The increased occurrence of Fusarium-mycotoxins in Norwegian cereals over the last decade, is thought to be caused by increased inoculum resulting from more cereal residues at the soil surface as a result of reduced tillage practices. In addition, weather conditions have increasingly promoted inoculum development and infection by Fusarium species. The objective of this work was to elucidate the influence of different tillage regimes (autumn plowing; autumn harrowing; spring plowing; spring harrowing) on the inoculum potential (IP) and dispersal of Fusarium spp. in spring oats. Tillage trials were conducted at two different locations in southeast Norway from 2010 to 2012. Oat residues from the previous year’s crop were collected within a week after sowing for evaluation. IP was calculated as the percentage of residues infested with Fusarium spp. multiplied by the proportion of the soil surface covered with residues. Fusarium avenaceum and F. graminearum were the most common Fusarium species recovered from oat residues. The IP of Fusarium spp. was significantly lower in plowed plots compared to those that were harrowed. Plowing in either the autumn or spring resulted in a low IP. Harrowing in autumn was more effective in reducing IP than the spring harrowing, and IP levels for the spring harrowed treatments were generally higher than all other tillage treatments examined. Surprisingly low levels of F. langsethiae were detected in the residues, although this species is a common pathogen of oat in Norway. The percentage of the residues infested with F. avenaceum, F. graminearum, F. culmorum, and F. langsethiae generally related to the quantity of DNA of the respective Fusarium species determined using quantitative PCR (qPCR). Fusarium dispersal, quantified by qPCR analysis of spore trap samples collected at and after heading, generally corresponded to the IP. Fusarium dispersal was also observed to increase after rainy periods. Our findings are in line with the general understanding that plowing is a means to reduce the IP of Fusarium spp. in cereal fields. The main inoculum source for F. langsethiae remains unclear. Our results will be useful in the development of forecasting tools to calculate the risk of Fusarium in cereals.

High concentrations of the mycotoxin deoxynivalenol (DON), produced by Fusarium graminearum have occurred frequently in Norwegian oats recently. Early prediction of DON levels is important for farmers, authorities and the Cereal Industry. In this study, the main weather factors influencing mycotoxin accumulation were identified and two models to predict the risk of DON in oat grains in Norway were developed: (1) as a warning system for farmers to decide if and when to treat with fungicide, and (2) for authorities and industry to use at harvest to identify potential food safety problems. Oat grain samples from farmers' fields were collected together with weather data (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013).A mathematical model was developed and used to estimate phenology windows of growth stages in oats (tillering, flowering etc.). Weather summarisations were then calculated within these windows, and the Spearman rank correlation factor calculated between DONcontamination in oats at harvest and the weather summarisations for each phenological window. DON contamination was most clearly associated with the weather conditions around flowering and close to harvest. Warm, rainy and humid weather during and around flowering increased the risk of DON accumulation in oats, as did dry periods during germination/seedling growth and tillering. Prior to harvest, warm and humid weather conditions followed by cool and dry conditions were associated with a decreased risk of DON accumulation. A prediction model, including only pre-flowering weather conditions, adequately forecasted risk of DON contamination in oat, and can aid in decisions about fungicide treatments.

High concentrations of the mycotoxins HT-2 and T-2 (HT2 + T2), primarily produced by Fusarium langsethiae, have occasionally been detected in Norwegian oat grains. In this study, we identified weather variables influencing accumulation of HT2 + T2 in Norwegian oat grains. Oat grain samples from farmers' fields were collected together with weather data (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013). Spearman rank correlation coefficients were calculated between the HT2 + T2 contamination in oats at harvest and a range of weather summarisations within estimated phenological windows of growth stages in oats (tillering, flowering etc.). Furthermore, we developed a mathematical model to predict the risk of HT2 + T2 in oat grains. Our data show that adequate predictions of the risk of HT2 + T2 in oat grains at harvest can be achieved, based upon weather data observed during the growing season. Humid and cool conditions, in addition to moderate temperatures during booting, were associated with increased HT2 + T2 accumulation in harvested oat grains, whereas warm and humid weather during stem elongation and inflorescence emergence, or cool weather and absence of rain during booting reduced the risk of HT2 + T2 accumulation. Warm and humid weather immediately after flowering increased the risk, while moderate to warm temperatures and absence of rain during dough development, reduced the risk of HT2 + T2 accumulation in oat grains. Our data indicated that HT2 + T2 contamination in oats is influenced by weather conditions both pre-and post-flowering. These findings are in contrast with a previous study examining the risk of deoxynivalenol contamination in oat reporting that toxin accumulation was mostly influenced by weather conditions from flowering onwards.

