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.
2024
Abstract
The biological durability of ten wood species was determined on the basis of results from laboratory agar block tests. The experiment utilised two specimen formats: standard EN 113-2 specimens (15 × 25 × 50 mm) and mini-blocks (5 × 10 × 30 mm) exposed to two fungi (Coniophora puteana and Trametes versicolor) for varying incubation periods. Mini-block tests yield dissimilar outcomes compared to the European standard test at six, eight, ten or 16 weeks of incubation. This discrepancy extended to both durability classifications based on median percentage mass loss and those based on relative mass loss (x-values). It was therefore concluded that laboratory tests with miniaturised specimens are not advisable as a substitute for conventional durability classification assessments.
Authors
Yi Zhang Xingru Yang Yijing Feng Zhiyue Dai Zhangmu Jing Yeqing Li Lu Feng Yanji Hao Shasha Yu Weijin Zhang Yanjuan Lu Chunming Xu Junting PanAbstract
Exploring the complex mechanism of anaerobic digestion with hydrothermal pretreatment (HTAD) for biomass efficiently and optimising the reaction conditions are critical to improving the performance of methane production. This study used H2O automated machine learning (AutoML) for comprehensive prediction, analysis, and targeted optimization of the HTAD system. An IterativeImputer system for data filling was constructed. The comparison of three basic regressors showed that random forest performed optimally for filling (R2 > 0.95). The gradient boosting machine (GBM) model was searched by H2O AutoML to show optimal performance in prediction (R2 > 0.96). The software was developed based on the GBM model, and two prediction schemes were devised. The generalization error of the software was less than 10%. The Shapley Additive exPlanations value showed that solid to liquid ratio, hydrothermal pretreatment (HT) temperature, and particle size have greater potential for improving cumulative methane production (CMP). A Bayesian-HTAD optimization strategy was devised, using the Bayesian optimization to directionally optimize the reaction conditions, and performing experiments to validate the results. The experimental results showed that the CMP was significantly improved by 51.63%. Compared to the response surface methodology, the Bayesian optimization relatively achieved a 2.21–2.50 times greater effect. Mechanism analyses targeting the experiments showed that HT was conducive to improving the relative abundance of Sphaerochaeta, Methanosaeta, and Methanosarcina. This research achieved accurate prediction and targeted optimization for the HTAD system and proposed multiple filling, prediction, and optimization strategies, which are expected to provide an AutoML optimization paradigm for anaerobic digestion in the future.
Authors
Klemens Schadauer Rasmus Astrup Johannes Breidenbach Jonas Fridman Stephan Gräber Michael Köhl Kari T. Korhonen Vivian Kvist Johannsen Francois Morneau Risto Päivinen Thomas RiedelAbstract
No abstract has been registered
Authors
Ivy Britzny Osae Peep Mardiste Dina Stober Sebastian Eiter Matthias Buchecker Monika SuškevičsAbstract
No abstract has been registered
Authors
Daniel Ruiz Potma Gonçalves Thiago Inagaki Luis Gustavo Barioni Newton La Scala Junior Maurício Roberto Cherubin João Carlos de Moraes Sá Carlos Eduardo Pellegrino Cerri Adriano AnselmiAbstract
Soils are the third largest carbon pool on Earth and play a crucial role in mitigating climate change. Therefore, understanding and predicting soil carbon sequestration is of major interest to mitigate climate change globally, especially in countries with strong agricultural backgrounds. In this study, we used a new database composed of 5029 samples collected up to 1-meter depth in three biomes that are most representative of agriculture, Pampas (Prairie), Cerrados (Savanna), and Atlantic Forest (Forest), to explore soil organic carbon (SOC) stocks and its environmental drivers. The Cerrado (Savanna) biome was the only one where croplands presented higher SOC stocks than native vegetation (Native vegetation 121.23 Mg/ha and croplands 127.85 Mg/ha or 5 % higher). From the tested models, the Random Forest outperformed the others, achieving an R2 of 0.64 for croplands and 0.56 for native vegetation. The accuracy of the models varied with soil depth, showing better predictions in shallow layers for croplands and deeper layers for native vegetation. Our results highlight the importance of clay content, precipitation, net primary production (NPP), and temperature as key predictors for soil carbon stocks in the studied biomes. The findings emphasize the importance of protecting the surface layers, especially in the Cerrado biome, to enhance SOC stocks and promote sustainable land management practices. Moreover, the results provide valuable insights for the development of nature-based carbon markets and suggest potential strategies for climate change mitigation. Enhancing our understanding of SOC dynamics and adopting precise environmental predictors will contribute to the formulation of targeted soil management strategies and accelerate progress toward achieving climate goals.
