Precision FarmingTECHNOLOGY AT GLANCE

by Iuri i PetrukHead of the Board, AgTech Ukraine

November 2020

DEFINITIONS

Tech FarmingSmart Agriculture

Smart Farming

e-Farming e-AgricultureDigital Farming

Digital Agriculture

PrecisionAg

Precision Agriculture

Precision FarmingAgriFoodTech

AgriTech

AgTech

Digital Agriculture is a data-driven concept, which includes wide set of digital tools and technologies along the agri-food value chain

AIMING TO

Reduce demand for manual labor

Increase information visibility

Emphasize automation

Optimize productivity

TO ACHIEVE

Allocated responsibility

Food traceability

Quality control

Sustainability

Precision Farming is a set of data-driven GIS based technologies designed for open field crops aiming to maximize profitability of every land parcel across the field based on spatial inequality insights

OLD SCHOOL APPROACH

field aggregation to optimize processes

NEW SCHOOL APPROACH

data driven solutions to maximize profitability

Shifting mentality: from field to plant

OLD SCHOOL APPROACH

Field size based decision making

Equal resources distribution

Unified processes (sometimes even on different fields)

NEW SCHOOL APPROACH

Spatial patterns based decision making

Resources redistribution

Increased cost efficiency

KEY PRINCIPLES:

Shifting mentality: from field to plant

OLD SCHOOL APPROACH

Limitation factor as productivity barrier

Production quality issues (additional cleaning, drying, calibration…)

Yield losses due to not optimal harvesting conditions

NEW SCHOOL APPROACH

Maximal use of land potential

Unified production quality

Decreased yield losses

KEY RESULTS:

With Precision Farmingwe replace inputs distribution uniformity with yield quality uniformity and profitability maximization

Old school New school

It’s all about DATAData Collection Data VisualizationData Processing Decision Making Implementation

DATA SOURCES Remote sensing (satellites, drones, photos)Sensors data (weather, soil)

Field operations data

Manual input data

Precision Farming scheme

GIS software

Field boundaries map

VRA MAPS

VR Seeding VR Fertilizing VR Spraying VR Irrigation

GPS guidance Soil mapping

Tillage Yield mapping Spot-on treatment* autonomous

Weather• Actual • Forecasting• Modelling

Mobile field scouting

Satellites & Drones Monitoring

Digital field journal

N application on-the-go* autonomous

Step-by-step digitalization Impossible to make a leap to VRA

without basic technologies integrated

Every step of precision farming integration brings you additional value

Operations precision is limited by the least precise technology

Every next layer of technologies is based on previous one

Trials and adjustments needed on every stage

Pixel optimization principle is the central idea of Precision Farming It is based on separate maintenance of every pixel of land within the field based on its measured parameters

30 m 250 m

Precision resolution evolution

250 × 250 m

Field zoning

30 × 30 m

Basic VRA maps

10 × 10 m

Precise VRA maps

Drone imagery

Plant based decision-making

Pixel size is determined by technology with the lowest resolution applied on the exact field

Precision resolution evolution

Drone Satellite

MODIS max 250 × 250 m (free) Landsat max 30 × 30 m (free) Sentinel 10 × 10 m (free) Planet 3,5 × 3,5 m (paid) WorldView 0,3 × 0,3 m (on demand)

Drones

Precision resolution evolution FIELD EQUIPMENT:

Full working width application control

Equipment sections control Distribution units control (seeders, nozzles, applicators)

Profitability is the key SPEND LESS

Preliminary planning

Optimal use of resources

On-time decisions making and implementation

Minimal to excluded after-harvest treatment

EARN MORE

Better quality – better price

Minimal field losses

Economy of scale Precision farming brings feasible results

on big fields with visible spatial inequality

Only high equipment capacity utilization makes its purchase profitable

More real field data – higher precision

VRA is affordable only for big companies and cooperatives

Too low economic effect on spatially uniform fields

Qualified personnel is required

Prospective technologies and solutions Precision Farming Service Companies

Soil carbon sequestration monitoring

Small robots and drones swarms

Autonomous robotic platforms for field operations

Electric and Hydrogen tractors

Distributed planning

Precision Farming VS Ecology & Sustainability Reduce soil compaction

Reduce unjustified losses

Decrease CO2 emissions

Reduce chemical pressure

Reduce soil and water pollution

Brings more info for food traceability

Refill nutrients deficit (soil quality preservation)