An Artificial Neural Network Model for Chilling Environment Control in Meat Production

Apirachai Wongsriworaphon; Arthit Apichottanakul; Teerawat Laonapakul; Supachai Pathumnakul

doi:10.4028/www.scientific.net/AMM.781.479

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 781An Artificial Neural Network Model for Chilling...

An Artificial Neural Network Model for Chilling Environment Control in Meat Production

Abstract:

In this study, artificial neural network with a supervised learning algorithm called vector-quantized temporal associative memory (VQTAM) is proposed to estimate chilled weight loss during chilling process of pig slaughtering plant. Four models based on carcass weights are developed. The results show that the proposed algorithms can accurately predict chilled weight loss with an error rate of less than 5% on average. The models are also employed to determine the suitable chilling times for each weight class.

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Periodical:

Applied Mechanics and Materials (Volume 781)

Pages:

479-482

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.781.479

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Online since:

August 2015

Authors:

Apirachai Wongsriworaphon, Arthit Apichottanakul, Teerawat Laonapakul, Supachai Pathumnakul*

Keywords:

Artificial Neural Network (ANN), Chilled Weight Loss, Pig, VQTAM

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References

[1] Savell, J. W., Mueller, S. L., & Baird, B. E. (2005). The chilling of carcasses. Meat Science, 70(3), 449–459.

DOI: 10.1016/j.meatsci.2004.06.027

Google Scholar

[2] Rosenvold, K., Andersen, H.J. (2003). Factors of significance for pork quality—a review Meat Science, 64, 219–237.

DOI: 10.1016/s0309-1740(02)00186-9

Google Scholar

[3] Long, V. P., & Tarrant, P. V. (1990). The effect of pre-slaughter showering and Postslaughter rapid chilling on meat quality in intact pork sides. Meat Science, 27(3), 181–195.

DOI: 10.1016/0309-1740(90)90050-g

Google Scholar

[4] Jones, S. D. M., Jeremiah, L. E., & Robertson, W. M. (1993). The effect of spray and blast-chilling on carcass shrinkage and pork muscle quality. Meat Science, 34(3), 351–362.

DOI: 10.1016/0309-1740(93)90083-t

Google Scholar

[5] Barreto, G. & Araujo, A. (2004). Identification and control of dynamical systems using the self-organizing map. IEEE Transactions on Neural Networks, 15(5), 1244-1259.

DOI: 10.1109/tnn.2004.832825

Google Scholar