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.
2020
Abstract
The aim of this work was to calculate farm specific LCAs for milk-production on 200 dairy farms in Central Norway, where 185 farmed conventional and 15 according to organic standards. We assume that there are variations in environmental emission drivers between farms and therefore also variation in indicators. We think that information can be utilized to find management improvements on individual farms. Farm specific data on inputs and production for the calendar years 2014 to 2016 were used. The LCAs were calculated for purchased products and on farm-emissions, including atmospheric deposition, biological nitrogen fixation, use of fertilizer and manure. The enteric methane emission from digestion was calculated for different animal groups. The functional unit was one kg energy- corrected milk (ECM) delivered at farm-gate. For the 200 dairy farms there were huge variations of farm characteristics, environmental per- formance and economic outcome. On average, the organic farms produced milk with a lower carbon footprint (1.2 kg CO2 eq./kg ECM) than the conventional ones (1.4 kg CO2 eq./kg ECM). The organic farms had also a lower energy intensity (3.1 MJ/kg ECM) and nitrogen intensity (5.0 kg N/kg N) than their conventional colleagues (4.1 MJ/kg ECM and 6.9 kg N/kg N respectively). The contribution margin was better on the organic farms with 6.6 NOK/kg ECM compared to the conventional with 5.9 NOK/kg ECM. The average levels of the environmental indicators were comparable but slightly higher than findings in other international studies. The current study proved that the FARMnor model allows to calculate LCAs for large number of individual farms. The results show that the environmental performance and economic outcome vary between farms. We recommend that farm specific LCA-results are used to unveil what needs to be changed for improving a farm’s environmental performance.
Abstract
The aim of this work was to calculate farm specific LCAs for milk-production on 200 dairy farms in Central Norway, where 185 farmed conventional and 15 according to organic standards. We assume that there are variations in environmental emission drivers between farms and therefore also variation in indicators. We think that information can be utilized to find management improvements on individual farms. Farm specific data on inputs and production for the calendar years 2014 to 2016 were used. The LCAs were calculated for purchased products and on farm-emissions, including atmospheric deposition, biological nitrogen fixation, use of fertilizer and manure. The enteric methane emission from digestion was calculated for different animal groups. The functional unit was one kg energy- corrected milk (ECM) delivered at farm-gate. For the 200 dairy farms there were huge variations of farm characteristics, environmental per- formance and economic outcome. On average, the organic farms produced milk with a lower carbon footprint (1.2 kg CO2 eq./kg ECM) than the conventional ones (1.4 kg CO2 eq./kg ECM). The organic farms had also a lower energy intensity (3.1 MJ/kg ECM) and nitrogen intensity (5.0 kg N/kg N) than their conventional colleagues (4.1 MJ/kg ECM and 6.9 kg N/kg N respectively). The contribution margin was better on the organic farms with 6.6 NOK/kg ECM compared to the conventional with 5.9 NOK/kg ECM. The average levels of the environmental indicators were comparable but slightly higher than findings in other international studies. The current study proved that the FARMnor model allows to calculate LCAs for large number of individual farms. The results show that the environmental performance and economic outcome vary between farms. We recommend that farm specific LCA-results are used to unveil what needs to be changed for improving a farm’s environmental performance.
Authors
Geneviève J. Parent Claudia Méndez-Espinoza Isabelle Giguère Melissa Magerøy Martin Charest Éric Bauce Joerg Bohlmann John J. MacKayAbstract
We review a recently discovered white spruce (Picea glauca) chemical defense against spruce budworm (Choristoneura fumiferana) involving hydroxyacetophenones. These defense metabolites detected in the foliage accumulate variably as the aglycons, piceol and pungenol, or the corresponding glucosides, picein and pungenin. We summarize current knowledge of the genetic, genomic, molecular, and biochemical underpinnings of this defense and its effects on C. fumiferana. We present an update with new results on the ontogenic variation and the phenological window of this defense, including analysis of transcript responses in P. glauca to C. fumiferana herbivory. We also discuss this chemical defense from an evolutionary and a breeding context.
