Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2022
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Tommi Nyman Saskia Wutke Elina Koivisto Tero Klemola Mark R. Shaw Tommi Andersson Håkon Haraldseide Snorre Hagen Ryosuke Nakadai Kai RuohomäkiSammendrag
Large areas of forests are annually damaged or destroyed by outbreaking insect pests. Understanding the factors that trigger and terminate such population eruptions has become crucially important, as plants, plant-feeding insects, and their natural enemies may respond differentially to the ongoing changes in the global climate. In northernmost Europe, climate-driven range expansions of the geometrid moths Epirrita autumnata and Operophtera brumata have resulted in overlapping and increasingly severe outbreaks. Delayed density-dependent responses of parasitoids are a plausible explanation for the 10-year population cycles of these moth species, but the impact of parasitoids on geometrid outbreak dynamics is unclear due to a lack of knowledge on the host ranges and prevalences of parasitoids attacking the moths in nature. To overcome these problems, we reviewed the literature on parasitism in the focal geometrid species in their outbreak range and then constructed a DNA barcode reference library for all relevant parasitoid species based on reared specimens and sequences obtained from public databases. The combined recorded parasitoid community of E. autumnata and O. brumata consists of 32 hymenopteran species, all of which can be reliably identified based on their barcode sequences. The curated barcode library presented here opens up new opportunities for estimating the abundance and community composition of parasitoids across populations and ecosystems based on mass barcoding and metabarcoding approaches. Such information can be used for elucidating the role of parasitoids in moth population control, possibly also for devising methods for reducing the extent, intensity, and duration of outbreaks.
Sammendrag
Berries of the genus Vaccinium are highly valued health-beneficial superfoods, which are commonly subjected to adulteration and mixed with each other, or with other common berry species. A quantitative DNA-based method utilizing a chip-based digital polymerase chain reaction (dPCR) technique was developed for identifying and quantifying wild lingonberry (V. vitis-idaea) and cultivated American cranberry (V. macrocarpon). The dPCR method with species-specific primers for mini-barcoding was designed based on the indel regions found in the trnI-CAU–trnL-CAA locus in the chloroplast genome. The designed primers were able to amplify only target species, enabling to distinguish the two closely related species with good sensitivity. Our results illustrated the ability of the method to identify lingonberry and American cranberry DNA using PCR without the need for probes or further sequencing. The dPCR method could also quantify the DNA copy number in mixed samples. Based on this study, the method provides a basis for a simple, fast, and sensitive quantitative authentication analysis of lingonberry and American cranberry by dPCR. Moreover, it can also provide a platform for authentication analyses of other plant species as well by utilizing the indel regions of chloroplast genomes.
Forfattere
F. M. R. Ziegler Anita Sønsteby A. Masny B. Schulten V. Uglosch M. Franzen L. Munnes S. Osorio Algar B. UsadelSammendrag
Det er ikke registrert sammendrag
Sammendrag
Weeds are one of the biggest problems that modern agriculture is facing worldwide due to the impact they have on crop productivity. Thus, there is a necessity to develop crop varieties with herbicide resistance or tolerance, which would provide cost-effective tools for helping farmers control weeds in the field. Development of herbicide-tolerant crops was initially based on conventional plant breeding and transgenic technology. In recent years, the emerging genome technologies, including ZFNs (zinc-finger nucleases), TALENs (transcription activator-like effector nucleases), and CRISPR (clustered regularly interspaced short palindromic repeat), provide us a new way for crop improvement through precise manipulation of endogenous genes in the plant genomes. Among these, CRISPR technologies, including nuclease systems, base editors, and prime editors, are really promising in creating novel crop germplasms with herbicide tolerance as they are simple, easy to use, and highly efficient. In this review, we briefly summarize the latest development and breakthroughs of CRISPR technologies in creating herbicide-tolerant crops. Finally, we discuss the future applications of CRISPR technologies in developing herbicide-tolerant crops.
