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

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Presentation on theme: "PA Methods to Diagnose Crop Performance ? Tim Neale 1 and John Heap 2 1 2 SARDI."— Presentation transcript:

1 PA Methods to Diagnose Crop Performance ? Tim Neale 1 and John Heap 2 1 2 SARDI

2 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

3 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?)

4 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

5 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

6 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

7 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

8 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

9 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

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