Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction
Mark Cooper A D , Carlos D. Messina A , Dean Podlich B , L. Radu Totir B , Andrew Baumgarten B , Neil J. Hausmann B , Deanne Wright B and Geoffrey Graham CA DuPont-Pioneer, 7250 NW 62nd Avenue, PO Box 552, Johnston, IA 50131, USA.
B DuPont-Pioneer, 8305 NW 62nd Avenue, PO Box 7060, Johnston, IA 50131, USA.
C DuPont-Pioneer, 7300 NW 62nd Avenue, PO Box 1004, Johnston, IA 50131, USA.
D Corresponding author. Email: mark.cooper@pioneer.com
Crop and Pasture Science 65(4) 311-336 https://doi.org/10.1071/CP14007
Submitted: 4 January 2014 Accepted: 27 February 2014 Published: 23 April 2014
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.
Additional keywords: envirotyping, genetics, genotyping, modeling, phenotyping, physiology, prediction, selection.
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