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.
2025
Authors
Cristina Micheloni Frank Willem Oudshoorn María Isabel Blanco Penedo Sari Autio Andrea Beste Jacopo Goracci Matthias Koesling Ursula Kretzschmar Eligio Malusá Maria Dolores Raigon Jimenez Bernhard Speiser Jan van der Blom Felix WäckersAbstract
The Expert Group for Technical Advice on Organic Production (EGTOP) was requested to advise on the use of several substances with plant protection or fertilising effects in organic production. The Group discussed whether the use of these substances and methods is in line with the objectives and principles of organic production, and whether they should be included in Regulation (EU) 2021/1165.
Authors
Cristina Micheloni Frank Willem Oudshoorn Sari Autio Andrea Beste María Isabel Blanco Penedo Jacopo Goracci Matthias Koesling Eligio Malusá Bernhard Speiser Jan van der Blom Felix Wäckers Ursula KretzschmarAbstract
The Expert Group for Technical Advice on Organic Production (EGTOP) was requested to advise on the use of several substances in organic production. The Group discussed whether the use of these substances is in line with the objectives and principles of organic production and whether they should therefore be included in Annex V of Commission Implementing Regulation (EU) 2021/1165.
Authors
Atle Wibe Berit Marie Blomstrand Lisa Deiana Davide Bochicchio Tommy Ruud Richard Helliwell Matthias Koesling Anne Grete Kongsted Marina Štukelj Marina Spinu A Vasiu Andrew Richard Williams Amalie Camilla Pedersen Helena Meijer Stig Milan ThamsborgAbstract
No abstract has been registered
Abstract
Context Dairy farming contributes approximately 2.5 % of annual global anthropogenic greenhouse gas (GHG) emissions, necessitating effective mitigation strategies. Two approaches are often discussed: low-intensity, low-cost production with minimal reliance on purchased inputs; and high-intensity production with higher-yielding cows to reduce land use and reduce methane emissions per unit of milk. Objective The objective was to identify management factors and farm characteristics that explain variations in GHG emissions, environmental, and economic performance. Indicators included were GHG emissions, land use occupation, energy intensity, nitrogen intensity, and gross margin. Methods Life Cycle Assessment (LCA) was used to calculate the environmental impacts for 200 commercial dairy farms in Central Norway based on farm activities, purchased inputs, machinery, and buildings from 2014 to 2016. A multiple regression analysis with backward elimination was conducted to highlight important variables for environmental impact and economic outcome. Results and conclusions A higher share of dairy cows was found to be the most important factor in reducing GHG emissions, energy and nitrogen intensity, and land use but also to decrease gross margin. Additional key factors for reducing environmental impact included less purchased nitrogen fertiliser, and higher forage yield. There were no statistical correlations between GHG emissions and gross margin per MJ of human-edible energy delivered. Significance Conducting LCA for many dairy farms allows to highlight important factors influencing environmental impact and economic outcome. Using the delivery of human-edible energy from milk and meat as a functional unit allows for a combined evaluation of milk and meat production on a farm.
Authors
Kristian Hansen Håvard Steinshamn Sissel Hansen Matthias Koesling Tommy Dalgaard Bjørn Gunnar HansenAbstract
To evaluate the environmental impact across multiple dairy farms cost-effectively, the methodological frame- work for environmental assessments may be redefined. This article aims to assess the ability of various statistical tools to predict impact assessment made from a Life Cyle Assessment (LCA). The different models predicted estimates of Greenhouse Gas (GHG) emissions, Energy (E) and Nitrogen (N) intensity. The functional unit in the study was defined as 2.78 MJMM human-edible energy from milk and meat. This amount is equivalent to the edible energy in one kg of energy-corrected milk but includes energy from milk and meat. The GHG emissions (GWP100) were calculated as kg CO2-eq per number of FU delivered, E intensity as fossil and renewable energy used divided by number of FU delivered, and N intensity as kg N imported and produced divided by kg N delivered in milk or meat (kg N/kg N). These predictions were based on 24 independent variables describing farm characteristics, management, use of external inputs, and dairy herd characteristics. All models were able to moderately estimate the results from the LCA calculations. However, their precision was low. Artificial Neural Network (ANN) was best for predicting GHG emissions on the test dataset, (RMSE = 0.50, R2 = 0.86), followed by Multiple Linear Regression (MLR) (RMSE = 0.68, R2 = 0.74). For E intensity, the Supported Vector Machine (SVM) model was performing best, (RMSE = 0.68, R2 = 0.73), followed by ANN (RMSE = 0.55, R2 = 0.71,) and Gradient Boosting Machine (GBM) (RMSE = 0.55, R2 = 0.71). For N intensity predictions the Multiple Linear Regression (MLR) (RMSE = 0.36, R2 = 0.89) and Lasso regression (RMSE = 0.36, R2 = 0.88), followed by the ANN (RMSE = 0.41, R2 = 0.86,). In this study, machine learning provided some benefits in prediction of GHG emission, over simpler models like Multiple Linear Regressions with backward selection. This benefit was limited for N and E intensity. The precision of predictions improved most when including the variables “fertiliser import nitrogen” (kg N/ha) and “proportion of milking cows” (number of dairy cows/number of all cattle) for predicting GHG emission across the different models. The inclusion of “fertiliser import nitrogen” was also important across the different models and prediction of E and N intensity.
