The Ministry of Agriculture, Livestock and Fisheries has approved, through Resolution 135/2025, the use of optical markers for the varietal identification of soybean samples. This technological advancement complements existing methods for wheat and barley, as well as molecular markers currently applied to soy and cotton.
This new tool enables the identification or verification of soybean varieties using real-time image processing powered by artificial intelligence. It can determine the predominant varieties in a sample along with their respective percentages. Analyses will be conducted by the Central Seed Analysis Laboratory of INASE and by authorized laboratories within the Territorial System of Seed Analysis Laboratories (SiTeLAS).
The system requires a minimum of 150 seeds or grains per analysis and considers results with 80% or higher similarity to the registered pattern as conclusive. Seeds treated with dyes or showing morphological alterations cannot be evaluated using this method. Additionally, breeders must submit pure samples to INASE to establish reference standards for new varieties within specified deadlines, according to a press release.
This development results from a collaborative effort between the National Seed Institute (INASE), breeding companies that provided samples, and suppliers of optical and molecular technologies. The implementation aims to strengthen compliance with the Seed and Phytogenetic Creations Law Nº 20.247, which ensures varietal identity and protects the intellectual property of plant genetic creations.
The Argentine Seeders Association (ASA) emphasized that this new step “continues to provide technology for the verification of varietal identity” and reaffirmed its commitment to extending these methods to other crops within the country’s productive matrix.
With this measure, Argentina solidifies a more precise and reliable system for trade control and the legal use of seeds, incorporating innovative tools to guarantee traceability, transparency, and genetic quality throughout the production chain.
