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.
2017
Authors
Graham Alan Ormondroyd Gry Alfredsen Raghavalu Thirumalai Durai Prabhakaran Simon F. Curling Bronia K. Stefanowski Morwenna J. Spear Lone RossAbstract
Microbiological degradation of wood by decay fungi can cause a rapid change in the structural properties of timber which can result in both strength and mass loss. Traditional techniques for the evaluation of decay (e.g. mass loss) lack the sensitivity to evaluate the effects of the very first stages of the decay process. This paper describes the effects of initial brown rot decay, defined by the amount of Poria placenta genomic DNA (gDNA) present in the samples, on the dynamic mechanical properties of the timber. It was found that there is a correlation between the mean storage modulus of the timber and the amount of P. placenta gDNA present, and therefore the level of decay. This shows that using dynamic mechanical analysis is a viable technique that can be used to study initial decay processes.
Abstract
No abstract has been registered
Authors
Monica Suarez Korsnes Reinert KorsnesAbstract
Korsnes, Monica Suarez; Korsnes, Reinert. Mitotic catastrophe in BC3H1 cells following yessotoxin exposure. Frontiers in Cell and Developmental Biology 2017 ;Volum 5.(30)
Authors
Johannes M. Baveco Anne Kari Bergjord Olsen Jarle W. Bjerke Magda E. Chudzinska Loïc Pellissier Caroline E. Simonsen Jesper Madsen Ingunn Tombre Bart A. NoletAbstract
No abstract has been registered
Authors
Dionisio Andújar Xavier Rodriguez Victor Rueda-Ayala Carolina San Martín Angela Ribeiro César Fernández-Quintanilla José DoradoAbstract
New technologies, such as Differential Global Positioning Systems (DGPS) and Geographic Information Systems (GIS), may be useful in order to create models to predict the spatio-temporal behaviour of weeds. The aim of this study was to generate a geometric model able to predict the patch expansion of S. halepense, a problematic perennial weed in maize crops in Central Spain. From previous infestation maps, the model describes new possible spreading areas for the upcoming growing season, and therefore, herbicide treatments can be planned on time. Two different experiments were implemented, in which initial patch density and size were examined. Patches of different size (1, 10 and 100 m2) and density (4, 20 and 100 shoots m−2), were established. These patches were visually identified, their perimeter defined and their density characterized, during three growing seasons (from 2008 to 2010 campaigns). According to this information different descriptors were built: (1) area and density of each patch; (2) the relative growth in width and length, according to space and time and compared with previous years; and (3) the increased density ratio, calculated in relation of patch size and distance to previous patch in the new infestation areas of expansion. All these descriptors were added to the model in order to predict the patch expansion in the last studied season (i. e., 2010) using previous maps (i. e., season 2008 and 2009). The model uses geometrical assimilation to predict, and two expansion assumptions were considered: (a) a conservative approach based on triangular geometry; and (b) a rectangular geometry which maximizes the simulated infested area. The results were compared with the ground truth map created in 2010. Each method showed weaknesses and strengths. The triangular approach minimized the infested area, mainly in the small patches, and therefore it could predict the expansion of previously established patches, but not the emergence of new ones. In contrast, the rectangular approach simulated the position of new foci, maximizing the infested area. Therefore, although a substantial reduction of herbicides is possible using both models, a final decision must be taken individually for each field.
Authors
Kine Svensson Oda Kjørlaug Svein Jarle Horn Jane Wittrup_AggerAbstract
Bio-Methane Potential (BMP) tests are used to evaluate the suitability of a biomass for anaerobic digestion. BMP data are usually presented as the amount of methane produced from a kilogram of volatile solids (VS) or chemical oxygen demand (COD) of the substrate. However, the most used methods for determination of VS and COD are not always accurate. Oven drying may underestimate VS content due to loss of volatile organic compounds, and incomplete chemical oxidation may lead to underestimation of COD content. Bomb calorimetry is an attractive alternative to COD measurements, because the physical state of the biomass sample does not influence the measurement, and because sample preparation is limited. In this study, 11 biomass samples, wet and dry, were analyzed with different methods for organic content determination. COD (determined by bomb calorimetry and by wet chemistry) and VS (by Karl Fischer titration and loss on drying; LOD) were compared, and used for determination of BMP. In general, the BMP estimated on a VS basis were higher than those estimated on COD basis. For certain biomass samples the method for VS determination also greatly influenced the results; for fishery waste the BMP was estimated as 928 L kg−1 based on LOD-VS compared to 394 L kg−1 based on KF-LOD. Thus, this study shows that determination of organic content is not trivial and the method of choice strongly influences the estimation of bio-methane potentials. Bomb calorimetry offers a possibility to measure energy content directly, independent of biomass composition and physical state.
