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.
2026
Authors
Desalegn Chala Diress Tsegaye Alemu Habtamu Alem Belachew Asalf Tadesse Melesse Eshetu_Moges Nega Tassie Abate Ayalew Wondie Aklilu Tilahun Tadesse Abebayehu Aticho Alemu Gonsamo Lanhui Wang Erick Lundgren Jeffrey Kerby Jens Christian SvenningAbstract
Abstract Water hyacinth is among the world’s most damaging aquatic invasive plants, forming dense mats that disrupt ecosystem functioning, fisheries, navigation, and livelihoods across tropical and subtropical freshwater systems. Its rapid spread is driven by clonal propagation, short life cycles, and prolific seed production, particularly under nutrient-enriched conditions. Although mechanical, chemical, and biological control methods are widely applied, their long-term effectiveness remains uncertain when underlying eutrophication persists. Here, we present a large-scale, one-time water hyacinth removal campaign in Lake Tana, Ethiopia’s largest lake and a UNESCO Biosphere Reserve, as a representative nutrient-rich tropical freshwater system. Using high-resolution satellite imagery, we quantified coverage one month before removal, one month after removal, and one year later. We integrated SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis with a socio-ecological system map to assess mitigation mechanisms and identify sustainable management pathways capable of providing long-term solutions to halt water hyacinth proliferation in freshwater bodies. The campaign removed over 75% (~1271 ha) of water hyacinth, yet within one year the plant resurged to levels ~18% higher than pre-removal. This rebound highlights the ecological resilience of water hyacinth and the limitations of short term, noncontinuous control strategies. Our analysis identifies unmanaged catchment nutrient inputs as the primary driver of proliferation. Lake Tana serves as a model system demonstrating that water hyacinth functions less as a traditional invader and more as a bioindicator of eutrophication. We propose a transferable conceptual and methodological framework combining continuous removal, catchment-based nutrient management, and circular bioeconomy approaches, offering globally relevant lessons for sustainable management of nutrient-enriched tropical freshwater systems.
Authors
Hanna Huitu Tor-Einar Skog Christophe Pradal Antonio Calatayud Tor Skaslien Brita Linnestad Ari Ronkainen Christian Fournier Marc Labadie Dave Skirvin Matti Pastell David Melchior Johannes Tobiassen Langvatn Berit NordskogAbstract
Decision support systems (DSS) in crop protection provide valuable support for pest risk prognosis and recommendations for pest control, enabling farmers to make better-informed decisions. As a part of the European Union’s strategy for the sustainable use of plant protection products, the “IPM Decisions” project developed an online platform that gives farmers and advisors access to a wide range of DSS for major pests, weeds, and diseases in a variety of crops across Europe. Multiple DSS models relevant for different crops and geographical regions of Europe were selected for integration in the platform. Information on the models is compiled into a model catalogue, which serves as a core component of the IPM Decisions platform. To facilitate the use of these models, two application programming interfaces (APIs) were developed. In line with the FAIR (findable, accessible, interoperable, and reusable) principles, the DSS API provides access to models and their metadata, including descriptions of input and output parameters. The weather API enables access to European online weather data sources and adapts this data to meet the requirements of DSS models. While these APIs are integrated into the IPM decisions platform, they are also open source, allowing other crop protection and farm management software to inspect, download, modify, install, run, and use them. In this article, we describe the development of the DSS and weather APIs, outline their structure and definitions, and present the services that DSS API and weather API provide. Finally, we demonstrate their application through three practical use cases.
Abstract
The study presents the results of nine years of field observations of ascospore release of Venturia inaequalis in the Skierniewice area in central Poland. In total, spores were trapped 221 times during 2005–2008 and 2010– 2014. Of these, 142 episodes lasted for less than 8 hours, 69 lasted from 8 to 29 hours, and 10 episodes lasted from 30 to 93 hours. Spore releases started in spring from 25 March to 28 April and ended from 27 May to 17 June, and the season for ascospore release lasted from 43 to 76 days, with an average of 58 days. During 139 ascospore releases, less than 1 000 spores per cubic meter of air were collected and during 25 discharges more than 10 000 spores were trapped. Releases of ascospores were highly related to rainfall and daylight. Two-thirds (67%) of the spores were trapped during rain. Only 12% of the discharges occurred without any registered rain, accounting for 7% of all trapped spores. Nearly three fourth (73%) of all ascospore release hours occurred in daylight, and 91% of the spores were trapped in daytime. Rainy nights with constant leaf wetness were observed, during which no spore releases occurred despite the rainfall. Ascospore releases were also less prominent at the beginning and end of the season and after weak rains. Rain was most effective as the trigger of discharges at temperature between 5 and 13 °C and when global radiation coinciding with rainfall was below 700 W/m2. In conclusion, the study confirms the dominant role of daytime rainfall in the release of ascospores by Venturia inaequalis.
