Mark Swainson

Laser surface modification for the prevention of biofouling by infection causing Escherichia Coli

Bacteria have evolved to become proficient at adapting to both extracellular and environmental conditions, which has made it possible for them to attach and subsequently form biofilms on varying surfaces. This has resulted in major health concerns and economic burden in both hospital and industrial environments. Surfaces which prevent this bacterial fouling through their physical structure represent a key area of research for the development of antibacterial surfaces for many different environments. Laser surface treatment provides a potential candidate for the production of antibiofouling surfaces for wide ranging surface applications within healthcare and industrial disciplines. In the present study, a KrF 248 nm Excimer laser was utilized to surface pattern polyethylene terephthalate (PET). The surface topography and roughness were determined with the use of a Micromeasure 2, 3D profiler. Escherichia coli (E. coli) growth was analyzed at high shear flow using a CDC Biofilm reactor for 48 h, scanning el...

Sensory quality assurance in the chilled and frozen ready meal, soup and sauce sectors

This chapter discusses the use of sensory evaluation in the assurance of product quality within the food production sectors of ready meals, soups and sauces. The chapter methodically reviews typical food processing stages, from recipe development through to end product supply, and considers how sensory assessment methods can be utilised to help assure the quality of the end products within these selected high-risk chilled food sectors. © 2010 Woodhead Publishing Limited All rights reserved.

A Novel Camera Based Approach for Automatic Expiry Date Detection and Recognition on Food Packages

There is abundant of information on food packages, which include the food name, the expiry date and the ingredients. These information, especially the expiry date needs to be coded correctly before the products can be released into the market/supply chains. Failure of printing the correct expiry date can lead to both the health issues to the public and financial issues for recalling product back and even reimbursement. In this paper, we develop an automatic system that can achieve the expiry date region detection and recognition in an efficient and effective way. A deep neural network (DNN) based approach is firstly applied to find the expiry date region on the food package. The date characters are then extracted and recognized through the image processing and machine learning methods from the expiry date region. The system is the first camera based automatic system for recognizing expiry date on food packages. And the results tested on different types of food packages show that the system can achieve good performance on both detection and recognition of the expiry date.