2003 IRISH SCIENTIST YEAR BOOK

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University of Limerick
Elfed Lewis, William Lyons & Marion O'Farrell
Online intelligent colour and temperature measurements used to control the process of cooking food

Food colour measurement using an optical fibre probe

With an ever-increasing volume in the throughput of the food industry, profit margins dictate that it is no longer acceptable for large errors to occur, as the result would be a significant financial loss. This is evident in the cooking of large batches of various food types in industrial ovens with conveyor belt lengths of up to 20 metres. The conveyor belts of these ovens may be fully loaded with food for maximum efficiency and the cost of an error in one batch would be intolerable for the producer. Automation in the cooking of the food is critical in order to control oven temperature, conveyor belt speed, height of steamers, etc., so that the food is cooked to the highest quality. There is a need for monitoring the food as it passes through the oven and determining that all the processing parameters are correct, the most important of these being the food's core temperature and the colour (both internal and external).

Grading the quality of a product - e.g. in terms of colour - ensures consistency in the product. Factors such as colour have a huge influence over a customer decision in purchasing a product, as they often have preconceived notions of how it should look - e.g. roast chickens must be golden, flame-grilled hamburgers must have black lines, and cooked sausage must be a rich brown. The fact that the food is cooked to a core temperature recommended by food safety authorities is taken for granted by the customer, but for the manufacturer it is a critical parameter indicating that all bacteria are killed and food poisoning is avoided. Therefore, it is clear that both colour and temperature are used to determine if a product is correctly cooked.


Online measurements of food temperature and colour using an optical fibre probe in the oven

The system described in this paper comprises two parts - colour measurement and temperature measurement - both using optical fibre sensors. The colour is measured by using a reflective probe and recording the light reflected in the visible spectrum, which is representative of the colour. This in effect mimics the eye, which reads the reflected light from objects to see their colour. In the case of humans, the eye sees and then the brain decides - e.g. is this red or blue? In this system, an Artificial Neural Network performs the decision-making. Artificial neural networks are highly parallel interconnected systems of elements (called neurons) which have been modelled from studies of biological nervous systems and thus draw on the analogies of adaptive biological learning. The network in this case exists in software stored in the memory of the supervising PC neurons. The software allows the neurons to be tied together with weighted connections that are analogous to synapses in the brain.

The temperature measurement requires a specially doped optical fibre whereby stimulation at a certain wavelength of light, 785nm (infra-red), causes it to absorb energy and emit light at a higher wavelength, 1060nm. When the stimulation is effectively 'cut off', the emission decays rapidly, but at a certain rate which is dependant on the surrounding temperature. By measuring that decay time, it is possible to determine the food sample temperature. This temperature measurement technique has been researched and developed by the collaborating research institution, City University, London, UK.

These sensor probes can be made to be as small as 2.5mm (including the stainless steel protective cover) and thus allow unobtrusive internal measurements of food (i.e. they don't cause physical damage to the food sample). This allows online measurements inside the ovens, thus removing the need to take random samples out for testing that will be subsequently thrown away, as well as speeding up the cooking process.

Contact: Dr Elfed Lewis, E-mail: [email protected] ;
Dr William Lyons, E-mail: [email protected] ;
Marion O'Farrell, E-mail: Marion.O'[email protected]