Maize genomes to fields (G2F): 2014-2017 field seasons: Genotype, phenotype, climatic, soil, and inbred ear image datasets

Bridget A. McFarland; Naser Alkhalifah; Martin Bohn; Jessica Bubert; Edward S. Buckler; Ignacio Ciampitti; Jode Edwards; David Ertl; Joseph L. Gage; Celeste M. Falcon; Sherry Flint-Garcia; Michael A. Gore; Christopher Graham; Candice N. Hirsch; James B. Holland; Elizabeth Hood; David Hooker; Diego Jarquin; Shawn M. Kaeppler; Joseph Knoll; Greg Kruger; Nick Lauter; Elizabeth C. Lee; Dayane C. Lima; Aaron Lorenz; Jonathan P. Lynch; John McKay; Nathan D. Miller; Stephen P. Moose; Seth C. Murray; Rebecca Nelson; Christina Poudyal; Torbert Rocheford; Oscar Rodriguez; Maria Cinta Romay; James C. Schnable; Patrick S. Schnable; Brian Scully; Rajandeep Sekhon; Kevin Silverstein; Maninder Singh; Margaret Smith; Edgar P. Spalding; Nathan Springer; Kurt Thelen; Peter Thomison; Mitchell Tuinstra; Jason Wallace; Ramona Walls; David Wills; Randall J. Wisser; Wenwei Xu; Cheng Ting Yeh; Natalia De Leon

doi:10.1186/s13104-020-4922-8

Maize genomes to fields (G2F): 2014-2017 field seasons: Genotype, phenotype, climatic, soil, and inbred ear image datasets

Bridget A. McFarland, Naser Alkhalifah, Martin Bohn, Jessica Bubert, Edward S. Buckler, Ignacio Ciampitti, Jode Edwards, David Ertl, Joseph L. Gage, Celeste M. Falcon, Sherry Flint-Garcia, Michael A. Gore, Christopher Graham, Candice N. Hirsch, James B. Holland, Elizabeth Hood, David Hooker, Diego Jarquin, Shawn M. Kaeppler, Joseph KnollGreg Kruger, Nick Lauter, Elizabeth C. Lee, Dayane C. Lima, Aaron Lorenz, Jonathan P. Lynch, John McKay, Nathan D. Miller, Stephen P. Moose, Seth C. Murray, Rebecca Nelson, Christina Poudyal, Torbert Rocheford, Oscar Rodriguez, Maria Cinta Romay, James C. Schnable, Patrick S. Schnable, Brian Scully, Rajandeep Sekhon, Kevin Silverstein, Maninder Singh, Margaret Smith, Edgar P. Spalding, Nathan Springer, Kurt Thelen, Peter Thomison, Mitchell Tuinstra, Jason Wallace, Ramona Walls, David Wills, Randall J. Wisser, Wenwei Xu, Cheng Ting Yeh, Natalia De Leon

Research output: Contribution to journal › Article › peer-review

21 Scopus citations

Abstract

Objectives: Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F's genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014-2017. Data description: Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.

Original language	English (US)
Article number	71
Journal	BMC Research Notes
Volume	13
Issue number	1
DOIs	https://doi.org/10.1186/s13104-020-4922-8
State	Published - Feb 12 2020

Bibliographical note

Funding Information:
We gratefully acknowledge support from: USDA Hatch program funds to mul‑ tiple PIs in this project; the USDA Agricultural Research Service; the Arkansas Corn and Grain Sorghum Board; the Clemson University, the Colorado Corn Administrative Committee; the Georgia Agricultural Commodity Commission for Corn; the Corn Marketing Program of Michigan; the Illinois Corn Marketing Board; the Iowa Corn Promotion Board; the Iowa State University Plant Sci‑ ences Institute; the Kansas Corn Commission; the Minnesota Corn Research and Promotion Council; National Corn Growers Association; Nebraska Corn Board; the Ohio Corn Marketing Program; the Ontario Ministry of Agriculture, Food, and Rural Affairs; the Texas Corn Producers Board and the Wisconsin Corn Promotion Board. We also acknowledge funding from the National Science Foundation under Grant Numbers #DBI‑0735191 and #DBI‑1265383 to support CyVerse (http://www.cyverse.org), #IOS‑1339362 to support phenotyping by JC and SPM, and USDA‑NIFA 2011‑67003‑30342 to RJW, SFG, JH, NL, SM, WX, and NDL. The funders had no role in the design and conduct of the study, data collection, and writing of the manuscript.

