The use of fuzzy logic table look-up scheme for modeling of glucose release from wheat starches

Document Type : Research Article

Authors

1 Associate Professor, Department of Chemical Engineering, Faculty of Engineering, University of Bonab , Bonab, Iran

2 Department of Chemical Engineering, Faculty of Engineering, University of Bonab

3 Department of Textile Engineering, Faculty of Engineering, University of Bonab

4 Professor in food physics and Engineering in Department of Food Science& Technology , Agriculture Faculty , Ferdowsi University of Mashhad, Iran

Abstract

In this study phosphorylated and hydroxypropylated wheat starches were produced with 0.096 and 2.106% degree of substitution, respectively. The gel samples of the starches were prepared with concentrations of 8% and 12% at volumes of 7.5 and 15 ml. The gel samples were subjected under digestion process at simulated mouth and gastrointestinal conditions. The results showed that about 80% of the final glucose release from the starch samples were obtained within the first 15 min of digestion at the simulated intestinal condition. The amounts of glucose release for phosphorylated starch were approximately 6-11%, and for hydroxypropylated starch were 16-19% lower than that for native wheat starch after digestion at this condition. Fuzzy logic table look-up scheme was used in order to model the amount of glucose release from the starch samples. The fuzzy inputs (volume, concentration and the digestion time under the simulated intestinal condition) for each sample comprised of respectively 3, 3 and 13 fuzzy sets with triangular membership functions. Moreover, the amount of glucose release with 34 fuzzy sets and triangular membership function was considered as the output of fuzzy modeling system. In this research, the Mamdani’s inference system was used to conduct fuzzy set operations and the minimum T-norm operator and the center of gravity defuzzifier were used to produce each fuzzy rule. The results obtained from the fuzzy logic table look-up scheme modeling system demonstrated high proficiency (R2 = 0.991-0.995) of that for estimation of the amount of glucose release from the wheat starch samples at the simulated intestinal conditions.

Graphical Abstract

The use of fuzzy logic table look-up scheme for modeling of glucose release from wheat starches

Highlights

  • A simulated gastrointestinal digestion system was used.
  • Major release of glucose was observed under the intestinal digestion conditions.
  • Hydroxypropylated starch showed the lowest amount of glucose release.
  • Fuzzy logic table look-up scheme had high efficiency for prediction of glucose release under the intestinal digestion conditions.

