The contribution of grass and clover root turnover to N leaching

Sources of inorganic and organic N leaching from grass-clover mixtures at field sites in Denmark, Germany and Iceland were investigated. Grass or clover was labelled with 15N-urea four times (autumn 2007, spring, summer and autumn 2008) prior to the leaching season in autumn and winter 2008. Soil water was sampled at 30 cm depth and analyzed for 15N-enrichment of dissolved inorganic N (DIN) and dissolved organic N (DON). Most 15N was recovered in DON for both labelled grass and clover at all sites. At the Danish site, grass and clover contributed more to the DON pool than the DIN whereas the opposite was observed at the German and Icelandic sites. The results show that both clover and grass contribute directly to N leaching from the root zone in mixtures, and that clover contribution is higher than grass. Furthermore, the present study indicates that roots active in the growth season prior to the drainage period contribute more to N leaching than roots active in the growth season the previous year, which is consistent with estimates of root longevity at the three sites

Forage herbs improve mineral composition of grassland herbage

Provision of an adequate mineral supply in the diets of ruminants fed mainly on grassland herbage can present a challenge if mineral concentrations are suboptimal for animal nutrition. Forage herbs may be included in grassland seed mixtures to improve herbage mineral content, although there is limited information about mineral concentrations in forage herbs. To determine whether herbs have greater macro- and micromineral concentrations than forage legumes and grasses, we conducted a 2-year experiment on a loamy-sand site in Denmark sown with a multi-species mixture comprised of three functional groups (grasses, legumes and herbs). Herb species included chicory (Cichorium intybus L.), plantain (Plantago lanceolata L.), caraway (Carum carvi L.) and salad burnet (Sanguisorba minor L.). We also investigated the effect of slurry application on the macro- and micromineral concentration of grasses, legumes and herbs. In general, herbs had greater concentrations of the macrominerals P, Mg, K and S and the microminerals Zn and B than grasses and legumes. Slurry application indirectly decreased Ca, S, Cu and B concentrations of total herbage because of an increase in the proportion of mineral-poor grasses. Our study indicates that including herbs in forage mixtures is an effective way of increasing mineral concentrations in herbage

Scalable Group Level Probabilistic Sparse Factor Analysis

Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a group level scalable probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex noise models than the presently considered.Comment: 10 pages plus 5 pages appendix, Submitted to ICASSP 1