Forfattere
Lone Ross Lizhen Huang Erik Trømborg Roja Modaresi Hanne Kathrine Sjølie Callum Aidan Stephen HillSammendrag
Det er ikke registrert sammendrag
Forfattere
Simon Weldon Bert van der Veen Eva Farkas Nazli Pelin Kocatürk Schumacher Alba Dieguez-Alonso Alice Budai Daniel RasseSammendrag
Sorption of nutrients such as NH4+ is often quoted as a critical property of biochar, explaining its value as a soil amendment and a filter material. However, published values for NH4+ sorption to biochar vary by more than 3 orders of magnitude, without consensus as to the source of this variability. This lack of understanding greatly limits our ability to use quantitative sorption measurements towards product design. Here, our objective was to conduct a quantitative analysis of the sources of variability, and infer which biochar traits are more favourable to high sorption capacity. To do so, we conducted a standardized remodelling exercise of published batch sorption studies using Langmuir sorption isotherm. We excluded studies presenting datasets that either could not be reconciled with the standard Langmuir sorption isotherm or generated clear outliers. Our analysis indicates that the magnitude of sorption capacity of unmodified biochar for NH4+ is lower than previously reported, with a median of 4.2 mg NH4+ g−1 and a maximum reported sorption capacity of 22.8 mg NH4+ g−1. Activation resulted in a significant relative improvement in sorption capacity, but absolute improvements remain modest, with a maximum reported sorption of 27.56 mg NH4+ g−1 for an activated biochar. Methodology appeared to substantially impact sorption estimates, especially practices such as pH control of batch sorption solution and ash removal. Our results highlight some significant challenges in the quantification of NH4+ sorption by biochar and our curated data set provides a potentially valuable scale against which future estimates can be assessed.
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Weeds may reduce crop yields significantly if managed improperly. However, excessive herbicide use increases risk of unwanted effects on ecosystems, humans and herbicide resistance development. Weed harrowing is a traditional method to manage weeds mechanically in organic cereals but could also be used in conventional production. The weed control efficacy of weed harrowing can be adjusted by e.g. the angle of the tines. Due to its broadcast nature (both crop and weed plants are disturbed), weed harrowing may have relatively poor selectivity (i.e. small ratio between weed control and crop injury). To improve selectivity, a sensor-based model which takes into account the intra-field variation in weediness and “soil density” in the upper soil layer (draft force of tines), is proposed. The suggested model is a non-linear regression model with three parameters and was based on five field trials in spring barley in SE Norway. The model predicts the optimal weed harrowing intensity (in terms of the tine angle) from the estimated total weed cover and SD per sub-field management unit, as well as a pre-set biological weed threshold (defined as the acceptable total weed cover left untreated). Weed cover and SD were estimated with RGB images (analysed with custom-made machine vision) and an electronic load cell, respectively. With current parameter values, the model should be valid for precision weed harrowing in spring barley in SE Norway. The next step is to test the model, and if successful, adjust it to more cereal species. Weeds may reduce crop yields significantly if managed improperly. However, excessive herbicide use increases risk of unwanted effects on ecosystems, humans and herbicide resistance development. Weed harrowing is a traditional method to manage weeds mechanically in organic cereals but could also be used in conventional production. The weed control efficacy of weed harrowing can be adjusted by e.g. the angle of the tines. Due to its broadcast nature (both crop and weed plants are disturbed), weed harrowing may have relatively poor selectivity (i.e. small ratio between weed control and crop injury). To improve selectivity, a sensor-based model which takes into account the intra-field variation in weediness and “soil density” in the upper soil layer (draft force of tines), is proposed. The suggested model is a non-linear regression model with three parameters and was based on five field trials in spring barley in SE Norway. The model predicts the optimal weed harrowing intensity (in terms of the tine angle) from the estimated total weed cover and SD per sub-field management unit, as well as a pre-set biological weed threshold (defined as the acceptable total weed cover left untreated). Weed cover and SD were estimated with RGB images (analysed with custom-made machine vision) and an electronic load cell, respectively. With current parameter values, the model should be valid for precision weed harrowing in spring barley in SE Norway. The next step is to test the model, and if successful, adjust it to more cereal species.
Sammendrag
Management of Scots pine (Pinus sylvestris L.) in Norway requires a forest growth and yield model suitable for describing stand dynamics of even-aged forests under contemporary climatic conditions with and without the effects of silvicultural thinning. A system of equations forming such a stand-level growth and yield model fitted to long-term experimental data is presented here. The growth and yield model consists of component equations for (i) dominant height, (ii) stem density (number of stems per hectare), (iii) total basal area, (iv) and total stem volume fitted simultaneously using seemingly unrelated regression. The component equations for stem density, basal area, and volume include a thinning modifier to forecast stand dynamics in thinned stands. It was shown that thinning significantly increased basal area and volume growth while reducing competition related mortality. No significant effect of thinning was found on dominant height. Model examination by means of various fit statistics indicated no obvious bias and improvement in prediction accuracy in comparison to existing models in general. An application of the developed stand-level model comparing different management scenarios exhibited plausible long-term behavior and we propose this is therefore suitable for national deployment.