Validation of topsoil texture derived from agricultural soil maps by current dense soil sampling

Agricultural soil maps were created to facilitate the management of fields. Such maps, at very large scale (1:5000), cover almost the entire agricultural land in Poland. These maps can be very useful for precision field management. However, they were prepared about 40–50 years ago using old mapping techniques with mainly field (organoleptic) examination of soil. For this reason it is necessary to verify agreement between such maps with the current soil status. In the case of detection of disagreements it is important to identify the causes and propose methods for improving soil maps. Only few studies were made in this aspect. The soil texture (ST) of the upper layer, as presented on the agricultural soil maps from the 1960s and 1970s, was compared with the actual ST of the same four fields in northern and central Poland. For laboratory ST determination, soil samples were collected in a dense sampling network. On average, the agreement of the ST presented on the agricultural soil maps and determined in this study was classified as medium for three fields and good for one field. However, the presence of field areas with poor agreement between the ST determined in this study and that shown on the agricultural maps was detected in all investigated fields. Identified causes for this comprised imprecision of ST determination using the organoleptic method, the generalization of the soil quality maps, and erosion processes during the years between soil mapping and this investigation. The improvement of ST presentation on the large scale soil maps might be achieved by quite denser soil sampling for ST analysis supported by ECa, yield and NDVI maps.     

Spatio-temporal analysis of crop rotations and crop sequence patterns in Northern Germany: potential implications on plant health and crop protection

Journal of Plant Diseases and Protection - Crop sequence patterns are considered as those schemes farmers apply within a single field to succeed crops over time, regardless of whether the same crop...     

Delineation of management zones with spatial data fusion and belief theory

Precision Agriculture - Precision agriculture, as part of modern agriculture, thrives on an enormously growing amount of information and data for processing and application. The spatial data used...     

Assessment of soil texture class on agricultural fields using ECa,Amber NDVI,and topographic properties

Soil texture (ST) is relatively stable over time, although it may change due to erosion, clay eluviation, and other processes. Soil texture affects soil quality, productivity and management. Therefore, indirect, accurate methods for assessing of soil texture classes (STCs) are needed in agricultural practice. A study was performed on four production fields in northern and central Poland to compare the fitting performance of STC models based on apparent electrical conductivity (ECa), topographic properties (elevation, slope gradient and wetness index) and Amber NDVI measurements. One common and accurate indicator of STCs was not found for all study fields. On average, ECa was most accurate in indicating areas of different STCs within the fields, but it tended to overestimate the size of sandy areas on loamy fields and vice versa. The accuracy of STC assessment using ECa measurements may be biased due to imperfect soil drainage, high elevations, which increase evaporation and STC variation with depth. STC assessment using Amber NDVI measurements may be useful, particularly on flat and sandy fields, but the results are affected by the same factors as ECa, and additionally by crop growth stages and by the weather conditions in the period preceding the measurements. Despite the good quantitative results of the STC assessment by elevation (one field) and by the topographic wetness index (another field), both terrain attributes failed to accurately indicate the distribution of some STC areas within each field. Therefore, in landscapes developed from deposits of the last glaciation relevant ST differences might not sufficiently be detected by the analysis of terrain attributes alone. The selection of STC predictors and evaluation of the assessment quality must consider both the quantitative indicators such as correlation and determination coefficients describing relationships between ST and ECa, NDVI and topography and percentage of a field area with accurately indicated STC and the distribution of areas with different STCs within a field. The use of ECa, NDVI values, and topographic properties for STC assessment may be useful in reducing costs of soil sampling and analysis, but cannot replace it.