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
Abstract
Web-based decision support systems (DSSs) are essential tools for precision crop protection, guiding farmers and advisors in implementing need-based control measures against pests, diseases, and weeds. These systems rely heavily on weather-driven models, where data accuracy and availability are critical. Leaf wetness is a key factor for infection and reproduction of many fungal plant pathogens, making it an important input in DSSs. However, the availability of leaf wetness data from weather services is variable, leading to the development of numerous estimation models without a universally accepted standard model. This study aimed to develop a robust mathematical model for estimating leaf wetness across diverse European climate zones and to integrate the model for enabling real-time leaf wetness estimates as inputs to web based DSSs. Hourly weather data, including leaf wetness, temperature, precipitation, relative humidity and wind speed were collected from automatic weather stations. Training data came from five Norwegian sites, while testing data covered 17 locations across Europe. Five machine learning based models (decision tree (DT), random forest, K-Nearest neighbour, multi-layer perception, long short-term memory (LSTM)) were trained and their performance compared with five existing empirical models (RH87, RH90, extRH, DPD, CART/SLD) from the literature. LSTM and DT achieved best performance, demonstrating strong robustness across climate zones. The LSTM model, required fewer data inputs and well suited for time-series data, was integrated into a Flask-based service for automatic use in forecasting models within the web-based IPM Decisions DSS platform, thereby enhancing the precision of this DSS.
Authors
Seth J. Dorman Hannah M. Rivedal David J. Maliszewski Todd N. Temple Casey Cruse Jing Zhou Pete A. Berry Robert J. Starchvick Chloe Oshiro Nicole AndersonAbstract
Epidemiology and management of aphid-transmitted yellow dwarf viruses (YDVs) have received international attention in small grain crops over the past century. However, focused research regarding YDV management in grass seed production systems, including perennial ryegrass (Lolium perenne L.), is limited. An integrated pest management program is needed to reduce the impact of the aphid-YDV complex in perennial grass seed crops. The objectives of the study were to evaluate the effects of nitrogen fertilizer rate, and the timing and frequency of foliar insecticide applications on aphid abundance, YDV disease incidence, and seed yield in two perennial ryegrass cultivars in small-plot field trials from 2021 to 2024. Trade-offs in economic returns across treatment combinations and YDV detection using remote sensing were also observed. Aphid and natural predator densities varied across foliar insecticide treatments. The high nitrogen rate increased YDV incidence across three field seasons in both cultivars. Seed yield and economic returns were greatest for the less susceptible cultivar when fully protected with one insecticide treatment per season (autumn, spring, and summer). A higher-than-recommended nitrogen rate did not increase seed yield across treatment combinations in first-year stands; however, an increase was observed in second- and third-year stands when YDV infection averaged >50%. Selecting resistant cultivars and reducing aphid populations during the autumn and spring aphid flights is critical for maximizing seed yield potential in perennial ryegrass. Furthermore, a lower nitrogen rate can be used in first-year stands to save input costs with no impact on seed yield potential.
Authors
Johannes BreidenbachAbstract
No abstract has been registered
Authors
Sissel Hansen Synnøve Rivedal Samson Øpstad Johannes Deelstra Trond Børresen Torfinn Torp Peter DörschAbstract
To study the effect of drainage intensity on GHG emissions and N drainage losses in cool-humid Norway, we established drainage systems with 6 and 12 m drain spacing in a previously undrained sandy loam (Mollic gleysol) collecting data in the years 2014–2016. After sowing a mixed grass ley, subsurface drainage was larger (1271 versus 699 mm) and mean ground water table (GWT) lower (102 versus 79 cm) with 6 than with 12 m drain spacing. Water filled pore space (WFPS) remained high throughout most of the year (> 80 %). It was highest in 12 m drain spacing, but shortly after fertilizations no differences between the two drainage systems were found. N2O emissions after fertilization were larger in the 12 m system than in the 6 m system. Cumulative N2O emissions in the 6 and 12 m system were 4.0 versus 2.5 kg N ha−2 yr−1. N leaching for the entire observation period (29 months) was larger in the 6 m (42 kg ha−1) than the 12 m (19 kg ha−1) system. Grass yields, plant N-recovery and fertilizer N use efficiency was larger with 6 than 12 m. The mean N2O emission factor was significantly higher with 6 than with 12 m drain spacing (1.4 versus 0.8 % N2O-N of N applied). The 6 m system acted as a net sink for CH4, whereas the 12 m system was a net CH4 source and had a higher climate forcing than the 12 m system (1390 versus 1110 g CO2 eq. m−2 yr−1), but scaled for grass dry matter yield the climate forcing was similar. We conclude that larger N2O emissions with 6 m drain spacing were likely due to a combination of less complete denitrification and a naturally higher SOM content at this site, releasing extra mineral N. Our study can therefore not confirm that increased drainage intensity intrinsically reduces N2O emissions from crop production in cool-humid climates.
