Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

2023

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Abstract

Black soldier fly larvae (BSFL) Hermetia illucens is fastest growing and most promising insect species especially recommended to bring high-fat content as 5th generation bioenergy. The fat content can be fully optimized during the life-cycle of the BSFL through various organic dietary supplements and environmental conditions. Enriched fat can be obtained during the larval stages of the BSF. The presence of high saturated and unsaturated fatty acids in their body helps to produce 70 % of extractable oil which can be converted into biodiesel through transesterification. The first-generation biodiesel process mainly depends on catalytic transesterification, however, BSFL had 94 % of biodiesel production through non-catalytic transesterification. This increases the sustainability of producing biodiesel with less energy input in the process line. Other carbon emitting factors involved in the rearing of BSFL are less than the other biodiesel feedstocks including microalgae, cooking oil, and non-edible oil. Therefore, this review is focused on evaluating the optimum dietary source to produce fatty acid rich larvae and larval growth to accumulate C16–18 fatty acids in larger amounts from agro food waste. The process of optimization and biorefining of lipids using novel techniques have been discussed herein. The sustainability impact was evaluated from the cultivation to biodiesel conversion with greenhouse gas emissions scores in the entire life-cycle of process flow. The state-of-the-art in connecting circular bioeconomy loop in the search for bioenergy was meticulously covered.

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Abstract

Ongoing efforts focus on quantifying plastic pollution and describing and estimating the related magnitude of exposure and impacts on human and environmental health. Data gathered during such work usually follows a receptor perspective. However, Life Cycle Assessment (LCA) represents an emitter perspective. This study examines existing data gathering and reporting approaches for field and laboratory studies on micro- and nanoplastics (MNPs) exposure and effects relevant to LCA data inputs. The outcomes indicate that receptor perspective approaches do not typically provide suitable or sufficiently harmonised data. Improved design is needed in the sampling, testing and recording of results using harmonised, validated and comparable methods, with more comprehensive reporting of relevant data. We propose a three-level set of requirements for data recording and reporting to increase the potential for LCA studies and models to utilise data gathered in receptor-oriented studies. We show for which purpose such data can be used as inputs to LCA, particularly in life cycle impact assessment (LCIA) methods. Implementing these requirements will facilitate proper integration of the potential environmental impacts of plastic losses from human activity (e.g. litter) into LCA. Then, the impacts of plastic emissions can eventually be connected and compared with other environmental issues related to anthropogenic activities.

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Seaweed is considered a potentially sustainable source of protein for human consumption, and rapid, accurate methods for determining seaweed protein contents are needed. Seaweeds contain substances which interfere with common protein estimation methods however. The present study compares the Lowry and BCA protein assays and protein determination by N-ratios to more novel spectroscopic methods. Linear regression of the height or the integrated area under the Amide II band of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) was used to predict seaweed protein with good prediction performance. Partial least squares regression (PLSR) was performed on both DRIFTS and near-infrared (NIR) spectra, with even higher prediction accuracy. Spectroscopy performed similar to or better than the calculated N-ratio of 4.14 for protein prediction. These spectral prediction methods require minimal sample preparation and chemical use, and are easy to perform, making them environmentally sustainable and economically viable for rapid estimation of seaweed protein.

2022

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Abstract

Rubus idaeus L. (red raspberry), is a perennial woody plant species of the Rosaceae family that is widely cultivated in the temperate regions of world and is thus an economically important soft fruit species. It is prized for its flavour and aroma, as well as a high content of healthful compounds such as vitamins and antioxidants. Breeding programs exist globally for red raspberry, but variety development is a long and challenging process. Genomic and molecular tools for red raspberry are valuable resources for breeding. Here, a chromosome-length genome sequence assembly and related gene predictions for the red raspberry cultivar ‘Anitra’ are presented, comprising PacBio long read sequencing scaffolded using Hi-C sequence data. The assembled genome sequence totalled 291.7 Mbp, with 247.5 Mbp (84.8%) incorporated into seven sequencing scaffolds with an average length of 35.4 Mbp. A total of 39,448 protein-coding genes were predicted, 75% of which were functionally annotated. The seven chromosome scaffolds were anchored to a previously published genetic linkage map with a high degree of synteny and comparisons to genomes of closely related species within the Rosoideae revealed chromosome-scale rearrangements that have occurred over relatively short evolutionary periods. A chromosome-level genomic sequence of R. idaeus will be a valuable resource for the knowledge of its genome structure and function in red raspberry and will be a useful and important resource for researchers and plant breeders.

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Abstract

Berries of the genus Vaccinium are highly valued health-beneficial superfoods, which are commonly subjected to adulteration and mixed with each other, or with other common berry species. A quantitative DNA-based method utilizing a chip-based digital polymerase chain reaction (dPCR) technique was developed for identifying and quantifying wild lingonberry (V. vitis-idaea) and cultivated American cranberry (V. macrocarpon). The dPCR method with species-specific primers for mini-barcoding was designed based on the indel regions found in the trnI-CAU–trnL-CAA locus in the chloroplast genome. The designed primers were able to amplify only target species, enabling to distinguish the two closely related species with good sensitivity. Our results illustrated the ability of the method to identify lingonberry and American cranberry DNA using PCR without the need for probes or further sequencing. The dPCR method could also quantify the DNA copy number in mixed samples. Based on this study, the method provides a basis for a simple, fast, and sensitive quantitative authentication analysis of lingonberry and American cranberry by dPCR. Moreover, it can also provide a platform for authentication analyses of other plant species as well by utilizing the indel regions of chloroplast genomes.