Authors
Nina SvartedalAbstract
No abstract has been registered
Abstract
Rapporten gir en oversikt over NIBIO sine aktiviteter i AdaptaN II prosjektet gjennomført i samarbeid med tsjekkiske partnere. NIBIO har bidratt med vurdering av erosjonsrisiko og modellering av erosjonstiltak for klimatilpasning på jordbruksarealer for et nedbørfelt i Větřkovice i Moravian – Silesian Region i Tsjekkia. Delrapport 1 gir en oversikt over aktuelle erosjonstiltak i bruk i Norge samt regelverk, støtteordninger og subsidier for miljøtiltak. Delrapport 2 gir en oversikt over viktige faktorer ved vurdering av erosjonsrisiko og resultat fra modellering av utvalgte erosjonstiltak, spesielt vegetasjonssoner og grasdekte vannveier for studieområdet i Tsjekkia.
Abstract
Denne rapporten gir en oversikt over NIBIO sine aktiviteter i AdaptaN II prosjektet gjennomført i samarbeid med tsjekkiske partnere. NIBIO har bidratt med vurdering av erosjonsrisiko og modellering av erosjonstiltak for klimatilpasning på jordbruksarealer for et nedbørfelt i Větřkovice i Moravian – Silesian Region i Tsjekkia. Delrapport 1 gir en oversikt over aktuelle erosjonstiltak i bruk i Norge samt regelverk, støtteordninger og subsidier for miljøtiltak. Delrapport 2 gir en oversikt over faktorer ved vurdering av erosjonsrisiko og resultat fra modellering av utvalgte erosjonstiltak, spesielt vegetasjonssoner og grasdekte vannveier for studieområdet i Tsjekkia.
Abstract
Ensiling of whole-crop biomass of barley before full maturity is common practice in regions with a short growing season. The developmental stage of barley at harvest can have a large impact on yield and nutritive composition. The relationships between crop growth, environmental conditions and crop management can be described in process-based simulation models. Some models, including the Basic Grassland (BASGRA) model, have been developed to simulate the yield and nutritive value of forage grasses, and usually evaluated against metrics of relevance for whole-crop silage. The objectives of this study were to: i) modify the BASGRA model to simulate whole-crop spring barley; ii) evaluate the performance of this model against empirical data on dry matter (DM) yield and nutritive value attributes from field experiments, divided into geographical regions; and iii) evaluate DM yield, nutritive value and cutting date under current and future climate conditions for three locations in Sweden and four cutting regimes. Main model modifications included addition of a spike pool, equations for carbon (C) and nitrogen (N) allocation to the spike pool and equations for C and N translocation from vegetative plant parts to spikes. Model calibration and validation against field trial data from Sweden, including samples harvested from late anthesis stage to hard dough stage that were either pooled or divided into regions, showed better prediction accuracy, evaluated as normalised root mean squared error (RMSE), of neutral detergent fibre (NDF) (7.58–18.4%) than of DM yield (16.8–27.8%), crude protein (15.5–23.2%) or digestible organic matter in the DM (DOMD) (12.0–22.2%). Model prediction using weather data representing 1990–2020 and 2021–2040 climate conditions for three locations in Sweden (Skara, Umeå, Uppsala) showed lower DM yield, earlier harvest and slightly higher NDF concentration on average (across locations and developmental stage at cutting) when using near-future climate data rather than historical data. The model can be used to evaluate whole-crop barley performance under production conditions in Sweden or in other countries with similar climate, soils and crop management regimes.
Authors
Luiz Claudio Garcia Guilherme H. Carraro Sandro Felema Allison J. Fornari Leandro J. V. Sformi Thiago InagakiAbstract
No abstract has been registered