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
Greenhouse cultivation can help meet food demand in a growing and increasingly urbanised population. Reliance on fossil-fuel heating and natural ventilation often makes conventional greenhouses energy- and carbon-inefficient. Closed greenhouses address these limitations through resource recycling and energy recovery. While a centralised environmental control system (ECS) integrating climate control and heat harvesting has shown potential to improve greenhouse crop performance at high latitudes, its year-round energy use and energy-related carbon footprint reduction potential remains insufficiently quantified. This study extends an existing dynamic greenhouse climate model to incorporate a novel centralised ECS integrating air recirculation, heating, cooling, and heat harvesting in (semi-)closed greenhouses. The model was validated using experimental data from Norway, reproducing temperature and relative humidity with RMSEs of 1.40–1.63 °C and 7.60–8.55%, respectively. Energy use and tomato yield were predicted with relative errors of 3.8–8.4% and 1.6–4.2%, respectively. Scenario simulations under Norwegian conditions showed that (semi-)closed greenhouses with heat harvesting can reduce fossil fuel use by over 80% while increasing tomato yields by 15–41% relative to open greenhouses, driven by changes in CO2 concentration and temperature following reduced ventilation and heat recovery. The performance of a fully closed greenhouse relying solely on on-site cold storage is constrained by cooling capacity and buffer size, particularly during summer; adding a supplemental cold energy source such as surface water can improve its performance. Despite heat harvesting, a residual boiler heating demand of 3–10% remains. Further gains in energy efficiency and crop performance may be achieved through optimised climate control.
Authors
Ishita Ahuja Arne Steffenrem Irena Fundova Helmer Belbo Torstein Myhre Inger Sundheim FløistadAbstract
When regenerating clearcut areas in Norway and several other countries, tree seedlings are planted adjacent to stumps of harvested trees to reduce snow load and provide shading, despite limited scientific evidence supporting this practice. This study investigated the role of tree-stumps as planting microsites in the establishment of Norway spruce (Picea abies (L.) Karst.) seedlings. We assessed the growth and survival of seedlings from two provenances: Undesløs seed orchard (60.7°, 140 m), consisting of tested parents from the lowland around 63–65°N, and seed collected from forests in the M4 provenance (64–65°N, 350–449 m), at two microsite types in Trøndelag County, Norway: beside stumps (Microsites-B) and at a distance from stumps (Microsites-D). Undesløs seedlings exhibited 100% survival at Microsites-B, whereas M4 seedlings showed higher survival at Microsites-D. Provenance had a significant effect on seedling height and diameter, while microsite type had no significant effect on these parameters. In 2022, significant differences in height and diameter were observed between provenances at Microsites-B. Phenotypic variations, including chlorotic, green, and brown needles, occurred in seedlings of both provenances across both microsite types. Overall, this single-site experiment provided no evidence that planting beside stumps improves growth/survival compared with planting at a distance away.
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Authors
Lampros LamprinakisAbstract
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Authors
Linghan Huang Tingxuan Zhuang Meiqi Zhang Syed Tahir Ata-Ul-Karim Kang Yu Krzysztof Kusnierek Wei Li Xiaojun Liu Yongchao Tian Yan Zhu Weixing Cao Qiang CaoAbstract
Early-season prediction of winter wheat yield and grain protein content is essential for guiding fertilizer and irrigation decisions and reducing uncertainty in variable agroecosystems, as yield affects profitability and quality affects market value and nutrition. Although multi-source data and both single-task learning (STL) and multi-task learning (MTL) are widely used for predicting grain yield and quality, the conditions under which each approach performs best remain poorly understood, especially when data availability, noise, and measurement or computational constraints vary. To address this gap, we conducted a three-year field experiment in Henan Province, China, compiling environmental, agronomic, and proximal-sensing variables across five growth stages. Seven subsets were constructed, including environmental, agronomic, sensor, and combined subsets, and STL/MTL variants of Multilayer Perceptron (MLP), Transformer, and Random Forest (RF) were benchmarked. SHapley Additive exPlanations (SHAP) analysis quantified feature- and stage-level contributions and guided construction of compact Top-K subsets for accuracy–efficiency trade-offs. Multi-source fusion substantially improved accuracy over single-source inputs, with the combined agronomic-sensor subset providing the best performance (yield R2 = 0.823; GPC R2 = 0.743). Under the current stage-aggregated multi-source representation, MLPs outperformed Transformers and RFs across configurations, indicating that compact nonlinear models were better suited to the present medium-dimensional tabular setting. MTL provided the greatest benefit with sparse feature sets or imbalanced predictive difficulty, whereas STL performed better when information was abundant and signals were strong. SHAP analysis showed that agronomic and sensor features associated with biomass accumulation, nitrogen status, water availability, and canopy light interception were key drivers of model predictions, particularly during erecting and early grain filling. These findings further show that the value of STL versus MTL depends on data-source composition and information richness, and that SHAP can be used not only for interpretation but also for reduced-feature subset design. Within the present plot-scale setting, this study therefore provides a decision-oriented framework for identifying both accuracy-oriented and efficiency-oriented configurations, with efficiency referring to feature parsimony, reduced input and preprocessing burden, and computational time for winter wheat yield and GPC.
