Barley malting quality and yield interrelationships and the effect on yield distribution of selection for malting quality in the early generations
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Relationships between malting quality attributes and grain yield in segregating populations can profoundly influence the intensity and sequence of trait selection. Consequently, the interrelationships between malting quality parameters predicted by near infrared transmittance (NIT) spectroscopy, grain weight, and grain yield in unselected populations of F2, F3, and F4 breeding lines from 4 barley crosses were examined. The simple and partial correlations between malt extract, protein content, and diastatic power were similar to those reported in previous studies except for a positive correlation between malt extract and diastatic power in the F2 and F3 generations. This positive relationship should enhance selection for improved malting quality in breeding programs. There were no relationships between grain yield and malting quality attributes, which would have an adverse impact on the intensity and sequence of trait selection. The effect of F2 and F3 selection for malting quality on F3 and F4 yield distributions was estimated by comparing the F3 and F4 yield distributions of the entire unselected population with those for the selected populations. Individual selection and sequential independent selection in the F2 and F3 generation for malting quality parameters predicted by NIT spectroscopy and grain weight in 4 crosses generally did not alter the nature of the subsequent yield distributions, yet 78–90% of lines could be discarded and there still existed adequate genetic gain for grain yield in the retained population of potentially good malting quality lines. These results indicate that barley breeders could use NIT spectroscopy to efficiently select in the early generations for malting quality prior to the conduct of yield testing and obtain good genetic gain for both malting quality and grain yield.Keywords:
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For a long time, ecologists have worked on gaining insight into the processes that govern the assembly of natural plant communities. Plant trait-based approaches have great potential to improve our understanding of community assembly and assessment of ecosystem services. In many trait-based studies, trait-for-species substitutions are used by assigning mean trait values to each species in a community, which means that only between-species trait variability (i.e. interspecific trait variability) is considered. As there is growing evidence of the importance of within-species trait variability (i.e. intraspecific trait variability), this work is dedicated to studying how the applicability of these trait-based approaches is constrained by intraspecific variability and scale dependence. It could be shown that both interspecific trait variability and intraspecific trait variability indeed determine the trait patterns among habitats, communities and species. As a consequence, neglecting either type of trait variability by relying on species potential trait values derived from a much larger scale than the processes studied can lead to misleading conclusions, also on the community level. The benefits of using species mean trait values derived from large databases for a trait-based study will strongly depend on the level and scale of the question. In summary, there is a need to clearly differentiate between realized and potential traits on all levels in trait-based studies.
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The aim of this study was to predict the trait and economic responses achievable for four economically important traits in the Ashanti Black pig (ABP) in Ghana using three different selection strategies. The objective traits modelled in this genetic improvement program were number of pigs weaned per sow per year (NW), back fat thickness (BFT), live weight at slaughter (SWT) and muscle depth (MD). All the traits modelled had favourable economic values with NW being the most important traits among the four. Generally, the genetic and economic returns from the multiple trait index selection (MTIS) and desired gains approach (DGA) were higher than those of the single trait selection strategy except for sole selection for NW (Ghana Cedis (GHS) 156.00). The economic returns for scenarios under MTIS and DGA were between 42 to 93% of the return from sole selection for NW. Single trait selection of MD, BFT and SWT gave the least economic responses. The three strategies modelled gave similar accuracy of selection ranging from 0.4834 to 0.6649 with scenarios under single trait selection giving relatively higher accuracies. The potential contribution of genetic improvement of ABP to the pig industry in Ghana is between GHS 1 060 000.00 and GHS 6 126 000.00. With clearly defined breeding objectives coupled with appropriate selection strategies, the value of the pig industry in Ghana could be improved with the ABP. Keywords: Desired gains approach, Multiple trait index selection, Single trait selection, traits
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Many morphological, behavioral, physiological, and life-history traits covary across the biological scales of individuals, populations, and species. However, the processes that cause traits to covary also change over these scales, challenging our ability to use patterns of trait covariance to infer process. Trait relationships are also widely assumed to have generic functional relationships with similar evolutionary potentials, and even though many different trait relationships are now identified, there is little appreciation that these may influence trait covariation and evolution in unique ways. We use a trait-performance-fitness framework to classify and organize trait relationships into three general classes, address which ones more likely generate trait covariation among individuals in a population, and review how selection shapes phenotypic covariation. We generate predictions about how trait covariance changes within and among populations as a result of trait relationships and in response to selection and consider how these can be tested with comparative data. Careful comparisons of covariation patterns can narrow the set of hypothesized processes that cause trait covariation when the form of the trait relationship and how it responds to selection yield clear predictions about patterns of trait covariation. We discuss the opportunities and limitations of comparative approaches to evaluate hypotheses about the evolutionary causes and consequences of trait covariation and highlight the importance of evaluating patterns within populations replicated in the same and in different selective environments. Explicit hypotheses about trait relationships are key to generating effective predictions about phenotype and its evolution using covariance data.
