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Item Open Access Connecting Supply Chain Through Sustainability: Initiating a Multi-Disciplinary, Multi-Industry Approach Using the Case of Beef Cattle(2019-03-07) White, Bradley J.; Kwon, Junehee; LeHew, Melody; Dollarhide, Patti J.Disciplinary perspectives of supply chains are influenced by the “silo” nature of academia. For example, educators typically train students about appropriate supply chain management starting with the manufacturer of products used in their particular industry, as opposed to investigating the entire supply chain from raw material producer to finished consumer product through disposal or recycling. When educating sustainability, understanding the extent and interrelated nature of the entire supply chain is essential. Without foundational knowledge and systems thinking, students may not understand the impact of business decisions on sustainability, and motivation to make sustainable choices may be lacking. This project aims to develop a Collaborative Grant Type 2 to infuse sustainability education into a variety of baccalaureate programs (e.g., animal sciences, hospitality and textile programs) using the study of beef cattle. Beef cattle present complex issues that involve a global view of the challenge to feed, clothe and fuel 9.6 billion people by the year 2050 while conserving finite resources.Item Open Access Building Field-Based Ecophysiological Genome-to-Phenome Prediction(2019-03-07) Albin, N.; Alderman, P.; Bello, N.; Chen, C.; Duke, L.; Flippo, D.; Fondjo-Fotou, F.; Fritz, A.; Hettiarachchi, G.; Howard, C.; Jagadish, K.; Kulesza, S.; Poland, J.; Santos, E.; Snow, J.; Welch, S.; Yan, L.Feeding the estimated global population of 9 billion persons by 2050 will require a doubling of the food supply. However, the annual yield rates of gain for major grain crops is only one-quarter to one half of that which is necessary to reach this target. Remedying this deficit necessitates drastic improvements in the ability to predict crop field behavior based on its genetics and the growth environment. This is critical both for breeding programs and for efficient management in farmers’ fields after new varieties are released. This project aims to increase the capacity of Kansas and Oklahoma to conduct research on quantitative prediction methodologies using wheat as a model crop plant
