Rice is consumed as a staple food by more than half of the world’s population. Due to a higher fibre and micronutrient content, brown rice is more nutritious than white rice, but the consumption of brown rice is significantly lower than that of white rice, primarily due to sensory attributes. Therefore, the present research aimed to identify the sensory attributes which drive liking of Australian-grown brown and white rice varieties. Participants (n = 139) tasted and scored (9-point hedonic scale) their liking (i.e., overall liking, aroma, colour and texture) of brown and white rice types of Jasmine (Kyeema), Low GI (Doongara), and Medium grain rice (Amaroo). In addition, participants scored aroma, colour, hardness, fluffiness, stickiness, and chewiness, on Just About Right Scales. A within-subjects crossover design with randomised order (William’s Latin Square design) was used with six repeated samples for liking and Just About Right scales. Penalty analyses were applied to determine the relative influence of perception of sensory attributes on consumer liking of the rice varieties. Across all varieties, white rice was liked more than brown rice due to the texture and colour, and Jasmine rice was preferred over Low GI and Medium Grain. Rice texture (hardness and chewiness) was the most important sensory attribute among all rice varieties and aroma was important for driving of liking between white rice varieties.
Our understanding of the human gut microbiome has grown exponentially. Advances in genome sequencing technologies and metagenomics analysis have enabled researchers to study microbial communities and their potential function within the context of a range of human gut related diseases and disorders. However, up until recently, much of this research has focused on characterizing the gut microbiological community structure and understanding its potential through system wide (meta) genomic and transcriptomic-based studies. Thus far, the functional output of these microbiomes, in terms of protein and metabolite expression, and within the broader context of host-gut microbiome interactions, has been limited. Furthermore, these studies highlight our need to address the issues of individual variation, and of samples as proxies. Here we provide a perspective review of the recent literature that focuses on the challenges of exploring the human gut microbiome, with a strong focus on an integrated perspective applied to these themes. In doing so, we contextualize the experimental and technical challenges of undertaking such studies and provide a framework for capitalizing on the breadth of insight such approaches afford. An integrated perspective of the human gut microbiome and the linkages to human health will pave the way forward for delivering against the objectives of precision medicine, which is targeted to specific individuals and addresses the issues and mechanisms in situ.
The demand for plant-based milk alternatives (PMAs) has grown rapidly in recent years, driven by health-conscious choices, environmental sustainability, ethical considerations, and environmental concerns. Among these, “barista-quality” PMAs play a critical role in coffee applications. However, achieving the desired sensory attributes (flavour and mouthfeel) and physicochemical properties (texture, foam formation, and stability) of PMAs to closely resemble dairy milk in coffee remains a significant challenge. This review provides a comprehensive analysis of the sensory and physicochemical characteristics of PMAs, with a particular focus on their performance in hot coffee beverages such as cappuccinos and lattes. It examines the fundamental issues and factors influencing the compatibility of PMAs in hot coffee, including flavour, texture, foam formation and stability, and consumer acceptance. Furthermore, this review explores potential strategies to address these sensory and physicochemical challenges, offering valuable insights into opportunities for innovation and product development. The aim is to guide the optimization of next-generation “barista-quality” PMAs with improved sensory and functional properties.
The dual-sugar intestinal permeability test is a commonly used test to assess changes in gut barrier function. However, it does not identify functional changes and the exact mechanism of damage caused by the increased intestinal permeability. This study aims to explore the application of untargeted metabolomics and lipidomics to identify markers of increased intestinal permeability. Fifty fasting male participants (18–50 years) attended a single visit to conduct the following procedures: assessment of anthropometric measures, assessment of gastrointestinal symptoms, intestinal permeability test, and assessment of blood samples 90 min post-administration of the intestinal permeability test. Rhamnose and lactulose were analysed using gas chromatography-mass spectrometry (GC-MS). Untargeted polar metabolites and lipidomics were assessed by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QToF MS). There was an elevated lactulose/rhamnose ratio in 27 subjects, indicating increased permeability compared to the remaining 23 control subjects. There were no significant differences between groups in characteristics such as age, body mass index (BMI), weight, height, and waist conference. Fourteen metabolites from the targeted metabolomics data were identified as statistically significant in the plasma samples from intestinal permeability subjects. The untargeted metabolomics and lipidomics analyses yielded fifteen and fifty-one statistically significant features, respectively. Individuals with slightly elevated intestinal permeability had altered energy, nucleotide, and amino acid metabolism, in addition to increased glutamine levels. Whether these biomarkers may be used to predict the early onset of leaky gut warrants further investigation.
Shiga toxigenic E. coli (STEC) are an important cause of foodborne disease globally with many outbreaks linked to the consumption of contaminated foods such as leafy greens. Existing methods for STEC detection and isolation are time-consuming. Rapid methods may assist in preventing contaminated products from reaching consumers. This proof-of-concept study aimed to determine if a metabolomics approach could be used to detect STEC contamination in spinach. Using untargeted metabolic profiling, the bacterial pellets and supernatants arising from bacterial and inoculated spinach enrichments were investigated for the presence of unique metabolites that enabled categorization of three E. coli risk groups. A total of 109 and 471 metabolite features were identified in bacterial and inoculated spinach enrichments, respectively. Supervised OPLS-DA analysis demonstrated clear discrimination between bacterial enrichments containing different risk groups. Further analysis of the spinach enrichments determined that pathogen risk groups 1 and 2 could be easily discriminated from the other groups, though some clustering of risk groups 1 and 2 was observed, likely representing their genomic similarity. Biomarker discovery identified metabolites that were significantly associated with risk groups and may be appropriate targets for potential biosensor development. This study has confirmed that metabolomics can be used to identify the presence of pathogenic E. coli likely to be implicated in human disease.