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Effect of flaxseed oil cake extract on the microbial quality, texture and shelf life of gluten-free bread
Extending the shelf life of gluten-free bread (GFB) is a challenge. Mainly due to the ingredients used and their characteristics, GFB has numerous drawbacks such as unsatisfactory texture and rapid staling beyond a low nutritional value. In the present study, flaxseed oil cake extract (FOCE) was used to replace water (25–100%) in GFB formulations in order to test FOCE’s potential to reduce GFB staling and extend microbial stability. Texture (TPA test), water activity (LF NMR), acidity (pH measurements) and microbiological quality of GFBs were tested. Moreover, the content of a lignan with broad health-promoting potential, secoisolariciresinol diglucoside (SDG), in GFB with FOCE was analyzed. The results showed that the use of FOCE enriched experimental GFB in valuable SDG (217–525 µg/100 g DM) while not causing adverse microbiological changes. A moderate level (25–50%) of FOCE did not change the main texture parameters of GFB stored for 72 h, the quality of which was comparable to control bread without FOCE. Meanwhile, higher proportions of FOCE (75–100% of water replacement) shortened GFB shelf life as determined by water activity and texture profile, suggesting that GFB with FOCE should be consumed fresh. To summarize, FOCE at moderate levels can add value to GFBs without causing a drop in quality, while still fitting in with the idea of zero waste and the circular economy.
Polymer-Solvent Interactions in Modified Starches Pastes–Electrokinetic, Dynamic Light Scattering, Rheological and Low Field Nuclear Magnetic Resonance Approach
Starch paste is a very complex dispersion that cannot be clearly classified as a solution, colloid or suspension and many factors affects its properties. As these ambiguities constitute a barrier to technological development, the aim of this study was to investigate the interaction of starch macromolecules with water by analysing the results of rheological properties, low field nuclear magnetic resonance (LF NMR), dynamic light scattering (DLS) and ζ potential analyses. Starch pastes with a concentration of 1%, prepared with distilled water and buffered to pH values of 2.5, 7.0 and 9.5 were analysed. It was proved that the pH buffering substantially decreased the values of consistency index but the pH value itself was not significant. LF NMR studies indicated that the dissolution of starch in water resulted in a reduction in spin-lattice as well as spin-spin relaxation times. Moreover, changes in relaxation times followed the patterns observed in rheological studies. Electrokinetic and DLS analyses showed that potential values are primarily influenced by the properties of the starches themselves and, to a lesser extent, by the environmental conditions. The conducted research also showed complementarity and, to some extent, substitutability of the applied research methods as well as exclusion chromatography (a method not used in this work).
The Prediction of Pectin Viscosity Using Machine Learning Based on Physical Characteristics—Case Study: Aglupectin HS-MR
In the era of technology development, the optimization of production processes, quality control and at the same time increasing production efficiency without wasting food, artificial intelligence is becoming an alternative tool supporting many decision-making processes. The work used modern machine learning and physical analysis tools to evaluate food products (pectins). Various predictive models have been presented to estimate the viscosity of pectin. Based on the physical analyses, the characteristics of the food product were isolated, including L*a*b* color, concentration, conductance and pH. Prediction was determined using the determination index and loss function for individual machine learning algorithms. As a result of the work, it turned out that the most effective estimation of pectin viscosity was using Decision Tree (R2 = 0.999) and Random Forest (R2 = 0.998). In the future, the prediction of pectin properties in terms of viscosity recognition may be significantly perceived, especially in the food and pharmaceutical industries. Predicting the natural pectin substrate may contribute to improving quality, increasing efficiency and at the same time reducing losses of the obtained final product.
Sustainable Protein Fortification: Impact of Hemp and Cricket Powder on Extruded Snack Quality
This research paper evaluates the functional and nutritional properties of extruded corn snacks fortified with plant-based hemp protein (HP) and insect-derived cricket powder (CP). With a focus on sustainable protein sources due to growing environmental concerns and the need for alternative protein sources, this study aims to enhance the nutritional profile of corn snacks. The incorporation of unconventional proteins into snacks is explored to meet consumer demands for sustainable and nutritious options. Results show that HP-enriched snacks have higher mineral content, such as calcium and magnesium, lower sodium content, and improved water interaction profiles. On the other hand, CP-fortified snacks exhibit higher protein content, essential amino acids, and moisture retention capabilities. Texture analysis reveals differences in hardness, cohesiveness, and springiness between HP and CP-enriched products. Moreover, color analysis indicates that HP and CP additives influence the color and appearance of the snacks, with CP enrichments leading to darker snacks. Sorption isotherm studies demonstrate varying hygroscopicity levels between HP- and CP-enriched samples, impacting their storage stability. Surface structure assessments show differences in the specific sorption surface area, suggesting unique properties attributed to each protein source. In conclusion, both hemp protein and cricket powder offer various advantages for snack fortification, providing opportunities to enhance nutritional profiles while addressing sustainability concerns.
