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.
2019
Authors
Isabella Righini Bram Vanthoor Michel Verheul Muhammad Naseer Henk Maessen Tomas Persson I. Tsafaras Cecilia StanghelliniAbstract
No abstract has been registered
Authors
J. William Allwood Tomasz Leszek Woznicki Yun Xu Alexandre Foito Kjersti Aaby Julie Sungurtas Sabine Freitag Royston Goodacre Derek Stewart Siv Fagertun Remberg Ola M Heide Anita SønstebyAbstract
Introduction Blackcurrant (Ribes nigrum L.) is an excellent example of a “super fruit” with potential health benefits. Both genotype and cultivation environment are known to affect the chemical composition of blackcurrant, especially ascorbic acid and various phenolic compounds. Environmental conditions, like temperature, solar radiation and precipitation can also have significant impact on fruit chemical composition. The relevance of the study is further accentuated by the predicted and ongoing changes in global climate. Objectives The aim of the present study was to provide new knowledge and a deeper understanding of the effects of post flowering environmental conditions, namely temperature and day length, on fruit quality and chemical composition of blackcurrant using an untargeted high performance liquid chromatography–photo diode array–mass spectrometry (HPLC– PDA–MS) metabolomics approach. Methods A phytotron experiment with cultivation of single-stemmed potted plants of blackcurrant cv. Narve Viking was conducted using constant temperatures of 12, 18 or 24 °C and three different photoperiods (short day, short day with night interruption, and natural summer daylight conditions). Plants were also grown under ambient outdoor conditions. Ripe berries were analysed using an untargeted HPLC–PDA–MS metabolomics approach to detect the presence and concentration of molecules as affected by controlled climatic factors. Results The untargeted metabolomics dataset contained a total of 7274 deconvolved retention time-m/z pairs across both electrospray ionisation (ESI) positive and negative polarities, from which 549 metabolites were identified or minimally annotated based upon accurate mass MS. Conventional principal component analysis (PCA) in combination with the Friedman significance test were applied to first identify which metabolites responded to temperature in a linear fashion. Multi-block hierarchical PCA in combination with the Friedman significance test was secondly applied to identify metabolites that were responsive to different day length conditions. Temperature had significant effect on a total of 365 metabolites representing a diverse range of chemical classes. It was observed that ripening of the blackcurrant berries under ambient conditions, compared to controlled conditions, resulted in an increased accumulation of 34 annotated metabolites, mainly anthocyanins and flavonoids. 18 metabolites were found to be regulated differentially under the different daylength conditions. Moreover, based upon the most abundant anthocyanins, a comparison between targeted and untargeted analyses, revealed a close convergence of the two analytical methods. Therefore, the study not just illustrates the value of non-targeted metabolomics approaches with respect to the huge diversity and numbers of significantly changed metabolites detected (and which would be missed by conventional targeted analyses), but also shows the validity of the non-targeted approach with respect to its precision compared to targeted analyses. Conclusions Blackcurrant maturation under controlled ambient conditions revealed a number of insightful relationships between environment and chemical composition of the fruit. A prominent reduction of the most abundant anthocyanins under the highest temperature treatments indicated that blackcurrant berries in general may accumulate lower total anthocyanins in years with extreme hot summer conditions. HPLC–PDA–MS metabolomics is an excellent method for broad analysis of chemical composition of berries rich in phenolic compounds. Moreover, the experiment in controlled phytotron conditions provided additional knowledge concerning plant interactions with the environment.
Authors
Inge Stupak Tat Smith Nicholas Clarke Teodorita Al-Seadi Lina Beniušienė Niclas Scott Bentsen Quentin Cheung Virginia Dale Jinke van Dam Rocio Diaz-Chavez Uwe Fritsche Martyn Futter Jianbang Gan Kaija Hakala Thomas Horschig Martin Junginger Yoko Kitigawa Brian Kittler Keith Kline Charles Lalonde Søren Larsen Dagnija Lazdina Thuy P. T. Mai-Moulin Maha Mansoor Edmund Mupondwa Shyam Nair Nathaniel Newlands Liviu Nichiforel Marjo Palviainen John Stanturf Kay Schaubach Johanny Arilexis Perez Sierra Vita Tilvikiene Brian Titus Daniela Thrän Sergio Ugarte Liisa Ukonmaanaho Iveta Varnagiryte-Kabasinskiene Maria WellischAbstract
No abstract has been registered
Abstract
Faecal contamination is one of the major factors affecting biological water quality. In this study, we investigated microbial taxonomic diversity of faecally polluted lotic ecosystems in Norway. These ecosystems comprise tributaries of drinking water reservoirs with moderate and high faecal contamination levels, an urban creek exposed to extremely high faecal pollution and a rural creek that was the least faecally polluted. The faecal water contamination had both anthropogenic and zoogenic origins identified through quantitative microbial source tracking applying host‐specific Bacteroidales 16S rRNA genetic markers. The microbial community composition revealed that Proteobacteria and Bacteroidetes (70–90% relative abundance) were the most dominant bacterial phyla, followed by Firmicutes, especially in waters exposed to anthropogenic faecal contamination. The core archaeal community consisted of Parvarchaeota (mainly in the tributaries of drinking water reservoirs) and Crenarchaeota (in the rural creek). The aquatic microbial diversity was substantially reduced in water with severe faecal contamination. In addition, the community compositions diverge between waters with dominant anthropogenic or zoogenic pollution origins. These findings present novel interpretations of the effect of anthropo‐zoogenic faecal water contamination on microbial diversity in lotic ecosystems.
