Standardising bull breeding soundness evaluations and reporting in Australia

There is substantial variation in bull breeding soundness evaluation procedures and reports in Australia; the situation is compounded by difficulties in interpretation and the validity of many reports. In an effort to overcome this, the scientific literature was reviewed [Fordyce G. In: Fordyce G, editor. Bull fertility: selection and management in Australia. Eight Mile Plains, Australia: Australian Cattle Vets; 2002] and the needs of stakeholders were considered in preparing a manual, Evaluating and Reporting Bull Fertility [Entwistle KW, Fordyce G. Evaluating and reporting bull fertility. Eight Mile Plains, Australia: Australian Cattle Vets; 2003.] that outlined standards for assessing and reporting bull breeding soundness. A new recording and reporting system, called Bull Reporter, is based on standards from this manual and groups bull fertility traits into five summary categories: Scrotum, Physical, Crush-side Semen, Sperm Morphology, and Serving. The client will generally select which categories they wish to have included in the evaluation to suit their specific purposes. While there is adequate room for comments, the veterinarian is not required to make an overall judgment of whether the bull has normal capacity to sire calves under natural mating management, but ensures the standards for each selected category are met. Professional, standardised, easy-to-read reports are produced either electronically [Entwistle KW, Fordyce G. Evaluating and reporting bull fertility. Eight Mile Plains, Australia: Australian Cattle Vets; 2003.] or manually. A bull owner or their agent signs the certificate to affirm that bulls have not undergone procedures to rectify faults which may have otherwise caused them to fail the standards. An accreditation system for assessing sperm morphology was established because of its demonstrated relationship with pregnancy rates and because of the difficulties in achieving consistent and accurate assessments among laboratories. It is considered that Bull Reporter is applicable to beef and dairy bulls across all levels of management, genotypes and environments throughout Australia, with substantial potential for application elsewhere in the world. Crown Copyright (c) 2006 Published by Elsevier Inc. All rights reserved.

Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative

Objective To improve the accuracy and completeness of reporting of studies of diagnostic accuracy, to allow readers to assess the potential for bias in a study, and to evaluate a study's generalisability. Methods The Standards for Reporting of Diagnostic Accuracy (STARD) steering committee searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list. Researchers, editors, and members of professional organisations shortened this list during a two day consensus meeting, with the goal of developing a checklist and a generic flow diagram for studies of diagnostic accuracy. Results The search for published guidelines about diagnostic research yielded 33 previously published checklists, from which we extracted a list of 75 potential items. At the consensus meeting, participants shortened the list to a 25 item checklist, by using evidence, whenever available. A prototype of a flow diagram provides information about the method of patient recruitment, the order of test execution, and the numbers of patients undergoing the test under evaluation and the reference standard, or both. Conclusions Evaluation of research depends on complete and accurate reporting. If medical journals adopt the STARD checklist and flow diagram, the quality of reporting of studies of diagnostic accuracy should improve to the advantage of clinicians, researchers, reviewers, journals, and the public.

Recommendations for animal DNA forensic and identity testing

Genetic analysis in animals has been used for many applications, such as kinship analysis, for determining the sire of an offspring when a female has been exposed to multiple males, determining parentage when an animal switches offspring with another dam, extended lineage reconstruction, estimating inbreeding, identification in breed registries, and speciation. It now also is being used increasingly to characterize animal materials in forensic cases. As such, it is important to operate under a set of minimum guidelines that assures that all service providers have a template to follow for quality practices. None have been delineated for animal genetic identity testing. Based on the model for human DNA forensic analyses, a basic discussion of the issues and guidelines is provided for animal testing to include analytical practices, data evaluation, nomenclature, allele designation, statistics, validation, proficiency testing, lineage markers, casework files, and reporting. These should provide a basis for professional societies and/or working groups to establish more formalized recommendations.

Estimating variable returns to scale production frontiers with alternative stochastic assumptions

Two stochastic production frontier models are formulated within the generalized production function framework popularized by Zellner and Revankar (Rev. Econ. Stud. 36 (1969) 241) and Zellner and Ryu (J. Appl. Econometrics 13 (1998) 101). This framework is convenient for parsimonious modeling of a production function with returns to scale specified as a function of output. Two alternatives for introducing the stochastic inefficiency term and the stochastic error are considered. In the first the errors are added to an equation of the form h(log y, theta) = log f (x, beta) where y denotes output, x is a vector of inputs and (theta, beta) are parameters. In the second the equation h(log y,theta) = log f(x, beta) is solved for log y to yield a solution of the form log y = g[theta, log f(x, beta)] and the errors are added to this equation. The latter alternative is novel, but it is needed to preserve the usual definition of firm efficiency. The two alternative stochastic assumptions are considered in conjunction with two returns to scale functions, making a total of four models that are considered. A Bayesian framework for estimating all four models is described. The techniques are applied to USDA state-level data on agricultural output and four inputs. Posterior distributions for all parameters, for firm efficiencies and for the efficiency rankings of firms are obtained. The sensitivity of the results to the returns to scale specification and to the stochastic specification is examined. (c) 2004 Elsevier B.V. All rights reserved.