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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.

2021

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The adoption of site-specific weed management (SSWM) technologies by farmers is not aligned with the scientific achievements in this field. While scientists have demonstrated significant success in real-time weed identification, phenotyping and accurate weed mapping by using various sensors and platforms, the integration by farmers of SSWM and weed phenotyping tools into weed management protocols is limited. This gap was therefore a central topic of discussion at the most recent workshop of the SSWM Working Group arranged by the European Weed Research Society (EWRS). This insight paper aims to summarise the presentations and discussions of some of the workshop panels and to highlight different aspects of weed identification and spray application that were thought to hinder SSWM adoption. It also aims to share views and thoughts regarding steps that can be taken to facilitate future implementation of SSWM.

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In March 2021, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by four families (Aliusviridae, Crepuscuviridae, Myriaviridae, and Natareviridae), three subfamilies (Alpharhabdovirinae, Betarhabdovirinae, and Gammarhabdovirinae), 42 genera, and 200 species. Thirty-nine species were renamed and/or moved and seven species were abolished. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.

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No abstract has been registered

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Conventional environmental risk assessment of chemicals is based on a calculated risk quotient, representing the ratio of exposure to effects of the chemical, in combination with assessment factors to account for uncertainty. Probabilistic risk assessment approaches can offer more transparency by using probability distributions for exposure and/or effects to account for variability and uncertainty. In this study, a probabilistic approach using Bayesian network modeling is explored as an alternative to traditional risk calculation. Bayesian networks can serve as meta-models that link information from several sources and offer a transparent way of incorporating the required characterization of uncertainty for environmental risk assessment. To this end, a Bayesian network has been developed and parameterized for the pesticides azoxystrobin, metribuzin, and imidacloprid. We illustrate the development from deterministic (traditional) risk calculation, via intermediate versions, to fully probabilistic risk characterization using azoxystrobin as an example. We also demonstrate the seasonal risk calculation for the three pesticides.

Abstract

The aquatic environment is constantly exposed to various chemicals caused by anthropogenic activities such as agricultural practices using plant protection products. Traditional Environmental Risk Assessment is based on calculated risk estimations usually representing a ratio of exposure to effects, in combination with assessment factors to account for uncertainty. In this study, we explore a more informative approach through probabilistic risk assessment, where probability distributions for exposure and effects are expressed and enable accounting for variability and uncertainty better. We focus on the risk assessment of various pesticides in a representative study area in the south east of Norway. Exposure data in this research was provided by the Norwegian Agricultural Environmental Monitoring Programme (JOVA)/ or predicted exposure concentration from a pesticide exposure model and effect data was derived from the NIVA Risk Assessment database (RAdb, www.niva.no/radb). A Bayesian network model is used as an alternative probabilistic approach to assess the risks of chemical. Bayesian Networks can serve as meta-models that link selected input and output variables from several separate project outputs and offer a transparent way of evaluating the required characterization of uncertainty for ERA. They can predict the probability of several risk levels, while facilitating the communication of estimates and uncertainties.

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Simple Summary Sugarcane, an important cash crop in Malawi, is susceptible to numerous insect pests, and many farmers rely heavily on chemical insecticides for their control. Biopesticides containing insect pathogens are used in several countries outside Malawi; however, the occurrence and use of insect pathogens is limited in Malawi. In this study, we evaluated the natural occurrence of insect pathogenic fungi in sugarcane (Saccharum officinarum) and in soil samples from sugarcane fields in Chikwawa District, southern Malawi. Insect pathogenic fungi from soil were isolated by baiting using larvae of the greater wax moth (Galleria mellonella). Insect pathogenic fungi were also isolated from surface-sterilized sugarcane leaves, stems, and roots. We found three types of insect pathogenic fungi: Beauveria bassiana, Metarhizium spp., and Isaria spp. Beauveria bassiana and Isaria spp. were found mostly from sugarcane leaves and stems, while Metarhizium spp. was mainly found in soils. To the best of our knowledge, this is the first report of B. bassiana and Isaria spp. occurring naturally as endophytes in sugarcane. Further, it is the first report of B. bassiana, Isaria spp. and Metarhizium spp. in the soil of sugarcane fields in Africa. Abstract The natural occurrence of entomopathogenic fungal endophytes in sugarcane (Saccharum officinarum) and in soil samples from sugarcane fields was evaluated in Chikwawa District, southern Malawi. Fungi from soil were isolated by baiting using Galleria mellonella larva. Fungal endophytes were isolated from surface-sterilized plant tissue sections. Forty-seven isolates resembled the genus Beauveria, 9 isolates were Metarhizium, and 20 isolates were Isaria. There was no significant difference in the number and type of fungal isolates collected from soil and from plant tissue. There was, however, a significant difference in the part of the plant where fungal species were isolated, which fungal species were isolated, and the number of fungal species isolated at each location. Phylogenetic analysis of 47 Beauveria isolates based on DNA sequencing of the Bloc intergenic region indicated that these isolates all belonged to B. bassiana and aligned with sequences of B. bassiana isolates of African and Neotropical origin. The Malawian B. bassiana isolates formed a distinct clade. No larvae died from infestation by multiple fungi. To the best of our knowledge, this is the first report of B. bassiana and Isaria spp. occurring naturally as endophytes in sugarcane. Further, it is the first report of B. bassiana, Isaria spp., and Metarhizium spp. in the soil of sugarcane fields in Africa.