r predicting for the first time the possibility to develop monogenotypic cultivars that are density-neutral (i.e., capable to attain maximal yields under a wide range of planting densities), while simultaneously possessing high yields per hectare under standard crop stands. The existence of density-neutral cultivars, further verified in maize , a crop whose hybrid performance is known to be highly density-dependent, demonstrated conclusively that density ceases to represent a component of crop yield potential, an idea that had been a widespread working assumption during the recent past (e.g., ). The same article  first presented the concept of ‘nonstop’ selection as an essential component of a comprehensive breeding procedure.
The partitioning of crop yield potential was incorporated in a novel software package designed to analyze data from honeycomb breeding experiments .
Through exploitation of the unique properties of the Honeycomb designs, it was subsequently possible to condense the three components of crop yield potential to two [24,25,26]. The two components are the Plant Yield Index PYI = (Figure 2; Design Code 4 exemplifies plants whose yield per plant is compared to the mean yield of the surrounding plants of the 30 remaining entries in the grey area), measuring with accuracy individual plant yield potential, and the Coefficient of Homeostasis CH = , measuring yield stability or homeostasis. The CH incorporates every factor affecting stability of performance, including heritability, heterozygosity, biotic and abiotic stresses, high planting densities, and any other source contributing to yield variability. The product of the two components measures the plant’s crop yield potential and constitutes the first of two novel equations used in the selection process.
The second equation results by replacing the parameter PYI by the Line Yield Index LYI = , where is the mean yield of the progeny line (lines 1 to 31 in this case) and the mean yield of all plants in the trial:
The concept of nonstop selection finds 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 cro