- Authors:
- Molgaard, J. P.
- Rasmussen, J.
- Henriksen, C. B.
- Source: Soil & Tillage Research
- Volume: 94
- Issue: 1
- Year: 2007
- Summary: Field experiments were conducted on sand and sandy loam from 2000 to 2002 to determine how timing of ridging affects potato tuber yield and quality depending on soil texture and the use of catch crops. On sand, ridging in winter increased soil N availability in the 0-50 cm soil layer in spring from 5.7 to 6.8 mg N kg(-1) soil (19%) compared with ridging in autumn (P
- Authors:
- Horfarter, R.
- Hougaard, H.
- Broge, N.
- Knudsen, L.
- Hansen, O. M.
- Schelde, K.
- Thomsen, A.
- Berntsen, J.
- Source: Precision Agriculture
- Volume: 7
- Year: 2006
- Summary: Several methods were developed for the redistribution of nitrogen (N) fertilizer within fields with winter wheat (Triticum aestivum L.) based on plant and soil sensors, and topographical information. The methods were based on data from nine field experiments in nine different fields for a 3-year period. Each field was divided into 80 or more subplots fertilized with 60, 120, 180 or 240 kg N ha-1. The relationships between plot yield, N application rate, sensor measurements and the interaction between N application and sensor measurements were investigated. Based on the established relations, several sensor-based methods for within-field redistribution of N were developed. It was shown that plant sensors predicted yield at harvest better than soil sensors and topographical indices. The methods based on plant sensors showed that N fertilizer should be moved from areas with low and high sensor measurements to areas with medium values.The theoretical increase in yield and N uptake, and the reduced variation in grain protein content resulting from the application of the above methods were estimated. However, the estimated increases in crop yield, N-uptake and reduced variation in grain protein content were small.
- Authors:
- Source: Review of agricultural experiments 2006. Trials and research in the agronomy sector.
Oversigt over Landsfors<o>gene 2006. Fors<o>g og unders<o>gelser i de land<o>konomiske foreninger.
- Year: 2006
- Summary: The organization and aims of the 'Landsforsgene', the collective name for the body that coordinates agricultural experiments in Denmark, are described. The growing season 2005-2006 in Denmark was characterized by long periods of severe drought in summer that resulted in lower crop yields, although the economic effect was mitigated to some extent by higher prices. Separate sections of the review deal with winter barley, winter rye, triticale, winter wheat, spring barley, oats, spring wheat, various seed crops, field seeds, winter rape, manures and calcium treatments, growing techniques, organic farming, potatoes, sugar beet, grass and green fodder crops, maize, plant breeding, general information on experimental design and aims, and a list of authors.
- Authors:
- Quine, T. A.
- Djurhuus, J.
- Heckrath, G.
- Van Oost, K.
- Govers, G.
- Zhang, Y.
- Source: Journal of Environmental Quality
- Volume: 34
- Issue: 1
- Year: 2005
- Summary: Tillage erosion had been identified as a major process of soil redistribution on sloping arable land. The objectives of our study were to investigate the extent of tillage erosion and its effect on soil quality and productivity under Danish conditions. Soil samples were collected to a 0.45-m depth on a regular grid from a 1.9-ha site and analyzed for Cs-137 inventories, as a measure of soil redistribution, soil texture, soil organic carbon (SOC) contents, and phosphorus (P) contents. Grain yield was determined at the same sampling points. Substantial soil redistribution had occurred during the past decades, mainly due to tillage. Average tillage erosion rates of 2.7 kg m(-2) yr(-1) occurred on the shoulderslopes, while deposition amounted to 1.2 kg m(-2) yr(-1) on foot- and toeslopes. The pattern of soil redistribution could not be explained by water erosion. Soil organic carbon and P contents in soil profiles increased from the shoulder- toward the toeslopes. Tillage translocation rates were strongly correlated with SOC contents, A-horizon depth, and P contents. Thus, tillage erosion had led to truncated soils on shoulderslopes and deep, colluvial soils on the foot- and toeslopes, substantially affecting within-field variability of soil properties. We concluded that tillage erosion has important implications for SOC dynamics on hummocky land and increases the risk for nutrient losses by overland flow and leaching. Despite the occurrence of deep soils across the study area, evidence suggested that crop productivity was affected by tillage-induced soil redistribution. However, tillage erosion effects on crop yield were confounded by topography-yield relationships.
- Authors:
- Ostergard, H.
- Pedersen, S.
- Kjellsson, G.
- Holm, P. B.
- Gylling, M.
- Buus, M.
- Boelt, B.
- Andersen, S. B.
