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.
2025
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Lucas K. Johnson Zhiqiang Yang Angela Erb Ryan Bright Grant M. Domke Tracey S. Frescino Crystal B. Schaaf Sean P. HealeyAbstract
No abstract has been registered
Authors
Andres Perea Sajidur Rahman Huiying Chen Andrew Cox Shelemia Nyamuryekung'e Mehmet Bakir Huping Cao Richard Estell Brandon Bestelmeyer Andres F. Cibils Santiago A. UtsumiAbstract
No abstract has been registered
Abstract
Chocolate spot (CS), caused by Botrytis fabae, is one of the most destructive fungaldiseases affecting faba bean (Vicia faba L.) globally. This study evaluated 33 fababean cultivars across two locations and over 2 years to assess genetic resistance andthe effect of fungicide application on CS progression. The utility of unmanned aerialvehicle–mounted multispectral camera for disease monitoring was examined. Signif-icant variability was observed in cultivar susceptibility, with Bolivia exhibiting thehighest level of resistance and Louhi, Sampo, Vire, Merlin, Mistral, and GL Sunriseproving highly susceptible. Fungicide application significantly reduced CS severityand improved yield. Analysis of canopy spectral signatures revealed the near-infraredand red edge bands, along with enhanced vegetation index (EVI) and soil adjustedvegetation index, as most sensitive to CS infection, and they had a strong negativecorrelation with CS severity ranging from −0.51 to −0.71. In addition, EVI enabledearly disease detection in the field. Support vector machine accurately classified CSseverity into four classes (resistant, moderately resistant, moderately susceptible, andsusceptible) based on spectral data with higher accuracy after the onset of diseasecompared to later in the season (accuracy 0.75–0.90). This research underscores thevalue of integrating resistant germplasm, sound agronomic practices, and spectralmonitoring for effectively identification and managing CS disease in faba bean
Authors
Frank Thomas Ndjomatchoua Richard Olaf James Hamilton Stutt Ritter Atoundem Guimapi Luca Rossini Christopher A GilliganAbstract
No abstract has been registered
Authors
Frank Thomas Ndjomatchoua Richard Olaf James Hamilton Stutt Ritter Atoundem Guimapi Luca Rossini Christopher A. GilliganAbstract
Empirical field data and simulation models are often used separately to monitor and analyse the dynamics of insect pest populations over time. Greater insight may be achieved when field data are used directly to parametrize population dynamic models. In this paper, we use a differential evolution algorithm to integrate mechanistic physiological-based population models and monitoring data to estimate the population density and the physiological age of the first cohort at the start of the field monitoring. We introduce an ad hoc temperature-driven life-cycle model of Bemisia tabaci in conjunction with field monitoring data. The likely date of local whitefly invasion is estimated, with a subsequent improvement of the model’s predictive accuracy. The method allows computation of the likely date of the first field incursion by the pest and demonstrates that the initial physiological age somewhat neglected in prior studies can improve the accuracy of model simulations. Given the increasing availability of monitoring data and models describing terrestrial arthropods, the integration of monitoring data and simulation models to improve model prediction and pioneer invasion date estimate will lead to better decision-making in pest management.
Authors
Christophe Moni Eva Farkas Claire Coutris Hanna Marika Silvennoinen Anders Aas Marit Almvik Liang Wang Kathinka Lang Xingang Liu Marianne StenrødAbstract
Biochar and pesticides are likely to be increasingly used in combination in agricultural soils, yet their combined effects on climate change mitigation remain unexplored. This study presents an 8-month incubation experiment with different soil types (silt loam and sandy loam), biochars (corncob and corn stem), and pesticides (with and without a pesticide mixture), during which CO2 production from soil organic matter (SOM) and biochar mineralisation was monitored using isotopic methods. A comprehensive modelling approach, describing all mineralisation results over the entire incubation with a reduced set of parameters, was employed to isolate the effects of biochar, pesticides, and their interactions across soil types and carbon pools, and captured the dynamic effect of biochar on SOM mineralisation. Over 99.5% of biochars remained inert after 8 months, confirming the role of biochar as a carbon sequestration technology. Biochar addition showed higher SOM stabilisation potential in soil with high clay content compared to soil with low clay content. This suggests that biochar amendment should be considered carefully in clay-depleted soils, as it could result in a loss of native SOM. Corn stem biochar, characterised by high surface area and low C/N ratio, demonstrated higher SOM stabilisation potential than corncob biochar with low surface area and high C/N ratio. Pesticide application reduced SOM mineralisation by 10% regardless of soil and biochar types. Finally, the interaction between corncob biochar and pesticides further reduced SOM mineralisation by 5%, while no interactive effect was observed with corn stem biochar. These findings highlight the importance of considering biochar-pesticide interactions when evaluating the impact of biochar amendments on native SOM stability.
Abstract
No abstract has been registered
Abstract
Data from the Norwegian national forest inventory spanning from 1994 to 2022 were analyzed to explore the growth dynamics of pure and mixed stands of Norway spruce and Scots pine. The derived large dataset enabled the development of models designed to assess how stand characteristics and drought interactively affect volume increment at the stand and individual tree level. The analysis revealed that pine-dominated stands outperform spruce-dominated stands at lower site qualities, while the opposite was true at higher site qualities. Mixed stands exhibited overyielding, with productivity exceeding the expected combined pure stand productivity of the individual species components. Based on model predictions, relative overyielding increased with stand age and declined with increasing site quality. Transgressive overyielding, where mixed stands outperform pure stands of either species, was predicted for medium site qualities. Drought-induced productivity losses increased with spruce proportion, especially at lower site qualities, and with stand density. The presence of pine in mixed stands mitigated the negative effects of drought on spruce. The findings of this study suggest that pure spruce stands should be avoided on lower-quality sites while mixed stands with appropriate thinning interventions should be promoted to maintain productivity under changing climatic conditions.