The effect of quinoa flour on wheat bread properties using fractal dimention based texture analysis of digital images

Document Type : Complete scientific research article

Authors

1 Associate Professor, Department of Food Sciences and Technology, Ferdowsi University of Mashhad (FUM)

2 PhD candidate, Department of Food Sciences and Technology, Ferdowsi University of Mashhad (FUM)

Abstract

Wheat bread is the main source of food world eide. Currently, cereal grains and their products are known as a very good source of dietary fibers. One of the suitable solutions to improve the characteristics of bread is to use different sources of alternative fiber, such as pseudo-cereals loke quinoa. Quinoa with the scientific name (Chenopodium quinoa Willd) is a dicotyledonous plant and belongs to the Chenopodaceae family. This pseudo-cereal contains 16 essential and non-essential amino acids. For this reason, it is considered by the World Food and Agriculture Organization (FAO) as a functional food. . In this research, the effect of quinoa flour in levels of 25%, 50%, 75% and 100% with wheat flour in formulation of bread in presense and absence of improvers is investigated. color parameters, image texture (including: energy, entropy, contrast and homogeneity) , tortuosity, the microstructure of the bread core (including: the total number of holes, the size of the holes and the total surface of the holes) and the porosity of the bread core tissue were investigated. The results of this research showed that increase in the percentage of quinoa flour, lead to increase in the parameter L* (brightness level) and a* of the samples, while b* decreased. Results also show that By increasing the percentage of quinoa flour, the energy, entropy and homogeneity of the samples increased, while the amount of contrast and tortuosity of the samples decreased. The total number of and the size of the holes, the total area of the holes and the porosity of the samples increased. These parameters increased with the increase of quinoa flour up to 50%, while in the 75% and 100% Quinoa flour in formuation caused decrease in the parameters parameter. The porous in 75% and 100% quinoa flour samples were more circular and also had a smaller size than the holes in the other samples. According to the results of this research, it can be said that due to the irregular and complex morphological structure of bread, it is possible to use Fractal dimension to investigate the effects of processes and compounds, and also image texture analysis is well able to express texture changes. The core and prousity are the results of different formulations and considering the textural parameters including contrast, homogeneity, entropy and energy, these changes can be observed noticeably. Based on the results, it was found that the sample containing 50% quinoa flour with improver showed better textural characteristics

