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Variable Rate Technology Show me where the numbers add up.

A Northern Mallee Prospective

By Alistair Murdoch Farmer

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Limited Root Access too Inter- Row Nutrients

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Introduction • What we were looking to control with VRT

• How we developed a stable layer.

• Ongoing evaluation of our spatial

management.

• Economics: Our experience

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Better Allocation of Input $ • A run of poor seasons in the early to mid

2000’s had us questioning our fertiliser spend.

• Dune – Swale land formation, so large soil type variability.

• Need to allocate inputs to PAW

• Massive difference in nutrient removal

• Technology was pretty well there.

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Implementation Developing a stable layer

• Elevation ? • We had no yield maps? • Ground truthing? • EM 38? • Gama? • Limited NDVI?

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Calibration of Data Layers

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Getting the Data to the Ground • Having the data file in a readable

format for the task controller.

• Knowing your systems strengths and weaknesses

• Technology today has data transfer as a key priority

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Low N

Large Amounts of Sulphur and Nitrogen Deficiency

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Ongoing Evaluation • Test strips at planting– 0 and 2X rates • N Rich stripes

• NDVI and Yield Data

• Ground truthing

• Stacked data.

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EM 38

Yield Map 0 N stripe

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Sentinel 2 Image

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0 P Application

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VRT use on-farm Today • VR Fertiliser and Seed at Sowing

• VR Topdress of N and S with Kuhn

Spreader

• Split sowing of crop types with one pass

• Some selective sprayer (Skelton Weed and Couch Grass)

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On Farm Economics • Early N is Critical on Dunes: 1t/ha

advantage 2015

• P response is as much rotational as P replacement.

• S Demand is closely linked to soil type.

• Not just macro nutrients that are worth VR.

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Take home message • Identify what you are looking to spatially

manage.

• Reach out to others to determine an effective entry data layer to get you started.

• Committing the time to evaluate your spatial management approach.