Long-term effects of cropping systems on the earthworm population in a loam soil

Six cropping systems, ranging from conventional arable without livestock to organic livestock farming dominated by ley, have been compared in 1990 and 2004 in SE Norway. Ley in the crop rotation increased density and biomass of earthworms and channels in both organic and conventional systems. A ley proportion higher than 25 % only increased the density of channels. Among the arable systems, the organic system had a higher density and biomass of earthworms as compared to the conventional systems. Among the fodder systems, the optimised system had the highest density of earthworms in 2004, but there were no differences between these systems in earthworm biomass or density of earthworm channels

N, P, and K Budgets and Changes in Selected Topsoil Nutrients over 10 Years in a Long-Term Experiment with Conventional and Organic Crop Rotations

This study presents soil system budgets of N, P and K in six contrasting cropping systems during 10 years of a long-term experiment in southeast Norway. The experiment included systems with arable cash-cropping and with mixed arable-dairy cropping (cash-and fodder crops), with organic and conventional management represented in both groups. All major nutrient inputs and outputs were measured or estimated. State of the art conventional cash-cropping appeared to be balanced in terms of N, whereas conventional mixed cropping had an N surplus. By contrast, less up to date conventional arable cash-cropping and all the organic systems showed indications of soil organic N depletion (negative N budgets). All the organic systems showed that mining of the soil P and K content occurs, whereas the conventional systems all had P and K surpluses. The results corresponded well with measured differences between systems in terms of ignition loss, P-AL, K-AL and K-HNO 3 measured in 2009. This study shows that a fertile soil may be exposed to substantial mining of N, P and K over many years before it is detectable by traditional analyses, and that field nutrient budgeting is a feasible, but data-demanding, approach to detect such misbalances at an early stage

Comparison of Risk Between Cropping Systems in Eastern Norway

The aim of this study was to compare production and policy risk of organic, integrated and conventional cropping systems in Norway. Experimental cropping system data (1991-1999) from eastern Norway were combined with budgeted data. Empirical distributions of total farm income for different cropping systems were estimated with a simulation model that uses a multivariate kernel density function to smooth the limited experimental data. Stochastic efficiency with respect to a function (SERF) was used to rank the cropping systems for farmers with various risk aversion levels. The results show that the organic system had the greatest net farm income variability, but the existing payment system and organic price premiums makes it the most economically viable alternative.organic, integrated and conventional crop farming, stochastic simulation, multivariate kernel estimator, risk aversion, stochastic efficiency with respect to a function, Crop Production/Industries, Risk and Uncertainty, Q12, C44,

Long-term effects of cropping systems on the earthworm populations in a loam soil

Abstract - Six cropping systems, ranging from conventional arable without livestock to organic livestock farming dominated by ley, have been compared since 1990 in SE Norway. Earthworm density (ED), earthworm biomass (EB), channel density (CD) and species of worms were measured in the topsoil (0-25 cm) in 1994 and 2004. Ley in the crop rotation increased EB, ED and CD in both organic and conventional systems, but a ley proportion higher than 25 % only increased CD. Among the arable systems, the organic system hosted more individuals (ED) and a higher biomass (EB) of earthworms as compared to the conventional systems. The conventional arable systems had low values in 2004, and only minor changes in EB and ED during the period compared with the other systems. The earthworm species observed were field worm (Aporrectodea caliginosa), pink worm (A. rosea) and night crawlers (Lumbricus terrestris)

Comparison of Conventional and IPM Cropping Systems: A Risk Efficiency Analysis

To support decision-makers considering adopting integrated pest management (IPM) cropping in Norway, we used stochastic efficiency analysis to compare the risk efficiency of IPM cropping and conventional cropping, using data from a long-term field experiment in southeastern Norway, along with data on recent prices, costs, and subsidies. Initial results were not definitive, so we applied stochastic efficiency with respect to a function, limiting the assumed risk aversion of farmers to a plausible range. We found that, for farmers who are risk-indifferent to moderately (hardly) risk averse, the conventional system was, compared to IPM, less (equally) preferred

N, P, and K Budgets and Changes in Selected Topsoil Nutrients over 10 Years in a Long-Term Experiment with Conventional and Organic Crop Rotations