Abstract
Disease symptoms, sources of inoculum, and patterns of spore release of Mycosphaerella ribis, the cause of Mycosphaerella leaf spot, were studied over three years in an organic blackcurrant planting receiving no fungicide applications. In addition to typical foliar symptoms, also fruit lesions were observed on the cultivars included in the study. Ascospores from leaf litter on the ground were trapped from bud break in April to mid-to-late July, but 99% were released by one month before. Conidia formed in old fruit cluster stalks overwintering on the blackcurrant shrubs were present from bud break to early August, but 99% were trapped from late May to mid-July. Conidia were found in leaf litter but were never captured in the spore trap, and ascospores were observed in old fruit cluster stalks. Degree-day models (base = 0˚C) were used to estimate the proportion of mature spores. Extended periods of dry conditions slowed spore maturation in the field. Models halting degree-day accumulation after 4 or 7 days with no rain (< 0.2 mm) or leaf wetness of < 12 h per day, gave the best performance for release of conidia or ascospores, respectively, if validated by data from controlled conditions in the laboratory. Ascospore release was suppressed during night, and if rain and wetness started during night and continued the following day, very few spores were released before sunrise. The present investigation provides new information that may be used when planning sanitary measures to reduce primary inoculum and predict spore release patterns for Mycosphaerella leaf spot.
Abstract
No abstract has been registered
Abstract
Background The soil-borne oomycete Phytophthora cactorum causes crown rot, a major disease of the allo-octoploid strawberry (Fragaria × ananassa Duch., 2n = 8× = 56) that limits cultivation worldwide. Resistance to P. cactorum is a highly desirable trait but is typically quantitative and moderately heritable. A better understanding of the genetic basis of resistance to crown rot is essential for developing durable crown rot-resistant cultivars. Results We conducted a genome-wide association study (GWAS) using multi-locus models on 100 wild strawberry accessions from South and North America. The accessions were genotyped using the Axiom™ 50 K strawberry SNP array and mapped to the F. × ananassa cv. Royal Royce v. 1.0 reference genome. Testing for resistance to P. cactorum revealed a wide range of phenotypes. A single genetic marker, AX-184528282, located on chromosome 7B, was strongly associated with resistance to P. cactorum and explained 53% of the observed phenotypic variation. This marker was present in several highly resistant exotic Fragaria accessions that represent potential donors for introgression of favorable alleles into modern strawberry cultivars. In addition, several strong candidate resistance genes were identified within the 2 Mb genomic region surrounding the significant marker. Conclusions This study advances understanding of resistance to P. cactorum in strawberry and identifies genetic resources that can accelerate the development of crown rot-resistant cultivars through marker-assisted breeding.
2025
Authors
Alexey Mikaberidze C. D. Cruz Ayalsew Zerihun Abel Barreto Pieter Simon A Beck Rocío Calderón Carlos Camino Rebecca E. Campbell Stephanie K.L. Delalieux Frédéric Fabre Elin Falla Stuart Fraser Kaitlin M. Gold Carlos Gongora-Canul Frédéric Hamelin Dalphy Ondine Camira Harteveld Cheng Fang Hong Melen Leclerc Da Young Lee Murillo Lobo Anne Katrin Mahlein Emily McLay Paul Melloy Stephen Parnell Uwe Rascher Jack Rich Irene Salotti Samuel Soubeyrand Susan Sprague Antony Surano Sandhya D. Takooree Thomas H. Taylor Suzanne Touzeau Pablo J. Zarco-Tejada Nik J. CunniffeAbstract
Plant diseases impair the yield and quality of crops and threaten the health of natural plant communities. Epidemiological models can predict diseaseand inform management. However, data are scarce, because traditional methods to measure plant diseases are resource intensive, which often limitsmodel performance. Optical sensing offers a methodology to acquire detailed data on plant diseases across various spatial and temporal scales. Keytechnologies include multispectral, hyperspectral, and thermal imaging, as well as light detection and ranging; the associated sensors can be installedon ground-based platforms, uncrewed aerial vehicles, airplanes, and satellites. However, despite enormous potential for synergy, optical sensing andepidemiological modeling have rarely been integrated. To address this gap, we first review the state of the art to develop a common language accessibleto both research communities. We then explore the opportunities and challenges in combining optical sensing with epidemiological modeling. Wediscuss how optical sensing can inform epidemiological modeling by improving model selection and parameterization and providing accurate maps ofhost plants. Epidemiological modeling can inform optical sensing by boosting measurement accuracy, improving data interpretation, and optimizingsensor deployment. We consider outstanding challenges in (A) identifying particular diseases; (B) data availability, quality, and resolution; (C) linkingoptical sensing and epidemiological modeling; and (D) emerging diseases. We conclude with recommendations to motivate and shape research andpractice in both fields. Among other suggestions, we propose standardizing methods and protocols for optical sensing of plant health and developingopen access databases including both optical sensing data and epidemiological models to foster cross-disciplinary work.
