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.

Prognostic breeding is a crop improvement methodology that utilizes prognostic equations to enable concurrent selection for plant yield potential and stability of performance. There is a necessity for plant breeders to accurately phenotype plants in the field and select effectively for high and stable crop yield in the absence of the confounding effects of competition. Prognostic breeding accomplishes this goal by evaluating plants for (i) plant yield potential and (ii) plant stability, in the same generation. The plant yield index, stability index and the plant prognostic equation are the main criteria used for the selection of the best plants and the best entries grown in honeycomb designs. The construction of honeycomb designs and analysis of experimental data in prognostic breeding necessitate the development of a computer program to ensure accurate measurement of the prognostic equations. The objective of this paper is to introduce the Prognostic Breeding Application JMP Add-In, a program for constructing honeycomb designs and analyzing data for the efficient selection of superior plants and lines. The program displays powerful controls, allowing the user to create maps of any honeycomb design and visualize the selected plants in the field. Multi-year soybean data are used to demonstrate key features and graphic views of the most important steps.