ABSTRACT
The utilization of natural waxes to form oleogels has emerged as a new and efficient technique for structuring liquid edible oil into solid-like structures for diverse food applications. The objective of this study was to investigate the interaction between sunflower wax (SW) and monoglycerides (MGs) in olive oil oleogels and assess their physical characteristics and storage stability. To achieve this, pure SW and a combination of SW with MGs in a 1:1 ratio were examined within a total concentration range of 6-12% w/w. The formed oleogels were characterized based on their microstructure, melting and crystallization properties, textural characteristics, and oxidative stability during storage. All the oleogels were self-standing, and, as the concentration increased, the hardness of the oleogels also increased. The crystals of SW oleogels were long needle-like, while the combination of SW and MGs led to the formation of crystal aggregates and rosette-like crystals. Differential scanning calorimetry and FTIR showed that the addition of MGs led to different crystal structures. The oxidation results revealed that oleogels had low peroxide and TBARS values throughout the 28-day storage period. These results provide useful insights about the utilization of SW and MGs oleogels for potential applications in the food industry.
ABSTRACT
Waxes and monoglycerides (MGs) added in edible oils form oleogels that can be used as an alternative structured fat, providing healthier substitutes to saturated and trans fats in foods. This study aimed to investigate the properties of oleogels formed by the interaction between monoglycerides and different waxes in various edible oils. For this purpose, waxes, namely rice bran (RBW), candelilla (CDW), sunflower (SW), and beeswax (BW), together with MGs in a total concentration level of 15% (w/w) were dissolved in several edible oils (olive, sunflower, sesame, and soybean). The structure and physical properties of oleogels were investigated using texture analysis, polarized light microscopy, melting point measurements, and Fourier-transform infrared spectroscopy (FTIR). The hardest structure was produced by SW/MG (5.18 N), followed by CDW (2.87 N), RBW (2.34 N), BW (2.24 N) and plain MG (1.92 N). Furthermore, RBW and SW led to a higher melting point (69.2 and 67.3 °C) than the plain MG oleogels (64.5 °C). Different crystallization structures, i.e., needle-like crystals and spherulites, were observed depending on the type of wax, its concentration, and the oil used. These results can be used to control the properties of oleogels by adjusting the gelator composition for a variety of potential food applications.
ABSTRACT
The effect of pH and water activity (aw) on the formation of biofilm by Salmonella enterica ser. Newport, previously identified as a strong biofilm producer, was assessed. Biofilm formation was evaluated in tryptone soy broth at 37 °C and at different combinations of pH (3.3-7.8) and aw (0.894-0.997). In total, 540 biofilm formation tests in 108 pH and aw combinations were carried out in polystyrene microtiter plates using crystal violet staining and optical density (OD; 580 nm) measurements. Since the individual effects of pH and aw on biofilm formation had a similar pattern to that observed for microbial growth rate, cardinal parameter models (CPMs) were used to describe these effects. CPMs described successfully the effects of these two environmental parameters, with the estimated cardinal values of pHmin, pHopt, pHmax, awmin and awopt being 3.58, 6.02, 9.71, 0.894 and 0.994, respectively. The CPMs assumption of the multiplicative inhibitory effect of environmental factors was validated in the case of biofilm formation using additional independent data (i.e. 430 OD data at 86 different combinations of pH and aw). The validation results showed a good agreement (r(2) = 0.938) between observed and predicted OD with no systematic error. In the second part of this study, a probabilistic model predicting the pathogen's biofilm formation boundaries was developed, and the degree of agreement between predicted probabilities and observations was as high as 99.8%. Hence, the effect of environmental parameters on biofilm formation can be quantitatively expressed using mathematical models, with the latter models, in turn, providing useful information for biofilm control in food industry environments.
