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.
2023
Abstract
No abstract has been registered
Authors
Ingerd Skow Hofgaard Guro Brodal Heidi Udnes Aamot Marit Almvik Aina Lundon Russenes Morten Lillemo Simon Graham EdwardsAbstract
Oat harvested from plants infested with plant pathogenic fungi within the Fusarium head blight (FHB) complex may sometimes contain high levels of mycotoxins, which makes the grain unsuitable for food and feed. Fusarium graminearum, a deoxynivalenol (DON) producer, and Fusarium langsethiae, a T-2 toxin (T2) and HT-2 toxin (HT2) producer, are commonly occurring in Norwegian oats. We have analysed grains of Nordic oat varieties and breeding lines for the content of mycotoxins and DNA of Fusarium species belonging to the FHB disease complex (Hofgaard et al. 2022). The grains were harvested from field trials located in South-East Norway in the years 2011-2020. The ranking of oat varieties according to HT2+T2 levels corresponded with the ranking according to the DNA levels of F. langsethiae. However, this ranking did not resemble the ranking for DON and F. graminearum DNA. Our results implies that a moderate resistance to DON producers does not guarantee a moderate resistance to HT2+T2 producers. Separate tests are therefore necessary to determine the resistance towards DON and HT2+T2 producers in oats. This creates practical challenges for the screening of FHB resistance in oats as todays’ screening focuses on resistance to F. graminearum and DON. We identified oat varieties with generally low levels of both mycotoxins and FHB pathogens which should be promoted to mitigate mycotoxin risk in Norwegian oats.
Abstract
The adults of the new species Zachvatkinibates svanhovdi A. Seniczak & S. Seniczak sp. nov. are described and illustrated from Norway, and this is the first finding of Zachvatkinibates Shaldybina, 1973 in Fennoscandia. This species is the most similar to Z. quadrivertex (Halbert, 1920), but differs from it mainly by the shape of notogastral setae, posterior tectum of notogaster and lack of postanal porose area Ap, which in Z. quadrivertex is present. In Z. svanhovdi, the prodorsal seta in is long, translamella is narrow, notogastral setae are short and distally pliable, notogastral porose areas are usually oval and of medium size, but Aa can be larger, especially in males. Dorsal crest on tarsus I is present. The cytochrome oxidase I (COI) barcodes (length: 658 bp) of five specimens of the new species are provided; the maximum variation within the species was 2.41% (p-dist). The morphology and ecology of the new species is compared with other Zachvatkinibates species. The knowledge on family Punctoribatidae in Fennoscandia is updated, and Mycobates carli (Schweizer, 1922) is first reported from Norway.
Abstract
No abstract has been registered
Authors
Habtamu AlemAbstract
This study aims to estimate eco-efficiency scores and identify determinants of Norwegian dairy farms using a parametric approach that accounts for methane emissions. The study incorporates an environmental output measure and draws on 30 years of panel data from 692 specialist dairy farms (1991–2020). The findings indicate that Norwegian dairy farms are inefficient, with room for improvement in the dairy production system and the environment. According to the average eco-efficiency score, conventional dairy farms could cut input use and CH4 emissions by 5% while maintaining output. Furthermore, the study found that land tenure, experience, and government subsidies all positively impact eco-efficiency. Policymakers should encourage the best-performing dairy farms to share information on increasing productivity while considering environmental concerns to achieve better social and agricultural development. It should be noted that the study only looks at livestock methane emissions; future research may investigate other environmental factors.
Authors
Habtamu AlemAbstract
No abstract has been registered
Abstract
Soil health assessments that integrate physical, chemical and biological indicators help the evaluation of soil functioning, provide a framework for monitoring soil degradation, guide land management activities and secure the delivery of soil ecosystem services. In this study, we assessed soil health by soil texture class on arable land in Southeast Norway and mid-Norway and between grassland and arable land in mid-Norway. We used descriptive statistics and the Welch t-test with unequal variance and Bonferroni corrections to compare a physical soil indicator (bulk density) and chemical indicators (organic matter, P-AL, K-AL, Ca-AL, Mg-AL, Na-AL and pH). We developed scoring curves from cumulative normal distribution functions on regional soil data for various soil indicators where climate, soil texture class and land use were considered. Our results show that for certain soil texture classes, average soil indicator values differed between pedo-climatic zones on arable land, but for others the difference was not significant. The variability between the pedo-climatic zones for these can be neglected, but for the ones that differ, the variability is important to consider when assessing soil health. Similarly, this was the case when comparing land use (grassland and arable land) for most soil indicators in mid-Norway. This finding illustrates the importance of addressing unique local conditions in soil health assessments. We propose aggregating similar soil texture classes where no differences are apparent when developing scoring curves. The sub-optimal levels of plant available nutrients (P-AL and K-AL) found in the soil in both pedo-climatic zones highlights the importance of suitable threshold values for targeted soil ecosystem services to ensure soil health and sustainable agricultural production. We also recommend prioritizing the most relevant soil ecosystem services to limit the number of soil indicators that need monitoring.
Abstract
The ageing population, climate change, and labour shortages in the agricultural sector are driving the need to reevaluate current farming practices. To address these challenges, the deployment of robot systems can help reduce environmental footprints and increase productivity. However, convincing farmers to adopt new technologies poses difficulties, considering economic viability and ease of use. In this paper, we introduce a management system based on the Robot Operating System (ROS) that integrates heterogeneous vehicles (conventional tractors and mobile robots). The goal of the proposed work is to ease the adoption of mobile robots in an agricultural context by providing to the farmer the initial tools needed to include them alongside the conventional machinery. We provide a comprehensive overview of the system’s architecture, the control laws implemented for fleet navigation within the field, the development of a user-friendly Graphical User Interface, and the charging infrastructure for the deployed vehicles. Additionally, field tests are conducted to demonstrate the effectiveness of the proposed framework.
Abstract
Weed harrowing is commonly used to manage weeds in organic farming but is also applied in conventional farming to replace herbicides. Due to its whole-field application, weed harrowing after crop emergence has relatively poor selectivity and may cause crop damage. Weediness generally varies within a field. Therefore, there is a potential to improve the selectivity and consider the within-field variation in weediness. This paper describes a decision model for precision post-emergence weed harrowing in cereals based on experimental data in spring barley and nonlinear regression analysis. The model predicts the optimal weed harrowing intensity in terms of the tine angle of the harrow for a given weediness (in terms of percentage weed cover), a given draft force of tines, and the biological weed damage threshold (in terms of percentage weed cover). Weed cover was measured with near-ground RGB images analyzed with a machine vision algorithm based on deep learning techniques. The draft force of tines was estimated with an electronic load cell. The proposed model is the first that uses a weed damage threshold in addition to site-specific values of weed cover and soil hardness to predict the site-specific optimal weed harrow tine angle. Future field trials should validate the suggested model.
Authors
Kushan D. Siriwardhana Dimantha I. Jayaneththi Ruchiru D. Herath Randika K. Makumbura Hemantha Jayasinghe Miyuru Gunathilake Hazi Md. Azamathulla Kiran Tota-Maharaj Upaka RathnayakeAbstract
No abstract has been registered