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Genomics of Wheat, the Basis of Our Daily Bread

  • Chapter
Genomics of Tropical Crop Plants

Abstract

Wheat, being an important source of calories across the Americas, Europe, North Africa and Asia, is the most widely grown food crop in the world. Wheat yields have undergone a spectacular rise over the last half century, contributing to the Green Revolution in Asia. However, productivity increases appear to have reached a plateau in recent years and many consider that new advances in genomics will be essential to delivery the rates of productivity increases necessary to prevent hunger. New molecular tools will enhance on-going wheat breeding, offering the plant breeder considerable advantages in time, cost, and response to selection. Perhaps most importantly, it is believed that genomics tools will also facilitate much more efficient utilization of new sources of genetic variation for important agronomic traits from wild species. This chapter provides an overview of the botany and conventional breeding of wheat including a summary of past successes, the current primary breeding targets, and the major constraints to achieving those goals. We then focus on genomic advances in bread wheat and durum wheat during the past decade and the implications of these advances for increasing resilience, stability and productivity in tropical, sub-tropical and semi-arid production systems across the world. This includes the use of genomics to improve the search for, and the characterization of, new beneficial genetic variation and the identification of molecular markers to facilitate the efficient manipulation of that variation in breeding programs. Finally, we provide a list of the currently available trait markers and a perspective on likely future trends and challenges in wheat molecular breeding.

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William, M., Langridge, P., Trethowan, R., Dreisigacker, S., Crouch, J. (2008). Genomics of Wheat, the Basis of Our Daily Bread. In: Moore, P.H., Ming, R. (eds) Genomics of Tropical Crop Plants. Plant Genetics and Genomics: Crops and Models, vol 1. Springer, New York, NY. https://doi.org/10.1007/978-0-387-71219-2_22

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