Przeglądaj wg Autor "Baranowska, Hanna Maria"

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    Assessment of molecular dynamics in natural Shilajit using low-field NMR relaxometry for geographical traceability
    (De Gruyter, 2026-01-19) Kamgar, Elham; Baranowska, Hanna Maria; Kaykhaii, Massoud; Nowicki, Marcin; Kowalczewski, Przemysław Łukasz; Zembrzuska, Joanna
    Shilajit (Mumijo) is a phytomineral exudate known for its therapeutic potential, traditionally used in Ayurvedic medicine. Its molecular composition and consequently its therapeutic properties are influenced by geographical origin. Low-field nuclear magnetic resonance (LF NMR) offers a non-destructive tool to assess the molecular behavior of Shilajit rapidly and non-destructively. Twelve raw Shilajit samples from five regions (Iran, India, Nepal, Russia, and Kyrgyzstan) were analyzed using LF NMR at 15 MHz. Longitudinal magnetization relaxation (T1) and transverse magnetization relaxation (T2) relaxation times were measured using an inversion-recovery and Carr–Purcell– Meiboom–Gill pulse sequence, respectively. Three distinct relaxation behavior groups were identified. Group I showed only T1 (solid samples with undetectable T2), group II exhibited single T1 and T2 (moderately viscous, hydrated samples), while group III revealed biphasic T2 relaxation (indicating proton heterogeneity). Clear differences in relaxation profiles were observed across geographical origins, with Iranian samples showing the widest range of T1 values, while Russian and some Iranian samples exhibited dual T2 components. LF NMR relaxation parameters (T1, T2) are strongly dependent on the geographic origin and molecular structure of Shilajit. The technique shows promise for use in authentication and traceability of Shilajit, enabling differentiation based on relaxation signatures.
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    Molecular Properties of Starch–Water Interactions in the Presence of Bioactive Compounds from Barley and Buckwheat—LF NMR Preliminary Study
    (Licensee MDPI, Basel, Switzerland, 2025) Adamczyk, Greta; Masewicz, Łukasz; Przybył, Krzysztof; Zaryczniak, Aleksandra; Kowalczewski, Przemysław Łukasz; Beszterda-Buszczak, Monika; Cichocki, Wojciech; Baranowska, Hanna Maria
    The retrogradation of starch strongly influences the texture and stability of starchy foods. This study applied low-field nuclear magnetic resonance (LF NMR) to examine the effect of buckwheat hull (BH) fiber and green barley (GB) on water dynamics in normal (NPS) and waxy (WPS) potato starch gels. Relaxation times (T1, T2) and mean correlation times (τc) were monitored during 15 days of storage to evaluate changes in water mobility and starch–polymer interactions. Results showed that WPS, with its high amylopectin content, retrograded earlier than NPS. The addition of BH inhibited conformational changes associated with water binding in WPS gels, indicating that insoluble fiber entrapped water within the amylopectin network. Conversely, GB promoted higher τc values in WPS, reflecting enhanced ordering and reduced water mobility, while its impact on NPS was minor. In NPS systems, BH decreased τc, suggesting disruption of amylose-driven structural reorganization. These findings demonstrate that BH and GB exert opposite effects on starch retrogradation and highlight their potential as functional additives for tailoring texture and stability in starch-based food systems.
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    The application of convolutional neural networks, LF-NMR, and texture for microparticle analysis in assessing the quality of fruit powders: Case study – blackcurrant powders
    (De Gruyter, 2025) Przybył, Krzysztof; Samborska, Katarzyna; Jedlińska, Aleksandra; Koszela, Krzysztof; Baranowska, Hanna Maria; Masewicz, Łukasz; Kowalczewski, Przemysław Łukasz
    It can be observed that dynamic developments in artificial intelligence contributing to the evolution of existing techniques used in food research. Currently, innovative methods are being sought to support unit processes such as food drying, while at the same time monitoring quality and extending their shelf life. The development of innovative technology using convolutional neural networks (CNNs) to assess the quality of fruit powders seems highly desirable. This will translate into obtaining homogeneous batches of powders based on the specific morphological structure of the obtained microparticles. The research aims to apply convolutional networks to assess the quality, consistency, and homogeneity of blackcurrant powders supported by comparative physical methods of low-field nuclear magnetic resonance (LF-NMR) and texture analysis. The results show that maltodextrin, inulin, whey milk proteins, microcrystalline cellulose, and gum arabic are effective carriers when identifying morphological structure using CNNs. The use of CNNs, texture analysis, and the effect of LF-NMR relaxation time together with statistical elaboration shows that maltodextrin as well as milk whey proteins in combination with inulin achieve the most favorable results. The best results were obtained for a sample containing 50% maltodextrin and 50%maltodextrin (MD50-MD70). The CNNmodel for this combination had the lowest mean squared error in the test set at 2.5741 × 10−4, confirming its high performance in the classification of blackcurrant powder microstructures.
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    Upcycling Potato Juice Protein for Sustainable Plant-Based Gyros: A Multidimensional Quality Assessment
    (Licensee MDPI, Basel, Switzerland, 2025) Smarzyński, Krzysztof; Kowalczewski, Przemysław Łukasz; Tomczak, Aneta; Zembrzuska, Joanna; Ślachciński, Mariusz; Neunert, Grażyna; Ruszkowska, Millena; Świątek, Michał; Nowicki, Marcin; Baranowska, Hanna Maria
    The growing demand for sustainable, nutritionally adequate plant-based foods has driven innovation in meat analogues. This study presents a novel approach to upcycling potato juice protein—a by-product of starch production—into plant-based gyros (PBG) enriched with iron and dietary fiber. Four formulations (PBG1-PBG4) were developed using a blend of potato, rice, wheat, and pea proteins, and fortified with either ferritin-rich sprout powder or ferrous sulfate. Comprehensive analyses were conducted to assess nutritional composition, mineral content, glycoalkaloid safety, antioxidant activity, texture, water mobility, sensory appeal, and microbiological stability. All variants met high-protein labeling criteria and exhibited favorable fiber and mineral profiles. In vitro digestion significantly enhanced antioxidant bioaccessibility, particularly phenolic acids. Sensory evaluations favored ferritin-enriched variants, which also demonstrated superior texture and consumer acceptance. Microbiological assessments confirmed safety for up to 10 days under refrigeration. These findings highlight the potential of potato juice protein as a sustainable, functional ingredient in next-generation plant-based meat analogues.