Deoxynivalenol (DON) in cereals, produced by Fusarium fungi, cause poisoning in humans and animals. Fusarium infections in cereals are favoured by humid conditions. Host species are susceptible mainly during the anthesis stage. Infections are also positively correlated with a regional history of Fusarium infections, frequent cereal production and non-tillage field management practices. Here, previously developed process-based models based on relative air humidity, rain and temperature conditions, Fusarium sporulation, host phenology and mycelium growth in host tissue were adapted and tested on oats. Model outputs were used to calculate risk indices. Statistical multivariate models, where independent variables were constructed from weather data, were also developed. Regressions of the risk indices obtained against DON concentrations in field experiments on oats in Sweden and Norway 2012-14 had coefficient of determination values (R) between 0.84 and 0.88. Regressions of the same indices against DON concentrations in oat samples averaged for 11 × 11 km grids in farmers' fields in Sweden 2012-14 resulted in R values between 0.27 and 0.41 for randomly selected grids and between 0.31 and 0.62 for grids with average DON concentration above 1000 μg kg grain in the previous year. When data from all three years were evaluated together, a cross-validated statistical partial least squares model resulted in R = 0.70 and a standard error of cross-validation (SECV) = 522 μg kg grain for the period 1 April-28 August in the construction of independent variables and R = 0.54 and SECV = 647 μg kg grain for 1 April-23 June. Factors that were not accounted for in this study probably explain large parts of the variation in DON among samples and make further model development necessary before these models can be used practically. DON prediction in oats could potentially be improved by combining weather-based risk index outputs with agronomic factors.

The aim of the study was to explore whether and how intensification would contribute to more environmentally friendly dairy production in Norway. Three typical farms were envisaged, representing intensive production strategies with regard to milk yield both per cow and per hectare in the three most important regions for dairy production in Norway. The scores on six impact categories for produced milk and meat were compared with corresponding scores obtained with a medium production intensity at a base case farm. Further, six scenario farms were derived from the base case. They were either intensified or made more extensive with regard to management practices that were likely to be varied and implemented under northern temperate conditions. The practices covered the proportion and composition of concentrates in animal diets and the production and feeding of forages with different energy concentration. Processes from cradle to farm gate were incorporated in the assessments, including on-farm activities, capital goods, machinery and production inputs. Compared to milk produced in a base case with an annual yield of 7250 kg energy corrected milk (ECM) per cow, milk from farms with yields of 9000 kg ECM or higher, scored better in terms of global warming potential (GWP). The milk from intensive farms scored more favourably also for terrestrial acidification (TA), fossil depletion (FD) and freshwater eutrophication (FE). However, this was not in all Highlights  Environmental impacts from milk production were lowest on farms with high yield per animal  High yields of energy-rich forage on intensive farms contributed to lower impacts  The proportion of concentrates in the diet per se was not important for the global warming potential

Sensitivity analysis and Bayesian calibration for testing robustness of the BASGRA model in different environments.

Young children have unique nutritional requirements, and breastfeeding is the best option to support healthy growth and development. Concerns have been raised around the increasing use of milk-based infant formulas in replacement of breastfeeding, in regards to health, social, economic and environmental factors. However, literature on the environmental impact of infant formula feeding and breastfeeding is scarce. In this study we estimated the environmental impact of four months exclusive feeding with infant formula compared to four months exclusive breastfeeding in a Norwegian setting. We used life-cycle assessment (LCA) methodology, including the impact categories global warming potential, terrestrial acidification, marine and freshwater eutrophication, and land use. We found that the environmental impact of four months exclusive feeding with infant formula was 35–72% higher than that of four months exclusive breastfeeding, depending on the impact category. For infant formula, cow milk was the main contributor to total score for all impact categories. The environmental impact of breastfeeding was dependant on the composition of the lactating mother’s diet. In conclusion, we found that breastfeeding has a lower environmental impact than feeding with infant formula. A limitation of the study is the use of secondary LCA data for raw ingredients and processes.

Fusarium graminearum is regarded as the main deoxynivalenol (DON) producer in Norwegian oats, and high levels of DON are occasionally recorded in oat grains. Weather conditions in the period around flowering are reported to have a high impact on the development of Fusarium head blight (FHB) and DON in cereal grains. Thus, it would be advantageous if the risk of DON contamination of oat grains could be predicted based on weather data. We conducted a functional data analysis of weather-based time series data linked to DON content in order to identify weather patterns associated with increased DON levels. Since flowering date was not recorded in our dataset, a mathematical model was developed to predict phenological growth stages in Norwegian spring oats. Through functional data analysis, weather patterns associated with DON content in the harvested grain were revealed mainly from about three weeks pre-flowering onwards. Oat fields with elevated DON levels generally had warmer weather around sowing, and lower temperatures and higher relative humidity or rain prior to flowering onwards, compared to fields with low DON levels. Our results are in line with results from similar studies presented for FHB epidemics in wheat. Functional data analysis was found to be a useful tool to reveal weather patterns of importance for DON development in oats.