Relation Between S2 and Later Generation Testcrosses of Two Corn Populations

Determination of the relative combining abilities of corn (Zea mays L.) inbred lines is an important feature of applied corn breeding programs. Combining ability is measured by the relative performance of a line in testcrosses to one or more testers. Inbred lines from BS13(S2)Cl and BSCB1(R)C7 corn populations were evaluated at the S2 and later generations of inbreeding. Intense selection was practiced among and within lines during inbreeding to develop the S5-equivalent and S8 generation lines. The objective of this study was to determine if the combining ability of lines in early generations (S2) of inbreeding was similar to the combining ability of lines at later generations of inbreeding. Testcross trials were conducted at four Iowa locations. Genetic correlations between the S2 and later generation testcrosses for gram yield were 0.9.7 for BS13(S)Cl and 0.86 for BSCB1(R)C7. The S2 testcross data were highly predictive of S8 testcross data, suggesting that early testing was effective in discriminating among these lines for relative combining abilities at later generations of inbreeding

Energy and Complexity in Evolving Collective Robot Bodies and Brains

The impact of the environment on evolving increasingly complex morphologies (bodies) and controllers (brains) remains an open question in evolutionary biology and has important implications for the evolutionary design of robots. This study uses evolutionary robotics as an experimental platform to evaluate relationships between environment complexity and evolving bodybrain complexity given energy costs on evolving complexity. We evolve robot body-brain designs for increasingly complex environments (difficult cooperative transport tasks) in a collective robotic gathering simulation. The impact of complexity costs on body-brain evolution is evaluated across such increasingly complex environments. Results indicate that complexity costs enable the evolution of simpler body-brain designs that are effective in simple environments but yield negligible behavior (task performance) differences in more complex environments

Evolving Behavior Allocations in Robot Swarms

Behavioral diversity is known to benefit problem solving in biological social systems such as insect colonies and human societies, as well as in artificial distributed systems including large-scale software and swarm-robotics systems. We investigate methods of evolving robot swarms in which individuals have heterogeneous behaviours. Two approaches are investigated to create swarm of size n. The first encodes a repertoire of n behaviours on a single individual, and hence evolves the swarm directly. The second approach uses two phases. First, a large repertoire of diverse behaviours is evolved and then another evolutionary algorithm is used to search for an optimal allocation of behaviours to the swarm. Results indicate that the two phase approach of generate then allocate produces significantly more effective collective behaviors (in terms of task accomplishment) than the direct evolution of behaviorally heterogeneous swarms

Evolving Herding Behaviour Diversity in Robot Swarms

Behavioural diversity has been demonstrated as beneficial in biological social systems, such as insect colonies and human societies, as well as artificial systems such as large-scale software and swarm-robotics systems. Evolutionary swarm robotics is a popular experimental platform for demonstrating the emergence of various social phenomena and collective behaviour, including behavioural diversity and specialization. However, from an automated design perspective, the evolutionary conditions necessary to synthesize optimal collective behaviours (swarm-robotic controllers) that function across increasingly complex environments (difficult tasks), remains unclear. Thus, we introduce a comparative study of behavioural-diversity maintenance methods (swarm-controller extension of the MAP-Elites algorithm) versus those without behavioural diversity mechanisms (Steady-State Genetic Algorithm), as a means to evolve suitable degrees of behavioural diversity over increasingly difficult collective behaviour (sheep-dog herding) tasks. In support of previous work, experiment results demonstrate that behavioural diversity can be generated without specific speciation mechanisms or geographical isolation in the task environment, although the direct evolution of a functionally (behaviorally) diverse swarm does not yield high task performance

Recurrent Selection to Alter Grain Methionine Concentration and Improve Nutritional Value of Maize

Methionine is an essential amino acid that is limiting in maize- (Zea mays L.) based diets. The objective of this work was to determine whether we could alter grain methionine concentration in random-mated maize populations by mass selection for methionine concentration using a microbial assay. In one study, we developed two populations by selecting for high or low methionine concentration (HM or LM, respectively) for three generations starting from the random-mated population BS11. Grain from these populations was used to formulate diets for a feeding trial in which 15 rats were fed HM grain and 15 rats were fed LM grain. Rats on the HM diet had a 0.018 higher feed efficiency (g gain/g feed) than rats on the LM diet. In a second study, we performed three cycles of selection for high or low methionine concentration starting with two random-mated populations, BS11 and BS31. We evaluated each cycle of selection in a field trial with two replications in each of two years. Methionine concentration was significantly correlated with the cycle of selection, changing on average 0.004 g methionine/100 g grain per cycle. Kernel mass, %N, oil, protein, starch, tryptophan, and lysine concentration did not exhibit significant correlations with cycle of selection. We conclude that recurrent selection for grain methionine concentration using a microbial assay is an effective method to alter methionine content

