Flokkur: Greinar

Tengiliður

Sigurlaug Skírnisdóttir

Verkefnastjóri

sigurlaug.skirnisdottir@matis.is

The infant gut microbiome plays a critical role in the early development of the immune system, brain function, metabolism, and defense against pathogens. However, data from underrepresented populations, like Iceland, with its distinct dietary and lifestyle habits, remain limited. This paper presents the initial findings from the Icelandic Diet and the Infant Gut Microbiome Development (IceGut) study. Fecal samples were collected at multiple time points, representing 328 unique study identifiers, with one to five samples per child, from before the introduction of solid foods up to 5 years of age, and postpartum samples from 214 mothers. Microbial composition and predicted functional potential were assessed using 16S rRNA gene sequencing. Children in the cohort followed typical gut microbiome maturation, but at 1 year of age, they showed a notably higher relative abundance of Blautia than reported in comparable cohorts. This time point marked a transition in both taxonomic composition and predicted functional gene counts. By 5 years, the children had higher observed richness than their mothers but lower Shannon and Simpson diversities. At 2 and 5 years, and in the mothers, samples positive for archaea had significantly higher alpha diversity than samples that tested negative for archaea. Mothers with gestational diabetes mellitus (GDM) exhibited a higher relative abundance of Blautia but a lower alpha diversity. The variance in offspring gut microbiome explained by maternal GDM became progressively stronger over time, being significant at the age of 5 and explaining 2.5% of the variance.

Tengiliður

Anna Þóra Hrólfsdóttir

Verkefnastjóri

annath@matis.is

The brown algae Ascophyllum nodosum is harvested from wild sources and used in seaweed meal production. It contains multiple valuable compounds, including polyphenols, polysaccharides and carotenoids that have bioactive properties. In current uses of biomass e.g. as raw material for alginate production, these compounds are not of any special interest, hence there is an opportunity for better utilization of the biomass. Therefore, the aim of the study was to investigate the potential of producing and upscaling production of a byproduct (a targeted seaweed extract produced with mixture of fresh seaweed and water) from the unutilized liquid side-streams obtained within traditional seaweed meal processing. That was performed by evaluating the efficiency of the liquid/solid separation (screw press vs decanter), centrifugation as a secondary separation step, as well as drying methods (spray drying vs freeze drying) on the obtained liquid extracts. Chemical and antioxidant properties were evaluated throughout the alternative processing and mass balances calculated. The results suggest that the decanter was more efficient for separation compared to the screw press due to higher yield of liquid retrieved. The chemical composition and antioxidant properties did not differentiate significantly, neither between the separation methods nor during further processing of the liquids (e.g. centrifugation or drying methods). Furthermore, the alginate remained in the solid phase during separation, and main components extracted with the liquid phase included salt, minerals, polyphenols, and carbohydrates. The results indicate that alternative processing with a decanter as primary separation step could be a feasible solution to meet the demands of full utilization and no-waste policies within seaweed production.

Tengiliður

Anna Þóra Hrólfsdóttir

Verkefnastjóri

annath@matis.is

With the increased seaweed production worldwide, there is a need to focus on improved production practices to produce high-quality seaweed biomass, especially if the biomass is intended for high-quality products and human consumption. Multispectral imaging (MSI) is a novel technique used as a quality control tool within the food industry due to its rapid, real-time measurements. Therefore, the study aimed to assess the possibilities of using MSI as a quality control tool within seaweed cultivation to predict the physicochemical (including proximate composition, trace minerals, pH, and color), microbiological (total viable counts (TVC)), sensory, and antioxidant properties of A. esculenta and S. latissima throughout diverse processing and handling. The results showed differences in spectra between species, and species classification got 100 % accuracy when using a Support Vector Machine (SVM) with the spectral data. Furthermore, results indicated that the partial least square regression (PLSR) models developed with cross-validation of the MSI data effectively predicted multiple quality parameters, including pH (R2CV= 0.94, RMSECV = 0.278), carbohydrate content (R2CV= 0.89, RMSECV = 0.76), protein content (R2CV= 0.94, RMSECV = 0.12), ash content (R2CV= 0.80, RMSECV = 0.51), and phenolic content (R2CV= 0.992, RMSECV = 0.24). In addition, the results showed possibilities of using the technology to assess several sensory properties. In conclusion, the results show the potential of using the MSI technology as an effective quality control tool within the seaweed industry to simultaneously evaluate multiple physicochemical properties of brown seaweed biomass.

Tengiliður

Hildur Inga Sveinsdóttir

Verkefnastjóri

hilduringa@matis.is

This study explores the potential of using multispectral imaging (MSI) techniques to predict the freshness of whole gutted Atlantic cod (Gadus morhua) throughout its shelf life during storage on ice. Spectral data were acquired from key anatomical regions – the gills, skin, and eyes – and analyzed using chemometrics methods, including partial least squares regression (PLSR) and artificial neural networks (ANNs). These models were trained to predict sensory evaluations performed by trained panelists using the Quality Index Method (QIM) as well as chemical- and microbiological analyses, total viable counts (TVC) and total volatile base nitrogen (TVB-N). Among the regions analyzed, the gills provided the most accurate predictions of the QIM score, with the ANN model achieving an R²_CV = 0.87 and an RMSECV of 2.0. Spectral analysis highlights the role of near-infrared (NIR) wavelengths in capturing spoilage-related biochemical and structural changes, complementing the visible spectrum, which primarily captures color changes. Our findings suggest that MSI combined with chemometric techniques could serve as an efficient, non-destructive alternative to traditional sensory freshness evaluations.

Tengiliður

Sigurlaug Skírnisdóttir

Verkefnastjóri

sigurlaug.skirnisdottir@matis.is

Chitosan is suggested to have prebiotic properties, yet clinical evidence on its in vivo effects on the human gut microbiota and various health factors remains scarce. This study aimed to evaluate the effects of chitosan supplementation on gut microbiota composition and various health factors in Icelandic females. Sixty Icelandic females (aged 26–70; BMI 19.1–35.0 kg/m²) were randomized to a 12-week intervention receiving either 3 g/day of encapsulated chitosan (LipoSan Ultra) (TRG, n = 28) or placebo (PLG, n = 32). Anthropometrics, health factors, endurance, and health status questionnaires were collected at baseline (T1) and post-intervention (T3). All values remained within reference ranges at both timepoints in both groups, except weight, waist circumference, and fat mass, which were above. In TRG, alkaline phosphatase (ALP) levels increased, and fecal consistency shifted toward constipation. 16S rRNA microbial analysis showed decreased diversity/evenness, increased T1–T3 separation by nonmetric multidimensional scaling, and higher Actinobacteriota abundance. Genus level shifts included reduced Blautia, Eubacterium hallii, CAG-56 levels and increased Ruminococcus gnavus, Clostridium innocuum, Bifidobacterium, and Holdemania. This novel clinical study demonstrates that 12 weeks of chitosan supplementation alters gut microbiota composition without affecting general health status in females.

Tengiliður

Sigurlaug Skírnisdóttir

Verkefnastjóri

sigurlaug.skirnisdottir@matis.is

Food production systems may act as transmission routes for antimicrobial-resistant (AMR) bacteria and AMR genes (AMRGs) to humans. However, the food resistome remains poorly characterized. Here 1,780 raw-material (milk, brine, fresh meat and so on), end-product (cheese, fish, meat products and vegetables) and surface (processing, cooling, smoking, ripening and packing rooms) samples from 113 food processing facilities were subjected to whole-metagenome sequencing. Assembly-free analyses demonstrated that >70% of all known AMRGs, including many predicted to confer resistance to critically important antibiotics, circulate throughout food production chains, with those conferring resistance to tetracyclines, β-lactams, aminoglycosides and macrolides being the most abundant overall. An assembly-based analysis highlighted that bacteria from the ESKAPEE group, together with Staphylococcus equorum and Acinetobacter johnsonii, were the main AMRG carriers. Further evaluation demonstrated that ~40% of the AMRGs were associated with mobile genetic elements, mainly plasmids. These findings will help guide the appropriate use of biocides and other antimicrobials in food production settings when designing efficient antimicrobial stewardship policies.