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
Authors
Heidi Udnes Aamot Adnan Šišić Lars Olav Brandsæter Silje Kvist Simonsen Birgitte Henriksen Jörg Peter BareselAbstract
Over the past decades, significant efforts have been made to promote the cultivation of legumes. Cultivation of legumes, particularly grain legumes, can reduce the use of mineral nitrogen fertilizers, enhance biodiversity, reduce dependence on imported feed proteins, and improve soil biological properties and humus content. Despite these efforts, grain legumes are still not widely grown. One major obstacle to legume cultivation is "legume fatigue". Legume fatigue limits the expansion of legume cultivation in many European regions. The exact causes of legume fatigue are not fully understood, but soil-borne diseases interacting with abiotic factors are believed to play a key role. Recent findings suggest that the balance between pathogen load and soil suppressiveness is critical. Some farms and regions do not report legume fatigue as a problem, while others experience severe limitations in legume production. Identifying the causes of this variation is urgent and requires a collaborative effort that covers different environments and includes comprehensive assessments of both biotic and abiotic factors. In a recently launched project, LeFaSus, a network of farms and long-term experiments has been established to identify the primary factors contributing to legume fatigue. This network spans a transect from southern to northern Europe, including Italy, Germany, Luxembourg, and Norway. The project aims to deliver a reliable set of indicators for both legume fatigue and disease-suppressive soils, linking these indicators to the management practices that likely influenced them. The background and plans for the project will be presented.
Abstract
No abstract has been registered
Authors
Heidi Udnes Aamot Magne Nordang Skårn Chloé Grieu Anne-Grete Roer Hjelkrem Katherine Ann Gredvig Nielsen Silje Kvist Simonsen Nora Steinkopf Anne Kjersti Uhlen Guro BrodalAbstract
Chocolate spot (CS) is one of the most destructive diseases affecting faba beans worldwide, leading to yield reductions of up to 90% in susceptible cultivars under conducive environmental conditions. Traditionally, the disease has been attributed to the fungal pathogens Botrytis fabae and Botrytis cinerea, however recent studies have identified three additional Botrytis species capable of causing the disease. Fungicide applications during flowering are commonly used to control the disease and limit damage to pod set, but this approach is not always effective. The reasons for this lack of control are not fully understood. To increase our understanding of the CS species complex in Norway, we used species-specific PCR to identify different Botrytis species in symptomatic leaves collected at various locations and years. Some Botrytis species are known to be high-risk pathogens for fungicide resistance development, but resistance in Norwegian Botrytis populations in faba bean have not previously been studied. Therefore, we obtained Botrytis isolates from diseased leaves and used a mycelial growth assay to assess their response to the active ingredients (boscalid and pyraclostrobin) in the fungicide commonly used for CS control in Norway. Resistance to both boscalid and pyraclostrobin was detected among B. cinerea isolates, while only resistance to boscalid was detected among B. fabae isolates. To elucidate resistance mechanisms, we analyzed target gene sequences for the presence of mutations known to confer resistance to the two active ingredients. Field experiments were conducted to test the efficacy of various spray timings and fungicides in early and late faba bean varieties. Additionally, we are developing a disease risk model for CS to better understand the conditions that lead to disease and to improve the timing of fungicide applications.
Authors
Alexey Mikaberidze Christian Cruz Ayalsew Zerihun Abel Barreto Pieter S. Beck Rocío Calderón Carlos Camino Rebecca Campbell Stephanie Delalieux Frederic Fabre Elin Falla Stuart Fraser Kaitlin Gold Carlos Gongora-Canul Frédéric Hamelin Dalphy Ondine Camira Harteveld Cheng-Fang Hong Melen Leclerc Da-Young Lee Murillo Lobo Jr Anne-Katrin Mahlein Emily McLay Paul Melloy Stephen Parnell Uwe Rascher Jack Rich Irene Sarlotti Samuel Soubeyrand Susie Sprague Antony Surano Sandhya Takooree Thomas Taylor Suzanne Touzeau Pablo Zarco-Tejada Nik CunniffeAbstract
Plant diseases impair yield and quality of crops and threaten the health of natural plant communities. Epidemiological models can predict disease and inform management. However, data are scarce, since traditional methods to measure plant diseases are resource intensive and this often limits model performance. Optical sensing offers a methodology to acquire detailed data on plant diseases across various spatial and temporal scales. Key technologies include multispectral, hyperspectral and thermal imaging, and light detection and ranging; the associated sensors can be installed on ground-based platforms, uncrewed aerial vehicles, aeroplanes and satellites. However, despite enormous potential for synergy, optical sensing and epidemiological modelling have rarely been integrated. To address this gap, we first review the state-of-the-art to develop a common language accessible to both research communities. We then explore the opportunities and challenges in combining optical sensing with epidemiological modelling. We discuss how optical sensing can inform epidemiological modelling by improving model selection and parameterisation and providing accurate maps of host plants. Epidemiological modelling can inform optical sensing by boosting measurement accuracy, improving data interpretation and optimising sensor deployment. We consider outstanding challenges in: A) identifying particular diseases; B) data availability, quality and resolution, C) linking optical sensing and epidemiological modelling, and D) emerging diseases. We conclude with recommendations to motivate and shape research and practice in both fields. Among other suggestions, we propose to standardise methods and protocols for optical sensing of plant health and develop open access databases including both optical sensing data and epidemiological models to foster cross-disciplinary work.
Abstract
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
Abstract
No abstract has been registered
Authors
Jarkko Hantula Malin Elfstrand Anne-Maarit Hekkala Ari Hietala Juha Honkaniemi Maartje Klapwijk Matti Koivula Juho Matala Jonas Rönnberg Juha Siitonen Fredrik WidemoAbstract
• Damage from wind, snow, spruce bark beetle, and large pine weevil are likely to be less severe in CCF than in RF. However, the conversion of RF to CCF may briefy expose stands to windthrow. • Browsing by large herbivores on saplings may limit regeneration of tree species other than spruce in continuous cover forestry and reduce tree species diversity, but alternative silvicultural practices may also increase forage availability in the feld and shrub layer. Browsing damage outcomes for saplings in CCF are diffcult to predict. • For many types of damage in CCF, substantial knowledge gaps complicate the assessment of damage risk.
Abstract
No abstract has been registered