Future challenges + Ag Tech Requirements Tillage Dermot Forristal - PowerPoint PPT Presentation

Future challenges + Ag Tech Requirements Tillage Dermot Forristal Teagasc CELUP Oak Park Crops Research

Challenges in the crops sector  Competition for land  Profitability per ha  Disease, Pest and Weed control ▶ E.g. loss of fungicide sensitivity / less new products ▶ IPM and cultural control  GHG emissions Positives ▶ World’s highest yields ▶ Labour efficient

Ag Tech Needs More precise management ‘Precise’ Management : Machine control  Auto-steer measuring + responding to ‘variability’.  Auto ‘section- control’  Any automated function  Fields: Spatial variability

‘SMART’ Sensors Measure Data Collect data communications Analyse Research Algorithms Decision Controllers

Mesmerised by Yield Maps ! 7t / ha 10t / ha 10t / ha 14t / ha Initial Assumption • All could yield 14t • At least 10t ? Not That Simple!  Huge expectations generated  Blinded by ‘possibilities’

Advances in Precision Ag but!

Variable rate application: Nitrogen  Applying N more accurately  Huge scope as optimum varies hugely: 100 – 300 kg/ha  Cost, quality and environmental consequences !

Crop Reflectance and N  Measure crop biomass and N content – crop reflectance  Reflectance scanner (multi-spec): ▶ Visible and NIR wave bands  Quite a bit of research since the 1970s!!

Farmstar N sensing - France

Yara N Sensor

E bee drone with Sensor

Does crop sensing work for N ?  BUT, Does it work? 1% or 3-4% yield improvement.  Algorithms not region specific ▶ Some maximise protein ▶ Some optimise yield  N is Not that simple  What comes from the soil ?  What is crop yield potential  Weather and soil impact on both  Need to measure and predict these  What’s needed to improve it: soil sensors, leaching prediction, crop growth models etc all need development

Precision Crop management Soil sensing: Crop sensing: Environment • Nutrients • Nutrients sensing: • Organic Carbon • Development • Structure / texture • Microclimate • Health / disease • Weather prediction • Microbiome • Yield / Quality • Moisture • Variability Supporting Tech transfer Data analytics Research support Crop Models Decision Support Systems Precision management response (spatially variable, real time or sequential)

Machine Guidance, Autosteer and Control

Machine Guidance: Steering, Headland systems

97% full header vs 87% Not 10% performance improvement

Does it Pay? (Getting Farmers to Adopt!)

Auto - steer + Section Control

Sprayer section control (avoids excess overlaps)

Guidance and Section control  Benefits: - depends on field  3m saving on headlands: 2.0% saving  Saving on short ground: 0.5%  No loss on tramlines: 4.0% Total saving 6.5%  Fungicide / Herbicide saving  Winter wheat: €16.00 / ha  Spring Barley: €8.76 / ha

Guidance and sprayer control costs Break even areas W. wheat: 128 / 172ha S. barley: 230 / 315ha

Machine control (– does it pay?)  Control systems on all machines  Sprayers  Fert spreaders  Combines  Seeders  Slurry / Muck  Diet feeders  Ploughs  Balers / Foragers  Tractors  Etc, etc

SMART can be simple and free ! Oilseed Rape N management

Oilseed rape: Canopy Management  Optimises N – Saves N  Optimises canopy size, pod number and yield. It Works: Why?  Good relationship between accumulated N and required N  Substantial research programme  Simple to operate  Free

Farm Management Applications

Farm management applications  Around for decades.  SMART phones breathing new life  Management; Agronomy; Animal / Herd; Financial  Regulatory compliance: Cattle ID; Farm health; Pesticides etc; Nitrates etc

Getting their hands on the Data!!

Farm data !!!  Data from: ▶ Reflectance sensors: Sattelite, Drone, Tractor mounted ▶ Soil sensors: Electrical conductivity, Tractor draught ▶ Soil Analysis: nutrients, pH, Carbon ▶ Yield mapping combine ▶ Input application: seeder, sprayer, fertiliser, manures ▶ Weather data: field level or region based ▶ Disease data; crop growth etc ▶ Financial data from farm at farm or field level  Who collects, transmits, stores, analyses and uses data?

Lots of players !  Tractor / equipment manufacturers: JD, CLAAS  ‘Positioning’ companies: TRIMBLE; TOPCON  Breeders / Chemical companies  Traditional Farm management companies  New Data management Hubs 365FARMNET

Conclusions  Huge potential in crop systems and machines  Concepts are there and good; but delivery challenging  Seek simple opportunities  For the user: the technology must pay .  For the developer: the technology must pay!