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References

  1. Dewettinck, K., Van Bockstaele, F., Kühne, B.., Van de Walle, D., Courtens, T. M. & Gellynck, X. (2008). Nutritional value of bread: Influence of processing, food interaction and consumer perception. J Cereal Sci, vol. 48, no. 2, pp. 243–257.
  2. Hidalgo, A. & Brandolini, A. (2014). Bread: Bread from Wheat Flour,” in Encyclopedia of Food Microbiology, vol 1., Elsevier Ltd, Academic Press, pp. 303–308.Dallagnol, A. M., Pescuma, M. , De Valdez, G. F. & Rollán, G. (2013). Fermentation of quinoa and wheat slurries by Lactobacillus plantarum CRL 778: proteolytic activity, Appl Microbiol Biotechnol, vol. 97, pp. 3129–3140.Świeca, M. , Sęczyk, Ł., Gawlik-Dziki, U. & Dziki, D. (2014). Bread enriched with quinoa leaves–The influence of protein–phenolics interactions on the nutritional and antioxidant quality, Food Chem, vol. 162, pp. 54–62.Oelke, E. A., Putnam, D. H., Teynor, T. M. & Oplinger, E. S. (1992). Alternative Field Crops Manual, uinoa, University of Wisconsin Extension, Cooperative Extension. http:\\www. hort. purdue. edu\newcrop\afcm\quinoa.
  3. James, L. E. A. (2009). Quinoa (Chenopodium quinoa Willd.): composition, chemistry, nutritional, and functional properties, Adv Food Nutr Res, vol. 58, pp. 1–31.Nsimba, R. Y. , Kikuzaki, H. & Konishi, Y. (2008). Antioxidant activity of various extracts and fractions of Chenopodium quinoa and Amaranthus spp. seeds, Food Chem, vol. 106, no. 2, pp. 760–766.Caperuto, L. C., Amaya‐Farfan, J. & Camargo, C. R. O. (2001). Performance of quinoa (Chenopodium quinoa Willd) flour in the manufacture of gluten‐free spaghetti, J Sci Food Agric, vol. 81, no. 1, pp. 95–101.Iglesias-Puig, E., Monedero, V. & Haros, M. (2015). Bread with whole quinoa flour and bifidobacterial phytases increases dietary mineral intake and bioavailability, LWT-Food Science and Technology, vol. 60, no. 1, pp. 71–77.Milovanović, M. M. , Demin, M., Vučelić-Radović, B., Žarković, B. & Stikić, R. (2014). Evaluation of the nutritional quality of wheat bread prepared with quinoa, buckwheat and pumpkin seed blends, Journal of Agricultural Sciences (Belgrade), vol. 59, no. 3, pp. 318–328.Föste M. et al. (2014). Impact of quinoa bran on gluten-free dough and bread characteristics, European Food Research and Technology, vol. 239, pp. 767–775.KrUpa-KozaK, U., Wronkowska, M. & Soral-ŚMietaNa, M. (2011). Effect of buckwheat flour on microelements and proteins contents in gluten-free bread, Czech Journal of Food Sciences, vol. 29, no. 2, pp. 103–108.Mendoza, F., Dejmek, P. & Aguilera, J. M. (2007). Colour and image texture analysis in classification of commercial potato chips, Food Research International, vol. 40, no. 9, pp. 1146–1154.Naji-Tabasi, S. & Mohebbi, M. (2015). Evaluation of cress seed gum and xanthan gum effect on macrostructure properties of gluten-free bread by image processing, Journal of Food Measurement and characterization, vol. 9, pp. 110–119.
  4. Wang, S., Opassathavorn, A. & Zhu, F. (2015). Influence of Quinoa Flour on Quality Characteristics of Cookie, Bread and Chinese Steamed Bread, J Texture Stud, vol. 46, no. 4, pp. 281–292, Aug. 2015, doi: 10.1111/jtxs.12128.Kvaal, K., Wold, J. P., Indahl, U. G., Baardseth, P. & Næs, T. (1998). Multivariate feature extraction from textural images of bread, Chemometrics and intelligent laboratory systems, vol. 42, no. 1–2, pp. 141–158.Ribotta, P. D., Pérez, G. T., Añón, M. C. & León, A. E. (2010). Optimization of additive combination for improved soy–wheat bread quality, Food Bioproc Tech, vol. 3, pp. 395–405.Santacruz-Vázquez, C. , Santacruz-Vázquez, V. , Chanona-Perez, J., Jaramillo-Flores, M. E., Welti-Chanes, J. & Gutierrez-Lopez, G. (2007). Fractal theory applied to food science, in Encyclopedia of agricultural, food, and biological engineering, Taylor & Francis London, pp. 1–13.Wu, D.¸ Yang, H., Chen, X., He, Y. & Li, X. (2008). Application of image texture for the sorting of tea categories using multi-spectral imaging technique and support vector machine, J Food Eng, vol. 88, no. 4, pp. 474–483.Gonzalez, R. C. (2009). Digital image processing. Pearson education india.PEDRESCHI, F., AGUILERA, J. M. & BROWN, C. A. (2000). Characterization of food surfaces using scale‐sensitive fractal analysis, J Food Process Eng, vol. 23, no. 2, pp. 127–143.Pérez-Nieto, A., Chanona-Perez, J. J., Farrera-Rebollo, R. R., Gutierrez-Lopez, G. F., Alamilla-Beltran, L. , & Calderon-Dominguez, G. (2010). Image analysis of structural changes in dough during baking, LWT-Food Science and Technology, vol. 43, no. 3, pp. 535–543.Yaseen, A. A., Shouk, A. A. & Ramadan, M. T. (2010). Corn-wheat pan bread quality as affected by hydrocolloids, Journal of American Science, vol. 6, no. 10, pp. 684–690.Park, B., Lawrence, K. C., Windham, W. R., Chen, Y.R. & Chao, K. (2002). Discriminant analysis of dual-wavelength spectral images for classifying poultry carcasses, Comput Electron Agric, vol. 33, no. 3, pp. 219–231.Gonzalez, R. C. (2009). Digital image processing. Pearson education india.Upadhyay, R., Ghosal, D. & Mehra, A. (2012). Characterization of bread dough: Rheological properties and microstructure, J Food Eng, vol. 109, no. 1, pp. 104–113.Peleg, M. & Normand, M. D. (1985). Characterization of the ruggedness of instant coffee particle shape by natural fractals, J Food Sci, vol. 50, no. 3, pp. 829–831.BARLElTA B. J. & BARBOSA‐CÁOVAS, G. V. (1993). Fractal Analysis to Characterize Ruggedness Changes in Tapped Agglomerated Food Powders, J Food Sci, vol. 58, no. 5, pp. 1030–1035, 1993, doi: 10.1111/J.1365-2621.1993.TB06105.X.Rahman, M. S. (1997). Physical meaning and interpretation of fractal dimensions of fine particles measured by different methods, J Food Eng, vol. 32, no. 4, pp. 447–456.Chanona, P. J. J., Alamilla, B. L., Farrera, R. R. R., Quevedo, R. , Aguilera, J. M. & Gutiérrez, L. G. F. (2003). Description of the convective air-drying of a food model by means of the fractal theory, Food Science and Technology International, vol. 9, no. 3, pp. 207–213, Jun. 2003, doi: 10.1177/1082013203035100.Kerdpiboon S. & Devahastin, S. (2007). Fractal characterization of some physical properties of a food product under various drying conditions, Drying Technology, vol. 25, no. 1, pp. 135–146.Farrera-Rebollo, R. R., de la Salgado-Cruz, M. P., Chanona-Pérez, J., Gutiérrez-López, G. F., Alamilla-Beltrán, L. & Calderón-Domínguez, G. (2012). Evaluation of Image Analysis Tools for Characterization of Sweet Bread Crumb Structure, Food Bioproc Tech, vol. 5, no. 2, pp. 474–484, Feb. 2012, doi: 10.1007/s11947-011-0513-y. Armero E. & Collar, C. (1996). Antistaling additives, flour type and sourdough process effects on functionality of wheat doughs, J Food Sci, vol. 61, no. 2, pp. 299–303.
Food Processing and Preservation Journal
Volume 16, Issue 1
April 2024
Pages 81-98

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