Étude de la distribution de Salmonella comme un descripteur des enjeux de biosécurité dans un réseau de production: élevages et abattoir de porcs.

La production porcine a fait l’objet de plusieurs études visant à réduire la prévalence de Salmonella sur les carcasses à l’abattoir. Ces études ont ciblé l’élevage comme une source de la contamination observée. Malgré la multitude de facteurs de risques identifiés dans les travaux antérieurs, des étapes restent à investiguer dans le réseau de production primaire porcin. L’objectif de ce projet était de décrire la contamination à l’interface du réseau de production porcin: entre la ferme et l’abattoir. Pour ce faire, un réseau composé de dix fermes et un abattoir a été choisi incluant les trasporteurs. Trente visites de fermes, 36 suivis de camions lors du chargement - livraison et 18 investigations de la cour arrière de l’abattoir ont été réalisés au cours des 13 mois de la phase terrain du projet. De ces 738 échantillons, les résultats ont démontré des profils spécifiques de fermes cumulant 9 sérovars de Salmonella et 4 lysotypes différents de S. Typhimurium. Le quai de chargement à la ferme présentait 34,21% d’échantillons positifs. Des isolats non différenciables de S. Derby contaminaient ce site pour quatre fermes distinctes. Dans la cour d’abattoir, Salmonella a été retrouvée abondamment sur tous les trajets de circulation des camions (67% n=144). L’existence d’un lien dynamique de contamination par le camion de livraison des porcs lors des opérations de livraison à l’interface élevage- abattoir a été documentée. Cette interface représente un réservoir de Salmonella et donc un risque permanent de contamination croisée du réseau de production vers l’abattoir mais aussi de retour vers l’élevage

Analyse de la distribution d'Escherichia coli, utilisée comme un marqueur microbiologique, dans un réseau de production porcin.

La présence d’Escherichia coli pathogènes en élevages porcins entraine des retards de croissance et la mortalité. La transmission des E. coli pathogènes entre les élevages et l'abattoir d’un même réseau de production n'est pas bien décrite. La détection des gènes de virulence des E. coli pathogènes pourrait permettre d’identifier un marqueur de contamination dans le réseau. L’objectif de cette étude a été d’identifier un marqueur de contamination E. coli dans un réseau de production porcine défini afin de décrire certains modes de transmission des E. coli pathogènes. Pour ce faire, une région géographique comprenant 10 fermes d’engraissement, un abattoir et un réseau de transport a été sélectionnée. Trois lots de production consécutifs par ferme ont été suivis pendant 12 mois. Des échantillons environnementaux ont été prélevés à l’intérieur et à l’extérieur des fermes (3 visites d’élevage), dans la cour de l’abattoir (2 visites lors de sorties de lot) et sur le camion de transport. La détection des gènes de virulence (eltB, estA, estB, faeG, stxA, stx2A, eae, cnf, papC, iucD, tsh, fedA) dans les échantillons a été réalisée par PCR multiplexe conventionnelle. La distribution temporelle et spatiale des gènes de virulence a permis d’identifier le marqueur de contamination ETEC/F4 défini par la détection d’au moins un gène d’entérotoxine ETEC (estB, estA et eltB) en combinaison avec le gène de l’adhésine fimbriaire (faeG). La distribution des échantillons positifs ETEC/F4 qualifie la cour de l’abattoir comme un réservoir de contamination fréquenté par les transporteurs, vecteurs de contamination entre les élevages. Ceci suggère le lien microbiologique entre l’élevage, les transporteurs et l’abattoir jouant chacun un rôle dans la dissémination des microorganismes pathogènes et potentiellement zoonotiques en production porcine.

Analyse de la distribution d'Escherichia coli, utilisée comme un marqueur microbiologique, dans un réseau de production porcin