Authors
Theresa Weigl Jorunn Børve Emily Follett Melissa Magerøy Hanne Larsen Carl Gunnar Fossdal Siv Fagertun RembergAbstract
The effect of harvest timing on postharvest ripening was investigated by changes in ethylene production, expression of ethylene biosynthesis genes MdACS1, MdACS6, (1-aminocyclopropane-1-carboxylic acid synthase 1 and 6) and the ACS degradation promoting gene MdETO1 (Ethylene overproducer 1). Apple fruit of two cultivars, ‘Red Aroma’ and ‘Rubinstep’, were harvested at three time points, early, middle, and late, at two-week intervals. Fruit were either treated with 1 ppm 1-Methylcyclopropene (1-MCP) or remained untreated, and stored at 4 °C in regular atmosphere. Late harvested, untreated apples reached peak ethylene production after the shortest time in cold storage ('Red Aroma' in week five, 'Rubinstep' in weeks nine and ten), while early harvested, untreated fruit reached their peak after a longer time ('Red Aroma' in week eight, 'Rubinstep' in weeks 13 and 14). Early harvested fruit experienced greater firmness loss and a higher increase in SCC/TA ratio during cold storage. Senescence in late harvested, untreated fruit was evident from low ethylene production after simulated shelf-life and increased physiological disorders in ‘Rubinstep’. In 1-MCP-treated fruit, ethylene production increased toward the end of storage, particularly in early harvested fruit, indicating a decline in 1-MCP efficacy over time. Gene expression analysis showed strong induction of MdACS1 during climacteric ripening. MdETO1 positively correlated with MdACS1 gene expression, suggesting positive co-regulation. The expression of MdACS6 was negatively correlated with simulated shelf-life and with 1-MCP treatment, suggesting regulation by temperature and metabolic state. Overall, harvest timing and 1-MCP strongly influenced the changes in fruit physiology during postharvest storage.
Authors
Mark Ramsden Berit Nordskog Tor-Einar Skog Dave Skirvin Angelo Marguglio Antonio Caruso Christophe Pradal Lise Jorgensen Mette Sonderskov Nikos Georgantzis Marko Debeljak Jurij Marinko Harm Brinks Bjorn Andersson Ilias Travlos Eleanor Dearlove Neil PaveleyAbstract
Crop protection and pest management are major economic and environmental concerns throughout Europe. The consultation of decision support systems (DSS) to guide decisions relating to Integrated Pest Management (IPM) is one of the key principles of IPM, reducing the ambiguity around potential risks to crop health. ‘Pests’ in this context include invertebrate pests, weeds and pathogens. The impact of DSS can be limited by a lack of awareness of DSS availability, inconsistencies in the user functions of different DSS, regional fragmentation of access, and a lack of transparency of the origin, validity, and benefits of DSS. Failure to address these limitations undermines trust in IPM DSS and leads to a reluctance of farmers and advisors to invest time in consulting multiple DSS sources as part of their agronomic decision toolbox. The EU-funded IPM Decisions project (Grant agreement ID: 817617) addressed these limitations by creating a Europe-wide free-access online platform. The IPM Decisions platform was designed in consultation with farmers, advisors and wider stakeholders to increase access to and uptake of IPM DSS integrated within it. It offers an end-point for IPM researchers and DSS developers to make adapted and novel DSS available to users, and provides a ‘one-stop shop' for farmers and advisors looking to consult free access or paid IPM DSS. Dedicated dashboards within the platform facilitate farm set up, consultation of DSS, comparison of DSS outputs, and adjustment of model parameters for adaption to different pests/regions. The IPM Decisions digital infrastructure enables easy integration of models and data with external platforms, providing a framework for accessing and sharing models and data between researchers and developers. The platform therefore provides both a ready to go user interface for new DSS, as well as the infrastructure to support and connect existing and future user interfaces.
Abstract
No abstract has been registered