Autors: Jukić M., Koceva Komlenić D., Mastanjević K., Mastanjević K., Lučan M., Popovici C., Nakov, G. N., Lukinac J.
Title: Influence of damaged starch on the quality parameters of wheat dough and bread
Keywords: Starch Dough Bread Rheology Gelatinisation

Abstract: A certain degree of damage to the starch granules is desirable but excessive level of starch damage can have deteriorating effect on the quality of the bakery products. The wheat flour with lower (3.15%) and higher degree of starch damage (6.13%) were produced by repeat grinding (two passes) in a laboratory mill. The rheological measurements of dough samples were conducted using Farinograph and Extensograph, and gelatinisation and pasting properties – differential scanning calorimetry and Micro Visco-Amylo-Graph. Texture profile analysis of bread samples were performed using a texture analyser, and specific volume by laser topography method.

References

    Issue

    , vol. 8, issue 3, pp. 512-521, 2019, Ukraine, Ukrainian Food Journal, DOI 10.24263/2304- 974X-2019-8-3-8

    Full text of the publication

    Цитирания (Citation/s):
    1. Rasheed M., Fan X., Guo B., Jiang J., Li M., Zhang Y., Zhang B., Cui Y., Unveiling the dynamic interactions of gluten–starch–water in frozen dough: An in-depth review, 2025, Comprehensive Reviews in Food Science and Food Safety, issue 2, vol. 24, DOI 10.1111/1541-4337.70120, eissn 15414337 - 2025 - в издания, индексирани в Scopus
    2. Quinte L., Valderrama I., Best I., Evaluation of the Effect of Improvers: Psyllium and Xanthan Gum in Bread Loaf with Partial Replacement of Quinoa Flour, 2025, Foods, issue 3, vol. 14, DOI 10.3390/foods14030418, eissn 23048158 - 2025 - в издания, индексирани в Scopus
    3. Lee E., Han H., Kweon M., Suitability of Whole-Wheat Flours Milled Using Different Mills and Conditions for Dough- and Batter-Based Sweet Goods, 2025, Journal of Food Science, issue 6, vol. 90, DOI 10.1111/1750-3841.70311, issn 00221147, eissn 17503841 - 2025 - в издания, индексирани в Scopus
    4. Zhou H., Zhang J., Zhou Q., Wang X., Min H., Qin B., Liang S., Wang X., Zhong Y., Cai J., Huang M., Li Q., Jiang D., Chen J., A 3D point cloud and deep learning based automated process for quantifying multi-scale phenotypes in sliced bread, 2025, Food Research International, issue 0, vol. 217, DOI 10.1016/j.foodres.2025.116865, issn 09639969, eissn 18737145 - 2025 - в издания, индексирани в Scopus

    Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus