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Norwegian Vegetables for Plant-Based Food: Understanding Challenges and Opportunities in the Vegetable Value Chain
Full text linkThis report outlines key research and actions to increase the use of Norwegian vegetables in plant-based foods by addressing barriers in pre-processing and product development. Limited pre-processing infrastructure, seasonal access and quality variation in Norwegian-based plant-food ingredients, fragmented supply chains, and high costs restrict industrial utilization and market growth. Key recommendations are to: - enhance pre-processing: Invest in facilities to handle, process, and supply vegetables efficiently into ingredients. - drive product innovation: Create consumer-friendly, tasty plant-based products with better shelf-life. - policy and collaboration: Strengthen links across the supply chain and support with targeted regulations. - engaging consumers: Educate on the benefits and uses of plant-rich diets to boost demand. These actions will improve supply chain efficiency, support sustainable consumption, and facilitate Norway's transition to a plant-rich food system.Norwegian Vegetables for Plant-Based Food: Understanding Challenges and Opportunities in the Vegetable Value ChainpublishedVersio
The effect of weather conditions from heading to harvest on gluten quality of spring wheat – A study of historical data 2005–2022
Full text linkThe gluten-viscoelastic properties are essential for breadmaking quality and are affected by both genotypes and environments, such as weather conditions. However, it is still not clear how weather conditions cause variation in gluten quality and at which stage of the grain filling they are critical. The aim of the study was to explore the relationship between weather parameters during grain filling and the viscoelastic properties of gluten. The gluten of spring wheat varieties grown over 17 seasons, resulting in a total of 70 different environments, was analyzed with the Kieffer extensibility rig. The variation in viscoelastic properties of gluten was mainly explained by environment, followed by genotype, while the genotype*environment interaction was small. The results also indicated that the periods around heading and physical maturity were the most critical when weather conditions affected the gluten quality. Our results also revealed that factors other than weather conditions are responsible for the variation in gluten quality.publishedVersio
The nasal microbiota of two marine fish species: diversity, community structure, variability and first insights into the impacts of climate change-related stressors
Full text linkVertebrate nasal microbiota (NM) plays a key role in regulating host olfaction, immunity, neuronal differentiation, and structuring the epithelium. However, little is known in fish. This study provides the first comprehensive analysis of the NM in two marine fish species, the European seabass and the Atlantic cod. Given its direct contact with the environment, fish NM is likely influenced by seawater. We analysed the community structure, specificity regarding seawater, and interindividual variability of 32 to 38 fish reared under ambient conditions. Additionally, we conducted a simulated laboratory experiment to investigate the influence of acidification and a simplified heatwave on cod NM (3 fish per replicate). High-throughput 16S rRNA sequencing revealed species-specific NM communities at the genus level with Stenotrophomonas and Ralstonia dominating seabass and cod NM, respectively. This suggests potential habitat- or physiology-related adaptations. The most abundant bacterial genera in seabass NM were alThe nasal microbiota of two marine fish species: diversity, community structure, variability and first insights into the impacts of climate change-related stressorsacceptedVersio
Genome-wide association analysis using multiple Atlantic salmon populations
Full text linkIn a previous study, we found low persistence of linkage disequilibrium (LD) phase across breeding populations of Atlantic salmon. Accordingly, we observed no increase in accuracy from combining these populations for genomic prediction. In this study, we aimed to examine if the same were true for detection power in genome-wide association studies (GWAS), in terms of reduction in p-values, and if the precision of mapping quantitative trait loci (QTL) would improve from such analysis. Since individual records may not always be available, e.g. due to proprietorship or confidentiality, we also compared mega-analysis and meta-analysis. Mega-analysis needs access to all individual records, whereas meta-analysis utilizes parameters, such as p-values or allele substitution effects, from multiple studies or populations. Furthermore, different methods for determining the presence or absence of independent or secondary signals, such as conditional association analysis, approximate conditional and joint analysis (COJO), and the clumping approach, were assessed.publishedVersio
Robust and Unified Semi-Supervised Unmixing of Hyperspectral Imaging for Linear and Multilinear Models
Full text linkThe spectral unmixing paradigm is an important analysis tool for hyperspectral (HS) images which allows one to decompose the 2D spatial information from the basic spectral signatures or endmembers. In this work, we introduce a semi-supervised perspective for spectral unmixing, where some end-members are known a priori, while the rest are estimated from the HS image. The proposal is relevant in unmixing scenarios where there is only available partial information of end-members, or when the known end-members are not fully representative of the scene. Our formulation simultaneously addresses linear and multilinear mixing models in a unified fashion. The proposed algorithms are referred as ESSEAE (Extended Semi-Supervised End-members and Abundance Extraction) for the linear model, and NESSEAE (Non-linear Extended Semi-Supervised End-members and Abundance Extraction) for the multilinear one. The estimation process is presented as a weighted optimal approximation problem with regularization terms for abundances, end-members and sparse noise components, which is solved by a cyclic coordinate descent optimization (CCDO) scheme. In this work, we derive closed-solutions at each step of the CCDO scheme, and just for the multilinear model, the end-members estimation involves a gradient descent scheme with optimal linear search. We validate first our contributions with synthetic HS images that include Gaussian and sparse noise components to evaluate their robustness, and compare them with supervised and unsupervised perspectives. In addition, we validated the linear scheme with a breast histological sample, and the multilinear approach with the Urban dataset. The use of two datasets from different fields guarantees the generalizability of the proposed formulation. In general, our semi-supervised spectral unmixing schemes provide accurate and robust results with a fast computational time, and as expected, present an overall performance in between the supervised and unsupervised approaches. All scripts for the proposed algorithms are freely available in https://github.com/Nicothe4th/ESSEAE-NESSEAE.publishedVersio
The safety assessment of microalgae-derived products as novel foods by the European Food Safety Authority
Full text linkRecent advancements in food research alongside the growing interest in new sources with enhanced nutritional value have led to an increasing development of food products derived from microalgae. Some of these products fall under the category of novel foods (NFs) in the European Union (EU) and their safety must be evaluated by the European Food Safety Authority (EFSA) before being authorised on the EU market. By August 2024, EFSA had evaluated eleven NFs derived from microalgae, including oils rich in docosahexaenoic acid (DHA) from Schizochytrium spp., whole biomass of the microalga Euglena gracilis and its derivative beta-glucan polymer (paramylon), ethanolic extract from Phaeodactylum tricornutum and oleoresin rich in astaxanthin from Haematococcus pluvialis. One of the key scientific requirements for the safety assessment of these products is the characterisation of the microalga strain, including its unambiguous taxonomic identification at species level and pathogenicity. The “Qualified Presumption of Safety” (QPS) status of the microalgae also plays a significant role in determining the safety assessment approach to be applied. Other relevant requirements comprise a thorough chemical characterisation (e.g., biotoxins, undesirable substances, heavy metals) together with microbiological and nutritional characterisation of the product, description of the manufacturing process and a toxicological and allergenicity assessment. By illustrating examples of NF that consist of, are isolated from or are produced by microalgae we highlight the main requirements needed for their safety assessment alongside the challenges encountered. Taking into account the continuous evolution of the microalga sector leading to innovative products, we also extend these requirements to the safety assessment of microalgal proteins, considering potential future mandates to assess algae-derived proteins as NFs by EFSA.publishedVersio
Clock and clock-related gene expression is light responsive in the Atlantic salmon (Salmo salar) embryo
Full text linkLight and photoperiod vary in a predictable manner throughout the daily and annual cycle that is utilized by organisms to direct processes of living. The aquaculture industry applies light to manipulate salmon development, but the effects have not yet been thoroughly investigated in early ontogeny. Here, salmon eggs and larvae were subjected to three different light regimes (continuous dark, continuous light and compressed simulated natural photoperiod [LD] to provide calendar time information). The expression of eight clock- and melatonin-related genes (clock1a.2, arntl1a.2, per1b, per2a, cry3b, nr1d1a, aanat2b, mtnr1b) was examined through one daily cycle before eyeing, after eyeing, and before start-feeding. Clock1a.2 and per2a showed indications of being maternally deposited, and expression increased for most genes through development. All genes showed clear differences in expression between light regimes, and rhythmically expressed genes were more abundant and with stronger rhythms under LD regime. Aanat2b was rhythmically expressed before eyeing, and all genes were rhythmically expressed under LD at start-feeding. Interestingly, at this time, the positive, negative, and stabilizing arm of the clock peaked simultaneously along with the melatonin-related genes mid-photophase. These results implore greater attention to the lighting conditions used during early development, as different lightings could have lasting effects.publishedVersio
Strengthening policy action to tackle social acceptability issues in European aquaculture
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Quantifying anisotropy in mozzarella cheese using spatially offset shortwave NIR spectroscopy
No full textThe anisotropic structure of Mozzarella cheese governs its texture and functionality in applications such as pizza. The pasta-filata process that forms a fibrous protein network creates anisotropy in Mozzarella. Variations in cooker-stretcher parameters, including temperature, rotor speed, and additives, affect the anisotropy and consequently the functional properties of Mozzarella. The traditional mechanical testing methods, although informative in assessing texture, do not describe the relation between macroscopic properties and molecular-level structural arrangements. This study presents a novel approach utilizing spatially offset shortwave near-infrared spectroscopy (SW-NIRS, 761–1081 nm) to characterize and quantify anisotropy in Mozzarella cheese. Nineteen designed Mozzarella samples were analyzed using two experimental setups. The first was a two-axis orthogonal measurement, where spectra were collected by measuring along two orthogonal sample axes corresponding to protein fibers aligned parallel and perpendicular to the light path. The second was a spinning setup, in which samples were placed on a rotating disc, and continuous spectra were collected over four complete 360° rotations within 40 s. Spectral data were acquired over five different distances from the illumination. Spectral variation, scattering, and absorbance were quantified using multiplicative scatter correction parameters and regression analysis, demonstrating a high correlation between anisotropy and optical measurements (r2 = 0.81). Spatially offset SW-NIRS thus provides a rapid, non-destructive tool for evaluating the structure-function relationship in Mozzarella cheese, with potential applicability to other food systems exhibiting significant anisotropic structures.publishedVersio