Quantitative analysis of Iowa stiff stalk synthetic

Stiff Stalk Synthetic is a synthetic variety that was deloped in the early 1930's by recombining 16 inbred lines that were considered to be above average for stalk quality. Because of the origin of the lines included in Stiff Stalk Synthetic, it is usually considered a Reid's Yellow Dent type. Stiff Stalk Synthetic (BSSS) has been used extensively in the cooperative federal-state corn breeding project at Ames, Iowa. BSSS has proved to be a good source of lines that have above average combining ability and stalk quality. BSSS was the source population for initiating half-sib recurrent selection in 1939 and one of the populations used for initiating reciprocal recurrent selection in 1949. Both selection programs have been continued to the present time. In addition, BSSS was included in basic research studies to determine the relative importance of different types of genetic effects and to estimate inbreeding depression for several quantitative traits. Results of these studies for BSSS were summarized and compared with data obtained from other corn populations. BSSS per se tended to yield below average, but it was above average for combining ability in crosses with other varieties. BSSS per formed as a Reid's Yellow Dent type because heterosis was greater in variety crosses with Lancaster Sure Crop types than in variety c rosses with Reid's Yellow Dent types. Regardless of the particular variety included in crosses, however, BSSS tended to make a positive contribution to the variety cross. Because nearly all variety cross trials were machine harvested with no gleaning, the above average stalk quality of BSSS may have been a contributing factor in the performance of BSSS in variety crosses. Quantitative genetic studies suggested BSSS has less genetic variability than many of the other corn varieties for yield. Whereas estimates of additive genetic variance in other corn populations were, on the average, 1.6 times greater than the variance due to dominance effects, the estimates of additive genetic variance for BSSS were similar to the variance for dominance effects. Estimates of inbreeding depression for yield, however, tended to be smaller for BSSS than for other varieties. Performance of BSSS per se, less additive genetic variance, and smaller inbreeding effects suggests that BSSS may have a higher frequency of favorable alleles than for other varieties. BSSS may be in the homozygous condition for some important loci. Gene frequencies of favorable alleles greater than 0.5 would reduce the relative proportion of the additive genetic variance to, the variance due to dominance effects and reduce the effects of inbreeding. Also, fixation of favorable alleles would affect variety performance per se and contribute to, improved combining ability. It seems the main features that distinguish BSSS from other corn varieties are better-than average stalk quality, source of lines with above average combining ability that have adaptation over wide areas, and frequencies of favorable alleles greater than 0.5. A wise choice of lines used to form BSSS and continued selection pressure for the past 40 years have developed improved strains of BSSS that have played an important role in continued genetic progress of hybrid corn.Arnel R. Hallauer, W. A. Russell, O. S. Smith, Department of Agronomy, Iowa State University, Ames, Iowa

Maize open-pollinated populations physiological improvement: validating tools for drought response participatory selection

Participatory selection—exploiting specific adaptation traits to target environments—helps to guarantees yield stability in a changing climate, in particular under low-input or organic production. The purpose of the present study was to identify reliable, low-cost, fast and easy-to-use tools to complement traditional selection for an e ective participatory improvement of maize populations for drought resistance/tolerance. The morphological and eco-physiological responses to progressive water deprivation of four maize open-pollinated populations were assessed in both controlled and field conditions. Thermography and Chl a fluorescence, validated by gas exchange indicated that the best performing populations under water-deficit conditions were ‘Fandango’ and to a less extent ‘Pigarro’ (both from participatory breeding). These populations showed high yield potential under optimal and reduced watering. Under moderate water stress, ‘Bilhó’, originating from an altitude of 800 m, is one of the most resilient populations. The experiments under chamber conditions confirmed the existence of genetic variability within ‘Pigarro’ and ‘Fandango’ for drought response relevant for future populations breeding. Based on the easiness to score and population discriminatory power, the performance index (PIABS) emerges as an integrative phenotyping tool to use as a refinement of the common participatory maize selection especially under moderate water deprivationinfo:eu-repo/semantics/publishedVersio

Capacidade combinatória entre 15 populações de milho de ciclo superprecoce no Brasil.

Suplemento. Edição dos resumos do 41º Congresso Nacional de Genética, Caxambu, MG, 1995