A-BIOMASS™

The Future of Food and Agriculture will need to be low carbon, resource-efficient, in-synch with nature and resilient to climate extremes. This will require granular measurement and causal learning of the many operational, biotic and abiotic variables that are responsible for yield productivity gains and losses at a field level, so that customized agronomic solutions can be deployed at scale.

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Solution
Architecture


Operational Optimization


Operational Risk Management

 
 

OPERATIONAL PLANNING

A-FORECAST™

Machine learning platform that learns every month from multiple year time series of hundreds of operational and biophysical variables and generates a monthly crop yield forecast at the field level, a year in advance.

 

OPERATIONAL PLANNING

A-NOWCAST™

Machine learning platform that can reconstruct a historical archive and can monitor the crop biomass productivity & biomass quality at the field level, every day.

 

OPERATIONAL PLANNING

A-FIELD™

Machine learning platform that can automatically detect farm boundaries and the type of crop planted, so that the biomass productivity and yield anomalies at the field level can be automatically monitored at scale.

 

OPERATIONAL OPTIMIZATION

A-NOMALY™

Machine learning platform that can automatically detect and monitor biomass growth anomalies in near real time classified by type of anomaly (pest, weed, disease-related, etc).

 

OPERATIONAL OPTIMIZATION

A-DIAGNOSTIC™

Probabilistic causal learning platform that understands the cause & effect relationships between operational, biotic and abiotic variables that are responsible for yield productivity gains and losses (Yield Gap) at a field level, so that customized agronomic solutions can be deployed at scale.

 

OPERATIONAL RISK MANAGEMENT

A-WEEDS™

Deep learning platform that can automatically detect weed pressure and classify by weed species with high accuracy across multiple crops (sugarcane, soybeans, cotton, maize, eucalyptus, etc) using UAV imagery so that Precision Weeding solutions (autonomous or not) can be deployed at scale.

 

OPERATIONAL RISK MANAGEMENT

A-ROW™

Machine learning platform that can automatically reconstruct the planting lines to estimate plant population and monitor the planting failures using UAV imagery so that Precision Replanting solutions (autonomous or not) can be deployed at scale.

 

OPERATIONAL RISK MANAGEMENT

A-TREE™

Machine learning platform that can automatically detect and count healthy trees using UAV imagery so that Precision Replanting solutions (autonomous or not) can be deployed at scale.

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Raizen

Over the last four years our partnership with Raízen Energia has been focused on developing and operating industrial scale machine learning and computer vision platforms for operational planning, optimization and risk management of 800.000 hectares of sugarcane.