The application of convolutional neural networks, LF-NMR, and texture for microparticle analysis in assessing the quality of fruit powders: Case study – blackcurrant powders
Abstract 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 CNN model 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.
An instrumental analysis of changes in the physicochemical and mechanical properties of smoked and mould salamis during storage
Upcycling Potato Juice Protein for Sustainable Plant-Based Gyros: A Multidimensional Quality Assessment
Insight into the Gluten-Free Dough and Bread Properties Obtained from Extruded Rice Flour: Physicochemical, Mechanical, and Molecular Studies
The present study aimed to evaluate the effect of the extrusion process and particle size on the properties of rice flour (microstructure, pasting properties), gluten-free dough (rheological properties), and bread (texture, specific volume, water absorption capacity, low-field nuclear magnetic resonance (LF NMR) relaxometry). Rice flours were extruded at 80 and 120 °C with feed moisture (15 and 30%) and with the same particle size (<132 and >132–200 µm). Significant differences were observed between the pasting profiles of the flours before and after extrusion. The pasting profile of extruded flours confirmed that hydrothermal treatment partially gelatinized the starch, decreasing the viscosity during heating. The water binding properties increased with the extrusion temperature and moisture content and also with the particle size of the flour. The most important parameter influencing the mechanical properties of the dough was the moisture content of the flour and significant differences were observed between fine (<132 μm) and coarse flours (>132–200 μm). The molecular dynamics of particles containing protons in the bound and bulk fractions in each sample do not depend on the extruder parameters or granulation of the obtained fraction. LF NMR results confirmed that extrusion of rice flour led to a significant decrease in the T21 value compared to the control sample and an increase in the T22 value in breads made with flours with particle size <132 μm. A linear relationship was found between the spin-spin relaxation times (T1) changes and the equilibrium water activity (ar). The results showed that bread with extruded rice flour at the same die temperature resulted in a significantly higher bread volume (31%) and lower hardness (27%) compared to the control. The highest hardness was observed in the case of samples prepared with extruded flour with the addition of 15% moisture, regardless of temperature and particle size.
Gluten-Free Bread Enriched with Potato and Cricket Powder: Comparative Study of the Effects of Protein on Physicochemical Properties Bonds and Molecular Interactions
The increasing demand for diverse foods and tailored nutrition encourages the development of innovative products, such as bread enriched with cricket powder (CP) or potato protein (PP). This study presents the preparation and analysis of gluten-free breads with CP and PP, focusing on their nutritional value and physical properties. Analytical methods included water activity measurement, bread volume, crumb color analysis, FTIR spectroscopy, low-field NMR relaxometry, and texture profile analysis. Ash content ranged from 0.60 ± 0.03% to 1.16 ± 0.11%, and caloric values ranged from 216.2 to 229.5 kcal/100 g. Water activity remained stable across all samples (0.975–0.976). Crumb color analysis showed the greatest change in CP samples (ΔE = 14.07), while PP had minimal impact (ΔE = 2.15). FTIR spectra revealed increased amide I and II bands, indicating higher protein content. NMR results demonstrated shorter T1, T21, and T22 times for CP, suggesting reduced water mobility and a denser structure, while PP samples showed higher values, indicating a looser, more hydrated matrix. Texture analysis confirmed that CP increased firmness and compactness, whereas PP enhanced springiness. These findings suggest that CP and PP can improve the nutritional and structural properties of gluten-free bread, offering valuable alternatives for modern dietary needs.
Thermogravimetric (TG/DTG) characterization of cold-pressed oil blends and Saccharomyces cerevisiae-based microcapsules obtained with them
Abstract The aim of this study was to develop yeast-based microcapsules (YBMCs) containing vegetable oil blends with n3/n6 fatty acids in a ratio of 5:1. The oil blends, as well as YBMCs with these oils, were analyzed in nitrogen and oxygen. The shape and course of the TG and DTG curves were observed for yeast cells with all types of oil blends. No differences were observed in shape because of the microencapsulation curves with all oil blends between YMBCs prepared using native and autolyzed yeast. The results show that the yeast cells could be used as efficient microcarriers for the encapsulation of cold-pressed oils in order to provide thermal stable ingredients for the food industry.
Chemical characteristics and thermal oxidative stability of novel cold-pressed oil blends: GC, LF NMR, and DSC studies
Plant oils contain a high content of unsaturated fatty acids. Studies of food products have revealed a considerable disproportion in the ratio of ω6 to ω3. This article presents information on the healthful qualities of eight new oil blends that contain a beneficial proportion of ω6 to ω3 fatty acids (5:1), as well as their degradation during heating at 170 and 200 °C. The fatty acid profile was analyzed by gas chromatography (GC), content of polar compounds and polymers of triacylglycerols by liquid chromatography (LC), water content was measured by the Karl Fischer method, and oxidative stability was measured by differential scanning calorimetry (DSC) and low-field nuclear magnetic resonance (LF NMR) methods. The results showed that during heating, the polar fraction content increased in samples heated at both analyzed temperatures compared to unheated oils. This was mainly due to the polymerization of triacylglycerols forming dimers. In some samples that were heated, particularly those heated to 200 °C, trimers were detected, however, even with the changes that were observed, the polar fraction content of the blends did not go beyond the limit. Despite the high content of unsaturated fatty acids, the analyzed blends of oils are characterized by high oxidative stability, confirmed by thermoanalytical and nuclear magnetic resonance methods. The high nutritional value as well as the oxidative stability of the developed oil blends allow them to be used in the production of food, in particular products that ensure an adequate supply of ω3 fatty acids.
