Response of organically managed grassland to available phosphorus and potassium in the soil and supplementary fertilization: field trials using grass-clover leys cut for silage

Effective use and recycling of manures together with occasional and judicious use of supplementary fertilizing materials forms the basis for management of phosphorus (P) and potassium (K) within organic farming systems. Replicated field trials were established at three sites across the UK to compare the supply of P and K to grass-clover swards cut for silage from a range of fertilizing materials, and to assess the usefulness of routine soil tests for P and K in organic farming systems. None of the fertilizing materials (farmyard manure, rock phosphate, Kali vinasse, volcanic tuff) significantly increased silage yields, nor was P offtake increased. However, farmyard manure and Kali vinasse proved effective sources of K to grass and clover in the short to medium term. Available P (measured as Olsen-P) showed no clear relationship with crop P offtake in these trials. In contrast, available K (measured by ammonium nitrate extraction) proved a useful measurement to predict K availability to crops and support K management decisions.

Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data

Site-specific management requires accurate knowledge of the spatial variation in a range of soil properties within fields. This involves considerable sampling effort, which is costly. Ancillary data, such as crop yield, elevation and apparent electrical conductivity (ECa) of the soil, can provide insight into the spatial variation of some soil properties. A multivariate classification with spatial constraint imposed by the variogram was used to classify data from two arable crop fields. The yield data comprised 5 years of crop yield, and the ancillary data 3 years of yield data, elevation and ECa. Information on soil chemical and physical properties was provided by intensive surveys of the soil. Multivariate variograms computed from these data were used to constrain sites spatially within classes to increase their contiguity. The constrained classifications resulted in coherent classes, and those based on the ancillary data were similar to those from the soil properties. The ancillary data seemed to identify areas in the field where the soil is reasonably homogeneous. The results of targeted sampling showed that these classes could be used as a basis for management and to guide future sampling of the soil.

On the development of horizontal CEN standards supporting the implementation of EU directives on sludge, soil and biowaste - Project HORIZONTAL

We give an overview on the development of "horizontal" European Committee for Standardisation (CEN) standards for characterising soils, sludges and biowaste in the context of environmental legislation in the European Union (EU). We discuss the various steps in the development of a horizontal standard (i.e. assessment of the possibility of such a standard, review of existing normative documents, pre-normative testing and validation) and related problems. We also provide a synopsis of European and international standards covered by the so-called Project HORIZONTAL. (C) 2004 Elsevier Ltd. All rights reserved.

Co-kriging when the soil and ancillary data are not co-located

Data such as digitized aerial photographs, electrical conductivity and yield are intensive and relatively inexpensive to obtain compared with collecting soil data by sampling. If such ancillary data are co-regionalized with the soil data they should be suitable for co-kriging. The latter requires that information for both variables is co-located at several locations; this is rarely so for soil and ancillary data. To solve this problem, we have derived values for the ancillary variable at the soil sampling locations by averaging the values within a radius of 15 m, taking the nearest-neighbour value, kriging over 5 m blocks, and punctual kriging. The cross-variograms from these data with clay content and also the pseudo cross-variogram were used to co-krige to validation points and the root mean squared errors (RMSEs) were calculated. In general, the data averaged within 15m and the punctually kriged values resulted in more accurate predictions.