Machine-actionable mode of action codes
On-line
Monday September 14 - 10:00 New York / 16:00 Berlin / 22:00 Beijing / 23:00 Tokyo
Tuesday September 15 - 02:00 Auckland
If you are a member of TC 347, please register via the ISO portal.
Otherwise, open registration is via Zoom at https://syngenta.zoom.us/meeting/register/h_fAZNWIQvyqmjD3FVR8ww. After registering, you will receive a confirmation email containing information about joining the meeting.
Under the umbrella of ISO Technical Committee 347 the home for standards to enable data-driven decisions in the world’s agrifood systems, ISO project 34705-7 is beginning to tackle crop protection product (pesticide) mode of action codes. The project aims to develop a data structure, specification and descriptions to encapsulate the existing XRAC codes generated by expert committees. It needs the help of experts like you who know some part of the picture and can help us develop the draft standard.
The ISO 34705-7 project team aims to do just this. Whether you have MoA expertise, data model expertise, and/or knowledge of stakeholders in this universe, we need your skills!
An analogy might help provide more background: just as medical doctors avoid prescribing the same type of antibiotic over and over because human pathogens can become resistant, farmers need to rotate different types of pesticide so weeds, insects, and diseases don't become resistant.
The mode of action (MoA) groups help farmers to manage this rotation of pesticides. The MoA code is the short identifier that tells you how a pesticide works and whether it belongs to the same group as another product. Today these codes often appear as small text on pesticide labels, such as "Group 11 Fungicide" or "Group 4 Herbicide." Humans can find the codes if they know where to look, but computers cannot reliably use them unless the information is structured and standardized for digital consumption, which is not yet the case.
Pesticides are used widely in modern agriculture, and in increasingly complex ways (e.g., using drones and spot-spraying robots). Helping farmers use chemicals accurately and safely, in compliance with their legally binding label, affords a valuable opportunity for information technologies to support decision-making, by developing machine-readable and machine actionable MoA codes and data structures.