Publisher Copyright:
© 2020 The Author(s).

Keywords

Environment
Field metadata
G × E
GBS
Genome
Genotype
Hybrid
Inbred
Maize
Phenotype

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10.1186/s13104-020-4922-8

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McFarland, B. A., Alkhalifah, N., Bohn, M., Bubert, J., Buckler, E. S., Ciampitti, I., Edwards, J., Ertl, D., Gage, J. L., Falcon, C. M., Flint-Garcia, S., Gore, M. A., Graham, C., Hirsch, C. N., Holland, J. B., Hood, E., Hooker, D., Jarquin, D., Kaeppler, S. M., ... De Leon, N. (2020). Maize genomes to fields (G2F): 2014-2017 field seasons: Genotype, phenotype, climatic, soil, and inbred ear image datasets. BMC Research Notes, 13(1), [71]. https://doi.org/10.1186/s13104-020-4922-8

McFarland, BA, Alkhalifah, N, Bohn, M, Bubert, J, Buckler, ES, Ciampitti, I, Edwards, J, Ertl, D, Gage, JL, Falcon, CM, Flint-Garcia, S, Gore, MA, Graham, C, Hirsch, CN, Holland, JB, Hood, E, Hooker, D, Jarquin, D, Kaeppler, SM, Knoll, J, Kruger, G, Lauter, N, Lee, EC, Lima, DC, Lorenz, A, Lynch, JP, McKay, J, Miller, ND, Moose, SP, Murray, SC, Nelson, R, Poudyal, C, Rocheford, T, Rodriguez, O, Romay, MC, Schnable, JC, Schnable, PS, Scully, B, Sekhon, R, Silverstein, K, Singh, M, Smith, M, Spalding, EP, Springer, N, Thelen, K, Thomison, P, Tuinstra, M, Wallace, J, Walls, R, Wills, D, Wisser, RJ, Xu, W, Yeh, CT & De Leon, N 2020, 'Maize genomes to fields (G2F): 2014-2017 field seasons: Genotype, phenotype, climatic, soil, and inbred ear image datasets', BMC Research Notes, vol. 13, no. 1, 71. https://doi.org/10.1186/s13104-020-4922-8

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title = "Maize genomes to fields (G2F): 2014-2017 field seasons: Genotype, phenotype, climatic, soil, and inbred ear image datasets",

abstract = "Objectives: Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F's genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014-2017. Data description: Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.",

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author = "McFarland, {Bridget A.} and Naser Alkhalifah and Martin Bohn and Jessica Bubert and Buckler, {Edward S.} and Ignacio Ciampitti and Jode Edwards and David Ertl and Gage, {Joseph L.} and Falcon, {Celeste M.} and Sherry Flint-Garcia and Gore, {Michael A.} and Christopher Graham and Hirsch, {Candice N.} and Holland, {James B.} and Elizabeth Hood and David Hooker and Diego Jarquin and Kaeppler, {Shawn M.} and Joseph Knoll and Greg Kruger and Nick Lauter and Lee, {Elizabeth C.} and Lima, {Dayane C.} and Aaron Lorenz and Lynch, {Jonathan P.} and John McKay and Miller, {Nathan D.} and Moose, {Stephen P.} and Murray, {Seth C.} and Rebecca Nelson and Christina Poudyal and Torbert Rocheford and Oscar Rodriguez and Romay, {Maria Cinta} and Schnable, {James C.} and Schnable, {Patrick S.} and Brian Scully and Rajandeep Sekhon and Kevin Silverstein and Maninder Singh and Margaret Smith and Spalding, {Edgar P.} and Nathan Springer and Kurt Thelen and Peter Thomison and Mitchell Tuinstra and Jason Wallace and Ramona Walls and David Wills and Wisser, {Randall J.} and Wenwei Xu and Yeh, {Cheng Ting} and {De Leon}, Natalia",

