Physicochemical Changes of the Gluten-Free Rice-Buckwheat Cookies during Storage – Artificial Neural Network Model

Authors

  • Mladenka Pestorić
    Affiliation
    Research Center for Technology of Plant Based Food Products, Institute of Food Technology, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
  • Marijana Sakač
    Affiliation
    Research Center for Technology of Plant Based Food Products, Institute of Food Technology, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
  • Lato Pezo
    Affiliation
    Engineering Department, Institute of General and Physical Chemistry, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia
  • Dubravka Škrobot
    Affiliation
    Research Center for Technology of Plant Based Food Products, Institute of Food Technology, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
  • Nataša Nedeljković
    Affiliation
    Research Center for Technology of Plant Based Food Products, Institute of Food Technology, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
  • Pavle Jovanov
    Affiliation
    Research Center for Technology of Plant Based Food Products, Institute of Food Technology, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
  • Bojana Filipčev
    Affiliation
    Research Center for Technology of Plant Based Food Products, Institute of Food Technology, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
  • Anamarija Mandić
    Affiliation
    Research Center for Technology of Plant Based Food Products, Institute of Food Technology, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
https://doi.org/10.3311/PPch.13155

Abstract

The influence of storage time, temperature, and packaging on some physicochemical characteristics of gluten-free rice-buckwheat cookies was studied. Shelf life markers, such as water activity (aw), hydroxymethylfurfural (HMF), firmness, and color parameters were modelled in relation to different storage conditions. Principal component analysis was applied to study the similarity among samples according to the observed parameters. The mathematical model in the form of an artificial neural network was developed to predict the physicochemical parameters of cookies during 6-month storage. The most evident differentiation among samples was observed for color coordinate a*, aw , and HMF. Regarding the methods for determination of the parameters, priority should be given to the instrumental determination of color as the most convenient method. The processing of experimental data allowed the creation of useful mathematical model to be used in predicting the behavior of physicochemical changes of cookies by different factor combinations during storage.

Keywords:

gluten-free cookies, shelf life markers, mathematical model

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Published Online

2019-04-23

How to Cite

Pestorić, M., Sakač, M., Pezo, L., Škrobot, D., Nedeljković, N., Jovanov, P. “Physicochemical Changes of the Gluten-Free Rice-Buckwheat Cookies during Storage – Artificial Neural Network Model”, Periodica Polytechnica Chemical Engineering, 63(4), pp. 609–617, 2019. https://doi.org/10.3311/PPch.13155

Issue

Vol. 63 No. 4 (2019)

Section

Articles