# Use of sensors and in silico models for the prediction of meat colour

Jason Sicard, Alain Kondjoyan, Fabrice Audonnet, Valérie Scislowski

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To cite this version:

Jason Sicard, Alain Kondjoyan, Fabrice Audonnet, Valérie Scislowski. Use of sensors and in silico models for the prediction of meat colour: Tools to reduce meat wastage. EFFoST International Conference 2022, Nov 2022, Dublin, Ireland. hal-03940995

HAL Id: hal-03940995

https://hal.inrae.fr/hal-03940995

Submitted on 16 Jan 2023

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Distributed under a Creative Commons Attribution 4.0 International License
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RÉPUBLIQUE
FRANÇAISE

Liberté
Égalité
Fraternité

INRAE

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viande performances

ADIV

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За Україну
INSTITUT
PASCAL

sciences de l'ingénierie et des systèmes

## Affiliations

INRAE

Jason SICARD
Alain KONDJOYAN

Institut Pascal

Fabrice AUDONNET

ADIV

Valérie SCISLOWSKI

## Context

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What I find scandalous is neither the poor nor the rich, but the amount of waste. (Mother Theresa)

20%

Over 20% of the meat produced globally is lost or wasted. (FAO)

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Consumers preferences for beef colour and packaging influence likelihood to purchase, but do not bias eating satisfaction (cooked). (Carpenter et al. 2001)

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# Use of sensors and in silico models for the prediction of meat colour

## Tools to reduce meat wastage

## Material and Methods

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## Results

* ✓ In meat juice, ORP measured by sensor is tightly correlated to a*.

* ✓ Mechanistic models predict the evolution of myoglobin in meat.

* ✓ Redness estimated from the fraction of oxymyoglobin.

* ✓ Ageing time and cutting direction are less impactful.

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## Conclusion

* ✓ Meat colour evolution due to oxidation is predictable; models can assist in the design of innovative and more sustainable food products.

## Perspectives

* ✓ Validation of the ORP/colour relation for meat contaminated by microorganisms.

* ✓ Diffusion-reaction model application to lamb, pork or fishes rich in myoglobin.

* ✓ Extension to off-flavours.

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Centre
Clermont Auvergne-Rhône-Alpes

UR0370 QuaPA
INRAE Site de Theix
63122 Saint-Genès-Champanelle
FRANCE

Tél. : + 33 (0)4 73 62 42 25

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jason.sicard@inrae.fr

www.clermont.inrae.fr/quapa

## References:

Kondjoyan, A.; Sicard, J.; Cucci, P.; Audonnet, F.; Elhayel, H.; Lebert, A.; Scislowski, V. Predicting the Oxidative Degradation of Raw Beef Meat during Cold Storage Using Numerical Simulations and Sensors—Prospects for Meat and Fish Foods. *Foods* **2022**, *11*, 1139, doi:**10.3390/foods11081139**.

Kondjoyan, A.; Sicard, J.; Badaroux, M.; Gatellier, P. Kinetics Analysis of the Reactions Responsible for Myoglobin Chemical State in Meat Using an Advanced Reaction–Diffusion Model. *Meat Science* **2022**, *191*, 108866, doi:**10.1016/j.meatsci.2022.108866**.