Abstract: The Green Revolution combined advancements in breeding and agricultural practice, and provided food security to millions of people. Daily food supply is still a major issue in many parts of the world and is further challenged by future climate change. Fortunately, life science research is currently making huge progress, and the development of future crop plants will be explored. Today, plant breeding typically follows one gene per trait. However, new scientific achievements have revealed that many of these traits depend on different genes and complex interactions of proteins reacting to various external stimuli. These findings open up new possibilities for breeding where variations in several genes can be combined to enhance productivity and quality. In this review we present an overview of genes determining plant architecture in barley, with a special focus on culm length. Many genes are currently known only through their mutant phenotypes, but emerging genomic sequence information will accelerate their identification. More than 1000 different short-culm barley mutants have been isolated and classified in different phenotypic groups according to culm length and additional pleiotropic characters. Some mutants have been connected to deficiencies in biosynthesis and reception of brassinosteroids and gibberellic acids. Still other mutants are unlikely to be connected to these hormones. The genes and corresponding mutations are of potential interest for development of stiff-straw crop plants tolerant to lodging, which occurs in extreme weather conditions with strong winds and heavy precipitation.

Abstract: Recent studies assessing plausible futures for agricultural markets and global food security have had contradictory outcomes. To advance our understanding of the sources of the differences, 10 global economic models that produce long-term scenarios were asked to compare a reference scenario with alternate socioeconomic, climate change, and bioenergy scenarios using a common set of key drivers. Several key conclusions emerge from this exercise: First, for a comparison of scenario results to be meaningful, a careful analysis of the interpretation of the relevant model variables is essential. For instance, the use of real world commodity prices differs widely across models, and comparing the prices without accounting for their different meanings can lead to misleading results. Second, results suggest that, once some key assumptions are harmonized, the variability in general trends across models declines but remains important. For example, given the common assumptions of the reference scenario, models show average annual rates of changes of real global producer prices for agricultural products on average ranging between -0.4% and +0.7% between the 2005 base year and 2050. This compares to an average decline of real agricultural prices of 4% p.a. between the 1960s and the 2000s. Several other common trends are shown, for example, relating to key global growth areas for agricultural production and consumption. Third, differences in basic model parameters such as income and price elasticities, sometimes hidden in the way market behavior is modeled, result in significant differences in the details. Fourth, the analysis shows that agro-economic modelers aiming to inform the agricultural and development policy debate require better data and analysis on both economic behavior and biophysical drivers. More interdisciplinary modeling efforts are required to cross-fertilize analyses at different scales.