101 ways to make PA work in Qld Vegetables

Sarah Limpus, Ian Layden & Julie O’Halloran

Department of Agriculture & Fisheries Queensland

The Project “Adoption of variable rate technology in

Queensland’s intensive vegetable productions systems”

Commercial farm demonstration sites across key Queensland vegetable producing regions - 17 businesses Commercially available technologies Installation & optimisation Strategic management strategies Capacity building

Kalbar Carrots Shared harvester fitted with load-based yield monitor Proximal biomass imagery & EM soil survey VR spreader Data management software

Kalbar Carrots – Identify Variability

Biomass - NDVI Carrot Yield EM Soil Survey

Kalbar Carrots - Ground truthing variability

11

2

2

0

100

200

300

400

500

600

700

N P K

NU

TRIE

NT

AN

ALY

SIS

(MG

/KG

)

Comparison of soil nutrient analysis of zone 1 & 2

Growthzone 1

Growthzone 2

66%

50%

30%

NDVI (Greenseeker)

Kalbar Carrots – Identify Variability

(31%)(62%)(7%)

+50%

Carrot Yield – Raw data Carrot Yield – Cleaned & Categorised

Zone 1

Zone 2

Kalbar Carrots – Treat Variability

Local Knowledge VRT Spreader

Kalbar Carrots – Data Mining

Yield

Thousands of individual, geo-referenced data points Multiple spatial layers

96%

EM Soil Survey 89%

NDV

IYI

ELD

NDVI (Greenseeker)

How much of the field is underperforming? By how much?

Is there value in increasing yield in poorer performing areas?

Economic analyses of variability vs management intervention

Farming values

Yield category

Area % area

0-40 t/ha 2.8 31

40-60 t/ha 5.6 62

60-100 t/ha 0.6 6

high $/ha low $/ha

Kalbar Carrots - Decision making Profit-Loss Map

Atherton Potatoes 250 ha fresh & processing

potato Mechanical harvester fitted

with load-based yield monitor

Satellite NDVI – cloud cover Retrofit planting box for VRT

fertiliser

Atherton Potatoes – Identify VariabilityPotato yield map

30% higher yielding variety

53%NDVI Sat Image - 0.8m resolution

Irrigated at capture

Pasture 4 yrs ago

Atherton Potatoes - Identify Variability

pH 4.5

pH 5.9

pH grid sampling

Conventional lime cost 60 t @ $9,600VRT lime cost 35 t @ $5,600 strategic spread

40% lime savings

Atherton Potatoes – Treat Variability

Lime prescription to target pH 5.5

0 t/ha

1.5 t/ha

2.5 t/ha

4.5 t/ha

Atherton Potatoes – Treat Variability EM mapping and & moisture probes (telemetry)

Low water holding capacity soils in the East

VRT irrigation, automatically manual

30% higher yielding variety

Atherton Potatoes – Data Mining

Zone Average (t/ha) % Area1 79.30 4.98%2 51.30 15.99%3 38.44 50.04%4 25.58 27.09%5 14.58 1.89%

Average/total 38.59 100%

Bowen Capsicums

BMS Soil Information Systems (EM mapping) 32 ha mapped/sampled

Bowen Capsicums - Identify Variability

53% with ESP >6%

As high as 20% at 0.5m

Yield consequences? Data doesn’t exist

Up to 60% based on calculations derived from Ayars & Westcott, 1994

Not seen here = good water/nutrition management

Soil tests & local erosion show considerable soil-structural effects

ESP %

Qld Globe Data > Bore station

Don River Delta

Keep an eye on water levels Leach in dry years only

Gypsum application 0-5 t/ha banded (traditional 1t/ha over 32 ha)

VRT increases GM by $9/ha OR 0.002% of the GM

Bowen Capsicums - Treat Variability

YES!

0 t/ha 1.75 t/ha 3.25 t/ha 5 t/ha

So why is PA in veg important? While not always straightforward, PA does help identify, quantify & treat variability Crop uniformity is critical – contract & mechanical harvesting, hand harvesting (reducing

multiple harvests) Current agronomy is very good – has been revised due to missing some important within block

factors affecting profitability (pests, irrigation, soil) More efficient & strategic utilisation of resources (inputs, labour) & land (environmental

advantages) Government investment has an important role in kick-starting/navigating adoption of new

technologies, particularly where market failure exists

Future Improved grower/agronomist readiness for emerging data challenges (storage, analysis, privacy,

mobile applications, robotics, automation) Traceability – becoming more important in the fresh sector (agronomic/chemical data on

demand, exact locations/harvest days, pack out, safety, quality ………)

Challenges Yield monitors are critical to adoption & understanding the cost

of variability – require significant optimisation & calibration to determine “marketable” yield

Data management, capacity building in utilising software, ‘cloud’ & mobile mapping applications e.g. Google Earth, Dropbox

Technology optimisation – not just plug & play technologies, compatibilities

Capacity building for ground truthing activities e.g. strategic/zonal sampling

Multiple layers & data mining to get the most out of the investment

This work was supported by the Queensland Department of Agriculture and Fisheries (DAF), Department of Environment and Heritage Protection and the Australian Government’s National Landcare Programme.This work was made possible by the co-operation of producers and commercial service providers.

Acknowledgements

Kengoon Farming ● Windhum Farms ● NorthQual ● Veejays ● Rieck Farming ● DJM Farming ●Ben Poggioli ● AustChilli ● Kalfresh ● Windolf Farms ● Rugby Farms ● Phantom Farms

Precision Agriculture ● Precision Ag Solutions ● Vanderfields ● BGA Agri Services ● GT Ag Services ● SST Software ● Bowen Crop Monitoring ● Tableland Fert ● Airborn Insight ●

BMS Laser Sat

ActivitiesAssess spatial variability

Crop Sensing•Satellite images•Proximal NDVI sensors

EMI Soil Mapping•Soil moisture•Clay content•Salt

Gridded Soil Sampling

Yield Monitoring•Retrofit existing harvesters•3 x potato•1 x sweet potato•1 x carrot (750+ ha)

Ground-truthing activities

Strategic crop monitoring

Pest/disease identification & mapping

Irrigation efficacy/moisture monitoring

EMI Soil Mapping

Strategic/zonal soil sampling

Management interventions

Irrigation redesign/VR

Variable rate applications•Lime•Fertiliser•Gypsum•Compost

Strategic management & software