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.
Abstract
No abstract has been registered
Abstract
The sustainability transitions literature suggests that individual firms struggle to move toward sustainability unless the broader socio-economic system also evolves. Despite firms' willingness to change, existing systemic challenges often impede their progress. This paper employs paradox theory to address this struggle and examines how firms balance economic and societal concerns in their transition from business thinking to sustainability thinking. Based on a qualitative case study of the food industry's collaboration initiatives on food waste reduction and prevention in Norway, the study identifies the systemic challenges and sustainability paradoxes that the industry faces. We find that the firms' efforts to reduce food waste collide with established food industry agreements, standards, business strategies, regulations, and agricultural policies, impeding a systemic and structural transformation of the industry. The paper discusses how the food industry may navigate these challenges collectively and draws implications for the sustainability transitions literature. Primarily, the conclusions signal a need for governance and incentive structures at the system level beyond the action space of individual firms, and secondarily, illustrate how such governance approaches to sustainability transitions are sector-specific and geographically embedded.
Abstract
Forest transpiration is often quantified by scaling up stem sap flow measured on a few trees within a stand. This procedure carries uncertainty related to the (ill)representativeness of the sampled trees for the entire stand, often comprising several thousand transpiring trees. Here, we explored the uncertainty reduction potential afforded by increasing the number of sampled trees within the stand – not by costly sap flow monitoring equipment – but by point dendrometers measuring sub-daily fluctuations in stem radii which partially correlate with xylem water movement (i.e., sap flow). Using measurements collected in a forest dominated by even-aged spruce trees over two growing seasons, we built an empirical model for estimating hourly sap flow from individual trees equipped with point dendrometers, then applied it to estimate the daily transpiration of the stand both with and without trees equipped with point dendrometers. We found that the expanded tree sample size reduced the uncertainty of the stand-level estimate by 31–37 %, suggesting that the benefit afforded by increasing the stand representativeness outweighed the cost of introducing modeling error. Given their relative simplicity and affordability, we encourage additional investigations into the use of point dendrometers for studying tree water relations and water consumption patterns of entire forested stands.
Authors
Dafni Foti Stephen Amiandamhen Eleni Voulgaridou Elias Voulgaridis Costas Passialis Stergios AdamopoulosAbstract
This study investigated the incorporation of various waste materials including wastepaper, Tetra Pak, wood chips and scrap tire fluff into flue gas desulfurization (FGD) gypsum and cement mortar matrices to produce sustainable composite materials. Four distinct composite types based on the waste materials were developed and evaluated for selected properties including thermal and acoustic insulation. The proportion of the waste materials was varied between 10 and 40 vol% of the base matrix. The compressive strength of the filled gypsum composites was in the range of 4.17–10.39 N/mm² while the pure gypsum was 11.38 N/mm². The addition of the wastes in gypsum composites reduced compressive strength by about 10% for the best recipe and as large as 60% for the worst combination. However, the measured strength still exceeds the strength of typical gypsum wallboard with a compressive strength of about 3–4 N/mm² for whole-board crushing tests and it is much lower for point loads. The normal-incidence sound absorption coefficient indicated that the waste-filled samples absorbed around 80% of the incident sound energy between 2000 and 3000 Hz, comparable to some commercial acoustic foams. The results highlight the potential of utilising these waste-based composites in environmentally friendly construction applications. Depending on the waste type and matrix used, the results revealed trade-offs between multi-functional performance and sustainability benefits.