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.
2018
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In order to establish the relationship between spectral reflectance and grass yield, we used a UAV-based hyperspectral camera and ground-based spectroradiometry to image a number of cultivated grasslands of different age and productivity in northern Norway. In addition, samples were taken to determine biomass and grass species composition. We investigated a number of vegetation indices as well as regression analysis to identify which spectral reflectance features can be used to map crop yield. We found poor relationships between NDVI and yield, but were able to obtain an acceptable relationship using all 15 available bands in the visible-near infrared range. Bands in the near infrared appear to contain most of the information related to yield.
Abstract
The aim of this study was to contribute to the development of pelleted compound recycling fertilizerswith favourable handling and spreading characteristics and balanced nutrient ratios by combiningnitrogen (N)- and phosphorus (P)-rich waste resources (meat bone meal, fish sludge or food waste)with potassium (K)-rich bottom wood ash. Pelleted compound recycling fertilizers with gooddurability and low dusting tendency were produced by roll-pelleting preheated waste resources at asuitable moisture content. However, the nutrient ratios in the final products were insufficientlybalanced, with too low N concentrations relative to P and K to meet crop demands. In a bioassayusing barley ( Hordeum vulgare) and a nutrient-deficient sand/peat mixture, the relative agronomiceffectiveness (RAE) of pelleted compound recycling fertilizers and reference recycling fertilizers was22–42% of that of mineral compound fertilizer. Growth limitation was due to reduced N availability(mineral fertilizer equivalent - MFE = 35–57%) or reduced P availability (MFE = 20–115%), with thegreatest P fertilizer value obtained for digestate based on dairy manure and fish sludge. Availability ofK in bottom wood ash was masked by the experimental soil.
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No abstract has been registered
Authors
Gry AlfredsenAbstract
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The estimated potential yield losses caused by plant pathogens is up to 16% globally (Oerke 2006) and most research in plant pathology aims to reduce yield loss in our crops directly or indirectly. Yield losses caused by a certain disease depend not only on disease severity, but also on the weather factors, the pathogen’s aggressiveness, and the ability of the crop to compensate for reduced photosynthetic area. The yield loss-disease relationship in a certain host-pathogen system might therefore change from year to year, making predictions for yield loss very difficult at the regional or even at the farmer’s level. However, estimating yield losses is essential to determine disease management thresholds at which acute control measures such as fungicide applications, or strategic measures such as crop rotation or use of resistant cultivars are economically and environmentally sensible. Legislation in many countries enforces implementation of integrated pest management (IPM), based on economic thresholds at which the costs due to a disease justify the costs for its management. Without a better understanding of the relationship between disease epidemiology and yield loss, we remain insufficiently equipped to design adequate IPM strategies that will be widely adapted in agriculture. Crop loss studies are resource demanding and difficult to interpret for one particular disease, as crops are usually not invaded by only one pest or pathogen at a time. Combining our knowledge on disease epidemiology, crop physiology, yield development, damage mechanisms involved, and the effect of management practices can help us to increase our understanding of the disease-crop loss relationship. The main aim of this paper is to review and analyze the literature on a representative host-pathogen relationship in an important staple food crop to identify knowledge gaps and research areas to better assess yield loss and design management strategies based on economic thresholds. Wheat is one of the most important staple foods worldwide and is susceptible to several important plant diseases. In our article, we focus on Septoria nodorum blotch (SNB) or Glume blotch of wheat as an example for a stubble-borne, seed-transmitted disease with a worldwide distribution causing considerable and regular yield losses. In their review on yield losses due to wheat pathogens in Australia, Murray and Brennan (2009) estimated the current annual economic loss due to SNB as high as $108 × 106, with potential costs as high as $230 × 106. The causal fungus, Parastagonospora nodorum, is currently serving as a model organism for molecular studies of the intimate relationship between necrotic effector-producing fungal strains and their corresponding susceptibility genes present in wheat cultivars (Oliver et al. 2012). In this paper, we analyze the literature on the biology of this common wheat pathogen, the yield loss it reportedly has caused, and the effect of control strategies to reduce this loss. Based on this analysis, we will evaluate the use of common management practices to reduce disease-related yield loss and identify related research needs.