note = "Funding Information: We gratefully acknowledge support from: USDA Hatch program funds to mul‑ tiple PIs in this project; the USDA Agricultural Research Service; the Arkansas Corn and Grain Sorghum Board; the Clemson University, the Colorado Corn Administrative Committee; the Georgia Agricultural Commodity Commission for Corn; the Corn Marketing Program of Michigan; the Illinois Corn Marketing Board; the Iowa Corn Promotion Board; the Iowa State University Plant Sci‑ ences Institute; the Kansas Corn Commission; the Minnesota Corn Research and Promotion Council; National Corn Growers Association; Nebraska Corn Board; the Ohio Corn Marketing Program; the Ontario Ministry of Agriculture, Food, and Rural Affairs; the Texas Corn Producers Board and the Wisconsin Corn Promotion Board. We also acknowledge funding from the National Science Foundation under Grant Numbers #DBI‑0735191 and #DBI‑1265383 to support CyVerse (http://www.cyverse.org), #IOS‑1339362 to support phenotyping by JC and SPM, and USDA‑NIFA 2011‑67003‑30342 to RJW, SFG, JH, NL, SM, WX, and NDL. The funders had no role in the design and conduct of the study, data collection, and writing of the manuscript. Publisher Copyright: {\textcopyright} 2020 The Author(s).",

year = "2020",

month = feb,

day = "12",

doi = "10.1186/s13104-020-4922-8",

language = "English (US)",

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T2 - 2014-2017 field seasons: Genotype, phenotype, climatic, soil, and inbred ear image datasets

AU - McFarland, Bridget A.

AU - Alkhalifah, Naser

AU - Bohn, Martin

AU - Bubert, Jessica

AU - Buckler, Edward S.

AU - Ciampitti, Ignacio

AU - Edwards, Jode

AU - Ertl, David

AU - Gage, Joseph L.

AU - Falcon, Celeste M.

AU - Flint-Garcia, Sherry

AU - Gore, Michael A.

AU - Graham, Christopher

AU - Hirsch, Candice N.

AU - Holland, James B.

AU - Hood, Elizabeth

AU - Hooker, David

AU - Jarquin, Diego

AU - Kaeppler, Shawn M.

AU - Knoll, Joseph

AU - Kruger, Greg

AU - Lauter, Nick

AU - Lee, Elizabeth C.

AU - Lima, Dayane C.

AU - Lorenz, Aaron

AU - Lynch, Jonathan P.

AU - McKay, John

AU - Miller, Nathan D.

AU - Moose, Stephen P.

AU - Murray, Seth C.

AU - Nelson, Rebecca

AU - Poudyal, Christina

AU - Rocheford, Torbert

AU - Rodriguez, Oscar

AU - Romay, Maria Cinta

AU - Schnable, James C.

AU - Schnable, Patrick S.

AU - Scully, Brian

AU - Sekhon, Rajandeep

AU - Silverstein, Kevin

AU - Singh, Maninder

AU - Smith, Margaret

AU - Spalding, Edgar P.

AU - Springer, Nathan

AU - Thelen, Kurt

AU - Thomison, Peter

AU - Tuinstra, Mitchell

AU - Wallace, Jason

AU - Walls, Ramona

AU - Wills, David

AU - Wisser, Randall J.

AU - Xu, Wenwei

AU - Yeh, Cheng Ting

AU - De Leon, Natalia

N1 - Funding Information: We gratefully acknowledge support from: USDA Hatch program funds to mul‑ tiple PIs in this project; the USDA Agricultural Research Service; the Arkansas Corn and Grain Sorghum Board; the Clemson University, the Colorado Corn Administrative Committee; the Georgia Agricultural Commodity Commission for Corn; the Corn Marketing Program of Michigan; the Illinois Corn Marketing Board; the Iowa Corn Promotion Board; the Iowa State University Plant Sci‑ ences Institute; the Kansas Corn Commission; the Minnesota Corn Research and Promotion Council; National Corn Growers Association; Nebraska Corn Board; the Ohio Corn Marketing Program; the Ontario Ministry of Agriculture, Food, and Rural Affairs; the Texas Corn Producers Board and the Wisconsin Corn Promotion Board. We also acknowledge funding from the National Science Foundation under Grant Numbers #DBI‑0735191 and #DBI‑1265383 to support CyVerse (http://www.cyverse.org), #IOS‑1339362 to support phenotyping by JC and SPM, and USDA‑NIFA 2011‑67003‑30342 to RJW, SFG, JH, NL, SM, WX, and NDL. The funders had no role in the design and conduct of the study, data collection, and writing of the manuscript. Publisher Copyright: © 2020 The Author(s).

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Y1 - 2020/2/12

N2 - Objectives: Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F's genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014-2017. Data description: Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.

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KW - Inbred

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KW - Phenotype

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Maize genomes to fields (G2F): 2014-2017 field seasons: Genotype, phenotype, climatic, soil, and inbred ear image datasets

Abstract

Bibliographical note

Keywords

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