event of substitution rate change occurs, the current rate of substitution is modified by a gamma-distributed random variable. Parameters of the model can be estimated using Bayesian inference. We use Markov chain Monte Carlo integration to evaluate the posterior probability distribution because the posterior probability involves high dimensional integrals and summations. Specifically, we use the Metropolis-Hastings-Green algorithm with 11 different move types to evaluate the posterior distribution. We demonstrate the method by analyzing a complete mtDNA sequence data set from 23 mammals. The model presented here has several potential advantages over other models that have been proposed to relax the clock because it is parametric and does not assume that rates change only at speciation events. This model should prove useful for estimating divergence times when substitution rates vary across lineages.

Bayesian phylogenetic inference via Markov chain Monte Carlo methods.

We derive a Markov chain to sample from the posterior distribution for a phylogenetic tree given sequence information from the corresponding set of organisms, a stochastic model for these data, and a prior distribution on the space of trees. A transformation of the tree into a canonical cophenetic matrix form suggests a simple and effective proposal distribution for selecting candidate trees close to the current tree in the chain. We illustrate the algorithm with restriction site data on 9 plant species, then extend to DNA sequences from 32 species of fish. The algorithm mixes well in both examples from random starting trees, generating reproducible estimates and credible sets for the path of evolution.