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.
2020
Abstract
No abstract has been registered
Authors
Trust Kasambala Richard Meadow Bishal K. Sitaula Ole Martin EkloAbstract
It is widely accepted that climate change will affect sugarcane production and its associated pests. The aim of this chapter is to review the impact of climate variability on factors and processes affecting environmental exposure of pesticides used in sugarcane production in Malawi. We indicate that changes in temperature and rainfall will have a dual effect on pesticide risk. Temperatures higher than 30–35 °C affect pesticide toxicity, though effects will vary with pesticide-pest combination. Rapid degradation of pesticides such as acetamiprid and atrazine is expected at temperatures above 30 °C. Higher temperature may increase the incidence and severity of pests such as red spider mites, prompting farmers to use more pesticides. On the other hand, the amount and timing of rainfall in relation to pesticide application are important determinants on the amount of pesticide residue remaining in the environment. There is a higher likelihood of pesticide transport to surface (through runoff) and percolating to groundwater at higher rainfall intensity. A higher soil water content will result in increased pesticide degradation. There is a need to determine the occurrence of pesticide residue in sugarcane cropping and aquatic systems surrounding sugarcane plantations. We highly recommend building capacity in this sector, particularly in biological control of pest species using microbial agents such as insect pathogenic fungi pathogens.
Abstract
No abstract has been registered
Authors
Anastasia Georgantzopoulou Claire Coutris Kuria Ndungu Christian Vogelsang Patricia Almeida Carvalho Ana Catarina Almeida Ailbhe MackenAbstract
The majority of nanomaterials (NMs) used in commercial applications are likely to enter the wastewater stream and reach wastewater treatment plants (WWTP). Studies have shown high association of NMs with sewage sludge therefore soils can be a sink for NM pollution making terrestrial organisms vulnerable. NMs undergo transformations in different environmental matrices leading to altered behaviour, bioavailability and subsequent toxicity that can differ from the pristinepristine material. The NM transformation and the potential hazard they pose in these compartments are poorly understood. The aim of the study was to elucidate (i) the behaviour of Ag and TiO2 NMs in sewage sludge and sludge amended-soil and (ii) the subsequent effects of transformed NMs on the coelomocytes of the earthworm E. fetida.Spherical polyvinylpyrrolidone (PVP)-coated Ag nanoparticles (Ag NPs, 25 nm) and uncoated TiO2 NPs (anatase, 5 nm primary size, NM-101,JRC) were used in this study. Two types of sludge were used for the exposures, one from a municipal WWTP (Oslo, Norway), and another from a lab-scale WWTP simulating biological wastewater treatment processes continuously dosed during 5 weeks with well-characterised Ag and TiO2 NPs. Earthworms (adults E. fetida) were exposed to LUFA 2.2 soil amended with sewage sludge at two application rates: 20 t ha-1 (maximum recommended application rate in Europe), and 3 times this application rate, i.e. 60 t ha-1 (worst-case scenario). After 12 and 39 days, coelomocytes were isolated from exposed earthworms, and effects on cell population, metabolic activity, lysosomal integrity and reactive oxygen species (ROS) formation were assessed. Characterization of NMs in the sludge amended-soil and soil elutriates, in whole earthworms and coelomocytes isolated from exposed earthworms, was carried out at the beginning (day 0), during (day 12) and the end (day 39) of the exposure period, using inductively coupled plasma-mass spectrometry (ICP-MS) and single-particle (sp)-ICP-MS. Dose and exposure time-dependent effects were observed, with an alteration in the cell composition of coelomocytes, increase in ROS formation and decrease in lysosomal membrane integrity being more pronounced at the highest exposure concentration. The importance of taking NM transformation into account and the sensitivity of the E. fetida coelomocytes as a model to study the effects of transformed NMs in vitro are discussed.
Abstract
The impact of historical and present drivers on biodiversity, particularly species richness and abundance, in afforestation areas concerning non-native tree species is still poorly understood. A better understanding is important to ensure appropriate forest management in the face of climate change and increasing demand for wood products. Here, we have reviewed 75 biodiversity studies in Sitka spruce plantations in NW Europe, forest management recommendations for maintaining biodiversity, timber production and carbon sequestration in Sitka spruce forests in coastal Norway compared to NW Europe. Due to more focus on non-market landscape benefits and protection sites in coastal areas, transformation of spruce plantations is common. Premature cutting of stands and shelterbelts and clearing away saplings has become the dominant management practice in Norway. Based on the extent of use in Norway, and results from biodiversity studies in Sitka spruce plantations in NW Europe, the quality of evidence for the prevailing practice and recommendations in coastal Norway is highly questioned. To reduce conflicts, we propose a more knowledge-based management, a broader perspective underpinning the range of afforestation goals, also including the use of alternative silvicultural methods to increase structural variation in Sitka spruce stands.