Abstract
No abstract has been registered
Abstract
Farmers in Northern Norway frequently experience winter damaged fields caused by ice encasement. The economic consequences are severe due to loss of fodder and costs with reestablishment of swards. It is therefore important to choose the best available varieties for the local climatic and environmental conditions. We tested eight Norwegian cultivars of timothy (Phleum pratense), for tolerance to ice encasement and their regrowth capacity. Both old and new cultivars, and cultivars with good overwintering capacity and less biomass production were tested against more productive cultivars with less overwintering capacity. The experiment was a semi-field setup and plants were established in pots which were placed outside. Half of the pots were covered with ice and half were kept under snow cover. During four months, pots were brought, once per month, into a greenhouse for thawing and measurement of biomass production under normal growth conditions. The results indicate that the old winter hardy cultivar ‘Engmo’ is least affected by ice encasement but produces little biomass. The joint Nordic cultivar ‘Snorri’ produced most biomass of all the cultivars after a treatment with ice cover. In conclusion, there is a large difference between cultivars in ice encasement tolerance, and ice cover affected regrowth capacity far more than snow cover
Authors
Trygve S. Aamlid Tatsiana Espevig Karin Juul Hesselsøe Wendy Marie Waalen Pia Heltoft Thomsen Sigridur Dalmannsdottir Carl Johan Lönnberg Michelle DaCosta Eric WatkinsAbstract
No abstract has been registered
Authors
Trygve S. Aamlid Tatsiana Espevig Karin Juul Hesselsøe Wendy Marie Waalen Pia Heltoft Thomsen Sigridur Dalmannsdottir C. J. Lönnberg M. DaCosta E R WatkinsAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Min Lin Melanie Stadlmeier Volker Mohler Kar-Chun Tan Andrea Ficke James Cockram Morten LillemoAbstract
Key message We identifed allelic variation at two major loci, QSnb.nmbu-2A.1 and QSnb.nmbu-5A.1, showing consistent and additive efects on SNB feld resistance. Validation of QSnb.nmbu-2A.1 across genetic backgrounds further highlights its usefulness for marker-assisted selection. Abstract Septoria nodorum blotch (SNB) is a disease of wheat (Triticum aestivum and T. durum) caused by the necrotrophic fungal pathogen Parastagonospora nodorum. SNB resistance is a typical quantitative trait, controlled by multiple quantitative trait loci (QTL) of minor efect. To achieve increased plant resistance, selection for resistance alleles and/or selection against susceptibility alleles must be undertaken. Here, we performed genetic analysis of SNB resistance using an eight-founder German Multiparent Advanced Generation Inter-Cross (MAGIC) population, termed BMWpop. Field trials and greenhouse testing were conducted over three seasons in Norway, with genetic analysis identifying ten SNB resistance QTL. Of these, two QTL were identifed over two seasons: QSnb.nmbu-2A.1 on chromosome 2A and QSnb.nmbu-5A.1 on chromosome 5A. The chromosome 2A BMWpop QTL co-located with a robust SNB resistance QTL recently identifed in an independent eightfounder MAGIC population constructed using varieties released in the United Kingdom (UK). The validation of this SNB resistance QTL in two independent multi-founder mapping populations, regardless of the diferences in genetic background and agricultural environment, highlights the value of this locus in SNB resistance breeding. The second robust QTL identifed in the BMWpop, QSnb.nmbu-5A.1, was not identifed in the UK MAGIC population. Combining resistance alleles at both loci resulted in additive efects on SNB resistance. Therefore, using marker assisted selection to combine resistance alleles is a promising strategy for improving SNB resistance in wheat breeding. Indeed, the multi-locus haplotypes determined in this study provide markers for efcient tracking of these benefcial alleles in future wheat genetics and breeding activities.
Authors
Hye-Seon Kim Jessica M. Lohmar Mark Busman Daren W. Brown Todd A. Naumann Hege Hvattum Divon Erik Lysøe Silvio Uhlig Robert H. ProctorAbstract
Background Sphingolipids are structural components and signaling molecules in eukaryotic membranes, and many organisms produce compounds that inhibit sphingolipid metabolism. Some of the inhibitors are structurally similar to the sphingolipid biosynthetic intermediate sphinganine and are referred to as sphinganine-analog metabolites (SAMs). The mycotoxins fumonisins, which are frequent contaminants in maize, are one family of SAMs. Due to food and feed safety concerns, fumonisin biosynthesis has been investigated extensively, including characterization of the fumonisin biosynthetic gene cluster in the agriculturally important fungi Aspergillus and Fusarium. Production of several other SAMs has also been reported in fungi, but there is almost no information on their biosynthesis. There is also little information on how widely SAM production occurs in fungi or on the extent of structural variation of fungal SAMs. Results Using fumonisin biosynthesis as a model, we predicted that SAM biosynthetic gene clusters in fungi should include a polyketide synthase (PKS), an aminotransferase and a dehydrogenase gene. Surveys of genome sequences identified five putative clusters with this three-gene combination in 92 of 186 Fusarium species examined. Collectively, the putative SAM clusters were distributed widely but discontinuously among the species. We propose that the SAM5 cluster confers production of a previously reported Fusarium SAM, 2-amino-14,16-dimethyloctadecan-3-ol (AOD), based on the occurrence of AOD production only in species with the cluster and on deletion analysis of the SAM5 cluster PKS gene. We also identified SAM clusters in 24 species of other fungal genera, and propose that one of the clusters confers production of sphingofungin, a previously reported Aspergillus SAM. Conclusion Our results provide a genomics approach to identify novel SAM biosynthetic gene clusters in fungi, which should in turn contribute to identification of novel SAMs with applications in medicine and other fields. Information about novel SAMs could also provide insights into the role of SAMs in the ecology of fungi. Such insights have potential to contribute to strategies to reduce fumonisin contamination in crops and to control crop diseases caused by SAM-producing fungi.