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The ability of agriculture to adapt to environmental changes and to address main issues of food quality and environment protection is a fundamental factor in achieving sustainability. Low yield capacity of contemporary sustainable farming systems, however, is a major obstacle to future growth of sustainable agriculture. In addition, increasing pressure is placed for higher food supply due to the projected population increase. To overcome these barriers and stimulate the wide adoption of sustainable agriculture, ample supply of cultivars that satisfy the requirements for sustainability without compromising productivity is essential. Otherwise, the viability of sustainable agriculture is unsound. Moreover, plant breeding has to be a non-stop process supporting agriculture because of the ongoing climate changes. The studies of the effects of competition on crop yield and selection efficiency unravelled important findings for plant breeders. Firstly, the uppermost cultivar type is the mono-genotypic and particularly the highest evolutionary grade of 'pure line'. Secondly, single plant selection is effective only when it is realized in the absence of competition for growth resources. Honeycomb methodology, by considering as a major principle the application of selection in the absence of competition, counteracts the disturbing effects of competition on selection effectiveness. Furthermore, the honeycomb experimental designs cope with the confounding implications of soil heterogeneity. These two findings help breeders to consider the individual plant as an evaluating and selection unit. As a consequence, the development of pure line cultivars that fully meet the needs of a sustainable agriculture is possible. Most importantly, honeycomb breeding exploits effectively not only favourable but marginal environments as well through the development of density-neutral cultivars. Marginal environments are exploited optimally when lower plant populations are used. It is of essence to realize that without the ability of exploiting successfully marginal environments which represent the majority of the production environments globally, sustainability in agriculture becomes problematic.

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Switchgrass (Panicum virgatum L.) is a main herbaceous species projected for use as feedstock in biofuel production. Understanding the nature of genetic variation for biomass yield and other important traits in switchgrass would aid cultivar development. The aim of this study was to estimate the genetic component of variation and narrow‐sense heritability for biomass yield and several morphological and phenological traits in lowland switchgrass. Thirty‐seven half‐sib families were evaluated during 2007–2009 at two south central Oklahoma locations, Ardmore and Burneyville. Half‐sib families were different for biomass yields and other traits, suggesting the presence of additive gene action in controlling these traits. Family × location effects were observed for biomass yield and days to spring regrowth. Stem thickness, plant spread, and spring regrowth showed family × year interaction effects. Days to flowering showed a significant family × location × year interaction. Narrow‐sense heritability for biomass yield was 0.13 based on half‐sib family variation and 0.29 based on parent–progeny regression, suggesting a complex genetics of biomass yield. Stem thickness also had low (≤0.27) and plant height and tillering ability had low to moderate (0.26–0.48) heritability. Heritabilities were moderate (0.47–0.70) for heading, flowering, and plant spread and relatively high (≥0.82) for spring regrowth. The biomass yield was positively correlated with tillering ability, plant height, and stem thickness. Rigorous family evaluation procedure and use of tillering ability as an indirect measure to improve biomass yield could enhanced gain from selection.

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In soybean [Glycine max (L.) Merr.], there is limited and inconsistent information on the confirmation of previously reported QTL. The objectives of this study were to: (i) confirm previously reported QTL for seed protein, seed oil, and seed weight in an independent population of PI97100 × ‘Coker 237’ with the same RFLP markers and (ii) verify previously reported QTL in an independent population of ‘Young’ × PI416937 for the same seed traits using SSR markers mapped in the same region as the original RFLP markers. Each population consisted of 176 F2:4 lines and was grown in randomized complete block trials in two or three different environments. Single‐factor analysis of variance was used to verify the QTL that had significant (P ≤ 0.01) associations. In the PI97100 × Coker 237 population, two (cqProt‐001 and cqProt‐002) of four previously described QTL for seed protein, two (cqOil‐001 and cqOil‐002) of three QTL for oil content, and none of three QTL for seed weight were confirmed in the independent population. In the Young × PI416937 population, none of the three previously reported QTL for protein was confirmed. One (cqOil‐003) of three QTL for oil content and two (cqSd wt‐001 and cqSd wt‐002) of three QTL for seed weight were verified. The unconfirmed QTL may have been false positive or they may have been specific for the sample of lines used in the original populations. These results confirm the necessity of validating QTL in parallel populations before utilizing them in a plant improvement program.