La présence d’Escherichia coli pathogènes en élevages porcins entraine des retards de croissance et la mortalité. La transmission des E. coli pathogènes entre les élevages et l'abattoir d’un même réseau de production n'est pas bien décrite. La détection des gènes de virulence des E. coli pathogènes pourrait permettre d’identifier un marqueur de contamination dans le réseau. L’objectif de cette étude a été d’identifier un marqueur de contamination E. coli dans un réseau de production porcine défini afin de décrire certains modes de transmission des E. coli pathogènes. Pour ce faire, une région géographique comprenant 10 fermes d’engraissement, un abattoir et un réseau de transport a été sélectionnée. Trois lots de production consécutifs par ferme ont été suivis pendant 12 mois. Des échantillons environnementaux ont été prélevés à l’intérieur et à l’extérieur des fermes (3 visites d’élevage), dans la cour de l’abattoir (2 visites lors de sorties de lot) et sur le camion de transport. La détection des gènes de virulence (eltB, estA, estB, faeG, stxA, stx2A, eae, cnf, papC, iucD, tsh, fedA) dans les échantillons a été réalisée par PCR multiplexe conventionnelle. La distribution temporelle et spatiale des gènes de virulence a permis d’identifier le marqueur de contamination ETEC/F4 défini par la détection d’au moins un gène d’entérotoxine ETEC (estB, estA et eltB) en combinaison avec le gène de l’adhésine fimbriaire (faeG). La distribution des échantillons positifs ETEC/F4 qualifie la cour de l’abattoir comme un réservoir de contamination fréquenté par les transporteurs, vecteurs de contamination entre les élevages. Ceci suggère le lien microbiologique entre l’élevage, les transporteurs et l’abattoir jouant chacun un rôle dans la dissémination des microorganismes pathogènes et potentiellement zoonotiques en production porcine.

Quality of handling and holding yard environment, and beef cattle temperament: 1. Relationships with flight speed and fear of humans.

Numerous tests have been used to measure beef cattle temperament, but limited research has addressed the relationship between such tests and whether temperament can be modified. One-hundred-and-forty-four steers were given one of three human handling and yarding experiences on six occasions during a 12-month grazing period post-weaning (backgrounding): Good handling/yarding, Poor handling/yarding and Minimal handling/yarding. At the end of this phase the cattle were lot-fed for 78 days, with no handling/yarding treatments imposed, before being transported for commercial slaughter. Temperament was assessed at the start of the experiment, during backgrounding and lot-feeding by flight speed (FS) and a fear of humans test, which measured the proximity to a stimulus person (zone average; ZA), the closest approach to the person (CA) and the amount the cattle moved around the test arena (total transitions; TT). During backgrounding, FS decreased for all treatments and at the end of backgrounding there was no difference between them. The rate of decline, however, was greatest in the Good group, smallest in the Minimal group with the Poor intermediate. In contrast, ZA was affected by treatment, with a greater reduction for the Good group than the others (P = 0.012). During lot-feeding, treatment did not affect FS, but all groups showed a decrease in ZA, with the greatest change in the Poor group, the least in the Good and the Minimal intermediate (P = 0.052). CA was positively correlated with ZA (r = 0.18 to 0.66) and negatively with TT (r = -0.180 to -0.659). FS was consistently correlated with TT only (r = 0.17 to 0.49). These findings suggest that FS and TT measure a similar characteristic, as do ZA and CA, but that these characteristics are different from one another, indicating that temperament is not a unitary trait, but has different facets. FS and TT measure one facet that we suggest is general agitation, whilst ZA and CA measure fear of people. Thus, the cattle became less agitated during backgrounding, but the effect was not permanently influenced by the quantity and quality of handling/yarding. However, Good handling/yarding reduced fearfulness of people. Fear of people was also reduced during lot-feeding, probably as a consequence of frequent exposure to humans in a situation that was neutral or positive for the cattle.

View of Paraiso Yard showing dredging equipment, Panama Canal. (ca. 1914)

Leonard Carpenter Panama Canal Collection. Photographs: Dredging, Soldiers, and Ships. [Box 1] from the Special Collections & Area Studies Department, George A. Smathers Libraries, University of Florida.

Survival in water of Campylobacter jejuni strains isolated from the slaughterhouse

Campylobacter jejuni cause gastroenteritis in humans. The main transmission vector is the consumption or handling of contaminated chicken meat, since chicken can be colonized asymptomatically by C. jejuni. However, water has been implicated as the transmission vector in a few outbreaks. One possibility is the contamination of water effluent by C. jejuni originating from chicken farm. The ability of C. jejuni to be transmitted by water would be closely associated to its ability to survive in water. Therefore, in this study, we have evaluated the ability of reference strains and chickenisolated strains to survive in water. Defined water media were used, since the composition of tap water is variable. We showed that some isolates survive better than others in defined freshwater (Fraquil) and that the survival was affected by temperature and the concentration of NaCl. By comparing the ability of C. jejuni to survive in water with other phenotypic properties previously tested, we showed that the ability to survive in water was negatively correlated with autoagglutination. Our data showed that not all chicken isolates have the same ability to survive in water, which is probably due to difference in genetic content.

