Estimating Maximum Possible Environmental Loading Amounts of Cryptosporidium parvum Attributable to Adult Beef Cattle

Populations of beef cattle represent a potential non-point source of environmental contamination for Cryptosporidium parvum if on-farm management practices fail to minimize transport from bovine manure to adjacent water sources. Characterizing this risk of contamination requires several parameters to be estimated, the most important being a valid and precise estimate of the oocyst loading rate per animal unit. The oocyst loading rate is defined in this study as the total number of oocysts excreted by a cohort of adult beef cows during a 24[emsp4 ]h period. We propose a methodology for estimating this parameter for low prevalent populations whereby the majority of individuals are test negative. Under specific degrees of confidence and at the population scale, this methodology generates estimates for maximal oocyst loading based on the sensitivity of the diagnostic test and the point prevalence and intensity of fecal shedding from a cross-sectional survey of the target population.Our cross-sectional survey on California beef cows generated a prevalence of infection of 1.1 % (6/557) and an intensity of oocyst shedding ranging from 219 to 5,491 oocysts/g, with a geometric mean of 835 oocysts/g from six positive cows. Negative binomial estimate of the percent recovery of the diagnostic assay was 0.235. Based on this percent recovery and using approximately 19.4[emsp4 ]mg of feces per assay, the DT₉₀ of our assay, defined as the concentration of oocysts at which our diagnostic assay had a 90 % probability of detecting one or more oocysts in a sample, was 755 oocyst/g feces. At a 95 % confidence level, the estimated maximum number of oocysts being excreted in the feces of California beef cows ranged from 4.8 to 14.4 oocysts/g feces/cow, or 7.7×10⁴ to 2.3×10⁵ oocysts/beef cow/day.     

Estimates of direct and maternal covariance functions for growth of Australian beef calves from birth to weaning

Records for birth and subsequent, monthly weights until weaning on beef calves of two breeds in a selection experiment were analysed fitting random regression models. Independent variables were orthogonal (Legendre) polynomials of age at weighing in days. Orders of polynomial fit up to 6 were considered. Analyses were carried out fitting sets of random regression coefficients due to animals'' direct and maternal, additive genetic and permanent environmental effects, with changes in variances due to temporary environmental effects modelled through a variance function, estimating up to 67 parameters. Results identified similar patterns of variation for both breeds, with maternal effects considerably more important in purebred Polled Herefords than a four-breed synthetic, the so-called Wokalups. Conversely, repeatabilities were higher for the latter. For both breeds, heritabilities decreased after birth, being lowest when maternal effects were most important around 100 days of age. Estimates at birth and weaning were consistent with previous, univariate results.     

Importance of adaptation and genotype × environment interactions in tropical beef breeding systems

This paper examines the relative importance of productive and adaptive traits in beef breeding systems based on Bos taurus and tropically adapted breeds across temperate and (sub)tropical environments. In the (sub)tropics, differences that exist between breeds in temperate environments are masked by the effects of environmental stressors. Hence in tropical environments, breeds are best categorised into breed types to compare their performance across environments. Because of the presence of environmental stressors, there are more sources of genetic variation in tropical breeding programmes. It is therefore necessary to examine the genetic basis of productive and adaptive traits for breeding programmes in those environments. This paper reviews the heritabilities and genetic relationships between economically important productive and adaptive traits relevant to (sub)tropical breeding programmes. It is concluded that it is possible to simultaneously genetically improve productive and adaptive traits in tropically adapted breeds of beef cattle grazed in tropical environments without serious detrimental consequences for either adaptation or production. However, breed-specific parameters are required for genetic evaluations. The paper also reviews the magnitude of genotype × environment (G × E) interactions impacting on production and adaptation of cattle, where 'genotype' is defined as breed (within a crossbreeding system), sire within breed (in a within-breed selection programme) or associations between economically important traits and single nucleotide polymorphisms (SNPs - within a marker-assisted selection programme). It is concluded that re-ranking of breeds across environments is best managed by the use of the breed type(s) best suited to the particular production environment. Re-ranking of sires across environments is apparent in poorly adapted breed types across extreme tropical and temperate environments or where breeding animals are selected in a temperate environment for use in the (sub)tropics. However, G × E interactions are unlikely to be of major importance in tropically adapted beef cattle grazed in either temperate or (sub)tropical environments, although sex × environment interactions may provide new opportunities for differentially selecting to simultaneously improve steer performance in benign environments and female performance in harsher environments. Early evidence suggests that re-ranking of SNPs occurs across temperate and tropical environments, although their magnitude is still to be confirmed in well-designed experiments. The major limitation to genetic improvement of beef cattle over the next decade is likely to be a deficiency of large numbers of accurately recorded phenotypes for most productive and adaptive traits and, in particular, for difficult-to-measure adaptive traits such as resistance to disease and environmental stressors.     

