Helping Farmers Feed the World with APIs and Data

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Helping Farmers Feed the World With APIs and Data

Stewart Collis, aWhere

Jeof Oyster, aWhere

Food Production

Weather Variability Population Growth

1ºC warming of the atmosphere triples weather

variance

for agriculture this means food insecurity and risk

Cold

Sink

Heat

Source

Heat

Engine

QH – QC = W (work output)

heat input heat output

Weather Variability

Population Increase

7.2 Billion

9.6 Billion

Less developed countries

More developed countries

Population

In billions

Population Growth and Food Demand

By 2050, our population will gain another 2.4 billion

people Source: United Nations Dept of Economic and Social Affairs

That means, in just 34 growing seasons, the world’s

580 million farmers must feed 9.6 billion while facing:

Increased Weather Variability rendering traditional practices ineffective

Information Gap lack of adequate data across the value chain

Lack of Field-Level insight to prevent risk and improve production

The Global Food Challenge

aWhere

Agricultural intelligence business since 1999

Cloud-based big data and analytics for agriculture

Long-term customers and growing

Deliver the best agricultural information every day,

globally

Weather Terrain™

Data every few kilometers

• 1.6 million surface points

• + Customer points

• A billion points daily

Forecast

• 8 days of hourly forecast (updated 4x daily)

Observed (20 years)• Precipitation

• Min/Max Temperature

• Min/Max Relative Humidity

• Max/Mean Windspeed

• Solar Radiation

Embu, Kenya

Panchagarh, Bangladesh

Data Sources

Ground

Doppler

Weather Stations

and Sensors

Satellite

Field

Observations

ModelsForecast, Pest,

Disease, Growth Stage

Global Perspective Field InsightRisk aWhere Weather

aWhere

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Risk aWhere combines data from

both Weather Terrain™ and global

agricultural commodity sources and

Weather aWhere field data to

produce market risk management

insights and recommendations that

are timely, robust and relevant.

Using global daily data (from

weather satellites, ground

observations, radar, spectral imagery,

weather forecast etc.) as input to

agronomic models we can monitor

any crop planting and provide field

specific recommendations, alerts

and predictions.

Weather• Daily Forecast

• Short Term Forecast

Advanced Weather

• Accumulations

• Trends

• Seasonal Comparisons

Agronomic• Harvest Planning

• Pest & Disease Alerts

• Predicted Yields

• Agronomic Actions

Agro-economic• Pre-season planning

• Market Options

• Commodity Trading Options

Weather Agronomics™

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Basic

Advanced

Use CasesApplications of aWhere Technology

Weather Variability

By knowing to

wait 15 days to plant

her corn, a farmer in Uganda misses a

drought period

and increases her yield by 3X

Predictive Analytics

A commercial vegetable grower

receives

real-time harvest date

predictionsand modifies his labor and harvesting

schedule

to reduce crop loss by 25%

Pest and Disease Models

A farmer receives an SMS alert

about Rice Blast Fungus with a recommendation to fertilize

within

7 days and prevents the disease

producing a 30 bushel surplus

Food Security, Commodity Risk

Using Data for Risk Analyses of

Production, Marketsand Food Security for specific crops like

rice, sugar, coffee, cocoa and others

Small Holder Farmers

Working with local partners to push

personalized agronomic tips

to farmers via

SMS, Voice and Mobile Apps

supported with Call Center Apps

Farmers are equipped to make

better growing decisions

Data Analytics : Targeted Information

Ground

Doppler

Weather Stations

and Sensors

Satellite

Field

Observations

ModelsForecast, Pest,

Disease, Growth Stage

Location

Specific

Increased Yield

and Quality

Increase

Incomes

Healthy, Robust

Populations

Last Word from a Farmer

Thank youStewart Collis Jeof

Oysterstewartcollis@awhere.com jeofoyster@awhere.comwww.awhere.com