Abstract: Phytocystatins are a well-characterized class of naturally occurring protease inhibitors that function by preventing the catalysis of papain-like cysteine proteases. The action of cystatins in biotic stress resistance has been studied intensively, but relatively little is known about their functions in plant growth and defence responses to abiotic stresses, such as drought. Extreme weather events, such as drought and flooding, will have negative impacts on the yields of crop plants, particularly grain legumes. The concepts that changes in cellular protein content and composition are required for acclimation to different abiotic stresses, and that these adjustments are achieved through regulation of proteolysis, are widely accepted. However, the nature and regulation of the protein turnover machinery that underpins essential stress-induced cellular restructuring remain poorly characterized. Cysteine proteases are intrinsic to the genetic programmes that underpin plant development and senescence, but their functions in stress-induced senescence are not well defined. Transgenic plants including soybean that have been engineered to constitutively express phytocystatins show enhanced tolerance to a range of different abiotic stresses including drought, suggesting that manipulation of cysteine protease activities by altered phytocystatin expression in crop plants might be used to improve resilience and quality in the face of climate change.

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: In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES-Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of crop models, we endorse that efforts be concentrated on selecting or rebuilding a model that includes approaches that better describe the agronomic conditions of the regions in which they will be applied. The use of such complex methodologies as crop models is associated with numerous sources of uncertainty, although these models are the best tools available to get insight in these complex agronomic systems. (C) 2015 Elsevier B.V. All rights reserved.