A review of rhizosphere carbon flow modelling

Rhizosphere processes play a key role in nutrient cycling in terrestrial ecosystems. Plant rhizodeposits supply low-molecular weight carbon substrates to the soil microbial community, resulting in elevated levels of activity surrounding the root. Mechanistic compartmental models that aim to model carbon flux through the rhizosphere have been reviewed and areas of future research necessary to better calibrate model parameters have been identified. Incorporating the effect of variation in bacterial biomass physiology on carbon flux presents a considerable challenge to experimentalists and modellers alike due to the difficulties associated with differentiating dead from dormant cells. A number of molecular techniques that may help to distinguish between metabolic states of bacterial cells are presented. The calibration of growth, death and maintenance parameters in rhizosphere models is also discussed. A simple model of rhizosphere carbon flow has been constructed and a sensitivity analysis was carried out on the model to highlight which parameters were most influential when simulating carbon flux. It was observed that the parameters that most heavily influenced long-term carbon compartmentalisation in the rhizosphere were exudation rate and biomass yield. It was concluded that future efforts to simulate carbon flow in the rhizosphere should aim to increase ecological realism in model structure. This revised version was published online in June 2006 with corrections to the Cover Date.     

The association of CAPN1 316 marker genotypes with growth and meat quality traits of steers finished on pasture

The objective of this paper was to determine the association of a SNP in the μ-calpain gene at position 316 with growth and quality of meat traits of steers grown on pasture. Fifty-nine Brangus and 20 Angus steers were genotyped for CAPN1 316. Warner Bratzler shear force was measured in l. lumborum samples after a 7-day aging period. A multivariate analysis of variance was performed, including shear force (WBSF), final weight (FW), average daily gain (ADG), backfat thickness (BFT), average monthly fat thickness gain (AMFTG), rib-eye area (REA), and beef rib-eye depth (RED) as dependent variables. The CAPN1 316 genotype was statistically significant. Univariate analyses were done with these variables. The marker genotype was statistically significant (p < 0.05) for WBSF (kg: CC: 4.41 ± 0.57; CG: 5.58 ± 0.20; GG: 6.29 ± 0.18), FW (kg: CC: 360.23 ± 14.71; CG: 381.34 ± 5.26; GG: 399.23 ± 4.68), and ADG (kg/d: CC: 0.675 ± 0.046; CG: 0.705 ± 0.016; GG: 0.765 ± 0.014) Shear force, final weight and average daily gain were significantly different according to the CAPN1 316 marker genotypes. The marker genotype was statistically significant in the multivariate analysis (p = 0.001). The first characteristic root explained 89% of the differences among genotypes. WBSF, FW and ADG were the most important traits in the first vector, indicating that animals with the marker genotype for lowest WBSF also have the lowest FW and ADG.     

A genome map of divergent artificial selection between Bos taurus dairy cattle and Bos taurus beef cattle

A number of cattle breeds have become highly specialized for milk or beef production, following strong artificial selection for these traits. In this paper, we compare allele frequencies from 9323 single nucleotide polymorphism (SNP) markers genotyped in dairy and beef cattle breeds averaged in sliding windows across the genome, with the aim of identifying divergently selected regions of the genome between the production types. The value of the method for identifying selection signatures was validated by four sources of evidence. First, differences in allele frequencies between dairy and beef cattle at individual SNPs were correlated with the effects of those SNPs on production traits. Secondly, large differences in allele frequencies generally occurred in the same location for two independent data sets (correlation 0.45) between sliding window averages. Thirdly, the largest differences in sliding window average difference in allele frequencies were found on chromosome 20 in the region of the growth hormone receptor gene, which carries a mutation known to have an effect on milk production traits in a number of dairy populations. Finally, for the chromosome tested, the location of selection signatures between dairy and beef cattle was correlated with the location of selection signatures within dairy cattle.