The Future of Crop Megaenvironments as Breeder Tools

A limitation of the ME concept is its stochastic nature, whereas in reality a given location will vary temporally from year to year, and spatially within farmers' fields and locally. The combination of water and temperature defines the occurrence of biotic and abiotic stresses and the ME concept was very useful in defining germplasm that has a specific combination of traits required within a given ME.

To better target germplasm development in the future, the ME will need to be refined to address different needs of the various production systems. GIS and remote sensing are powerful tools to classify environments with biophysical parameters (Hodson and White, 2007a; Lobell and Ortiz-Monasterio, 2007; Hodson and White, Chapter 13, this volume) and to estimate probability ranges for precipitation and use soil parameters (e.g. micronutrient deficiencies or toxicities and pH) to characterize environments.

Cooper and Fox (1996) suggested using probe genotypes as an indirect approach to characterize environments. Although a limitation of this approach is the dependency on suitable contrasting genotypes, and using contrasting genotypes for different traits may lead to varying environmental characterization, Mathews et al. (2004) used pairs of two contrasting genotypes, ideally iso-lines, for 14 adaptation relevant traits and identified environment-specific factors that contribute to environmental classification.

Combining remote sensing with modelling further enhances the options to classify environments. Lobell and Ortiz-Monasterio (2005, 2006, 2007) used modelling and remote sensing to estimate grain yields and measure the effect of night and day temperature on yield. Sutherst et al. (2000) applied models to estimate the vulnerability of a given environment for pests and diseases.

It has been suggested that environments could be classified based on the methods described in the previous paragraphs, including major biotic and abiotic constraints, as well as other traits important for adaptation and adoption by farmers (W.H. Pfeiffer, Colombia, 2009, personal communication). Considering available genetic variability and heritability for each of these traits and availability of markers, the probability and success rate to find solutions through breeding interventions can be calculated. This classification will also show in which environments greatest progress to raise productivity will come from agronomic or genotype-by-management interventions in cases where there is no or insufficient genetic variability for traits of interest. An index can be developed for important production systems considering these factors, and eventually this will allow setting of priorities and allocation of resources based on where the likelihood for successful intervention is highest.

The ME concept has proved to be very successful in characterizing major wheat, rice and maize growing areas and defining germplasm pools that possess the combination of traits related to general adaptation (phenology), tolerance or resistance to the prevailing biotic and abiotic stresses and end-use quality characteristics. Since year-to-year climatic conditions are projected to become more variable due to climate change (IPPC, 2007), widely adapted cultivars will be crucial to buffer unpredictable climate stresses such as drought, heat and cold, while being input responsive in years with agroecological conditions that are favourable to crop productivity. To identify such culti-vars, multi-location testing remains the most efficient system since it allows substitution of temporal with spatial variation. MEs are defined across continents (Fig. 7.1), and therefore regional and annual fluctuations in occurrence of abiotic and biotic stresses cancel each other out. In 1 year, elite lines can be evaluated in a multitude of different environments and those best buffered against the highly variable stresses will be selected for as parents in crossing programmes and as potential cultivars for further testing. International evaluation networks based on exchange of and free access to germplasm and multi-location testing are therefore a cornerstone in the strategies and efforts to develop wheat, rice and maize germplasm that is adapted to the increasingly variable growing conditions encountered due to global climate change.

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