Nutrient Redistribution and Optimisation Project

Nutrient Redistribution and Optimisation Project (Total Project $54,150 - SADIF commitment $32,185)

The Project 

The core function of this project was to increase grower and industry knowledge on the redistribution of nutrients across the farm and optimise dairy effluent as an on-farm ‘natural resource’ alongside the current synthetic fertiliser program. 

This project aims to bridge that gap by demonstrating how intensive soil data can inform practical on-farm decisions by highlighting nutrient variability and movement. 

Through three demonstration sites across South Australia, the project worked with farmers and their consultants to improve nutrient management, enhance productivity, and ensuring the long-term sustainability of dairy systems.

Approach to mapping soil variability 

Soil variability was initially investigated on approximately 300ha across the three participating dairies with a mix of irrigated and rainfed paddocks. The area was sampled using a grid soil mapping approach which:

Divided the paddocks into 1ha grids with soil samples taken along a 100m transect and combined to make one representative sample for each grid.

Samples were analysed for pH(CaCl2), Exchangeable Cations (Ca, Mg, K, Na), Olsen P and Colwell P. 

At the conclusion of 2024, 50ha of was resampled at each dairy, with the selection of sampling locations based on discussions with the growers and management interventions.

Nutrient availability was highly variable across all three dairies, with significant proportions of the study area having sufficient nutrients (for example Phosphorus and Potassium) while there were also areas with significant nutrient deficiencies. 

For example, Burrungule Dairy:

Colwell P: Average 224 mg/kg, range 36-450 mg/kg (critical level for dairy = 35-58 mg/kg

depending on PBI). Phosphorus Buffering Index: Average 193, Range 75-390.

Olsen P: Average 70 mg/kg, range 9-148 mg/kg. 

Potassium: Average 230 mg/kg, range 32-744 mg/kg (critical level for dairy = 130-150

mg/kg depending on soil texture).

Soil and Nutrient Action Plan was developed based on grid soil sampling results,

farm management objectives and the limitations and potential of utilising dairy effluent.

Each dairy had different objectives:     

Burrungule Dairy was to maintain productivity and optimise nutrient management. The ability to utilise effluent on other areas of the farm is currently limited by irrigation infrastructure as well as the time constraints to cart and spread to other regions. 

Alta Vista Enterprises was to target under-performing paddocks through improved pasture

species and nutrient management. The ability to further utilise effluent was limited by the lack of irrigation infrastructure as well as the challenge of carting slurry and spreading especially on the hillier terrain. Alta Vista commenced grid soil sampling prior to this case study, with an initial focus on improving soil pH and P in selected paddocks.

Paltridge’s priorities were to create and ply variable rate lime application maps to target a pH of 5.5, create Variable Rate P and K maps to target 45mg/kg and 200mg/kg, respectively. And to further investigate the potential to better target effluent applications based on the soil results in the South Block and assess the viability of more effluent being applied on North Block.

Conclusions

All involved dairies in the study area showed that there was significant nutrient variability in the soils, with potential for re-allocated and in some cases, reduced fertiliser applications.  The comparison of mapping different farms, as well as paddocks with different lineage and histories, provided an insightful look into the variability of soils with the influence of different histories and terrain. For all the participants, the ability to utilise and optimise dairy effluent to ‘textbook perfection’ was limited due to physical constraints of the irrigation infrastructure as well as

labour and management challenges. However, utilisation of the grid soil mapping results has

led to the reduction of fertiliser inputs, as well as the reallocation of fertilisers to regions that were more depleted than realised. The confidence for the farm managers and their consultants to utilise the detailed soil data has opened new pathways and decision-making tools.