s additional substantiation to the wealth of earlier and recent data pointing to the high fluidity of plant genomes, which are capable to sense and respond to environmental stimuli by several mechanisms, releasing heritable de novo adaptive genetic or epigenetic variation [27,28,29,30,31,32,33,34,35,36]. Extensive analysis of the use of variance in selection experiments is given in [37,38].
This concept paper uses cotton as a case study, drawing from two different sets of experimental data. In the first set, the aim was to expose and effectively exploit this newly generated adaptive variation for breeding purposes. For this, it was necessary to control the effects of interplant competition, soil heterogeneity, and genotype-by-environment interactions on selection efficiency. The equations were used effectively to identify and select superior lines within a leading elite cotton cultivar, revealing big differences in yield and stability even within this very uniform, by conventional standards, material. In another, earlier study, the efficiency of selection using the concepts of honeycomb breeding led to the build-up of resistance to cotton soil pathogens in the comparative very short time of one selection year. Both studies demonstrate the necessity and the means for nonstop improvement of crop yield and stability mechanisms, one of which is resistance to biotic stresses, and testify to the existence of untapped plasticity in the cotton genome. This yet unexploited genome plasticity is not unique to cotton, as it has become evident in other crops, legumes and cereals alike [15,39,40,41,42]. Thus, it can be beneficially exploited to bridge the gap between potential and actual crop yield in a wide array of cases.
2. Key Attributes Underlying the Supremacy of the Two Prognostic Equations
1. The choice of the individual plant grown under ultra-wide plant spacings as unit of evaluation and selection to eliminate the confounding effects of density and competition on single-plant yields.
2. The partition of the plant crop yield potential into two components: (1) the plant yield potential, and (2) the plant stability of performance. The invention of the honeycomb selection designs permits the formulation of two parameters measuring the two components with high precision and accuracy.
3. The realization of accurate and precision whole-plant field phenotyping for crop yield potential.
4. The possibility of applying ultra-high selection pressures (1 to 0.5%, meaning less than 1% plants retained after the comparative evaluation) and the resulting attainment of high advance through selection without sacrificing accuracy of selection. Although in theory , the higher the selection pressures, the higher the expected progress through selection, in conventional breeding practice, the working selection pressures are commonly at the level of 10% or more.
5. The growing of plants in the absence of competition cancels the undesirable correlation between the CV and the mean that confounds predictions and permits the use of CV to select for stability of performance.
6. The predictive power of the two equations is further increased due to the possibility to select in the same generation plants characterized by high and stable crop yield potential, as opposed to progeny testing requiring at least two successive generations.
7. The increase of the genetic gain per annum from the average 1% genetic gain attained by conventional breeding, to a two-digit percentage.
8. The production of density-neutral cultivars possessing a number of advantages, including avoidance of reseeding in case of non-satisfactory germination and increased tolerance to drought stress through use of lower seeding rates.
9. The increase of the effectiveness of molecular breeding by enabling to rank an unlimited number of plants for crop yield potential with equal accuracy of assessment.
10. The unit of selection in honeycomb breeding is the individual plant, while the unit of analysis in molecular breeding is also the individual plant genome. This offers the possibility to succ