Employing spectroscopic and pattern recognition techniques to examine food quality both internally and externally as it cooks in an industrial oven

M. O'Farrell; E. Lewis; C. Flanagan; W. B. Lyons; N. Jackman

doi:10.1117/12.566671

Employing spectroscopic and pattern recognition techniques to examine food quality both internally and externally as it cooks in an industrial oven

M. O'Farrell
, E. Lewis
, C. Flanagan
, W. B. Lyons
, N. Jackman

University of Limerick
Food Design Applications Ltd.

Research output: Contribution to journal › Conference article › peer-review

Abstract

An Optical fibre based sensor system has been developed for the purpose of examining the colour of food products online as they cook in a large-scale industrial oven. By classifying the colour of each cooking stage it is possible to automatically determine if the food is cooked to an optimum perceived colour. Developments have been made on previous work by the authors [1] by further examining the internal colour of the food and testing the repeatability of the system. Spectroscopic techniques are employed to determine the colour and this signal is interrogated using an Artificial Neural Network.

Original language	English
Pages (from-to)	313-316
Number of pages	4
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	5502
DOIs	https://doi.org/10.1117/12.566671
Publication status	Published - 2004
Event	Second European Workshop on Optical Fibre Sensors, EWOFS'04 - Santander, Spain Duration: 9 Jun 2004 → 11 Jun 2004

Keywords

Artificial Neural Network
Back Propagation Learning
Colour Classification
Feed Forward Networks
Food Processing Industry
Optical Fibre Sensor
Pattern Recognition
Process Control
Spectroscopy

Access to Document

10.1117/12.566671

Cite this

@article{b950165942aa4fb4ba58d5d71807f970,

title = "Employing spectroscopic and pattern recognition techniques to examine food quality both internally and externally as it cooks in an industrial oven",

abstract = "An Optical fibre based sensor system has been developed for the purpose of examining the colour of food products online as they cook in a large-scale industrial oven. By classifying the colour of each cooking stage it is possible to automatically determine if the food is cooked to an optimum perceived colour. Developments have been made on previous work by the authors [1] by further examining the internal colour of the food and testing the repeatability of the system. Spectroscopic techniques are employed to determine the colour and this signal is interrogated using an Artificial Neural Network.",

keywords = "Artificial Neural Network, Back Propagation Learning, Colour Classification, Feed Forward Networks, Food Processing Industry, Optical Fibre Sensor, Pattern Recognition, Process Control, Spectroscopy",

author = "M. O'Farrell and E. Lewis and C. Flanagan and Lyons, \{W. B.\} and N. Jackman",

year = "2004",

doi = "10.1117/12.566671",

language = "English",

volume = "5502",

pages = "313--316",

journal = "Proceedings of SPIE - The International Society for Optical Engineering",

issn = "0277-786X",

note = "Second European Workshop on Optical Fibre Sensors, EWOFS'04 ; Conference date: 09-06-2004 Through 11-06-2004",

}

Employing spectroscopic and pattern recognition techniques to examine food quality both internally and externally as it cooks in an industrial oven. / O'Farrell, M.; Lewis, E.; Flanagan, C. et al.
In: Proceedings of SPIE - The International Society for Optical Engineering, Vol. 5502, 2004, p. 313-316.

Research output: Contribution to journal › Conference article › peer-review

TY - JOUR

T1 - Employing spectroscopic and pattern recognition techniques to examine food quality both internally and externally as it cooks in an industrial oven

AU - O'Farrell, M.

AU - Lewis, E.

AU - Flanagan, C.

AU - Lyons, W. B.

AU - Jackman, N.

PY - 2004

Y1 - 2004

N2 - An Optical fibre based sensor system has been developed for the purpose of examining the colour of food products online as they cook in a large-scale industrial oven. By classifying the colour of each cooking stage it is possible to automatically determine if the food is cooked to an optimum perceived colour. Developments have been made on previous work by the authors [1] by further examining the internal colour of the food and testing the repeatability of the system. Spectroscopic techniques are employed to determine the colour and this signal is interrogated using an Artificial Neural Network.

AB - An Optical fibre based sensor system has been developed for the purpose of examining the colour of food products online as they cook in a large-scale industrial oven. By classifying the colour of each cooking stage it is possible to automatically determine if the food is cooked to an optimum perceived colour. Developments have been made on previous work by the authors [1] by further examining the internal colour of the food and testing the repeatability of the system. Spectroscopic techniques are employed to determine the colour and this signal is interrogated using an Artificial Neural Network.

KW - Artificial Neural Network

KW - Back Propagation Learning

KW - Colour Classification

KW - Feed Forward Networks

KW - Food Processing Industry

KW - Optical Fibre Sensor

KW - Pattern Recognition

KW - Process Control

KW - Spectroscopy

UR - https://www.scopus.com/pages/publications/5544284888

U2 - 10.1117/12.566671

DO - 10.1117/12.566671

M3 - Conference article

AN - SCOPUS:5544284888

SN - 0277-786X

VL - 5502

SP - 313

EP - 316

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Second European Workshop on Optical Fibre Sensors, EWOFS'04

Y2 - 9 June 2004 through 11 June 2004

ER -

Employing spectroscopic and pattern recognition techniques to examine food quality both internally and externally as it cooks in an industrial oven

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this