Wholegrain consumption has been associated with beneficial health effects including reduction of diabetes and cancer risk; however, the underlying mechanisms are not fully understood. The aim of this study was to characterize the effects of wholegrain rye intake on circulating metabolites in a human intervention study using untargeted metabolomics. The intervention consisted of 2 successive 4-wk periods in a randomized crossover design, where 15 adults consumed wholegrain rye bread (WGR) or white wheat bread enriched with fermented rye bran (WW+RB), following a 4-wk rye-free period with white wheat bread (WW). Fasting plasma samples were collected at the end of each period and analyzed using liquid chromatography-mass spectrometry. Metabolic profiles were compared to identify compounds discriminating WGR from the WW+RB and WW periods. Because peripheral serotonin is produced mainly in the gut, a hypothesis of its altered biosynthesis as a response to increased cereal fiber intake was tested by measuring intestinal serotonin of mice fed for 9 wk on a high-fat diet supplemented with different sources of fiber (rye bran flour, ground wheat aleurone, or powdered cellulose). Five endogenous metabolites and 15 rye phytochemicals associated with WGR intake were identified. Plasma concentrations of serotonin, taurine, and glycerophosphocholine were significantly lower after the WGR than WW period (Q < 0.05). Concentrations of 2 phosphatidylethanolamine plasmalogens, PE(18:2/P-18:0) and PE(18:2/P-16:0), were lower after the WGR period than the WW+RB period (Q < 0.05). The concentration of serotonin was significantly lower in the colonic tissue of mice that consumed rye bran or wheat aleurone compared with cellulose (P < 0.001). Wholegrain rye intake decreases plasma serotonin in healthy adults when compared with refined wheat. Intake of rye bran and wheat aleurone decreases colonic serotonin in mice. These results suggest that peripheral serotonin could be a potential link between wholegrain consumption and its associated health effects. Data used in the study were derived from a trial registered at www.clinicaltrials.gov as NCT03550365.

The current food production system is unsustainable, necessitating a shift towards plant-based diets. Nutritious options fulfill basic needs but may not satisfy hedonic ones. Our novel approach is to promote healthier eating habits without compromising on the pleasantness of eating by using extended reality technologies and multimodal interaction. We present a multisensory augmentation system integrating augmentations in olfaction, touch, and vision. We studied the experience of eating plant-based balls and meatballs. In an experiment with 40 participants, haptic and visual augmentations were found to have significant effects: augmented meatballs and plant-based balls were perceived as bigger and heavier compared to non-augmented versions. However, olfactory augmentation did not produce a similar effect: participants did not notice a stronger aroma with augmented balls compared to non-augmented balls, and the augmented plant-based version had a less appealing scent than its non-augmented counterpart. Moreover, the findings of the study indicate that our multisensory augmentation system had no significant effect on taste perception.

Little is known about how plant-based products influence satiation compared to corresponding meat-based products. As augmented reality (AR) intensifies sensory experiences, it was hypothesized to improve satiation. This study compared satiation between intake of meatballs and plant-based balls and plant-based balls intensified with AR for visual, olfactory, and haptic sensory properties. Intake order of the meatballs, plant-based balls, and augmented plant-based balls, eaten on separate days, was randomized. Satiation was measured from twenty-eight non-obese adults as ad libitum intake of the balls and extra snacks, and as subjective appetite sensations. Liking and wanting to eat the products were also investigated. There were no differences between the products in satiation. Before tasting the augmented plant-based balls were less liked than the meatballs (p = 0.002) or plant-based balls (p = 0.046), but after eating the first ball or eating the ad libitum number of balls the differences in liking disappeared. Wanting evaluations were similar for each product and decreased during eating (p < 0.001). A group of participants susceptible to AR was found (n = 11), described by decreased intake when augmentation was applied. Among the sub-group, wanting to eat the augmented balls was lower before tasting (p = 0.019) and after eating the first ball (p = 0.002) and appetite was less suppressed after eating the balls ad libitum (p = 0.01), when compared to non-susceptible participants. We conclude that meatballs and plant-based balls were equal in inducing satiation, and multisensory augmentation did not influence satiation. However, the augmentation decreased liking evaluations before tasting. Further studies are needed to explore differences between consumer groups in susceptibility to augmentation.

Background and objectives: A concept of personalized eating originates from personalized nutrition, where dietary advice is tailored to an individual. In personalized nutrition solutions, dietary advice is more and more based on clinical biomarkers, genetics, and the gut microbiome. However, there is evidence that tailored dietary advice based only on personal dietary data is effective in facilitating changes in dietary intakes. Thus, the aim is to create a personalized eating solution: a prototype of data platform recommends foods by linking individual’s dietary data with product information via specified rules. Methods: The data platform is integrated with an external global food product database and a user interface (UI), and the system structure is: (1) a personal profile, (2) a rules engine with functionality for setting tags and filtering rules, and (3) a knowledge database (food product database). The food product database is integrated via an open API (application programming interface) with the platform, and is utilized to retrieve product information for the filtering rules. When using the platform for the first time, a user must enter demographic data and information about specific dietary criteria and personal preferences. With the permission from the user, the data platform may also retrieve data for the personal profile from other integrated services, including wearable devices. Food recommendations are generated by filtering the product information based on the personal profile and food groups selected by the user. The user can access the food recommendations via a web-based UI. The platform also includes an API, which allows the recommendations to be integrated to existing wellness applications and devices. Results and Discussion: The personalized eating solution suitability for use by consumers and ecommerce services will be tested in 2023. A strength is that the solution considers personal preferences to motivate users, such as values related to the consumption of ethic and sustainable products. However, the food recommendation rules rely on formal information about products in the external food database. In the future, the solution could be used for research, commercial, and healthcare purposes in facilitating dietary changes to promote health and wellbeing.