Monday, 15 February 2021

Making pasture variables work for you


Getting the best out of our pastures has been and still is New Zealand farmers’ competitive advantage. Throughout the previous editions of this magazine we have updated you on our work to transform farmers’ capability in this area with our Primary Growth Partnership Programme (PGP) – Pioneering to Precision. Before we tell you what the programme has achieved to date, we should first revisit the PGP's basic premise.

It is no surprise that we see variability in pasture production and quality within our farms through differences in slope, aspect, soils, climate, pasture composition and management factors. This variability impacts animal performance and farm profitability, so how do we account for it when optimising capital and maintenance fertiliser requirements based on actual and potential productivity?

It can be done simply by:

  1. Classifying the farm into different land management units based on productivity measures, including farmer knowledge
  2. Undertaking soil and herbage sampling to assess the fertility status of these units
  3. Econometric modelling to optimise the financial outcome
  4. Allocating fertiliser and lime to achieve the optimum soil fertility levels.

‘Optimal fertility levels’ are achieved when the cost of fertiliser (product and application) equals the financial return from the additional pasture grown2. For dairy farms, economics dictate that farmers should ensure the fertility status in terms of P, K, S and lime is at, but does not exceed, the biological optimum for optimal pasture production. For sheep and beef farms an econometric approach (see above) should be considered when deciding on allocations between land management units due to differing margins.

Fertiliser is a large ticket item within farm working expenses, so it makes sense to see if we can optimise capital and maintenance fertiliser requirements further. 

To achieve this, within the PGP Ravensdown has developed a suite of analytical tools (see infographic above) using Geographical Information Systems (GIS) to assess actual and potential pasture productivity. By incorporating the critical factors contributing to the variability within land management units we can arrive at a detailed spatial recommendation of optimal soil fertility targets tailored for each farm. 

These tools can incorporate soil fertility of land management units, either derived from traditional physical soil sampling or by hyperspectral remote sensing. The advantage the remote sensing approach offers is the ability to provide a more detailed assessment, with the hyperspectral sensor’s capability to collect estimates at a resolution of 10,000 samples (equivalent) per hectare. For example, on one lower North Island hill country farm within the programme, traditional soil testing found, albeit expected, a variability in soil Olsen P between land management units of 6 to 40 units across the farm from 15 soil tests. In comparison across the same land management units, the remote sensing estimates showed a range of 3 to 99 Olsen P units from 9,111,073 sensor observations.

This technology focusing on hill country is still undergoing validation to ensure it is sufficiently robust and is concentrated on Olsen P. The inclusion of physical soil sampling along with the decision support tools developed within the programme offer advantages - the soil sampling is not constricted to the spring and autumn seasons (remote sensing requires clear skies and pasture to be actively growing) so should be able to be offered in greater capacity. The soil sampling option is already proven in both dairy and sheep and beef operations and has the added ability to include K and lime. Some generalisations for fertiliser and lime allocation still do need to be made, such as:

  • Accounting for the precision of the mode of application, i.e. aerial vs truck 
  • The minimum size of land areas for variable rate nutrient application 
  • The choice of fertiliser products to generate a practical plan. 

Nonetheless, the resulting nutrient applications from our PGP approach are more precise when taking account of the variability across the farm (slope, soils, climate, animal transfer of nutrients, effluent and irrigation applications). The benefits are achieved by maximising the return on fertiliser spend by driving efficiencies in pasture production, which impacts animal performance and ultimately profitability. More precisely identifying areas to receive no fertiliser also confers a material environmental benefit. 

The future is exciting for where this technology will head with ongoing advancements to GPS guidance systems and automated flow control in truck and topdressing aircraft. This means variable rate strategies can be put into practice more effectively.