Abstract
Organic amendments can improve grassland productivity. Timothy and tall fescue were sown on a sandy loam and a coarse sand at Særheim, Norway, in September 2016 and on a loamy sand at Skierniewice, Poland, in April 2017, and cut and fertilised according to normal practices for the two regions from 2017 to 2019. At both sites, 0.75 kg DM m-2 of either digested or undigested manure (the latter with or without 2.9 kg biochar m-2) were incorporated prior to sowing. On the coarse sand at Særheim, total seasonal tall fescue yield in 2018 was 46–60% higher in the organic amendment treatments, and total seasonal timothy yield in the digestate treatment was 97% higher, than in the control treatment for the same species with only mineral fertiliser. On the sandy loam at Særheim and the loamy sand at Skierniewice, none of the amendments resulted in significant yield increments. These results indicate a clear effect on soil type on grassland biomass response to organic amendments.
Authors
Johannes Breidenbach Janis Ivanovs Annika Kangas Mats Nilsson Thomas Nord-Larsen Rasmus AstrupAbstract
No abstract has been registered
Authors
Johannes BreidenbachAbstract
No abstract has been registered
Authors
Rui Xia Yalin Yang Xingliang Pan Chenchen Gao Yuanyuan Yao Xuewei Liu Tsegay Teame Fengli Zhang Juan Hu Chao Ran Zhen Zhang Jihong Liu Clarke Zhigang ZhouAbstract
Quorum quenching (QQ) blocks bacterial cell-to-cell communication (i.e., quorum sensing), and is a promising antipathogenic strategy to control bacterial infection via inhibition of virulence factor expression and biofilm formation. QQ enzyme AiiO-AIO6 from Ochrobactrum sp. M231 has several excellent properties and shows biotherapeutic potential against important bacterial pathogens of aquatic species. AiiO-AIO6 can be secretory expressed in Bacillus subtilis via a non-classical secretion pathway. To improve AiiO-AIO6 production, four intracellular protease-deletion mutants of B. subtilis 1A751 were constructed by individually knocking out the intracellular protease-encoding genes (tepA, ymfH, yrrN and ywpE). The AiiO-AIO6 expression plasmid pWB-AIO6BS was transformed into the B. subtilis 1A751 and its four intracellular protease-deletion derivatives. Results showed that all recombinant intracellular protease-deletion derivatives (BSΔtepA, BSΔymfH, BSΔyrrN and BSΔywpE) had a positive impact on AiiO-AIO6 production. The highest amount of AiiO-AIO6 extracellular production of BSΔywpE in shake flask reached 1416.47 U/mL/OD600, which was about 121% higher than that of the wild-type strain. Furthermore, LC–MS/MS analysis of the degrading products of 3-oxo-C8-HSL by purification of AiiO-AIO6 indicated that AiiO-AIO6 was an AHL-lactonase which hydrolyzes the lactone ring of AHLs. Phylogenetic analysis showed that AiiO-AIO6 was classified as a member of the α/β hydrolase family with a conserved “nucleophile-acid-histidine” catalytic triad. In summary, this study showed that intracellular proteases were responsible for the reduced yields of heterologous proteins and provided an efficient strategy to enhance the extracellular production of AHL lactonase AiiO-AIO6.
Authors
Hainie Zha Yuxin Miao Tiantian Wang Yue Li Jing Zhang Weichao Sun Zhengqi Feng Krzysztof KusnierekAbstract
Optimizing nitrogen (N) management in rice is crucial for China’s food security and sustainable agricultural development. Nondestructive crop growth monitoring based on remote sensing technologies can accurately assess crop N status, which may be used to guide the in-season site-specific N recommendations. The fixed-wing unmanned aerial vehicle (UAV)-based remote sensing is a low-cost, easy-to-operate technology for collecting spectral reflectance imagery, an important data source for precision N management. The relationships between many vegetation indices (VIs) derived from spectral reflectance data and crop parameters are known to be nonlinear. As a result, nonlinear machine learning methods have the potential to improve the estimation accuracy. The objective of this study was to evaluate five different approaches for estimating rice (Oryza sativa L.) aboveground biomass (AGB), plant N uptake (PNU), and N nutrition index (NNI) at stem elongation (SE) and heading (HD) stages in Northeast China: (1) single VI (SVI); (2) stepwise multiple linear regression (SMLR); (3) random forest (RF); (4) support vector machine (SVM); and (5) artificial neural networks (ANN) regression. The results indicated that machine learning methods improved the NNI estimation compared to VI-SLR and SMLR methods. The RF algorithm performed the best for estimating NNI (R2 = 0.94 (SE) and 0.96 (HD) for calibration and 0.61 (SE) and 0.79 (HD) for validation). The root mean square errors (RMSEs) were 0.09, and the relative errors were <10% in all the models. It is concluded that the RF machine learning regression can significantly improve the estimation of rice N status using UAV remote sensing. The application machine learning methods offers a new opportunity to better use remote sensing data for monitoring crop growth conditions and guiding precision crop management. More studies are needed to further improve these machine learning-based models by combining both remote sensing data and other related soil, weather, and management information for applications in precision N and crop management.