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The Long And The Short Of Environmental Sampling Management!
Autoscribe Informatics is providing two opportunities to have a close-up look at the new Environmental Sampling module for the Matrix Gemini LIMS (Laboratory Information Management System).
A 4-minute video provides a short demonstration of this versatile module which has been designed in conjunction with a leading food safety organisation, Deibel Laboratories. Aimed at anyone involved in environmental sampling of production and storage areas in food/beverage production and other industries, it uniquely links sampling point locations, test results and corrective action plans in one easy to use graphical environment.
For those who would like a longer and more detailed demonstration of the system, a recording of a webinar on the subject, recently presented by Autoscribe Informatics, is now available to view. The software demonstration is presented against the background of the need to move away from screening towards preventative measures against food-borne contamination both as required by the new Food Safety Modernisation Act (FSMA) implemented by the FDA, and in terms of the financial benefits of this approach.
The webinar covers the factors to consider when implementing an environmental monitoring program. The demonstration shows many facets of the software including how it provides:
- Set up of locations and sampling sites
- Visual maps of results status
- Trending of results
- Assignment of actions when the results indicate the need
- Association of results with a sampling site
- Reporting of results
The software provides clear documentation of preventative measures against food-borne contamination. This includes the ability to report the results and corrective actions taken when microorganism levels exceed safe levels. It provides an easy framework for expert set up and adjustment of the system while reducing the expertise needed to operate it on a daily basis. It allows the implementation of data management strategies that increase security and the availability of data.