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.
2015
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Authors
Björn RingselleAbstract
Elymus repens is a perennial grass weed that causes great yield losses in a variety of crops in the southern and northern temperate zones. Primary control methods for E. repens are herbicides or intensive tillage, both of which have a number of negative side-effects, e.g. herbicides can contaminate groundwater, and tillage can cause increased nitrogen leaching. The aim of this thesis was to investigate how to make non- herbicide control of Elymus repens more resource efficient in terms of less energy demanding soil cultivation and reduced nitrogen leaching. Three field experiments were used to test cover crop competition, mowing and different types of optimised tillage techniques and timing, as well as the combination of under-sown cover crops and mowing or row hoeing. The growth, biomass allocation and morphological responses of E. repens to competition were studied in a greenhouse experiment. The effect of competition from under-sown cover crops on E. repens seems to depend greatly on the cover crop biomass achieved. At high biomass levels, the cover crop can be highly suppressive (Paper IV) and reduce nitrogen leaching (Paper III), while at low levels they can still provide benefits such as reduced E. repens shoot biomass and increased subsequent cereal yield (Paper I). However, a low-yielding red clover cover crop increased E. repens rhizome production by 20-30%. Under-sown cover crops were successfully combined with both mowing and row hoeing (Paper I & III), but while repeated mowing reduced E. repens rhizome production by 35% it could not be shown to give a competitive advantage to the cover crops over E. repens (Paper I). However, the low nitrogen leaching and reduced downward transport of nitrogen when mowing or row hoeing was combined with under-sown cover crops make them interesting control methods for future research. Delaying tine cultivation by a few days after harvest did not reduce E. repens control, but a delay by 20 days tended to result in higher E. repens rhizome biomass and shoot densities, compared to performing it within a few days of harvest. Repeated tine cultivation did not improve control of E. repens or increase subsequent cereal yield, compared to a single cultivation directly after harvest. Repeated cultivation during autumn should therefore not be used categorically, but only when there is reason to believe the shoots will pass the compensation point due to the autumn conditions. We conclude that a site specific approach is necessary to achieve resource efficient control of E. repens.
Abstract
The objective of this pilot study was to compare resource use in a mountainous summer farming landscape between old and modern dairy cow breeds during a five-day period. The modern breed used a larger part of the landscape than the old breed, most likely due to differences in habitat patterns. The old breed group preferred semi-natural pastures, while the modern breed preferred overgrown semi-natural meadows, intermediate fen, intermediate wooded fen, and grass-rich sub-alpine birch woodland. Both breeds spent most time grazing grasses, but the modern breed showed a higher frequency of grasses and Vaccinium myrtillus in its diet, while the old breed showed a higher frequency of bushes and trees. The pilot study shows some trends supplementing and strengthening earlier results on how modern and traditional cattle breeds are differing in their impact on vegetation based on their use of space and their different diets.
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No abstract has been registered
Authors
Anne-Cécile Delwaide Lawton L. Nalley Bruce L. Dixon Diana M. Danforth Rodolfo M. Jr. Nayga Ellen J. Van Loo Wim VerbekeAbstract
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Abstract
The purpose of our study is to explore the possibility to use proximate RGB imagery as basis for site-specific management of perennial weeds in small grain cereals. The targeted species are the broadleaved weeds Cirsium arvense (L.) Scop. (Creeping thistle) and Sonchus arvensis L. (Perennial sowthistle) and the grass weed Elymus repens (L.) Gould. (Common quackgrass). These are the main challenges for perennial weed control in cereals in Norway and temperate zone. The overall idea is to make weed maps based on images acquired during harvest in autumn (August/September) and use these maps for site-specific weed management when these species are normally managed in Norway, i.e. 3-4 weeks after harvest (E. repens) or in the following spring, i.e. late May/early June (C. arvense and S. arvensis). An on-the-go weed detection and glyphosate application in one operation before harvest is also a possible usage of our image-based method where this timing of glyphosate application is allowed. Images were acquired with a consumer grade camera mounted on a 3 m pole and tilted to mimic images acquired from the roof of a combine harvester. Images were acquired few days before harvest, a period where the cereals are yellowish and weed leaves and stalks are still green. Plots, 8 m by 8 m, were established in cereals to cover a wide range in weed pressure- and flora. The four plot corners were marked with white styrofoam balls mounted on sticks prior imaging and recorded with GPS (10 cm accuracy). The machine vision algorithm performs first a geometrical transform to represent the images as pseudo-orthonormal to the ground plane. This transform is aided by white styrofoam balls marking the corners of the plot with known distance. In the intended practical use, the transform can be done by obtaining the camera-angle and heading from inertial and GPS measurements and assuming level ground. The classification algorithm starts by segmenting the image into a class for green parts of the weeds (leaf, stalk), and three classes for flower heads (yellow, white and purple), by using threshold filters in the HSV colour space. A connected components analysis is then performed on each of the binary images, where the very small regions are filtered out. The area and centre of each region is calculated for comparison with ground truth observations. Two types of ground truth data for evaluation of the algorithm are available: Manual assessment of weed coverage from computer display of images and weed maps based on GPS measurements at the time for their management. Machine vision algorithm outputs versus ground truth data will be presented.
Authors
Jorunn BørveAbstract
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Authors
Torsten Källqvist May Sæthre Katrine Borgå Hubert Dirven Ole Martin Eklo Merete Grung Jan Ludvig Lyche Marit Låg Asbjørn Magne Nilsen Line Emilie SverdrupAbstract
No abstract has been registered