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.
2022
Authors
Asima Akagić Amila Oras Fuad Gaši Mekjell Meland Pakeza Drkenda Senad Memić Nermina Spaho Sanja Oručević Žuljević Igor Jerković Osman Musić Metka HudinaAbstract
Traditional pear cultivars are increasingly in demand by consumers because of their excellent taste, the possibility of use in sustainable food production systems, convenience as raw materials for obtaining products of high nutritional quality, and perceived health benefits. In this study, individual sugars, organic acids, and polyphenols in the fruits of nine traditional and one commercial pear cultivar during two growing seasons were determined by HPLC. A significant influence of cultivars, growing years, and their interaction on the content of analyzed primary and secondary metabolites was determined. The commercial pear cultivar ‘Président Drouard’ and traditional cultivars ‘Dolokrahan’, ‘Budaljača’, and ‘Krakača’ had a lower content of all analyzed sugars. Overall, traditional pear cultivars had higher total polyphenols in the peel and pulp than ‘Président Drouard’, with the exception ‘Takiša’ and ‘Ahmetova’. High polyphenol content detected in ‘Budaljača’, ‘Dolokrahan’, and ‘Krakača’ shows the utilization value of traditional pear germplasm. The obtained data can serve as practical supporting data for the use of traditional pears in the neutraceutical, pharmaceutical, and food industries.
Abstract
No abstract has been registered
Authors
Tommi Nyman Saskia Wutke Elina Koivisto Tero Klemola Mark R. Shaw Tommi Andersson Håkon Haraldseide Snorre Hagen Ryosuke Nakadai Kai RuohomäkiAbstract
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.
Abstract
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.
Authors
F. M. R. Ziegler Anita Sønsteby A. Masny B. Schulten V. Uglosch M. Franzen L. Munnes S. Osorio Algar B. UsadelAbstract
No abstract has been registered
Abstract
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.
Authors
Lone Ross Lizhen Huang Erik Trømborg Roja Modaresi Hanne Kathrine Sjølie Callum Aidan Stephen HillAbstract
No abstract has been registered
Authors
Simon Weldon Bert van der Veen Eva Farkas Nazli Pelin Kocatürk Schumacher Alba Dieguez-Alonso Alice Budai Daniel RasseAbstract
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.
Abstract
No abstract has been registered
Abstract
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.