Abstract
In many applications, estimates are required for small sub-populations with so few (or no) sample plots that direct estimators that do not utilize auxiliary variables (e.g. remotely sensed data) are not applicable or result in low precision. This problem is overcome in small area estimation (SAE) by linking the variable of interest to auxiliary variables using a model. Two types of models can be distinguished based on the scale on which they operate: i) Unit-level models are applied in the well-known area-based approach (ABA) and are commonly used in forest inventories supported by fine-resolution 3D remote sensing data such as airborne laser scanning (ALS) or digital aerial photogrammetry (AP); ii) Area-level models, where the response is a direct estimate based on a sample within the domain and the explanatory variables are aggregated auxiliary variables, are less frequently applied. Estimators associated with these two model types can make use of sample plots within domains if available and reduce to so-called synthetic estimators in domains where no sample plots are available. We used both model types and their associated model-based estimators in the same study area with AP data as auxiliary variables. Heteroscedasticity, i.e. for continuous dependent variables typically an increasing dispersion of re- siduals with increasing predictions, is often observed in models linking field- and remotely sensed data. This violates the model assumption that the distribution of the residual errors is constant. Complying with model assumptions is required for model-based methods to result in reliable estimates. Addressing heteroscedasticity in models had considerable impacts on standard errors. When complying with model assumptions, the precision of estimates based on unit-level models was, on average, considerably greater (29%–31% smaller standard errors) than those based on area-level models. Area-level models may nonetheless be attractive because they allow the use of sampling designs that do not easily link to remotely sensed data, such as variable radius plots.
Authors
Mohsen Ghanbari Vahid AkbariAbstract
Increased discrimination capability provided by polarimetric synthetic aperture radar (PolSAR) sensors compared to single and dual polarization synthetic aperture radar (SAR) sensors can improve land use monitoring and change detection. This necessitates reliable change detection methods in multitemporal PolSAR datasets. This paper proposes an unsupervised change detection algorithm for multilook PolSAR data. In the first step of the method, the Hotelling-Lawley trace (HLT) statistic is applied to measure the similarity of two multilook covariance matrices. As a result of this step, a scalar test statistic image is generated. Then, in the second step, a generalized Kittler and Illingworth (K&I) minimum-error thresholding algorithm is developed to perform on the test statistic image and discriminate between changed and unchanged areas. The K&I thresholding algorithm is based on the generalized Gamma distribution for statistical modeling of change and no-change classes. The proposed methodology is tested on a simulated PolSAR data and two C-band fully PolSAR datasets acquired by the uninhabited aerial vehicle SAR and RADARSAT-2 SAR satellites. The experiments show that the proposed algorithm accurately discriminates between change and no-change areas providing detection results with noticeably lower error rates and higher detection accuracy values compared to those of a CFAR-type thresholding of the HLT statistic. Also, the performance of the HLT statistic compared to the other statistics applied on the multilook polarimetric SAR data is assessed. Goodness-of-fit test results prove that the estimated generalized Gamma class conditional models adequately fit the corresponding change and no-change classes.
Abstract
No abstract has been registered
Authors
Matthew Schwarzkopf Michael Burnard Viacheslav Tverezovskiy Andreas Treu Miha Humar Andreja KutnarAbstract
Within the Slovenian region of Istria, the olive growing and oil production industry is strong. This industry has a long history and the olives grown here have high levels of biologically active compounds including a variety of phenolic compounds. Using residual materials generated by this industry in potential wood protection systems would not only valorise low-value materials and stimulate rural economies but would also provide an alternative to currently used oil-based protection systems. The objective of this study was to produce an oil treatment for wood protection and assess its efficacy in reducing leaching, weathering effects, and fungal decay. Two maleinisation techniques were used to chemically modify low-value lampante oil in an attempt to limit leaching when impregnated in wood. Pinus sylvestris (Scots pine) and Fagus sylvatica (European beech) were treated with the modified oils and underwent leaching, accelerated weathering, and decay tests. Leaching of the treatment oils was relatively low compared with other experiments and beech wood specimens treated with a direct maleinisation treatment showed improvement in performance compared to control specimens. In addition, it was found that the modified oils were not completely removed from the wood after solvent extraction indicating that they could potentially be used as an immobilisation agent in combination with other treatments thereby reducing the amount of active component of the protective agent.