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
Authors
Inghild Økland Agnar Kvalbein Wendy Marie Waalen Lise Bjørnstad Trygve S. Aamlid Tatsiana EspevigAbstract
No abstract has been registered
Abstract
WOOL QUALITY OF NORWEGIAN WHITE SPÆL SHEEP BREED Lise GRØVA 1), Inger Anne Boman 2) 1) NIBIO, Norwegian Institute of Bioeconomy Research, Gunnars veg 6, 6630 Tingvoll, Norway; lise.grova@nibio.no 2) NSG, Norwegian sheep and goat association, Postboks 104, N-1431 Ås The Norwegian White Speal Sheep are characterised by their fluke-shaped and tapered short tail, dual-coated wool and the ability to thrive under harsh environmental conditions. The income in Norwegian sheep farming comes from lamb meat, wool and pelts. Today, wool is of minor economic importance, commonly accounting for less than 10% of the income. However, the interest of wool as a sustainable and local fibre is increasing. Wool quality traits of the Norwegian White spæl breed has been reported to be declining; i.e. an increase in medulated fibres and in kemp. To address this challenge, there has been developed and incorporated 1) wool quality assessment tutorials for farmers and breeders, 2) included heritability estimates of wool fleece weight and quality class in index calculations, and 3) conducted OFDA analysis of wool from breeding rams for three consecutive years. The work was initiated by the research-project KRUS - Enhancing local wool value chains in Norway (NFR 244618/E50) and has been carried out by NIBIO, the Norwegian Sheep Breeders Association (NSG), Animalia and Norilia. Wool quality assessment tutorials for farmers and breeders are available as a.pdf and video for free download from NSG webpage (nsg.no). A ‘wool evaluation kit’ with a magnifier is available for purchase, also from NSG. Implementing index estimates was made possible when including fleece weigh and fleece classification from all sheared lambs at slaughter into the Norwegain National Sheep Recording system. Further, OFDA analysis were conducted on wool from breeding rams collected autumn 2015, 2016 and 2017. The wool samples were analysed using the optical FD analyser (OFDA100; BSC Electronics Pty Ltd, Western Australia, Australia). OFDA analysis is conducted to describe wool quality traits, development of quality traits over time and also development of quality traits at different age of breeding rams. Preliminary results from this study will be presented at the conference. Keywords: sheep, wool quality, Norwegian white spæl, dual felt, double-coat
Abstract
No abstract has been registered
2017
Authors
Johannes BreidenbachAbstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
Agricultural landscapes are products of farming activity in the past and present. They are everyday landscapes for many people and are important for outdoor recreation. Many plant and animal species find their habitat in these landscapes, and a high number of cultural heritage sites can also be found there. At the same time, agricultural landscapes are continuously subject to change. To ensure sufficient information on how these landscapes change, a national monitoring programme with the acronym “3Q” was initiated in 1998, to document status, continuity and change in agricultural landscapes in Norway. The Division of Survey and Statistics at NIBIO is responsible for the programme.
Abstract
No abstract has been registered
Authors
Xian Li Shuhe Zhao Hong Yang Dianmin Cong Zhaohua ZhangAbstract
Land use and cover change (LUCC) is important for the global biogeochemical cycle and ecosystem. This paper introduced a change detection method based on a bi-band binary mask and an improved fuzzy c-means algorithm to research the LUCC. First, the bi-band binary mask approach with the core concept being the correlation coefficients between bands from different images are used to locate target areas with a likelihood of having changed areas. Second, the improved fuzzy c-means (FCM) algorithm was used to execute classification on the target areas. This improved algorithm used distances to the Voronoi cell of the cluster instead of the Euclidean distance to the cluster center in the calculation of membership, and some other improvements were also used to decrease the loops and save time. Third, the post classification comparison was executed to get more accurate change information. As references, change detection using univariate band binary mask and NDVI binary mask were executed. The change detection methods were applied to Landsat 8 OLI images acquired in 2013 and 2015 to map LUCC in Chengwu, north China. The accuracy assessment was executed on classification results and change detection results. The overall accuracy of classification results of the improved FCM is 95.70% and the standard FCM is 84.40%. The average accuracy of change detection results using bi-band mask is 88.92%, using NDVI mask is 81.95%, and using univariate band binary mask is 56.01%. The result of the bi-band mask change detection shows that the change from farmland to built land is the main change type in the study area: total area is 9.03 km2. The developed method in the current study can be an effective approach to evaluate the LUCC and the results helpful for the land policy makers.
Authors
Vigdis Vandvik Tessa Bargmann Sigrid Skrivervik Bruvoll Matthew I. Daws Kristine Grimsrud Hanna Lee Pål Thorvaldsen Liv Guri Velle Joachim Paul TöpperAbstract
No abstract has been registered
Authors
Anto Raja Dominic Ole Martin Eklo Marianne Stenrød Eivind Solbakken Roar Lågbu P Horney D Daehmlow Jörn StrassemeyerAbstract
No abstract has been registered