Food safety and development of the beef industry in China

Food safety concerns have escalated in China as they have elsewhere, especially in relation to meats. Beef production and consumption has increased proportionately faster than all other meats over the last two decades. Yet the slaughtering, processing and marketing of beef remains, for the most part, extremely primitive when compared with Western beef supply chains. By comparing the economics of household slaughtering with that of various types of abattoirs, this paper explains why household slaughtering and wet markets still dominate beef processing and distribution in China. The negative economic, social and industry development implications of enforcing more stringent food safety regulations are highlighted. The willingness/capacity of consumers to pay the added cost of better inspection and other services to guarantee food safety is investigated. In this context, the paper also evaluates the market opportunities for both domestic and imported Green Beef. The paper questions the merit of policy initiatives aimed at modernising Chinese beef supply chains for the mass market along Western lines. (C) 2002 Elsevier Science Ltd. All rights reserved.

Sensitivity and specificity of pooled faecal culture and serology as flock-screening tests for detection of ovine paratuberculosis in Australia

The flock-level sensitivity of pooled faecal culture and serological testing using AGID for the detection of ovine Johne's disease-infected flocks were estimated using non-gold-standard methods. The two tests were compared in an extensive field trial in 296 flocks in New South Wales during 1998. In each flock, a sample of sheep was selected and tested for ovine Johne's disease using both the AGID and pooled faecal culture. The flock-specificity of pooled faecal culture also was estimated from results of surveillance and market-assurance testing in New South Wales. The overall flock-sensitivity of pooled faecal culture was 92% (95% CI: 82.4 and 97.4%) compared to 61% (50.5 and 70.9%) for serology (assuming that both tests were 100% specific). In low-prevalence flocks (estimated prevalence

An approach to verifying and debugging simulation models governed by ordinary differential equations: Part 1. Methodology for residual generation

For dynamic simulations to be credible, verification of the computer code must be an integral part of the modelling process. This two-part paper describes a novel approach to verification through program testing and debugging. In Part 1, a methodology is presented for detecting and isolating coding errors using back-to-back testing. Residuals are generated by comparing the output of two independent implementations, in response to identical inputs. The key feature of the methodology is that a specially modified observer is created using one of the implementations, so as to impose an error-dependent structure on these residuals. Each error can be associated with a fixed and known subspace, permitting errors to be isolated to specific equations in the code. It is shown that the geometric properties extend to multiple errors in either one of the two implementations. Copyright (C) 2003 John Wiley Sons, Ltd.

An approach to verifying and debugging simulation models governed by ordinary differential equations: Part 2. Residuals analysis and a case study

In Part 1 of this paper a methodology for back-to-back testing of simulation software was described. Residuals with error-dependent geometric properties were generated. A set of potential coding errors was enumerated, along with a corresponding set of feature matrices, which describe the geometric properties imposed on the residuals by each of the errors. In this part of the paper, an algorithm is developed to isolate the coding errors present by analysing the residuals. A set of errors is isolated when the subspace spanned by their combined feature matrices corresponds to that of the residuals. Individual feature matrices are compared to the residuals and classified as 'definite', 'possible' or 'impossible'. The status of 'possible' errors is resolved using a dynamic subset testing algorithm. To demonstrate and validate the testing methodology presented in Part 1 and the isolation algorithm presented in Part 2, a case study is presented using a model for biological wastewater treatment. Both single and simultaneous errors that are deliberately introduced into the simulation code are correctly detected and isolated. Copyright (C) 2003 John Wiley Sons, Ltd.