Mapping subsoil acidity and shallow soil across a field with information from yield maps, geophysical sensing and the grower

Abstract

Management decisions, such as subsoil liming or varying fertilizer inputs to take account of soil depth and anticipated yields require knowledge of where subsoil constraints to root growth occur across the field. We used selected yield maps based on criteria derived from crop simulation, apparent soil electrical conductivity (EC a ), gammaray emission maps and a soil type map drawn by the grower to predict the spatial distribution of subsoil acidity and shallow soil across a field. Yield maps integrate the effects of variation in soil and climate, and it was only under specific seasonal conditions that subsoil constraints depressed yields. We used crop simulation modelling to select yield maps with a large information content on the spatial distribution of these constraints and to omit those with potentially misleading information. Yield and other spatial data layers were used alone or in combination to develop subsoil mapping options to accommodate differences in data availability, access to precision agriculture techniques and the grower's aptitude and preference. One option used gamma-ray spectrometry and EM38 survey as a dual-sensing system to improve data interpretation. Gamma-ray spectrometry helped to overcome the inability of current EC a -based methods to sense soil depth in highly weathered sandy soil over cemented gravel. A feature of the approaches presented here is the use of grower and agronomist knowledge, and experience to help interpret the spatial data layers and to evaluate which approach is most suitable and likely to be adopted to suit an individual.

Scope to improve phosphorus (P) management and balance efficiency of crop and pasture soils with contrasting P status and buffering indices

“…Given that 63% of pasture, 87% of wheat, 89% of dairy soil samples appear to contain Colwell P concentrations above the CV for 90-95% of maximum production, yields are more likely to be constrained by other factors such as lack of water, soil acidity, and other nutrient deficiencies (Table 3). Practices to ameliorate many of these other constraints already exist, including (i) the application of liming materials to manage soil acidity (Snars et al 2004;Wong et al 1998;Wong et al 1995), (ii) improving water holding and P retention, and reducing Colwell P/PBI of sandy soils (Wong and Asseng 2006;Vlahos et al 1989;Summers et al 1993), (iii) relieving subsoil constraints to root growth to capture some leached P (Wong and Asseng 2007), and (iv) using techniques to identify site specific nutrient needs (Wong et al 2001(Wong et al , 2008(Wong et al , 2010.…”

The arable farmer as the assessor of within-field soil variation

“…Those studies did not consider the size and nature of the field, which restricted the full potential knowledge of the farmers. When this restriction was not made in advance, Australian farmers indicated that there were more than three types of soil in a given field (Oliver et al 2010;Wong et al 2008).…”

Adoption of variable rate fertiliser application in the Australian grains industry: status, issues and prospects

“…While farmer knowledge can go some way towards diagnosis of causes (Oliver et al 2010), other methods (see review by Robertson et al 2007) are under development such as some geophysical techniques (Wong et al 2008), temporal dynamics of remotely sensed NDVI (Adams and Maling 2005;Robertson et al 2007), and temporal dynamics of multiple yield maps (Lawes et al 2009). Because causes of variation are context specific, no one method is universally applicable.…”