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    Panzea is an NSF-funded project called "Biology of Rare Alleles in Maize and its Wild Relatives". We are investigating the connection between phenotype (what we see) and genotype (the genes underlying the phenotype) - of complex traits in maize and its wild relative, teosinte, and specifically in how rare genetic variations contribute to overall plant function. These studies will enrich our knowledge of evolution, sustainable agriculture, and genetic diversity and conservation. Over the 10 years of the project, we have trained many new scientists at all levels and generated key resources for the public, teachers, and scientific researchers.


      MaizeGDB is a community-oriented, long-term, federally funded informatics service to researchers focused on the crop plant and model organism Zea mays. Genomic, genetic, sequence, germplasm, gene product, metabolic pathways, functional characterization, literature reference, diversity, and expression are among the datatypes stored at MaizeGDB. At the project's website are custom interfaces enabling researchers to browse data and to seek out specific information matching explicit search criteria. First released in 1991 with the name MaizeDB, the Maize Genetics and Genomics Database, now MaizeGDB (since 2003), is funded, developed, and hosted by the USDA-ARS located at Ames, Iowa.

      Data from: Gas emissions from dairy barnyards

        To assess the magnitude of greenhouse gas (GHG) fluxes, nutrient runoff and leaching from dairy barnyards and to characterize factors controlling these fluxes, nine barnyards were built at the U.S. Dairy Forage Research Center Farm in Prairie du Sac, WI (latitude 43.33N, longitude 89.71W). The barnyards were designed to simulate outdoor cattle-holding areas on commercial dairy farms in Wisconsin. Each barnyard was approximately 7m x 7m; areas of barnyards 1-9 were 51.91, 47.29, 50.97, 46.32, 45.64, 46.30, 48.93, 48.78, 46.73 square meters, respectively. Factors investigated included three different surface materials (bark, sand, soil) and timing of cattle corralling. Each barnyard included a gravity drainage system that allowed leachate to be pumped out and analyzed. Each soil-covered barnyard also included a system to intercept runoff at the perimeter and drain to a pumping port, similar to the leachate systems.

        Low-Disturbance Manure Incorporation

          The LDMI experiment (Low-Disturbance Manure Incorporation) was designed to evaluate nutrient losses with conventional and improved liquid dairy manure management practices in a corn silage (*Zea mays*) / rye cover-crop (*Secale cereale*) system. The improved manure management treatments were designed to incorporate manure while maintaining crop residue for erosion control. Field observations included greenhouse gas (GHG) fluxes from soil, soil nutrient concentrations, crop growth and harvest biomass and nutrient content, as well as monitoring of soil physical and chemical properties. Observations from LDMI have been used for parameterization and validation of computer simulation models of GHG emissions from dairy farms (Gaillard et al., submitted). The LDMI experiment was performed as part of the Dairy CAP.

          Manure application methods for alfalfa-grass

            The MAMA experiment (Manure Application Methods for Alfalfa-Grass), from the USDA-ARS research station in Marshfield, WI was designed to evaluate nutrient and pathogen losses with conventional and improved liquid dairy manure management practices for alfalfa-grass production. Observations from MAMA have also been used for parameterization and validation of computer simulation models of greenhouse gas (GHG) emissions from dairy farms.

            Effects of tannin in dairy cow diets and land application of manure on soil gas fluxes and nitrogen dynamics

              This experiment was designed to determine if tannin concentration and nitrogen (N) content of field-applied dairy cow manure influences greenhouse gas (GHG) emissions from soil, soil N mineralization, and plant productivity. The data presented include experimental design, soil physical characteristics, gas fluxes, soil nitrogen at 0-10 cm depth, soil nitrogen at 10-20 cm depth, chemical characteristics of dairy manure, and crop yield and biomass characteristics.

              Data from: Soil Water Holding Capacity Mitigates Downside Risk and Volatility in US Rainfed Maize: Time to Invest in Soil Organic Matter?

                This dataset includes county-level annual data on maize (Zea mays L.) yield, soil physical and chemical characteristics, and mean weather data for 2000 through 2014 for IL, MI, MN and PA. The data were aggregated from public databases, including NASS Quick Stats, NOAA Climate Data Online, and the USDA-NRCS Web Soil Survey. U.S. counties were the experimental unit for this study, and all data are county-level averages. Covariances among county-level maize yield stability and environmental variability were analyzed using structural equation models (SEM) and linear mixed effects (LME) models.