2024
Abstract
Aims To develop a methodology to study uptake and redistribution by plants of NH4+ from deep soil, applying it to investigate deep root N uptake by cultivated grassland species. Methods A slow-release 15NH4+ label adsorbed to clinoptilolite was placed into soil (depth 42 cm) well below the densest root zone in well-established monospecific stands of five grass and two clover species. Species showing a variety of deep rooting patterns, N acquisition strategy, forage qualities, and persistence in hemiboreal conditions were chosen. The label was placed in early spring and tracked throughout one or two growing seasons in two repeated experiments. Results After two growing seasons ~ 90% of the label was tracked in the soil and harvested herbage of grasses, less in clovers. Deep N uptake was limited in spring, increased during mid-season, and was strongest in autumn in all species, despite lower herbage yield in autumn. Species differed in ability to recover and maintain 15N in the soil–plant system. In one growing season, Lolium perenne L., Phleum pratense L., Schedonorus pratensis (Huds.) P.Beauv. and Schedonorus arundinaceus (Schreb.) Dumort herbage recovered ~ 65% of the label, Poa pratensis L. 54%, and Trifolium pratense L. and Trifolium repens L. 36–48%. Label transport to topsoil was observed, mainly attributable to plant nutrient redistribution rather than physical diffusion. Conclusions The innovative slow-release 15N label enabled tracing species differences and seasonal changes in uptake of NH4+ from deep soil. Among the tall-growing grasses, growth vigor appeared as important for deep N uptake as expected root depth.
Authors
Cristina Micheloni Frank Willem Oudshoorn María Isabel Blanco Penedo Sari Autio Andrea Beste Marie Bourin Jacopo Goracci Matthias Koesling Ursula Kretzschmar Eligio Malusá Bernhard Speiser Jan van der Blom Felix WäckersAbstract
The Expert Group for Technical Advice on Organic Production (EGTOP) was requested to advise on the replacement of the wording ‘factory farming’ in Regulation (EU) 2021/11652, Annex II. The opinion of the Group is that the wording ‘factory farming’ is not appropriate to express which animal-derived fertilisers are allowed, restricted, or forbidden to be used in organic farming, as currently defined in Annex II of the Regulation (EU) 2021/1165. Therefore, following an in-depth analysis of possible criteria suitable for defining a method to differentiate animal-derived fertilisers for which use are currently acceptable in organic farming, two major criteria were selected to this purpose: origin of the fertiliser and the occurrence of processing. Depending on the application of these two criteria, the amount of total nitrogen applicable per year and per hectare from conventional animal-derived fertilisers is restricted or not allowed. This restriction is meant to reduce the risk of introducing pollutants into the soil of organic farms. These criteria and their implementation were considered to fulfil the pragmatic approach taken by the Group for not substantially increasing the burden to organic farmers, allowing verification by certifying bodies, and, at the same time, fostering the adoption of other practices of soil fertilization and supporting the reputation of the organic farming sector. A multicriteria approach can be implemented to regulate the use of animal-derived fertilisers in organic farms, to replace the wording ‘factory farming origin forbidden’. Moreover, even though animal by-products are out of the scope of the point 1.9.4 in Annex II of Regulation (EU) 2018/848, the need of a consistent approach to the use of animal-derived fertilising products and considering that these kinds of products are used as a source of nitrogen, the Group recommends including them in the same quantitative approach and resulting restrictions proposed for farmyard manure and its derivatives.
Authors
Cristina Micheloni Frank Willem Oudshoorn María Isabel Blanco Penedo Sari Autio Andrea Beste Marie-Christine Bourin Jacopo Goracci Matthias KoeslingAbstract
The Expert Group for Technical Advice on Organic Production (EGTOP) was requested to advise on the use of several substances for use in organic production of food or feed. The Group discussed whether the use of these substances and methods is in line with the objectives and principles of organic production, and whether they should be included in Reg. (EU) 2021/1165.
Authors
Kristian Hansen Matthias Koesling Håvard Steinshamn Bjørn Gunnar Hansen Tommy Dalgaard Sissel HansenAbstract
In this study, 200 Norwegian dairy farms were analyzed over three years to compare greenhouse gas emissions, nitrogen (N) intensity, gross margin, and land use occupation between organically and conventionally managed farms. Conventionally managed farm groups were constructed based on propensity matching, selecting the closest counterparts to organically managed farms (n=15). These groups, each containing 15 farms, were differentiated by an increasing number of matching variables. The first group was matched based on geographical location, milk quota, and milking cow units. In the second match, the proportion of milking cows in the total cattle herd was added, and in the third, the ratio of milk delivered to milk produced and concentrate usage per dairy cow were included. The analysis showed that the conventionally managed farms (n=185) had higher greenhouse gas emissions (1.42 vs 0.98 kg CO2 per 2.78 MJ of edible energy from milk and meat, calculated as GWP100-AR4) and higher N intensity (6.9 vs 5.0 kg N input per kg N output) compared to the organic farms (N=15). When comparing emissions per kg of energy-corrected milk (ECM) delivered, conventional farms also emitted more CO2 (1.07 vs 0.8 kg CO2 per kg ECM). Furthermore, conventionally managed farms showed lower gross margins both in terms of NOK per 2.78 MJ edible energy delivered (5.8 vs 6.5 NOK) and per milking cow unit (30 100 vs 34 400 NOK), and they used less land (2.9 vs 3.6 m² per 2.78 MJ edible energy delivered) compared to organic farms. No differences were observed among the three conventionally managed groups in terms of emissions, N intensity, land use occupation, and gross margin.
Abstract
Ruminants, including sheep, contribute significantly to methane emissions, thus resulting in high emissions per kg of product. However, they can utilise plant material unsuitable for human consumption, thereby transforming it into valuable, protein-rich food. Grazing also preserves cultural landscapes and can contribute to carbon sequestration. Under¬standing the balance between these factors within the climate change context is crucial. This study inves-tigates the environmental impact of meat, milk, and wool production from sheep farming in Norway and Slovenia.