U.S. flag

An official website of the United States government

AgroAtlas

    The Russian-English Agricultural Atlas is the world’s most comprehensive source of information on the geographic distribution of plant-based agriculture in Russia and neighboring countries. The Atlas contains 1500 maps that illustrate the distribution of 100 crops, 560 wild crop relatives, 640 diseases, pests and weeds, and 200 environmental parameters. Additionally, the Atlas provides detailed biological descriptions, illustrations, metadata and reference lists. Currently, individual maps can be downloaded and viewed using freely available AgroAtlas GIS Utility software, which can also be downloaded at this site.

    Data from: Genetic Diversity and Population Structure of the USDA Sweetpotato (Ipomoea batatas) Germplasm Collections Using GBSpoly

      Population structure and genetic diversity of 417 USDA sweetpotato (*Ipomoea batatas*) accessions originating from 8 broad geographical regions (Africa, Australia, Caribbean, Central America, Far East, North America, Pacific Islands, and South America) were determined using single nucleotide polymorphisms (SNPs) identified with a genotyping-by-sequencing (GBS) protocol, GBSpoly, optimized for highly heterozygous and polyploid species.

      The GRIN-Global Project

        GRIN-Global (GG) is a database application that enables genebanks to store and manage information associated with plant genetic resources (germplasm) and deliver that information globally. The GRIN-Global project's mission is to provide a scalable version of the Germplasm Resource Information Network (GRIN) suitable for use by any interested genebank in the world.

        Cassavabase

          The Next Generation Cassava Breeding (NEXTGEN Cassava) project aims to significantly increase the rate of genetic improvement in cassava breeding and unlock the full potential of cassava, a staple crop central to food security and livelihoods across Africa. The project will implement and empirically test a new breeding method known as Genomic Selection that relies on statistical modeling to predict cassava performance before field-testing, and dramatically accelerates the breeding cycle.