Within and between-field spatial variation in soil phosphorus in permanent grassland

Abstract

Soil phosphorus (P) concentrations above certain critical thresholds are a problem in many areas leading to its transport into surface and ground waters. Site-specific nutrient applications and the development of nutrient management plans for farms would help to optimize nutrient applications, meet crop requirements and take into consideration current soil nutrient status. In Northern Ireland, high concentrations of soil P are common, whereas low concentrations of soil potassium (K) and sulphur (S) have been reported in many silage fields. This study used grid and transect soil sampling to measure within-and between-field spatial variation in soil Olsen-P status across a 50-ha permanent grassland site used for silage production. Soil phosphorus indices ranged from Index 1 to Index 4 within single fields. The spatial patterns of soil P across fields suggested that there was scope for site-specific P fertilizer applications, with variable quantities of P being applied to different fields and within individual fields. Site-specific nutrient management has the potential to reduce excess P applications in some areas and avoid deficiencies in others, thereby minimizing environmental problems and optimizing yield.

Precision agriculture applied to soybean: Part III - Spatial and temporal variability of yield

“…The use is justified by the significant reduction in the required number of soil samples, which depending on the sampling grid used, involves intensive use of labor for sampling and laboratory analysis, thus increasing the production cost (Zhang et al, 2010). The cost of sampling and analysis may cause the application of precision agriculture techniques to be unfeasible (McCormick et al, 2009).…”

Spatial variability of some soil properties varies in oil palm (<i>Elaeis guineensis</i> Jacq.) plantations of west coastal area of India

“…Prior to geostatistical analyses, the data were examined for the presence of trend (by "Geostatistical analyst" of ArcGIS 10.1) and removed (by fitting to second order polynomial). According to McCormick et al (2009), trend in the variation signals a departure from the intrinsic hypothesis in which the process is assumed to be random and it violates the assumptions on which geostatistics is based on. By removing the trend, it will be possible to more accurately model the variation because the trend will not be influencing the spatial analysis (Kerry and Oliver, 2007).…”

Sensor Technologies for Precision Soil Nutrient Management and Monitoring

“…However, intensive grid sampling is laborious, time consuming and expensive (King et al, 2005;Srinivasan, 2006) and thus impractical for implementation in large scale (McCormick et al, 2009). It is, therefore, desirable to develop a more rapid means of obtaining spatial and temporal data for detailed variability mapping (Brevik et al, 2006;King et al, 2005).…”