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Ag Data Commons migration begins October 18, 2023

The Ag Data Commons is migrating to a new platform – an institutional portal on Figshare. Starting October 18 the current system will be available for search and download only. Submissions will resume after the launch of our portal on Figshare in November. Stay tuned for details!


    The Breedbase system has evolved from the Sol Genomics Network (SGN) and Cassavabase and related sites (see RTBbase.org).Breedbase is striving to be a complete breeding management system, including field management, data collection, crossing utilities, and advanced trial analysis.

    CottonGen: Cotton Database Resources

      CottonGen (https://www.cottongen.org) is a curated and integrated web-based relational database providing access to publicly available genomic, genetic and breeding data to enable basic, translational and applied research in cotton. Built using the open-source Tripal database infrastructure, CottonGen supersedes CottonDB and the Cotton Marker Database, which includes sequences, genetic and physical maps, genotypic and phenotypic markers and polymorphisms, quantitative trait loci (QTLs), pathogens, germplasm collections and trait evaluations, pedigrees, and relevant bibliographic citations, with enhanced tools for easier data sharing, mining, visualization, and data retrieval of cotton research data.


        The genosim package simulates genotypes, breeding values, and phenotypes; simulates DNA sequence read depth (numbers of A and B alleles); and resolves SNP conflicts between parent and offspring genotypes.

        Code from: Using cameras for precise measurement of two-dimensional plant features

          Images are used frequently in plant phenotyping to capture measurements. This chapter offers a repeatable method for capturing two-dimensional measurements of plant parts in field or laboratory settings using a variety of camera styles (cellular phone, DSLR), with the addition of a printed calibration pattern. The method is based on calibrating the camera using information available from the EXIF tags from the image, as well as visual information from the pattern. Code is provided to implement the method, as well as a dataset for testing. We include steps to verify protocol correctness by imaging an artifact. The use of this protocol for two-dimensional plant phenotypoing will allow data capture from different cameras and environments, with comparison on the same physical scale.

          Data from: Starch and dextrose at 2 levels of rumen-degradable protein in iso-nitrogenous diets: Effects on lactation performance, ruminal measurements, methane emission, digestibility, and nitrogen balance of dairy cows

            This feeding trial was designed to investigate two separate questions. The first question is, “What are the effects of substituting two non-fiber carbohydrate (NFC) sources at two rumen-degradable protein (RDP) levels in the diet on apparent total-tract nutrient digestibility, manure production and nitrogen (N) excretion in dairy cows?”. This is relevant because most of the N ingested by dairy cows is excreted, resulting in negative effects on environmental quality. The second question is, “Is phenotypic residual feed intake (pRFI) correlated with feed efficiency, N use efficiency, and metabolic energy losses (via urinary N and enteric CH4) in dairy cows?”. The pRFI is the difference between what an animal is expected to eat, given its level of productivity, and what it actually eats. The goal was to determine whether production of CH4, urinary N or fecal N is a driver of pRFI.

            The Triticeae Toolbox

              [The Triticeae Toolbox](https://triticeaetoolbox.org/) (T3) webportal hosts data generated by the Triticeae Coordinated Agricultural Project (CAP), funded by the National Institute for Food and Agriculture (NIFA) of the United States Department of Agriculture (USDA). T3 contains SNP, phenotypic, and pedigree data from wheat and barley germplasm in the Triticeae CAP integrating rapidly expanding DNA marker and sequence data with traditional phenotypic data.