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.2019-03-222019-03-222019-03-07http://hdl.handle.net/2097/39458Feeding 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 planten-USThis Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).http://rightsstatements.org/vocab/InC/1.0/Image