Stone, Roger C. and Hammer, Graeme L. (2004) Climate variability, climate forecasting, and improved crop design. In: 5th Princess Chulabhorn Science Congress: Evolving Genetics and Its Global Impact, 16-20 August 2004, Bangkok.
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Official URL: http://www.cri.or.th/en/ac_pc.php
Crop production in many world regions can be highly variable on a year-to-year basis. Much of the variability in crop yield can be attributed, in part, to climate variability. Research in recent years has opened the opportunity to predict, at least in probabilistic terms, a considerable amount of that variability. Integration of climate forecasting systems with crop models means that prediction of potential crop yield is also possible in many work regions. Indeed, recent research has demonstrated that forecasting on decadal or interdecadal time scales may now be possible. The interesting issue then arises as to whether there is potential for use of knowledge of climate variability and climate forecasting to the plant breeding programs. In particular, knowledge of overall environmental conditions at a location for the ensuing 10-13 years may have value in the selection of new varieties for more marginal environments. The question then arises as to whether this type of climate information would have value in provision of more defensive breeding programs. Plant breeding is about packaging gene networks into genotypes using appropriate search strategies that seek ‘best fitness’ on the gene-environment landscape. A key step forward may be to enhance breeding search strategies through environment characterisation and assessment of trait values. The value of this approach is to connect crop model and climate model with a quantitative genetics model to simulate ‘fitness’ in order to evaluate new breeding strategies. It is then possible to identify the relative frequency of environment types using simulation studies for the entire period of climatological record (e.g. 100 years). Changes in the frequencies of environmental types effect overall yield likelihood and cause G*E.(genotype by environment). This is important in weighting the representativeness of the selection environments. Thus, the importance of a weighted selection becomes apparent as this process better accommodates large GxE and improves yield more rapidly than conventional selection. Crop physiology and modelling can improve efficiency in genetic improvement of crops by characterising environments for weighted selection and in assisting with decisions on the level of investment in traits by assessing their likely value. However, this approach will be of less eventual value if the breeding programs make their selection based on ‘average climate’ for a location or in an atypical year when the selection should be based on the prevailing or likely long-term climate pattern more appropriate for that location.
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