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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.

2008

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Abstract

Lack of automatic weed detection tools has hampered the adoption of site-specific weed control in cereals. An initial object-oriented algorithm for the automatic detection of broad-leaved weeds in cereals developed by SINTEF ICT (Oslo, Norway) was evaluated. The algorithm ("WeedFinder") estimates total density and cover of broad-leaved weed seedlings in cereal fields from near-ground red-green-blue images. The ability of "WeedFinder" to predict 'spray'/'no spray' decisions according to a previously suggested spray decision model for spring cereals was tested with images from two wheat fields sown with the normal row spacing of the region, 0.125 m. Applying the decision model as a simple look-up table, "WeedFinder" gave correct spray decisions in 65-85% of the test images. With discriminant analysis, corresponding mean rates were 84-90%. Future versions of "WeedFinder" must be more accurate and accommodate weed species recognition.

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Abstract

The Gram-positive bacterium Clavibacter michiganensis subsp. sepedonicus is the causal agent of bacterial wilt and ring rot of potato. So far, only two proteins have been shown to be essential for virulence, namely a plasmid-encoded cellulase CelA and a hypersensitive response-inducing protein. We have examined the relative expression of CelA and eight putative virulence factors during infection of potato and in liquid culture, using quantitative real-time PCR. The examined putative virulence genes were celB, a cellulase-encoding gene and genes encoding a pectate lyase, a xylanase and five homologues of the Clavibacter michiganensis subsp. michiganensis pathogenicity factor Pat-1 thought to encode a serine protease. Six of the nine assayed genes were up-regulated during infection of potato, including celA, celB, the xylanase gene, and two of the pat genes. The pectate lyase gene showed only slightly elevated expression, whereas three of the five examined pat genes were down-regulated during infection in potato. Interestingly, the two up-regulated pat genes showed a noticeable sequence difference compared to the three down-regulated pat genes. These results reveal several new proteins that are likely to be involved in Clavibacter michiganensis subsp. sepedonicus pathogenicity.

Abstract

Achieving multifunctionality on a parcel of land, or in a landscape as a whole, requires a delicate balance between the different functions. This is particularly so when one of the desired functions is agricultural production. This paper examines the special challenges involved when cultural landscapes are protected by law. Norwegian `Landscape Protection Areas` are intended to preserve the landscape character of special landscapes. Ideally these landscapes should preserve ecological functions, whilst at the same time allowing for recreation and tourism, and the economic returns to ensure continued use of the landscape in the future. Balancing these functions is fraught with difficulties. The former agricultural systems that shaped these cultural landscapes may no longer be viable from the perspective of food production, and biodiversity is notoriously bad at paying for itself. Are the farmers that own the land willing to take on new roles as landscape managers rather than food producers? And who will pay for this? We present results of a questionnaire to farmers that own or manage farmland in Landscape Protection Areas. Of the 893 respondents, almost a quarter claimed that their farm business had been negatively affected by landscape protection. Niche products or alternative income possibilities had not been realised. We found a generally negative attitude towards municipal authorities and 24 % of respondents were strongly against the establishment of new Landscape Protection Areas, even if the State paid compensation for their economic loss. Based on results of the study we suggest that major improvements to the protection system could be made simply by improving communication between management authorities and farmers and involving farmers in making management plans.

Abstract

Many time series analysis methods depend on equally spaced observations with no data point missing. If this condition is met, powerful techniques are available that identify temporal structures such as trends, periodic phenomena or nonlinear dynamics. Unfortunately, most observations of natural systems, in particular over longer periods of time such as decades, are prone to sampling errors leading to missing points in the observations. Singular System Analysis (SSA) is a powerful tool to extract the dynamics contained in time series at arbitrary temporal scales. In its original formulation, however, SSA relies as well on data without missing values. Recently several extensions to SSA have been proposed which are designed to fill the gaps, exploiting the dynamics contained in the sampled parts of the series to estimate the structure of the signal at the position of missing values. SSA consists of two steps: Decomposition and reconstruction. For the decomposition the time series under investigation is embedded into a trajectory matrix and decomposed with singular value decomposition. The reconstruction (of selected components) of the time series employs the left and right singular values to obtain additive components of the time series. In the original variant of SSA both steps are dependent on gap free data sets. In order to evaluate the power of SSA for time series with missing values we simulate 1000 series of different processes - ARMA(2,3) and red noise contaminated sine waves. Several gap–schemes (continuous, periodic, and uniformly distributed) are used to create time series with up to 50% (artificially) missing values. SSA is applied on all surrogate series. The decomposition as well as the reconstruction is compared systematically to the gap free benchmark. In addition we evaluate the ability of SSA to capture periodic phenomena in the presence of missing values and whether periodical gaps lead to the identification of spurious periods. We demonstrate that SSA successfully reproduces the signal part of time series (i.e. components with large eigenvalues) for up to 30% missing values. For less significant components with higher rank numbers, the presence of gaps is increasingly deleterious. A number of distributed smaller gaps, a situation most likely to occur in observations, spoils the analysis to a much lesser degree than a single large gap. Thus, these new variants of SSA substantially enlarge the set of observational time series amenable to the analysis, and allows for obtaining precise estimates of the signal at the position of missing data points.

Abstract

Many time series analysis methods depend on equally spaced observations with no data point missing. If this condition is met, powerful techniques are available that identify temporal structures such as trends or periodic phenomena or nonlinear dynamics. Unfortunately, most of observations of natural systems, in particular over longer periods of time such as decades, are prone to sampling errors leading to missing points in the observations. Singular System Analysis (SSA) is a powerful tool to extract the dynamics contained in time series at arbitrary temporal scales...