Microbiological Evaluation of Pacific Shrimp Processing

Microbiological evaluation of Pacific shrimp (Pandalus jordani) processing was made from samples obtained at five key processing points. The microbial count of raw shrimp ranged from 1.3 x 10(6) to 3.0 x 10(6). The initial microbial flora, in order of predominance, was Acinetobacter-Moraxella, Flavobacterium, Pseudomonas, gram-positive cocci, and Bacillus species. No yeasts were isolated. Differences in processing practices influenced both microbial count and the shrimp flora. The microbial load, however, always increased after peeling and sorting operations and decreased after cooking, washing, and brining steps. Significantly, the gram-positive cocci were recovered with increasing frequency after each processing step, reaching 76% of the total load in a final product. Most of them, however, were coagulase-negative.     

A line-balancing strategy for designing flexible assembly systems

We present a rough-cut analysis tool that quickly determines a few potential cost-effective designs at the initial design stage of flexible assembly systems (FASs) prior to a detailed analysis such as simulation. It uses quantitative methods for selecting and configuring the components of an FAS suitable for medium to high volumes of several similar products. The system is organized as a series of assembly stations linked with an automated material-handling system moving parts in a unidirectional flow. Each station consists of a single machine or of identical parallel machines. The methods exploit the ability of flexible hardware to switch almost instantaneously from product to product. Our approach is particularly suitable where the product mix is expected to be stable, since we combine the hardware-configuration phase with the task-allocation phase. For the required volume of products, we use integer programming to select the number of stations and the number of machines at each station and to allocate tasks to stations. We use queueing network analysis, which takes into account the mean and variance of processing times among different products to determine the necessary capacity of the material-handling system. We iterate between the two analyses to find the combined solution with the lowest costs. Work-in-process costs are also included in the analysis. Computational results are presented.     

Comparison of dose-response relationships for ethyl methanesulfonate and 1-ethyl-1-nitrosourea in Drosophila melanogaster spermatozoa

The relative importance of different sites of alkylation on DNA was determined by comparing two ethylating agents. 1-Ethyl-1-nitrosourea (ENU) ethylates DNA with a higher proportion of total adducts on ring oxygens than ethyl methanesulfonate, which ethylates with a higher proportion of total adducts on the N-7 of guanine. Research with somatic cells in culture and prokaryotes strongly suggests that O6-guanine (O6-G) is the principal genotoxic site. To determine the importance in germ-line mutagenesis of the O6-G site relative to the N-7 of guanine, dose-response curves were constructed for both ENU and EMS, where dose was measured as total adducts per deoxynucleotide (APdN) and response as sex-linked recessive lethals (SLRL) induced in Drosophila melanogaster spermatozoa. For both mutagens the dose response curve was linear and extrapolated to the origin. The dose-response curve for ENU was fit to an equation m = 6.2D, and the dose response curve for EMS, from this and previous experiments, was m = 3.2D where m = %SLRL and D = APdN X 10(-3). Therefore, ENU is 1.9 times more efficient per adduct in inducing SLRL mutations than EMS. In vitro studies showed that ENU induced 9.5% of its total adducts on O6-G while EMS induced 2.0% of its adducts on O6-G. If O6-G was the sole genotoxic site, then ENU should be 4.8 times more efficient per adduct than EMS. In contrast, if N-7 G was the sole genotoxic site, ENU would be only 0.19 as effective as EMS. It was concluded that while O6-G was the principal genotoxic site, N-7 G made a significant contribution to germ-line mutagenesis.