- Tolstrup, K.
- Mikkelsen, S. A.
- Source: DIAS Report, Plant Production
- Issue: 94
- Year: 2003
- Summary: The paper focuses on the possible sources of dispersal (cross pollination, seed dispersal, vegetative dispersal, dispersal by farming machinery, dispersal during handling and transport) from genetically modified crop production to conventional and organic production, the extent of dispersal and the need for control measures, and the possible control measures for ensuring the co-existence of genetically modified production with conventional and organic production systems. Specific sections are provided on the crops currently genetically modified in Denmark or likely to be within the next few years (oilseed rape, maize, beet, potatoes, barley, wheat, triticale, oats, rye, forage and amenity grasses, grassland legumes, field peas, faba beans and lupins, and vegetable seeds). Brief discussions on the legislation, seed production, monitoring and analytical methods used, and measures to ensure crop purity (such as reducing pollen dispersal, reducing seed dispersal, adopting cultural methods reducing pollen and seed dispersal) are also presented.
- Authors:
- Kristensen, E. S.
- Alrøe, H. F.
- Hansen, B.
- Source: Agriculture, Ecosystems & Environment
- Volume: 83
- Issue: 1-2
- Year: 2001
- Summary: Ever increasing attention is being paid to the environmental impact of intensive agricultural practices, and in this context organic farming is gaining recognition as a relatively friendly production system. In general, the risk of harmful environmental effects is lower with organic than with conventional farming methods, though not necessarily so. This review examines organic farming in the light of European conditions with special regard to recent research findings from Denmark. It specifies the environmental problems caused by modern farming practices and discusses appropriate indicators for assessing their impact. A driving force-state-response (DSR) framework is employed to organise and understand the processes and mechanisms that lie behind the impact of agriculture on nature and the environment. Important groups of environmental indicators are selected that characterise (a) the aquatic environment (nitrate and phosphorus leaching), (b) the soil (organic matter, biology and structure), (c) the ecosystem (arable land, semi-cultivated areas, small biotopes and landscape), and (d) resource usage and balances (nitrogen, phosphorus, potassium and energy use).
The paper also reviews several empirical studies. With regard to soil biology, organic farming is usually associated with a significantly higher level of biological activity (bacteria (Monera), fungi (Mycota), springtails (Collembola), mites (Arachnida), earthworms (Lumbricus terrestris)), due to its versatile crop rotations, reduced applications of nutrients, and the ban on pesticides. In most cases there is also a lower surplus of nutrients and less leaching with organic than with conventional farming. However, poor management (e.g., the ploughing of grass and legumes (Fabates) at the wrong time of year with no subsequent crops to capture the mineralised nitrogen), low self-sufficiency in feed, and problems with certain production systems (such as those involved in organic pig farming, i.e., grazing sows, low crop yields), can lead to a high level of leaching in some organic systems. Organic farming is faced with a need to expand and develop in line with increasing demands for organic food and growing environmental concerns. This requires closer attention to the goals, values and principles on which organic practices are based, and more research into the influence of organic farming on different aspects of the environment.
- Authors:
- Parton, W. J.
- Mueller, T.
- Molina, J. A. E.
- Li, C.
- Komarov, A. S.
- Klein-Gunnewiek, H.
- Kelly, R. H.
- Jensen, L. S.
- Jenkinson, D. S.
- Frolking, S.
- Franko, U.
- Coleman, K.
- Chertov, O. G.
- Arah, J. R. M.
- McGill, W. B.
- Powlson, D. S.
- Smith, J. U.
- Smith, P.
- Thornley, J. H. M.
- Whitmore, A. P.
- Source: Geoderma
- Volume: 81
- Issue: 1-2
- Year: 1997
- Summary: Nine soil organic models were evaluated using twelve datasets from seven long-term experiments. Datasets represented three different land-uses (grassland, arable cropping and woodland) and a range of climatic conditions within the temperate region. Different treatments (inorganic fertilizer, organic manures and different rotations) at the same site allowed the effects of differing land management to be explored. Model simulations were evaluated against the measured data and the performance of the models was compared both qualitatively and quantitatively. Not all models were able to simulate all datasets; only four attempted all. No one model performed better than all others across all datasets. The performance of each model in simulating each dataset is discussed. A comparison of the overall performance of models across all datasets reveals that the model errors of one group of models (RothC, CANDY, DNDC, CENTURY, DAISY and NCSOIL) did not differ significantly from each other. Another group (SOMM, ITE and Verberne) did not differ significantly from each other but showed significantly larger model errors than did models in the first group. Possible reasons for differences in model performance are discussed in detail.