Cooked pork sausage processing with different levels of coriander essential oil and sodium nitrite - ann modelling
2018
Ikonić, Bojana (https://orcid.org/0000-0003-4053-9193) | Šojić, Branislav (https://orcid.org/0000-0001-7909-8917) | Ikonić, Predrag | Pavlić, Branimir (https://orcid.org/0000-0002-3551-7478) | Tomović, Vladimir (https://orcid.org/0000-0001-5055-1781) | Jokanović, Marija (https://orcid.org/0000-0002-1282-175X) | Škaljac, Snežana (https://orcid.org/0000-0002-9102-8417)
Artificial neural networks (ANNs) have been used as a modelling tool in several food processing applications. The main advantage of ANNs is the ability to estimate any linear or nonlinear function, without the need for prior transformations. The aim of this work was to determine the relative importance of coriander (Coriandrum sativum L.) essential oil, sodium nitrite and storage time on colour, oxidative and microbial stability of cooked pork sausages using artificial neural network. Results suggest that artificial neural networks are good prediction tool for selected network outputs. According to high values of coefficient of determination, experimental results are in very good agreement with computed ones (R2>0.99, for all observed outputs). Mathematical models, generated by ANNs, were employed to optimize process parameters in order to use less sodium nitrite and, in the same time, to keep the same quality and safety of this type of sausage. Obtained results showed that partial substitution of nitrites (40% reduction) with coriander essential oil (approx. 0.12 µL/g) enable the extension of storage time (around 50 days), providing negligible lipid oxidative changes (TBARS approx. 0.12 mg MDA/kg), acceptable microbial growth (TPC approx. 2.5 log CFU/g) and desirable red color (a* approx. 11.1).
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