Abstract
No abstract has been registered
Authors
Tor J. JohansenAbstract
No abstract has been registered
Authors
Tore SkrøppaAbstract
No abstract has been registered
Abstract
Global Forest Watch (GFW) provides a global map of annual forest cover loss (FCL) produced from Landsat imagery, offering a potentially powerful tool for monitoring changes in forest cover. In managed forests, FCL primarily provides information on commercial harvesting. A semi-autonomous method for providing data on the location and attributes of harvested sites at a landscape level was developed which could significantly improve the basis for catchment management, including risk mitigation. FCL in combination with aerial images was used for detecting and characterising harvested sites in a 1607 km2 mountainous boreal forest catchment in south-central Norway. Firstly, the forest cover loss map was enhanced (FCLE) by removing small isolated forest cover loss patches that had a high probability of representing commission errors. The FCLE map was then used to locate and assess sites representing annual harvesting activity over a 17-year period. Despite an overall accuracy of >98%, a kappa of 0.66 suggested only a moderate quality for detecting harvested sites. While errors of commission were negligible, errors of omission were more considerable and at least partially attributed to the presence of residual seed trees on the site after harvesting. The systematic analysis of harvested sites against aerial images showed a detection rate of 94%, but the area of the individual harvested site was underestimated by 29% on average. None of the site attributes tested, including slope, area, altitude, or site shape index, had any effect on the accuracy of the area estimate. The annual harvest estimate was 0.6% (standard error 12%) of the productive forest area. On average, 96% of the harvest was carried out on flat to moderately steep terrain (<40% slope), 3% on steep terrain (40% to 60% slope), and 1% on very steep terrain (>60% slope). The mean area of FCLE within each slope category was 1.7 ha, 0.9 ha, and 0.5 ha, respectively. The mean FCLE area increased from 1.0 ha to 3.2 ha on flat to moderate terrain over the studied period, while the frequency of harvesting increased from 249 to 495 sites per year. On the steep terrain, 35% of the harvesting was done with cable yarding, and 62% with harvester-forwarder systems. On the very steep terrain (>60% slope), 88% of the area was harvested using cable yarding technology while harvesters and forwarders were used on 12% of the area. Overall, FCL proved to be a useful dataset for the purpose of assessing harvesting activity under the given conditions.
Authors
Xiao Huang Chaoqing Yu Tongbi Tu Shaoqiang Ni ShengChao Qiao Jim W Hall Mats Höglind Hanna Marika SilvennoinenAbstract
In the past decade, China imported massive quantities of soybean from the international market to meet its increasing domestic demand for protein[1]. However, China’s soybean imports from US decreased from 32.86 Mt (Million tons, 34% of the total 95.54 Mt) in 2017 to 16.64 Mt (19% of the total 88.03 Mt) in 2018[2] due to the China-US trade war. To reduce China’s reliance on imports, the Chinese government has been making policy incentive, e.g. higher subsidies, to encourage farmers for soybean cultivation. Traditionally Northeast China is the key production area for soybean. Soybean cultivation is tightly linked to the regional climate and environment. On the one hand, the local soybean growth is vulnerable[3] to the frequent meteorological hazards (e.g. droughts, floods) in the Northeast China[4]. The meteorological risks for soybean production in this area still remain unknown. On the other hand, albeit with relatively high production cost[5] and low water use efficiency[6], the local soybean cultivation is expected to effectively improve the nitrogen use efficiency and therefore alleviate the growing environment pollutions in this region[7]. Yet so far there are few quantitative research being reported on this environmental issue. Our research aims to explore both the meteorological risks and environmental costs of the policy-driven soybean expansion. We have developed a new version of the soybean growth algorithms within the DNDC (DeNitrification-DeComposition) model including nitrogen biogeochemical processes and performed regional simulations for soybean-related cropping systems in Northeast China. We will present the following results by combining model outputs and observations: (i) potential yield and the meteorological risks of soybean cultivation; (ii) fertilizer reduction in different crop rotation systems and the corresponding benefits to water ecosystem; and (iii) consequences of different policy scenarios (e.g. change in subsidy, GMO permission) to soybean production and environment.
Authors
Valentina Gallina Silvia Torresan Alex Zabeo Jonathan Rizzi Sandro Carniel Mauro Sclavo Lisa Pizzol Antonio Marcomini Andrea CrittoAbstract
Coastal erosion is an issue of major concern for coastal managers and is expected to increase in magnitude and severity due to global climate change. This paper analyzes the potential consequences of climate change on coastal erosion (e.g., impacts on beaches, wetlands and protected areas) by applying a Regional Risk Assessment (RRA) methodology to the North Adriatic (NA) coast of Italy. The approach employs hazard scenarios from a multi-model chain in order to project the spatial and temporal patterns of relevant coastal erosion stressors (i.e., increases in mean sea-level, changes in wave height and variations in the sediment mobility at the sea bottom) under the A1B climate change scenario. Site-specific environmental and socio-economic indicators (e.g., vegetation cover, geomorphology, population) and hazard metrics are then aggregated by means of Multi-Criteria Decision Analysis (MCDA) with the aim to provide an example of exposure, susceptibility, risk and damage maps for the NA region. Among seasonal exposure maps winter and autumn depict the worse situation in 2070–2100, and locally around the Po river delta. Risk maps highlight that the receptors at higher risk are beaches, wetlands and river mouths. The work presents the results of the RRA tested in the NA region, discussing how spatial risk mapping can be used to establish relative priorities for intervention, to identify hot-spot areas and to provide a basis for the definition of coastal adaptation and management strategies.