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The future of breeding is now

Products and services

Our Seed Accelerator service is designed to help you achieve your goals in the most efficient way possible. With our expertise in plant genetics and breeding, we work closely with seed companies to customize plant breeding solutions for your needs. From predicting the best varieties to advance through genomic selection to gene discovery with GWAS, we are here to help drive your business forward.

GWAS

About us

Wheat

McClintock has developed a proprietary AI breeding platform to accelerate the production of new crop varieties. Our cutting edge AI/machine learning platform leverages both public and client datasets to tailor breeding solutions for our partners. We partner with plant breeders and seed companies to deliver the highest quality traits in the shortest time possible at the most affordable price. Our mission is to provide our partners with the tools they need to create the best crops and grow the most nutritious foods.

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In addition to our breeding platform, we also provide consulting services to assist in the use of gene editing technology into a product development pipeline, help define gene candidates to improve intrinsic yield and identify germplasm-specific gene/allele targets to most rapidly advance client germplasm.

Latest News 

Green ripening soybean field, agricultural landscape.jpg
McClintock Partners with Amfora
June 2023

 

McClintock has entered into an agreement with Amfora to deliver AI breeding capabilities to the Amfora plant breeding program.  The partnership will accelerate the development of high protein soy varieties with improved qualities such as increase oleic acid content and lower linolenic acid profiles.

Agricultural Fields

McClintock announces release of AI Predictive Breeding Pipeline

June 2023

 

McClintock has launched its predictive breeding pipeline enabling the full suite of AI enabled breeding capabilities including genomic selection, marker assisted selection, genome wide association and crossing prediction, a simulation model to identify the best sets of parents to maximize yield gains while retaining diversity in breeding materials.

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