Keywords

Main Subjects

References

[1]. Singh, J., Dartois, A., & Kaur, L. (2010). Starch digestibility in food matrix: a review. Trends  Food Sci. Technol., 21(4), 168–180.
[2]. Bordoloi, A., Singh, J., & Kaur, L. (2012). In vitro digestibility of starch in cooked potatoes as affected by guar gum: microstructural and rheological characteristics. Food Chem., 133(4), 1206–1213.
[3]. Dartois, A., Singh, J., Kaur, L., & Singh, H.  (2010). Influence of guar gum on the in vitro starch digestibility-rheological and microstructural characteristics. Food Biophys., 5(3), 149–160.
[4]. Singh, J., Kaur, L., & McCarthy, O. (2007). Factors influencing the physico-chemical, morphological, thermal and rheological properties of some chemically modified starches for food applications—a review. Food Hydrocoll., 21(1), 1–22.
[5]. Yousefi, A., & Razavi, S.M.A. (2015). Dynamic rheological properties of wheat starch gels as affected by chemical modification and concentration. Starch-Stärke, 67(7-8), 567–576.
[6]. Yousefi, A., Razavi, & S.M.A. (2015). Steady shear flow behavior and thixotropy of wheat starch gel:  impact of chemical modification, concentration and saliva addition. J. Food Process Eng., 39(1), 31–43.
[7]. Han, J.-A., & BeMiller, J.N. (2007). Preparation and physical characteristics of slowly digesting modified food starches. Carbohydr. Polym., 67(3), 366–374.
[8]. Wolf, B.W., Bauer, L.L, & Fahey, G.C. (1999). Effects of chemical modification on in vitro rate and extent of food starch digestion: an attempt to discover a slowly digested starch. J. Agric. Food Chem., (47), 4178–4183.
[9]. Koo, S.H., Lee, K.Y., Lee, H.G. (2010). Effect of cross-linking on the physicochemical and physiological properties of corn starch. Food Hydrocoll., 24(6), 619–625.
[10]. Chung, H.-J., Shin, D.-H., & Lim, S.-T. (2008). In vitro starch digestibility and estimated glycemic index of chemically modified corn starches. Food Res. Int. 41(6), 579–585.
[11]. Nguyen, G. T., & Sopade, P. A. (2018). Modeling starch digestograms: Computational characteristics of kinetic models for in vitro starch digestion in food research. Compr. Rev. Food Sci. Food Saf., 17(5), 1422-1445.
[12].  Das, A., Ben-Menachem, T., Farooq, F.T., Cooper, G.S., Chak, A., Sivak, M.V., & Wong, R.C. (2008). Artificial neural network as a predictive instrument in patients with acute nonvariceal upper gastrointestinal hemorrhage. Gastroenterology,134, 65–74.
[13]. Song, W., & Wu, Y. (2017). Application of Fuzzy Neural Network in Diagnosis of Gastrointestinal System Diseases. Adv. Eng. Res., 130, 1454-1458.
[14]. Al-Kasasbeh, R., Korenevskiy, N., Alshamasin, M., Ionescou, F., & Smith, A. (2013). Prediction of gastric ulcers based on the change in electrical resistance of acupuncture points using fuzzy logic decision-making. Comput. Methods Biomech. Biomed. Engin., 16(3), 302-313.
[15]. Maldonado-Valderrama, J., Terriza, J. H., Torcello-Gómez, A., & Cabrerizo-Vilchez, M. A. (2013). In vitro digestion of interfacial protein structures. Soft Matter, 9(4), 1043-1053.
[16] Olawoye, B., Fagbohun, O. F., Gbadamosi, S. O., & Akanbi, C. T. (2020). Succinylation improves the slowly digestible starch fraction of cardaba banana starch. A process parameter optimization study. Artif. Intell. Agric., 4, 219-228.
[17] Olawoye, B., Gbadamosi, S. O., Otemuyiwa, I. O., & Akanbi, C. T. (2020). Improving the resistant starch in succinate anhydride‐modified cardaba banana starch: A chemometrics approach. J. Food Process. Preserv., 44(9), e14686.
[18]. Johnson, D.P. (1969). Spectrophotometric determination of the hydroxypropyl group in starch ethers. Anal. Chem., 41, 859–860.
[19]. Jackson, M.L. (1967). Soil Chemical Analysis, Ed. M.L. Jackson, Prentice Hall of India, Pvt. Ltd, New Delhi, 151-154.
[20]. Yousefi, A., & Razavi, S.M.A. (2016). Steady shear flow behavior and thixotropy of wheat starch gel: Impact of chemical modification, concentration and saliva addition. J. Food Process Eng., 39(1), 31-43.
[21]. Wang, L.X. (1997). A course in fuzzy systems and control. Prentice-hall international, Inc, 153-167.
[22]. Hung, P.V., & Morita, N. (2005). Physicochemical properties of hydroxypropylated and cross-linked starches from A-type and B-type wheat starch granules. Carbohydr. Polym., 59, 239-246.
[23]. Sang, Y., Seib, P.A., Herrera, A.I., Prakash, O., & Shi, Y.C. (2010). Effects of alkaline treatment on the structure of phosphorylated wheat starch and its digestibility. Food Chem., 118, 323-327.
[24]. Sanz, T., & Luyten, H. (2006). Release, partitioning and stability of isoflavones from enriched custards during mouth, stomach and intestine in vitro simulations. Food Hydrocoll., 20, 892-900.
[25]. Ioannou, I., Perrot, N., Curt, C., Mauris, G., & Trystram, G. (2004). Development of a control system using the fuzzy set theory applied to a browning process–a fuzzy symbolic approach for the measurement of product browning: development of a diagnosis model–part I. J. Food Eng., 64, 497-506.
[26]. Vaquiro, H.A., Bon, J., & Diez, J. L. (2008). Fuzzy logic application to drying kinetics modeling. 17th IFAC World Congress, COEX, Korea, South, 2206-2211.
[27]. Khodabakhshaghdam, S., Yousefi, A., Mohebbi, M., Razavi, S.M.A., Orooji, A., & Akbarzadeh-Totonchi, M.R. (2015). Modeling for drying kinetics of papaya fruit using fuzzy logic table look-up scheme. Int. Food Res. J., 22(3), 1234-1239.
Innovative Food Technologies
Volume 9, Issue 3
May 2022
Pages 255-268

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History

  • Receive Date: 18 January 2022
  • Revise Date: 22 March 2022
  • Accept Date: 29 March 2022

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