Application of prognostic breeding in maize
Vasileios Greveniotis A C and Vasilia A. Fasoula B DA Hellenic Agricultural Organisation ‘Demeter’, Industrial and Forage Crops Institute, National Center for Quality Control Classification and Standardisation, 1st km Karditsas-Mitropolis, Karditsa 43100, Greece.
B Institute of Plant Breeding, Genetics and Genomics and Center for Applied Genetic Technologies, University of Georgia, 111 Riverbend Road, Athens, GA 30602, USA.
C Democritus University of Thrace, Department of Agricultural Development, Orestiada 68200, Greece.
D Corresponding author. Email: vfasoula@uga.edu; vfasoula@yahoo.com
Crop and Pasture Science 67(6) 605-620 https://doi.org/10.1071/CP15206
Submitted: 23 June 2015 Accepted: 23 December 2015 Published: 28 June 2016
Abstract
Innovative approaches and new efficiencies in plant breeding are required to accelerate the progress of genetic improvement through selection. One such approach is the application of prognostic breeding, which is an integrated crop-improvement methodology that enables selection of plants for high crop yield potential by evaluating its two components: plant yield potential and stability of performance. Plant yield and stability are assessed concurrently in each generation by utilising the plant prognostic equation. The genetic material used for this study was 2350 F2 plants (C0) of the commercial maize hybrid Costanza. The study presents the results of the application of prognostic breeding for 6 years in two contrasting environments (A and B), starting from C0 and ending in C5. It utilises ultra-high selection pressures (1.5% to 0.5%) to isolate superior lines with crop yield comparable to Costanza, and estimates the annual genetic gain accomplished through application of this selection strategy. Application of prognostic breeding led to the isolation of superior lines whose productivity was comparable to Costanza. The productivity gap between Costanza and the best selection was reduced from 87% (C0) to 0.5% (C5) in trial 1 (environment A), from 87% (C0) to 2% (C5) in trial 2 (environment B) and from 70% (C0) to 1% (C3) in trial 3 (environment B). Genetic gain was much higher (up to 50%) in the early cycles C0–C2 of prognostic breeding and smaller in cycles C3–C5. The best lines selected were evaluated in randomised complete block trials across both environments and 2 years. Across years, the top two lines in environments A and B averaged 87% and 91% of the Costanza yield, respectively, and they had higher prolificacy (greater number of ears per plant) than Costanza. Across all cycles, the average annual genetic gain ranged from 23% to 36% in the different trials, providing evidence that selection efficiency can be significantly maximised by using this breeding strategy.
Additional keywords: crop yield potential, moving complete block designs, moving grids, moving replicates, plant density, plant phenotyping equation, plant yield index, response to selection, sibling plants, soil heterogeneity, stability of performance, whole-plant field phenotyping.
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