Latest advances in imaging techniques for characterizing soft, multiphasic food materials

Microstructural studies of imitation cheese with a shift in continuous phase

When casein is replaced with starch in imitation cheese, the functionality changes. Three different microscopy methods were applied to understand the microstructural differences in the product depending on which component dominates the microstructure. Confocal Laser Scanning Microscopy (CLSM) for component identification. Scanning Electron Microscopy (SEM) and Cryogenic Scanning Electron Microscopy (Cryo-SEM) for studying surface structures. Differences in the surface structures were detected between SEM and Cryo-SEM. In SEM, starch appeared rough and protein smooth, while in Cryo-SEM no starch roughness of the surface was found. A change in starch modification and effects of protein prehydration was also analysed. Adding octenyl succinic anhydride (OSA) modified starch for emulsifying properties resulted in a microstructure with fragmented protein at a protein level of 7 %, but not at 9 or 12 %. Protein prehydration had limited effect on microstructure. On a macrostructural level, the change to an emulsifying starch increased hardness in imitation cheese with 7 and 9 % protein. Protein prehydration slightly decreased the hardness, but the difference was not significant at all concentrations. This research provides valuable information about the microstructure of imitation cheese at a 50/50 composition, how the microstructure changes with an emulsifying starch and what occurs after a protein prehydration was included in the production.

Comparative study on chain conformations, physicochemical and rheological properties of three acidic polysaccharides from Opuntia dillenii Haw. fruits

In this study, three acidic polysaccharides (OFPP-1, OFPP-2 and OFPP-3) were isolated from the pulps of Opuntia dillenii Haw. fruits, and their chain conformations, physicochemical and rheological properties were investigated. The molecular weight and conformational parameters (Mw, Mn, Mz, Rg and Rh) of OFPPs in 0.1 M NaNO3 solution were detected by HPSEC-MALLS-RI. In addition, based on the parameters ρ and v, it was concluded that these three polysaccharide chains exhibited sphere-like conformation in 0.1 M NaNO3 solution, which was consistent with AFM and TEM observations. Furthermore, the Congo Red experiment showed that OFPP-2 had a triple-helix structure, which may be conducive to its biological activity. This study also found that OFPPs were semi-crystalline structures with high thermal and pH stability. The rheological analyses indicated that the apparent viscosity of OFPPs solutions exhibited concentration-, temperature-, and pH-dependence, and the viscoelasticity of them was affected by molecular characteristics and concentration. The results of this study are helpful to elucidate the structure-activity relationship of OFPPs. Moreover, this study can provide theoretical reference for the application of OFPPs as bioactive ingredients or functional materials in the food, pharmaceutical and cosmetic industries and the development and utilization of the O. dillenii Haw. fruits resource.

Atomic Force Microscopy of Phytosterol Based Edible Oleogels

This work reviews the use of atomic force microscopy (AFM) as a tool to investigate oleogels of edible triglyceride oils. Specific attention is given to those oleogels based on phytosterols and their esters, a class of material the authors have studied extensively. This work consists of a summary of the role of AFM in imaging edible oleogels, including the processing and preparation steps required to obtain high-quality AFM images of them. Finally, there is a comparison between AFM and other techniques that may be used to obtain structural information from oleogel samples. The aim of this review is to provide a useful introduction and summary of the technique for researchers in the fields of gels and food sciences looking to perform AFM measurements on edible oleogels.

