PA Methods to Diagnose Crop Performance ? Tim Neale 1 and John Heap 2 1 PrecisionAgriculture.com.au 2 SARDI

Seedling “Diagnostic Agronomy” Yes To the beach! No What Went Wrong?? Black box & Can of worms Vegetative biomass Water limited yield in all zones? Another Black box & Can of worms Grain yield The ultimate integrator

What Went Wrong? ( Crop grain yield is the ultimate integrator of constraints Spatial-temporal patterns (PA) give excellent diagnostic clues - eg gap between vegetative biomass and grain yield Real-time sensing vs. historical diagnosis Yield constraints - Natural or man-made (management) - Natural: Biological, Soil, Other - Treatable or untreatable (practicality, economics) - Simple or complex (eg ARG x subsoil constraints?)

PA Methods to Diagnose and Manage Crop Performance Identify problem zones Management decision: Amelioration vs ↓ inputs Yield (+ biomass) maps Management actionDiagnose (ID) problem Observation, knowledge, experience, tests, PA data VRT options, economics, experience, risk PA VRT equipment

Constraints to achieving water limited yield (incomplete list for example only) Biological Weeds Soilborne diseases Foliar diseases Soil biota Insects Soil N P pH Other nutrients Soil depth Soil texture Boron Salinity Water repellance Other Frost Wind Herbicide toxicity Water-logging Compaction Lodging

PA technologies and data to diagnose crop performance (incomplete list for example only) Real-time (sensors) N application (CropCircle, CropSpec, Greenseeker) Herbicide application (WeedSeeker) Technologies Yield/Protein monitors EM38 Satellite imagery Aerial imagery Weed mapping (CropCircle, CropSpec etc) Gamma Data Yield/Protein maps ECa maps Biomass maps Soil maps Weed maps Disease inoculum maps Elevation (DEMs) Thermal maps Slope/aspect Drainage models

Diagnostic Agronomy: Where are we? Sound agronomic knowledge at paddock level Good range of diagnostic tests and tools PA research - good progress on specific problems Need an integrated approach to diagnose zone constraints Best diagnostic models are in good agronomists heads

Diagnostic Agronomy: Next steps? Need to capture and codify agronomist’s knowledge and diagnostic process – aided by PA data. Synergistic combination of technologies important (e.g. gamma + EM38) Need sound economic mapping and VRT strategies Human observation and experience critical to success

Potential GRDC investment: Integrated Diagnostic Model Identify major constraints Define/research characteristics of constraints Construct a diagnostic tool for constraints (similar to plant taxonomy?) Field test diagnostic tool Sampling/testing promotion? Develop mapping and VRT technologies Practical techniques and economics