Authors
Clifton Makate Gerard Cornelissen Jan Mulder Vegard Martinsen Brian Ogenrwoth Jackline Bonabana-Wabbi Alfred Obia George Kaweesi Øyvind Nystad HandbergAbstract
Conservation agriculture (CA) and the use of biochar as a soil amendment can promote productive, resilient, and sustainable smallholder farming. However, adopting these practices requires a shift from conventional methods, potentially changing labour use and returns, the extent of which remains poorly understood. Using data from a randomized controlled trial (RCT) of 400 farmers designed to be representative of smallholder farmers in two districts of Uganda, this study assesses how an informational intervention (delivered through instruction and participatory field demonstrations) on CA methods with and without biochar affect labour use and productivity. Control group farmers were compared to those receiving (i) CA and (ii) CA+BIOCHAR interventions. First difference and inverse probability–weighted regression-adjustment model results indicate that the CA+BIOCHAR intervention increased labour use, with no significant labour productivity gains, compared to the control group. Labour input rose by about 36%, driven by a 54% increase in family labour, while hired labour input declined. Extra work was hence met by family labour rather than paid work. Labour savings occurred only in land preparation, and overall returns to labour were roughly 45% lower than conventional practice. The shifts in labour use and productivity are largely attributable to the information intervention, which increased cultivated area, area under minimum tillage, crop diversity, and biochar application. Taken together, these findings show that, over the study period following the intervention, the promoted CA and biochar package was associated with higher labour demand and no clear labour productivity gains. Bundling training with complementary interventions that tackle the labour burden inherent in smallholder agriculture may be necessary to achieve both labour-saving and labour productivity gains from CA and biochar adoption.
Authors
Seth J. Dorman Hannah M. Rivedal Casey Cruse Todd N. Temple Dustin W. Herb Robert J. Starchvick Nicole P. AndersonAbstract
Grass seed crops are susceptible to yellow dwarf viruses transmitted by aphids. The Willamette Valley in Oregon, United States, is the leading producer of cool-season grass seed crops globally, and industry reports have attributed seed yield loss and shortened stand longevity to aphid-transmitted yellow dwarf viruses. Genetic resources are needed for effective and sustainable management of this pest, specifically the Rhopalosiphum padi–PAV pathosystem, in grass seed production to reduce foliar insecticide applications and maintain optimum seed yield potential. High-throughput phenotyping methods are needed to screen grass seed cultivars to identify resistant traits for traditional breeding programs. An automated video tracking procedure was optimized to evaluate host plant resistance in cool-season grass seed crops to R. padi–PAV with live plants and viruliferous and nonviruliferous aphid populations. Feeding behavior recorded with automated video tracking was strongly correlated with “ground-truthed” observations by human observers. Partial resistance (antixenosis and antibiosis) and tolerance traits were detected in select perennial ryegrass and tall fescue cultivars evaluated with traditional phenotyping methods in a greenhouse setting and with high-throughput phenotyping using automated video tracking in the laboratory. Across grass cultivars, nonviruliferous aphids had greater fitness and preference for noninfected grass plants compared with viruliferous aphids. Automated video tracking can be used as a high-throughput phenotyping method for continued evaluation of host plant resistance in grasses grown for seed production, as well as to identify resistant genotypes in other grass crops susceptible to aphid–yellow dwarf virus virus–vector systems.
Abstract
Blue rings (BRs) are wood anatomy anomalies that present great potential in identifying cold spells during the growing season. In this study, we investigated the effect of temperature anomalies on the occurrence of two types of BR in Pinus sylvestris at its northern distribution limit in Norway. Of the 3508 individual tree rings from 1727 to 2022 analysed, we identified 206 BRs from a span of 85 years, the oldest formed in 1730. We distinguished two types of BR: Type A with normal earlywood and latewood ending with a thin blue layer; and Type B with the entire latewood zone replaced by earlywood-like tracheids. Our results demonstrate that the two types have a common climatic trigger – a cool spring and autumn. However, Type A is more linked to tree-ring width, whereas Type B is associated more closely with tree ontogeny and local environmental constraints. Although we observed the formation of BRs even in old trees, we found that they formed more frequently in young specimens. We showed that while the short-term cyclical drivers of Type A remained persistent, the climatic or environmental drivers associated with Type B gradually diminished under climate change. Our study demonstrates that the differentiation of BRs into types can contribute to a better understanding of their driving factors; however, detailed intra-annual phenological and xylogenetic monitoring will be crucial to achieve further insights.