Survival, growth, behavior, hematology and serum biochemistry of mice under different concentrations of orally administered amorphous silica nanoparticle

Silica nanoparticles (SiNPs) are used extensively in consumer products and biomedical research basically due to ease of production and low cost. However, insufficient literature is reported regarding the toxicity and biocompatibility of SiNPs. The present study aimed to investigate the potential role of amorphous SiNPs on survival, growth, behavioral alterations, hematology and serum biochemistry of mice at four concentrations (control, 50, 100 and 150 mg/kg/day) of an oral supplementation for a period of 3 months. Signs of toxicity (lethargy, nausea, coma, tremors, vomiting and diarrhea, etc.) were noted at 9:00 am and 9:00 pm (twice a day) and the body weight of each of these mice was measured every week. The data were subjected to mean, standard deviation (S.D). Moreover, One-Way Analysis of Variance (ANOVA) and Dunnett's test were applied for analysis of statistical significance between groups by using SPSS software, version 20. All the mice survived with minor alterations in behavior and no significant weight changes were observed during the stipulated time period. Complete blood count (CBC) analysis indicated non-significant (P ≥ 0.05) systemic dysfunctions of organ systems. However, there was elevation in the level of AST and ALT in the analysis of serum biochemistry, while the values of all other examined parameters were not-significant (P ≥ 0.05). The study concluded that orally administered large silica nanoparticles up to the dose level of 150 mg/kg/day are nontoxic for the in vivo use in mice.

Predicting bilgewater emulsion stability by oil separation using image processing and machine learning

Bilgewater is a shipboard multi-component oily wastewater, combining numerous wastewater sources. A better understanding of bilgewater emulsions is required for proper wastewater management to meet discharge regulations. In this study, we developed 360 emulsion samples based on commonly used Navy cleaner data and previous bilgewater composition studies. Oil value (OV) was obtained from image analysis of oil/creaming layer and validated by oil separation (OS) which was experimentally determined using a gravimetric method. OV (%) showed good agreement with OS (%), indicating that a simple image-based parameter can be used for emulsion stability prediction model development. An ANOVA analysis was conducted of the five variables (Cleaner, Salinity, Suspended Solids [SS], pH, and Temperature) that significantly impacted estimates of OV, finding that the Cleaner, Salinity, and SS variables were statistically significant (p < 0.05), while pH and Temperature were not. In general, most cleaners showed improved oil separation with salt additions. Novel machine learning (ML)-based predictive models of both classification and regression for bilgewater emulsion stability were then developed using OV. For classification, the random forest (RF) classifiers achieved the most accurate prediction with F1-score of 0.8224, while in regression-based models the decision tree (DT) regressor showed the highest prediction of emulsion stability with the average mean absolute error (MAE) of 0.1611. Turbidity also showed a good emulsion prediction with RF regressor (MAE of 0.0559) and RF classifier (F1-score of 0.9338). One predictor variable removal test showed that Salinity, SS, and Temperature are the most impactful variables in the developed models. This is the first study to use image processing and machine learning for the prediction of oil separation for the application of bilgewater assessment within the marine sector.

Evaluation of the Miscibility of Novel Cocoa Butter Equivalents by Raman Mapping and Multivariate Curve Resolution-Alternating Least Squares

Cocoa butter (CB) is an ingredient traditionally used in the manufacturing of chocolates, but its availability is decreasing due to its scarcity and high cost. For this reason, other vegetable oils, known as cocoa butter equivalents (CBE), are used to replace CB partially or wholly. In the present work, two Peruvian vegetable oils, coconut oil (CNO) and sacha inchi oil (SIO), are proposed as novel CBEs. Confocal Raman microscopy (CRM) was used for the chemical differentiation and polymorphism of these oils with CB based on their Raman spectra. To analyze their miscibility, two types of blends were prepared: CB with CNO, and CB with SIO. Both were prepared at 5 different concentrations (5%, 15%, 25%, 35%, and 45%). Raman mapping was used to obtain the chemical maps of the blends and analyze their miscibility through distribution maps, histograms and relative standard deviation (RSD). These values were obtained with multivariate curve resolution-alternating least squares. The results show that both vegetable oils are miscible with CB at high concentrations: 45% for CNO and 35% for SIO. At low concentrations, their miscibility decreases. This shows that it is possible to consider these vegetable oils as novel CBEs in the manufacturing of chocolates.