This study presents soil system budgets of N, P and K in six contrasting cropping systems during 10 years of a long-term experiment in southeast Norway. The experiment included systems with arable cash-cropping and with mixed arable-dairy cropping (cash- and fodder crops), with organic and conventional management represented in both groups. All major nutrient inputs and outputs were measured or estimated. State of the art conventional cash-cropping appeared to be balanced in terms of N, whereas conventional mixed cropping had an N surplus. By contrast, less up to date conventional arable cash-cropping and all the organic systems showed indications of soil organic N depletion (negative N budgets). All the organic systems showed that mining of the soil P and K content occurs, whereas the conventional systems all had P and K surpluses. The results corresponded well with measured differences between systems in terms of ignition loss, P-AL, K-AL and K-HNO3 measured in 2009. This study shows that a fertile soil may be exposed to substantial mining of N, P and K over many years before it is detectable by traditional analyses, and that field nutrient budgeting is a feasible, but data-demanding, approach to detect such misbalances at an early stage

Forage yield and quality estimation by means of UAV and hyperspectral imaging

This study investigated the potential of in-season airborne hyperspectral imaging for the calibration of robust forage yield and quality estimation models. An unmanned aerial vehicle (UAV) and a hyperspectral imager were used to capture canopy reflections of a grass-legume mixture in the range of 450 nm to 800 nm. Measurements were performed over two years at two locations in Southeast and Central Norway. All images were subject to radiometric and geometric corrections before being processed to ortho-images, carrying canopy reflectance information. The data (n = 707) was split in two, using half the data for model calibration and the remaining half for validation. Several powered partial least squares regression (PPLSR) models were fitted to the reflectance data to estimate fresh (FM) and dry matter (DM) yields, as well as crude protein (CP), dry matter digestibility (DMD), neutral detergent fibre (NDF), and indigestible neutral detergent fibre (iNDF) content. Prediction performance of these models was compared with the prediction performance of simple linear regression (SLR) models, which were based on selected vegetation indices and plant height. The highest prediction accuracies for general models, based on the pooled data, were achieved by means of PPLSR, with relative root-mean-square errors of validation of 14.2% (2550 kg FM ha−1), 15.2% (555 kg DM ha−1), 11.7% (1.32 g CP 100 g−1 DM), 2.4% (1.71 g DMD 100 g−1 DM), 4.8% (2.72 g NDF 100 g−1 DM), and 12.8% (1.32 g iNDF 100 g−1 DM) for the prediction of FM, DM, CP, DMD, NDF, and iNDF content, respectively. None of the tested SLR models achieved acceptable prediction accuracies.publishedVersio

Abundance and diversity of spiders (Araneae) in barley and young leys

Volume: 41Start Page: 168End Page: 17

Forage yield and quality estimation by means of UAV and hyperspectral imaging

This study investigated the potential of in-season airborne hyperspectral imaging for the calibration of robust forage yield and quality estimation models. An unmanned aerial vehicle (UAV) and a hyperspectral imager were used to capture canopy reflections of a grass-legume mixture in the range of 450 nm to 800 nm. Measurements were performed over two years at two locations in Southeast and Central Norway. All images were subject to radiometric and geometric corrections before being processed to ortho-images, carrying canopy reflectance information. The data (n = 707) was split in two, using half the data for model calibration and the remaining half for validation. Several powered partial least squares regression (PPLSR) models were fitted to the reflectance data to estimate fresh (FM) and dry matter (DM) yields, as well as crude protein (CP), dry matter digestibility (DMD), neutral detergent fibre (NDF), and indigestible neutral detergent fibre (iNDF) content. Prediction performance of these models was compared with the prediction performance of simple linear regression (SLR) models, which were based on selected vegetation indices and plant height. The highest prediction accuracies for general models, based on the pooled data, were achieved by means of PPLSR, with relative root-mean-square errors of validation of 14.2% (2550 kg FM ha−1), 15.2% (555 kg DM ha−1), 11.7% (1.32 g CP 100 g−1 DM), 2.4% (1.71 g DMD 100 g−1 DM), 4.8% (2.72 g NDF 100 g−1 DM), and 12.8% (1.32 g iNDF 100 g−1 DM) for the prediction of FM, DM, CP, DMD, NDF, and iNDF content, respectively. None of the tested SLR models achieved acceptable prediction accuracies