All growers make observations of their soil and topography and assess the implications for yield to help inform how they manage a paddock. Single sample or transect soil testing is commonly used and more advanced approaches may include sap or petiole testing in-crop for nutrient management. In recent years, we have had increasing access to low-cost spatial data, which can enable variable-rate soil and crop management (yield, imagery, soil conductivity, topography and soil tests).
Our soils guidebook: history, experience and science
GroundCover™ Issue: 137 November - December 2018 | Author: Andrew Whitlock
The following article is from a paper presented at the GRDC Farm Business Update in Bendigo, Victoria, by Andrew Whitlock, director of research and innovation at Precision Agriculture and a south-western Victoria grain grower
Suboptimal allocation of inputs and missed opportunities to resolve variable soil constraints remain issues for paddock management – a lost opportunity to save money and/or maximise yield potential.
To address this, a range of tools is available to inform or define paddock variability. The applicability of the tool or tools used will be determined by the soil constraint or productivity issue being tested – keeping in mind that a single layer of data may not fully define the issues and the treatment.
Common tools and information resources used to define and describe variability include:
- Yield data – can identify zones of variable productivity that warrant further investigation but will not identify the factors that are constraining yield without additional knowledge and/or data. Yield data can also be used to build nutrient removal maps (phosphorus is the most common nutrient to be managed using this data).
- Electromagnetic induction (EM-38 dual dipole) – measures a combination of soil salinity, clay and soil moisture at depth (approximately 1.5 metres). For many paddocks it can provide an accurate soil map. Soil cores and associated analyses (ideally segmented cores to explore soil profile) are essential to extract paddock management value from such soil maps.
- Gamma radiometrics – used predominantly in combination with EM-38 on sand plains and in gravel soils where soil conductivity is less effective in isolation. It effectively measures the natural radioactive decay of potassium, thorium and uranium in the top 30 to 45 centimetres of the soil.
- Normalised difference vegetation index (NDVI) – provides an assessment of canopy density, biomass and plant vigour. NDVI will not define the underlying factor promoting or limiting plant growth – it simply indicates where to investigate (visual, plant testing, soil testing) and helps define boundaries around such factors.
- Global navigation satellite system (GNSS) – underpins elevation mapping. This data can be converted into digital elevation models, informing water management such as drainage design, waterlogging zones, erosion control and water harvesting.
Soil testing can define a broad range of soil physical, chemical, biological and hydraulic properties. Disease pathogen and nematode monitoring can be included in this process.
Our understanding of economic response curves to a range of crop inputs links back to many years of research in soils with known chemical element concentrations.
Growers and agronomists use key measures for management decisions, such as Colwell phosphorus coupled with phosphorus buffering index (PBI) for phosphorus applications and soil pH coupled with a crop sequence plan to determine a lime application rate. We can extend this thinking to how to develop an accurate variable-rate management application in areas where temporal yield variability is less consistent/predictable (anywhere other than low-rainfall dune–swale systems).
We ideally want to use the same soil measurement from the input response research for developing variable-rate management zones. The most common method of paddock zoning is grid soil mapping (soil transect sampling per grid unit, typically one to four hectares). The simplicity is appealing as we no longer rely on building assumptions around relationships between spatial datasets. A grid soil map can provide a baseline for several seasons (especially for growers who can link nutrient removal maps via their yield data). Grid Colwell or Olsen P, pH and exchangeable cations (potassium, sodium, magnesium, aluminium) are the more common soil elements tested when grid soil mapping (zero to 10cm).
Soil probes or sensors that assess soil elements in situ are becoming increasingly popular as they offer a lower cost per sample, enabling greater sampling density. But these sensors struggle to generate accurate results across all soil types and moisture levels and thus it is essential to calibrate every paddock with traditional wet chemistry laboratory analysis.
When addressing within-paddock variability, the highest return on investment is often achieved by addressing the key soil health factors limiting crop performance. Soil acidity (variable-rate lime) and sodicity (variable-rate gypsum) are common strategies to ameliorate soil constraints and unlock yield potential.
As the key soil constraints are ameliorated and broader measures of soil health are improved, site-specific crop management can be implemented. Seasonal management strategies (predominantly variable-rate nutrition, disease and pest control) are developed with the combination of underlying soil levels (grid or zonal soil testing) and crop monitoring information (NDVI, yield maps and boots on the ground).
Macro nutrient supply (predominantly nitrogen, phosphorus and potassium) via seeding and spreading are the most common variable-rate strategies used.
Caution must be used when yield and/or NDVI maps are solely used to define zones for variable-rate management strategies. Plant growth and final yield is influenced by many factors, with the dominant influences being the key plant growth constraints for that particular season.
Paddock knowledge is essential when interpreting yield and NDVI maps and such maps can be valuable in defining dominant constraints but rarely offer an ability to map subclinical factors. For example, crop performance zones for a certain paddock may be great at defining severe subsoil constraints (rooting depth/plant-available water capacity) but do not accurately inform the variability of soil phosphorus and/or surface soil pH.
We are seeing an explosion of interest in agricultural technology and we can expect to see numerous technologies hit the market in coming years. When evaluating the value of a sensor technology for your farm, start with a clear understanding of exactly what it is measuring and how this data can be converted into an action. A well-designed ground-truthing process must be employed when relying on surrogate datasets to determine variable-rate application plans.
Where possible, paddock mapping analysis should be linked with well-established science-based principles. In essence, precision agriculture is simply the intensification of an agronomic management decision. It is important to secure partnerships with businesses that can support all steps of the variable-rate management process: agronomy, data collection/processing and application.
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