San Joaquin / Urbana / Mississippi River / Asheville / Madison / Washington / DC / Champaign / Sacramento / /
Company
Agronomy Journal / /
Country
Uruguay / Niger / United States / Syria / / /
Event
Environmental Issue / /
Facility
Penn State University / Cooperative Institute / College Park / Institute of Natural Resource Sustainability / National Climatic Data Center / USDA National Institute of Food / Fort Collins / /
IndustryTerm
farm site / software engineering / optimization algorithm / energy / irrigation applications / energy budget / chemicals / predictive systems / /
NaturalFeature
Arizona / Sacramento valley / California / San Joaquin valley / /
Organization
Univ. of Illinois / USDA FRIS / Agricultural Statistics Board / Earth System Science Interdisciplinary Center / American Society of Agronomy / North Carolina State Univ. / Division of Illinois State Water Survey / National Climatic Data Center / National Oceanic and Atmospheric Administration / USDA / Mississippi State Univ. / Bowling Green State Univ. / USDA National Institute of Food and Agriculture / Colorado State Univ. / Natural Resource Ecology Lab. / Institute of Natural Resource Sustainability / Cooperative Institute for Climate and Satellites / Univ. of Maryland / USDA Economic Research Service / National Agricultural Statistics Service / National Weather Service / /
Person
Virginia Unirrigated Irrigated / Wei Gao / Daniel L. Schmoldt / Kenneth Kunkel / Choi / Yt / Xin-Zhong Liang / Arthur N. Samel / Yuan / Fig / Min Xu / K. Raja Reddy / Foley / /
Position
farmer / Major / representative / MATERIALS AND METHODS Model Development Given / /
Xin-Zhong Liang,* Min Xu, Wei Gao, K. Raja Reddy, Kenneth Kunkel, Daniel L. Schmoldt, and Arthur N. Samel ABSTRACT Prediction of cotton (Gossypium hirsutum L.) production under a changing climate requires a coupled model