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23 April 2014 Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction
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Abstract

For the foreseeable future, plant breeding methodology will continue to unfold as a practical application of the scaling of quantitative biology. These efforts to increase the effective scale of breeding programs will focus on the immediate and long-term needs of society. The foundations of the quantitative dimension will be integration of quantitative genetics, statistics, gene-to-phenotype knowledge of traits embedded within crop growth and development models. The integration will be enabled by advances in quantitative genetics methodology and computer simulation. The foundations of the biology dimension will be integrated experimental and functional gene-to-phenotype modelling approaches that advance our understanding of functional germplasm diversity, and gene-to-phenotype trait relationships for the native and transgenic variation utilised in agricultural crops. The trait genetic knowledge created will span scales of biology, extending from molecular genetics to multi-trait phenotypes embedded within evolving genotype–environment systems. The outcomes sought and successes achieved by plant breeding will be measured in terms of sustainable improvements in agricultural production of food, feed, fibre, biofuels and other desirable plant products that meet the needs of society. In this review, examples will be drawn primarily from our experience gained through commercial maize breeding. Implications for other crops, in both the private and public sectors, will be discussed.

© CSIRO 2014
Mark Cooper, Carlos D. Messina, Dean Podlich, L. Radu Totir, Andrew Baumgarten, Neil J. Hausmann, Deanne Wright, and Geoffrey Graham "Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction," Crop and Pasture Science 65(4), 311-336, (23 April 2014). https://doi.org/10.1071/CP14007
Received: 4 January 2014; Accepted: 1 February 2014; Published: 23 April 2014
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