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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.

2019

Abstract

The objective of this paper was to examine how cutting frequency, silage fermentation patterns and clover performance in grass-clover swards influence the use of inputs and profitability in an organic dairy system. A linear programming model was developed to compare a three-cut and a two-cut system for a model farm in Central Norway, either with restricted or extensive silage fermentation at low or high red clover (Trifolium pratense L.) proportion in the sward, giving 8 different silage types in all. Input-output relations incorporated into the model were derived from a meta-analysis of organic grassland field trials in Norway as well as a silage fermentation experiment, and with feed intakes and milk yields from simulations with the ‘TINE Optifôr’ feed ration planner in the Norfor feed evaluation system. The model maximized total gross margin of farms with 260,000 l milk quota and housing capacity for 45 cows, with separate model versions for each of the 8 silage types. Farmland availability varied from 30 to 70 ha with 40 ha as the basis. Our results suggested that farmland availability and marginal return of a competing barley crop profoundly influenced the profitability of the different silage types. A high clover proportion increased dry matter (DM) yields and was far more important for profitability than the score on the other factors considered at restricted land availabilities. Profits with the three-cut systems were always greater than those with the two-cut systems, the former being associated with greater silage intakes and improved dairy cow performances but lower DM forage yields. Three-cut systems were further favoured as land availability increased and also by a lower marginal return of barley. Although use of an acidifying silage additive improved feed intakes and milk production per cow, the practice reduced total milk production and depressed profit compared to untreated, extensively fermented silage at restrictive land availabilities. With more land available, and in particular at a low marginal return of barley, use of a silage additive was profitable.

Abstract

This paper describes the development and utility of the Norwegian forest resources map (SR16). SR16 is developed using photogrammetric point cloud data with ground plots from the Norwegian National Forest Inventory (NFI). First, an existing forest mask was updated with object-based image analysis methods. Evaluation against the NFI forest definitions showed Cohen's kappa of 0.80 and accuracy of 0.91 in the lowlands and a kappa of 0.73 and an accuracy of 0.96 in the mountains. Within the updated forest mask, a 16×16 m raster map was developed with Lorey's height, volume, biomass, and tree species as attributes (SR16-raster). All attributes were predicted with generalized linear models that explained about 70% of the observed variation and had relative RMSEs of about 50%. SR16-raster was segmented into stand-like polygons that are relatively homogenous in respect to tree species, volume, site index, and Lorey's height (SR16-vector). When SR16 was utilized in a combination with the NFI plots and a model-assisted estimator, the precision was on average 2–3 times higher than estimates based on field data only. In conclusion, SR16 is useful for improved estimates from the Norwegian NFI at various scales. The mapped products may be useful as additional information in Forest Management Inventories.

To document

Abstract

The number of invasive alien pest and pathogen species affecting ecosystem functioning, human health and economies has increased dramatically over the last decades. Discoveries of invasive pests and pathogens previously unknown to science or with unknown host associations yet damaging on novel hosts highlights the necessity of developing novel tools to predict their appearance in hitherto naïve environments. The use of sentinel plant systems is a promising tool to improve the detection of pests and pathogens before introduction and to provide valuable information for the development of preventative measures to minimize economic or environmental impacts. Though sentinel plantings have been established and studied during the last decade, there still remains a great need for guidance on which tools and protocols to put into practice in order to make assessments accurate and reliable. The sampling and diagnostic protocols chosen should enable as much information as possible about potential damaging agents and species identification. Consistency and comparison of results are based on the adoption of common procedures for sampling design and sample processing. In this paper, we suggest harmonized procedures that should be used in sentinel planting surveys for effective sampling and identification of potential pests and pathogens. We also review the benefits and limitations of various diagnostic methods for early detection in sentinel systems, and the feasibility of the results obtained supporting National Plant Protection Organizations in pest and commodity risk analysis.