Abstract
Pine wood nematode (PWN), Bursaphelenchus xylophilus, is a threat for pine species (Pinus spp.) throughout the world. The nematode is native to North America, and invaded Japan, China, Korea, and Taiwan, and more recently Portugal and Spain. PWN enters new areas through trade in wood products. Once established, eradication is not practically feasible. Therefore, preventing entry of PWN into new areas is crucial. Entry risk analysis can assist in targeting management to reduce the probability of entry. Assessing the entry of PWN is challenging due to the complexity of the wood trade and the wood processing chain. In this paper, we develop a pathway model that describes the wood trade and wood processing chain to determine the structure of the entry process. We consider entry of PWN through imported coniferous wood from China, a possible origin of Portuguese populations, to Europe. We show that exposure increased over years due to an increase in imports of sawn wood. From 2000 to 2012, Europe received an estimated 84 PWN propagules from China, 88% of which arose from imported sawn wood and 12% from round wood. The region in Portugal where the PWN was first reported is among those with the highest PWN transfer per unit of imported wood due to a high host cover and vector activity. An estimated 62% of PWN is expected to enter in countries where PWN is not expected to cause the wilt of pine trees because of low summer temperatures (e.g., Belgium, Sweden, Norway). In these countries, PWN is not easily detected, and such countries can thus serve as potential reservoirs of PWN. The model identifies ports and regions with high exposure, which helps targeting monitoring and surveillance, even in areas where wilt disease is not expected to occur. In addition, we show that exposure is most efficiently reduced by additional treatments in the country of origin, and/or import wood from PWN-free zones. Pathway modelling assists plant health managers in analyzing risks along the pathway and planning measures for enhancing biosecurity.
Abstract
Fields experiments were conducted during two growing seasons (2010–2011 and 2012–2013) at three seeding dates to identify stink bug (Hemiptera: Pentatomidae) species and to determine their seasonal population density fluctuation and damage caused to three common bean (Phaseolus vulgaris L.) cultivars “Ica Pijao,” “Cubacueto 25–9,” and “Chévere.” Stink bug species observed were Nezara viridula (L.), Piezodorus guildinii (Westwood), Chinavia rolstoni (Rolston), Chinavia marginatum (Palisot de Beauvois), and Euschistus sp. The most prevalent species was N. viridula in both seasons. The largest number of stink bugs was found in beans seeded at the first (mid September) and third (beginning of January) seeding dates. Population peaked at BBCH 75 with 1.75, 0.43, and 1.25 stink bugs/10 plants in 2010–2011 and with 2.67, 0.45, and 1.3 stink bugs/10 plants in 2012–2013 in the fields seeded the first, second, and third seeding dates, respectively. The lowest numbers of stink bugs were found in beans seeded at the second (mid November) seeding date. A significant negative correlation between relative humidity and number of stink bugs was found in 2010–2011, and a similar tendency was observed in 2012–2013. The highest seed and pod damage levels occurred in cv. “Chévere” and the lowest in cv. “ICA Pijao” during both seasons. Results suggest that cv. “ICA Pijao” and the second (mid November) seeding date is the best choice to reduce stink bug damage.
Authors
Eduarda Molina-Alcaide Maria Dolores Carro Michael Roleda Martin Riis Weisbjerg Vibeke Lind Margarita Novoa-GarridoAbstract
Author's accepted version (post-print). Available from 29/03/2018.
Authors
Margarita Novoa-Garrido Celine Rebours Lise Aanensen Torfinn Torp Vibeke Lind Håvard SteinshamnAbstract
Author's accepted version (post-print). This is an Accepted Manuscript of an article published by Taylor & Francis in Acta agriculturae Scandinavica. Section A, Animal science on 16/04/2017, available online: http://wwww.tandfonline.com/10.1080/09064702.2017.1310287.