Phenotyping and other breeding approaches for a New Green Revolution

Food security is a global concern in view of the ongoing global (social and climate) change. The challenges to food security from global change, sharply increasing food and feed demands, whereas increasing the frequency and severity of stresses, coupled with degradation and scarcity of natural resources, are indeed urgent and real (Prasanna et al. 2013). Crop production must double by 2050 to meet future production demands (Tilman et al. 2011). The ability to achieve this increase represents a significant challenge to plant breeders. Crop yields must increase at a rate of 2.4% per year, yet the average rate of increase is only 1.3%with yields stagnating in up to 40% of land under cereal production (Ray et al. 2012, 2013). Therefore, crops with higher yield potential and more resistant to abiotic stress conditions are needed to address such challenges. This will be only achievable by speeding up the rate of breeding gains (Hawkesford et al. 2013). Constraints in phenotyping capability currently limit our ability to dissect the genetics of quantitative traits, especially for those complex traits related to yield and stress tolerance. Development of effective field‐based high‐throughput phenotyping remains a bottleneck for future breeding advances. While laboratory analyses of key plant parts may complement direct phenotyping in the field, such traits do not always translate well to field conditions (Araus and Cairns 2014). More efficient crop phenotyping will be pivotal in the future to hasten the breeding pipeline and to take full advantage of the revolution in molecular techniques and bioinformatics (Araus and Cairns 2014). Crop phenotyping is a research area in rapid expansion, in which a wide variety of approaches is being explored, from high‐throughput field phenotyping to the evaluation at the cellular level in vitro (Masuka et al. 2012; Prasanna et al. 2013). Increasing emphasis is being given to the high‐throughput field phenotyping, which is most often focused on predicting agronomic and physiological performance. Whereas such phenotyping is usually performed at the canopy level (Lobos et al. 2014), it may be also successfully implementedmeasuring individual organs like leaves (Garriga et al. 2014). High‐ throughput phenotyping implies usually an empirical approach, allowing breeders to use genome profile or phenotype without necessarily understanding the underlying biology (Cabrera‐Bosquet et al. 2012). However, there are particular targets that still require more specialized phenotyping. This is the case, for example, for the roots, which are responsible for water and nutrient uptake (Carvalho et al. 2014), or the green inflorescences that may also contribute as photosynthetic organs to final yield (Sanchez‐Bragado et al. 2014). Selecting for more efficient organs may be pivotal, particularly when breeding for a higher performance under abiotic stress conditions. A more efficient phenotyping will be achieved not only through the deployment of more precise, faster and throughput methods but also through a better definition of the target traits for phenotyping. A classical approach in the research for traits increasing yield potential and adaptation to stress are the retrospective studies, where varieties developed at different ages are cultivated together under common growing conditions (Zhou et al. 2014). Improved phenotyping techniques will not only help to provide further success of conventional breeding for complex quantitative traits but also to the full implementation of molecular breeding, including mapping and other forward‐ genetics approaches, as well as transgenic breeding (Gao et al. 2014) and other reverse‐genetics methods such as tilling (Chen et al. 2014). The present special issue of JIPB derives from the “EU Workshop on Phenotypic Profiling and Technology Transfer on Crop Breeding” hosted at the University of Barcelona during September 2012, in the context of the EU‐project OPTICHINA (Optimizing Chinese Agriculture). This issue represents a continuation from previous special issues of JIPB published in the context of the OPTICHINA project (Parry et al. 2012).