Simulation of Sawmill Yard Operations Using Software Agents

Bergkvist insjön AB is a sawmill yard which is capable of producing 350,000 cubic meter of timber every year this requires lot of internal resources. Sawmill operations can be classified as unloading, sorting, storage and production of timber. In the company we have trucks arriving at random they have to be unloaded and sent back at the earliest to avoid queuing up of trucks creating a problem for truck owners. The sawmill yard has to operate with two log stackers that does several tasks including transporting the logs from trucks to measurement station where the logs will be sorted into classes and dropped into pockets from pockets to the sorted timber yard where they are stored and finally from there to sawmill for final processing. The main issue that needs to be answered here is the lining up trucks that are waiting to be unload, creating a problem for both sawmill as well as the truck owners and given huge production volume, it is certain that handling of resources is top priority. A key challenge in handling of resources would be unloading of trucks and finding a way to optimize internal resources.To address this problem i have experimented on different ways of using internal resources, i have designed different cases, in case 1 we have both the log stackers working on sawmill and measurement station. The main objective of having this case is to make sawmill and measurement station to work all the time. Then in case 2, i have divided the work between both the log stackers, one log stacker will be working on sawmill and pocket_control and second log stacker will be working on measurement station and truck. Then in case 3 we have only one log stacker working on all the agents, this case was designed to reduce cost of production, as the experiment cannot be done in real-time due to operational cost, for this purpose simulation is used, preliminary investigation into simulation results suggested that case 2 is the best option has it reduced waiting time of trucks considerably when compared with other cases and it showed 50% increase in optimizing internal resources.

Simulation and optimisation techniques for sawmill yard operation : A literature review

Increasing costs and competitive business strategies are pushing sawmill enterprises to make an effort for optimization of their process management. Organizational decisions mainly concentrate on performance and reduction of operational costs in order to maintain profit margins. Although many efforts have been made, effective utilization of resources, optimal planning and maximum productivity in sawmill are still challenging to sawmill industries. Many researchers proposed the simulation models in combination with optimization techniques to address problems of integrated logistics optimization. The combination of simulation and optimization technique identifies the optimal strategy by simulating all complex behaviours of the system under consideration including objectives and constraints. During the past decade, an enormous number of studies were conducted to simulate operational inefficiencies in order to find optimal solutions. This paper gives a review on recent developments and challenges associated with simulation and optimization techniques. It was believed that the review would provide a perfect ground to the authors in pursuing further work in optimizing sawmill yard operations.

Multi-agent simulation of sawmill yard operations

This paper reports the findings of using multi-agent based simulation model to evaluate the sawmill yard operations within a large privately owned sawmill in Sweden, Bergkvist Insjön AB in the current case. Conventional working routines within sawmill yard threaten the overall efficiency and thereby limit the profit margin of sawmill. Deploying dynamic work routines within the sawmill yard is not readily feasible in real time, so discrete event simulation model has been investigated to be able to report optimal work order depending on the situations. Preliminary investigations indicate that the results achieved by simulation model are promising. It is expected that the results achieved in the current case will support Bergkvist-Insjön AB in making optimal decisions by deploying efficient work order in sawmill yard.

Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.

Use of three rapid detection systems to evaluate the prevalence and dissemination of Salmonella in a Brazilian poultry slaughterhouse

Prevalence and dissemination of Salmonella in a Brazilian poultry slaughterhouse were evaluated by three rapid detection systems (SS/SV(TM), VICAM, OSRT(TM), Unipath/Oxoid, and REVEAL(TM), Neogen), plus the conventional procedure. The carcasses were sampled after bleeding (P1), defeathering (P2), evisceration (P3), washing (P4), chilling (P5) and the packaged end-product (P6). In the first set of carcasses, the Salmonella incidence determined by the conventional method was 38.3% and 22.5% by SS/SV(TM). In the set for evaluation of OSRT(TM), the number of positive samples was the same detected by the cultural procedure (49.0%). In the third set, the positivity by the conventional procedure was 33.3%, and 5.0% by REVEAL(TM). The comparisons of positives in the first and third sets of carcasses were significantly different (P < 0.05). The positivity for Salmonella, in carcasses at P1 to P6, as determined by at least one of the methods, was 47.5%, 47.5%, 32.5%, 30.0%, 30.0% and 37.7%, respectively.