# Preventing the waste of animal source foods by predicting the kinetics of oxidation reactions

Jason Sicard, Alain Kondjoyan

► To cite this version:

Jason Sicard, Alain Kondjoyan. Preventing the waste of animal source foods by predicting the kinetics of oxidation reactions: Reaction-diffusion modelling of a 44-reactions chemical scheme. EFFoST International Conference 2022, Nov 2022, Dublin, Ireland. hal-03940969

HAL Id: hal-03940969

https://hal.inrae.fr/hal-03940969

Submitted on 16 Jan 2023

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# Preventing the waste of animal source foods by predicting the kinetics of oxidation reactions

Reaction-diffusion modelling of a 44-reactions chemical scheme.

Jason Sicard, Alain Kondjoyan

## BACKGROUND

<figure><img src="image_4.png" /></figure>

Carbon footprint
of meat

<figure><img src="image_5.png" /></figure>

Consumers reject
brown-colour meat

<figure><img src="image_6.png" /></figure>

Myoglobin
influences colour

<figure><img src="image_7.png" /><figcaption>Deoxy-</figcaption></figure>

Modified Atmosphere
Packaging

## OBJECTIVE

<figure><img src="image_8.png" /></figure>

PREVISION OF
MYOGLOBIN
CHEMICAL STATE

## MATERIAL AND METHOD

### 3 groups of reactions

* Myoglobin oxidation reactions

### $O_2$

* mitochondrial respiration

* production of hydrogen peroxide by glycolysis

### Fe

* Fenton reactions (non-heme iron)

### Ao

* Water-soluble antioxidants reactions

<figure><img src="image_9.png" /></figure>

resolution of **diffusion** (finite-difference)
and **reactions** (ordinary differential equations)

$$ \frac{d[C_i]}{dt} = \sum_{j=1}^{N} a_{ij} k_j \left( \prod_{i \in [1, M], a_{ij} < 0} [C_i]^{-a_{ij}} \right) $$

<figure><img src="image_10.png" /></figure>

?

Sensitivity analysis
(homogeneous $O_2$)

* Simplified reaction scheme

Rate constants literature

<figure><img src="image_11.png" /></figure>

Diffusion of $O_2$

* Reaction-diffusion model

<figure><img src="image_12.png" /></figure>

Optimization

* Consolidated rate-constant values

<figure><img src="image_13.png" /></figure>

Validation with experimental in-depth myoglobin profiles on longissimus lumborum muscle

Ex. impact of the rate constant of the oxidation of deoxymyoglobin reaction

$$ MbFe^{2+} + O_2 \rightarrow MbFe^{2+}O_2 $$

MbO₂, 4h (20°C)

<figure><img src="image_14.png" /></figure>

MMb, 4h (20°C)

<figure><img src="image_15.png" /></figure>

## RESULTS

* Water-soluble antioxidants offset the effect of Fenton chemistry on the shape of $MbO_2$ and MMb profiles.

* MAP extends the shelf-life of meat by increasing both $CO_2$ and $O_2$ to preserve the bright red colour. However, high oxygen also increases both the intensity and width of subsurface browning, eventually leading to a bright red surface covering a thick brown meat.

<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>

reactions
optimized*
scheme

## DISCUSSION

* This model allows for the identification of conditions leading to colour instability or other phenomena sometimes observed in practice when using MAP.

* The influence of a change in environmental conditions on microorganisms and microorganisms' influence on colour and safety also need to be considered.

* Supplemental comparison data is needed to evaluate the activation energy of reactions. (see 2nd ref.)

* Multi-compartments modelling would be required to go further, notably to account for marbling fat particles and the reactions that take place in them.

* This methodological approach successfully represented a complex scheme of reactions involved in the variation of surface quality of a solid food and is **applicable to other foods!**

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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
M : jason.sicard@inrae.fr

www.clermont.inrae.fr/quapa

## References:

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.

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.

<footnote>*to provide the same results as the complete scheme for the targeted compounds (myoglobin states, oxygen and hydrogen peroxide)</footnote>