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
Elymus repens is a problematic perennial weed in annual crops, grasslands and leys. Rhizome fragmentation by vertical disking can potentially reduce E. repens abundance with minimal tillage, but data are lacking on its efficiency in forage production. In a two-year study (2017–2018, 2018–2019) conducted in two forage grass-clover leys that were mostly weed-free except for large E. repens populations, this study examined effects on forage yield, botanical composition, and E. repens rhizome biomass of rhizome fragmentation at significant growth initiation in spring (early rhizome fragmentation, ERF) and/or when conditions allowed after the first forage cut (late rhizome fragmentation, LRF). Cold, wet springs and hard, dry soil in summer delayed treatment in both treatment years, to late spring (ERF) and late summer/early autumn (LRF). In the treatment year, ERF reduced first-cut forage yield by 44% compared with no rhizome fragmentation, while LRF decreased second- and third-cut yield by 24% and 53%, respectively. In the year after treatment, ERF increased total forage yield by on average 10%, while LRF had no effect. Over both years, combined forage yield was reduced by 11% by ERF and 4% by LRF. Both treatments reduced E. repens rhizome biomass, but inconsistently (ERF by 25% in one year only, LRF by 24% at one of two sites). ERF reduced E. repens incidence in forage by 10% in the treatment year, but had no effect in the following year. Thus, rhizome fragmentation by vertical disking can reduce E. repens abundance in grass-clover leys, but the effect is inconsistent and forage yield can be impaired, especially in swards with much E. repens. Moreover, disking is hampered by hard, dry soil conditions.
Abstract
No abstract has been registered
Authors
Håvard SteinshamnAbstract
No abstract has been registered
Authors
Yupeng Zhang Guangxun Fan Tuomas Toivainen Torstein Tengs Igor A. Yakovlev Paal Krokene Timo Hytönen Carl Gunnar Fossdal Paul GriniAbstract
Plants must adapt with increasing speed to global warming to maintain their fitness. One rapid adaptation mechanism is epigenetic memory, which may provide organisms sufficient time to adapt to climate change. We studied how the perennial Fragaria vesca adapted to warmer temperatures (28°C vs. 18°C) over three asexual generations. Differences in flowering time, stolon number, and petiole length were induced by warmer temperature in one or more ecotypes after three asexual generations and persisted in a common garden environment. Induced methylome changes differed between the four ecotypes from Norway, Iceland, Italy, and Spain, but shared methylome responses were also identified. Most differentially methylated regions (DMRs) occurred in the CHG context, and most CHG and CHH DMRs were hypermethylated at the warmer temperature. In eight CHG DMR peaks, a highly similar methylation pattern could be observed between ecotypes. On average, 13% of the differentially methylated genes between ecotypes also showed a temperature-induced change in gene expression. We observed ecotype-specific methylation and expression patterns for genes related to gibberellin metabolism, flowering time, and epigenetic mechanisms. Furthermore, we observed a negative correlation with gene expression when repetitive elements were found near (±2 kb) or inside genes. In conclusion, lasting phenotypic changes indicative of an epigenetic memory were induced by warmer temperature and were accompanied by changes in DNA methylation patterns. Both shared methylation patterns and transcriptome differences between F. vesca accessions were observed, indicating that DNA methylation may be involved in both general and ecotype-specific phenotypic variation.
Abstract
No abstract has been registered
Abstract
Artificial freezing tests were performed on seedlings from Norway spruce families at the end of the first growing season. Similar tests were made on twigs collected from trees in a progeny test at the end of growing season nine. The 26 families in the early test were included in the short-term progeny test with 100 full-sib families from a 10 x 10 factorial cross. All families were also planted in seven field trials in Norway, Sweden and Finland, from which data on mortality, tree heights and stem damage at age 10 years are available. Significant difference was found among families for freezing test injuries on whole intact seedlings at the end of the first growing season and for lethal temperature of needles on detached twigs collected at the end of growing season nine. However, no relationships were found between the freezing test scores of families in the two types of tests or few between these scores and the traits measured in the short-term and field trials. The results show that frost hardiness testing of families at a young age, grown under artificial temperature and light conditions in nursery, is a weak predictor of their performance under natural conditions in field at older ages.
Abstract
Material exiting the harvester is composed of chaff and straw. Chaff is a by-product of grain harvest comprises weed seeds and husk. Harvest Weed Seed Control (HWSC) systems aim at collecting and/or killing weed seeds in the chaff fraction during crop grain harvest. If chaff is removed or processed via impact mills or concentrated in a narrow zone in the field and collected, the overall weed infestation may be reduced in the following years. Chaff may be used as a new biomass feedstock, for example, as a renewable energy source, material for construction ( e.g. , insulating boards, cardboard, bedding), soil improvement ( e.g ., mulch, mushroom compost), and for agricultural purposes ( e.g. , weed growth inhibitor, animal diet). Using chaff directly is unfavorable because of its low bulk density. Therefore, compressing chaff into pellets can improve its handling. In this preliminary study, we assessed how pelletizing would affect the germinability of weed seeds in the chaff pellets. Whole wheat chaff and fine wheat chaff sieved were mixed with seeds of the two weed species scentless mayweed ( Tripleurospermum inodorum (L.) Sch.Bip.) and cornflower ( Centaurea cyanus L.), respectively. While 22% of T. inodorum seeds and 59% of C. cyanus seeds in wheat chaff samples were able to germinate, no weed seeds germinated from moist pelletized original and fine wheat chaff samples. The study indicates a low risk of spreading weed seeds with pelletized chaff probably because the heating during the pelletizing process kills the weed seeds.
Authors
Zahra BitarafanAbstract
No abstract has been registered
Authors
Trygve S. AamlidAbstract
No abstract has been registered
Abstract
Wetlands are simply areas that are fully or partially saturated with water. Not much attention has been given to wetlands in the past, due to the unawareness of their value to the general public. However, wetlands have numerous hydrological, ecological, and social values. They play an important role in interactions among soil, water, plants, and animals. The rich biodiversity in the vicinity of wetlands makes them invaluable. Therefore, the conservation of wetlands is highly important in today’s world. Many anthropogenic activities damage wetlands. Climate change has adversely impacted wetlands and their biodiversity. The shrinking of wetland areas and reducing wetland water levels can therefore be frequently seen. However, the opposite can be seen during stormy seasons. Since wetlands have permissible water levels, the prediction of wetland water levels is important. Flooding and many other severe environmental damage can happen when these water levels are exceeded. Therefore, the prediction of wetland water level is an important task to identify potential environmental damage. However, the monitoring of water levels in wetlands all over the world has been limited due to many difficulties. A Scopus-based search and a bibliometric analysis showcased the limited research work that has been carried out in the prediction of wetland water level using machine-learning techniques. Therefore, there is a clear need to assess what is available in the literature and then present it in a comprehensive review. Therefore, this review paper focuses on the state of the art of water-level prediction techniques of wetlands using machine-learning techniques. Nonlinear climatic parameters such as precipitation, evaporation, and inflows are some of the main factors deciding water levels; therefore, identifying the relationships between these parameters is complex. Therefore, machine-learning techniques are widely used to present nonlinear relationships and to predict water levels. The state-of-the-art literature summarizes that artificial neural networks (ANNs) are some of the most effective tools in wetland water-level prediction. This review can be effectively used in any future research work on wetland water-level prediction.