Virtual reality (VR) technology is emerging as a tool for simulating different eating environments to better understand consumer sensory response to food. This research explored the impact of different environmental contexts on participants’ hedonic ratings of two different food products: beef steaks, and milk chocolate, using VR as the context-enhancing technology. Two separate studies were conducted. For beef, two different contextual conditions were compared: traditional sensory booths and a VR restaurant. For chocolate, data were generated under three different contextual conditions: traditional sensory booths, VR Irish countryside; VR busy city (Dublin, Ireland). All VR experiences were 360-degree video based. Consumer level of engagement in the different contextual settings was also investigated. The results showed that VR had a significant effect on participants’ hedonic responses to the food products. Beef was rated significantly higher in terms of liking for all sensory attributes when consumed in the VR restaurant. While for chocolate, the VR countryside context generated significantly higher hedonic scores for flavour and overall liking in comparison to the sensory booth. Taken together, both studies demonstrate how specific contextual settings can impact participants’ sensory response to food products, when compared to a traditional sensory laboratory condition.

The objective of the present study was to determine if animals who were genetically divergent in the predicted tenderness of their meat actually produced more tender meat, as well as what the implications were for other organoleptic properties of the meat. The parental average genetic merit for meat tenderness was used to locate 20 “Tough genotype” heifers and 17 “Tender genotype” heifers; M. longissimus thoracis steaks from all heifers were subjected to sensory affective analysis (140 consumers) and sensory profiling using two trained sensory panels. All sample steaks were treated identically regarding pre- and post-mortem handling, storage, cooking and presentation (i.e., randomised, blind coded). For the affective consumer study, eight steaks were sectioned from the same location of the striploin muscles from each of the heifers. In total, 108 steaks from the Tender genotype and 118 from the Tough genotype were tested in the consumer study to determine the preference or liking of these steaks for appearance, aroma, flavour, tenderness, juiciness and overall acceptability. The consumer study found that the Tender genotype scored higher (p < 0.0001) for liking of tenderness, juiciness, flavour and overall acceptability compared to the Tough genotype. Similar results were generally found for the separate consumer age cohorts (18–64 years) with lower sensory acuity in the 65+ age cohort. For the descriptive analysis, the Tender genotype scored numerically more tender, juicy and flavoursome, although the differences were only significant for one of the panels. The critical outcome from this study is that parental average genetic merit can be used to pre-select groups of animals for tenderness, which, in turn, can be detected by consumers.

Seaweed is a naturally rich source of nutrients and exhibits techno-functional properties that are under study for their potential as ingredients in meat products. However, seaweed is associated with a particular flavor profile, and optimization of the sensory profile should be conducted alongside technical performance. This study investigated the feasibility of the application of sea spaghetti (Himanthalia elongata) in the production of low-salt beef patties and recorded the associated sensory profile and consumer hedonic-emotional response. Eight beef patty formulations with varying salt (0–1%) and seaweed (0–5%) contents were subjected to quantitative descriptive analysis via a trained sensory panel (n = 8) and six the formulations were selected for consumer testing (liking, emotional associations, saltiness perception, and purchase intent) by a group of 105 Irish resident consumers. The trained panel results showed that the intensity of seaweed odor, flavor, and visual presence in burgers was negatively related to the intensity of beef odor and flavor and that seaweed addition (5%) significantly increased the saltiness perception of low-salt burgers. Burgers with 1% added seaweed, although perceived by consumers as less salty, could substitute NaCl in low-salt beef patties without deterioration of their liking among regular burger consumers. Consumers associated all seaweed-containing samples, especially those containing 1% of sea spaghetti, with being good, pleasant, satisfied, and warm. The higher inclusion of sea spaghetti (2.5%) led to significantly lower overall liking and reduced purchase intent, while consumers associated this formulation with emotions such as being more adventurous, aggressive, and wild. Consumers who rejected seaweed burgers had the highest level of food neophobia and avoided foods with additives. The results demonstrate that 1% sea spaghetti seaweed can be successfully incorporated into low-salt beef patties, resulting in hedonic and emotional benefits without significantly increasing the salt content.

Fermentable oligo-, di-, monosaccharides and polyols (FODMAPs) are carbohydrates which can cause symptoms of irritable bowel syndrome (IBS).

The sensory quality of meat, encompassing the traits of appearance, texture, and flavour, is essential to consumer acceptance. Conventional quality assessment techniques, such as instrumental methods and trained sensory panels, often face limitations due to their destructive and time-consuming nature. In recent years, optical sensing techniques have emerged as a fast, non-invasive, and non-destructive technique for the prediction of quality attributes in meat and meat products, achieving prediction accuracies of over 90%. This review critically examines the potential of optical sensing techniques, such as near-infrared spectroscopy (NIRS), Raman spectroscopy, and hyperspectral imaging (HSI), to inform about the sensory attributes of red meat, aligning with industrial demands for early information on the predicted sensory performance of inventory to support meeting consumer requirements. Recent trends and the remaining challenges associated with these techniques will be described. While technical issues related to spectral data acquisition and data processing are important challenges when considering industrial implementation, overall, optical sensing techniques, in tandem with recent developments in digitalisation and data analytics, provide potential for the online prediction of meat sensory quality in the meat processing industries. Establishing technologies for enhanced information on the product and improved possibilities for quality control will help the industry to meet consumer demands for a consistent quality of product.