Molecular Properties of Starch-Water Interactions in the Presence of Bioactive Compounds from Barley and Buckwheat-LF NMR Preliminary Study
The Rheology, Texture, and Molecular Dynamics of Plant-Based Hot Dogs
The rising demand for plant-based alternatives to traditional meat products has led to the development of plant-based sausages (PBSs) that closely mimic the texture and taste of their meat counterparts. This study investigates the rheological and textural properties, as well as proton molecular dynamics, of hot dog-type PBSs and batters used in their production. Various formulations were analyzed to understand how different ingredients and processing methods affect the characteristics of the final products. Our findings reveal that the incorporation of specific plant proteins and hydrocolloids significantly influences the rheological behavior and texture profile of sausages. The hardness of the samples ranged from 4.33 to 5.09 N/mm and was generally higher for the products with inorganic iron sources. Regarding the viscoelastic properties, all the samples showed larger values of the storage modulus than the loss modulus, which indicates their solid-like behavior. Additionally, the study utilized advanced proton nuclear magnetic resonance (NMR) techniques to elucidate the molecular dynamics within plant-based matrices, providing insights into water distribution and mobility. Key findings highlight the impact of different plant proteins and additives on the texture and stability of sausage analogs.
Pasta with Kiwiberry (Actinidia arguta): Effect on Structure, Quality, Consumer Acceptance, and Changes in Bioactivity during Thermal Treatment
In this study, kiwiberry lyophilizate (KBL) was incorporated into pasta at different levels (5%, 10%, and 15% w/w). Kiwiberry fruits’ characteristics (ascorbic acid, carotenoids, phenolic compounds, and antioxidant activity determination) as well as physical (cooking properties, color, microscopic structure determination, texture, and water molecular dynamics analysis by low-field NMR) and chemical analyses (proximate composition phenolic compounds composition and antioxidant activity) of KBL-enriched pasta were investigated. The replacement of semolina with KBL in the production of pasta significantly changed its culinary properties. Results showed that the addition of KBL leads to a reduction in optimal cooking time and cooking weight (47.6% and 37.3%, respectively). Additionally, a significant effect of the KBL incorporation on the color of both fresh and cooked pasta was observed. A significant reduction in the L* value for fresh (27.8%) and cooked (20.2%) pasta was found. The KBL-enriched pasta had a different surface microstructure than the control pasta and reduced firmness (on average 44.7%). Low-field NMR results have confirmed that the ingredients in kiwiberry fruit can bind the water available in fresh pasta. The heat treatment resulted in increasing the availability of phenolic compounds and the antioxidant activity (64.7%) of cooked pasta. Sensory evaluation scores showed that the use of 5–10% of the KBL additive could be successfully accepted by consumers.
Nutritional and Bioactive Properties of Plant-Based Sausages Containing Potato Protein, Ferritin, and a Blend of Cold-Pressed Oils
Pulses-Fortified Ketchup: Insight into Rheological, Textural and LF NMR-Measured Properties
Tomato ketchup is one of the most popular foods eaten all over the world. To improve the texture of these sauces, modified starches are used most commonly. This may be negatively assessed by consumers. The solution to this problem could be the use of legume flours, as beyond thickening potential, they are recognized as plant foods of high nutritional value. The aim of the work was to estimate the applicability of pulse flour as a texture-forming agent for ketchup. A comprehensive assessment of the quality of ketchup was made, both in terms of sensory properties and instrumentally analyzed physicochemical features: acidity, color, texture, rheological properties, and dynamics of water molecules using the LF NMR method. It was stated that pulse flours are suitable for use as forming agents for ketchup, although they have slightly weaker thickening properties with a consistency index ranging from 5.06–6.82 Pa·sn, compared to acetylated distarch adipate (19.48 Pa·sn). Texture, which is the most important parameter for consumer acceptance of ketchup, can be successfully analyzed using instrumental methods. Firmness ranged from 0.51 N for lentil and pea-fortified ketchup to 0.55 N for the lupine variant. Ketchup thickened with different pulses and flours reveals slightly different individual sensory characteristics, so it makes it possible to create a new gamut of healthy tomato sauces. The highest overall sensory score was attributed accordingly to lentils (6.9), lupine (6.2), chickpeas (6.1), and peas (5.8).