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Reactions of aryl diazonium salts with formaldoxime and acetaldoxime at room temperature gave p-acetylbenzaldehyde (1a) (Yield 25%), p-acetaminobenzaldehyde (1b) (Yield 50%), p-Bromoacetophenone (1c) (Yield 60%), p-nitroacetophenone (1d) (Yield 64%), o-chlorobenzonitrile (2a) (Yield 50～57%) and 2, 4-dinitrobenzonitrile (2b) (Yield 54～64%).Reaction of p-acetaminobenzaldehyde (1b) with aminothiourea gave (TB I) (4). Yield 90%, m. p. 223～224℃.
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Loss of traits can dramatically alter the fate of species. Evidence is rapidly accumulating that the prevalence of trait loss is grossly underestimated. New findings demonstrate that traits can be lost without affecting the external phenotype, provided the lost function is compensated for by species interactions. This is important because trait loss can tighten the ecological relationship between partners, affecting the mainte- nance of species interactions. Here, we develop a new perspective on so-called 'compensated trait loss' and how this type of trait loss may affect the evolutionary dynamics between interacting organisms. We argue that: (1) the frequency of compensated trait loss is currently underestimated because it can go unnoticed as long as ecological interactions are maintained; (2) by analysing known cases of trait loss, specific factors promoting compensated trait loss can be identified and (3) genomic sequencing is a key way forwards in detecting compensated trait loss. We present a comprehensive literature survey showing that compensated trait loss is taxonomically widespread, can involve essential traits, and often occurs as replicated evolution- ary events. Despite its hidden nature, compensated trait loss is important in directing evolutionary dynamics of ecological relationships and has the potential to change facultative ecological interactions into obligatory ones.
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An expanding trend for genetically engineered (GE) crops is to cultivate varieties in which two or more single trait products have been combined using conventional breeding to produce a stacked trait product that provides a useful grouping of traits. Here, we report results from compositional analysis of several GE stacked trait products from maize and soybean. The results demonstrate that these products are each compositionally equivalent to a relevant non-GE comparator variety, except for predictable shifts in the fatty acid profile in the case of stacked trait products that contain a trait, MON 87705, that confers a high-oleic-acid phenotype in soybean. In each case, the conclusion on compositional equivalence for the stacked trait product reflects the conclusions obtained for the single trait products. These results provide strong support for conducting a reassessment of those regulatory guidelines that mandate explicit characterization of stacked trait products produced through conventional breeding.
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People differ from each other in their typical patterns of behavior, thought, and emotion and these patterns are considered to constitute their personalities (Funder, 2001). For various reasons, for example because certain trait levels may help to attain certain goals or fulfill certain social roles, people may experience that their actual trait levels are different from their ideal trait levels. In this study, we investigated (1) the impact of age on discrepancies between actual and ideal Big Five personality trait levels and (2) the impact of these discrepancies on personality trait changes across a period of two years. We use data of a large, nationally representative, and age-diverse sample (N = 4,057, 17-94 years, M = 53 years). Results largely confirmed previously reported age effects on actual personality trait levels but were sometimes more complex. Ideal trait levels exceeded actual trait levels more strongly for younger compared to older adults. Unexpectedly, neither ideal trait levels nor their interaction with beliefs about the extent to which personality is malleable vs. fixed predicted trait change over two years (controlling for actual trait levels). We conclude that ideal-actual trait level discrepancies may provide an impetus for change but that they appear to neither alone nor in combination with the belief that personality trait change is possible suffice to produce such change. We discuss commitment, self-efficacy, and strategy knowledge as potential additional predictors of trait change.
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Personality psychology
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The purpose of this introductory chapter is to introduce the Trait Emotional Intelligence (trait EI) construct selected as the foundation of this book, to examine the role that trait EI has in leadership and education, and to provide a history of the trait EI construct. In addition, this chapter discusses the principal arguments in the scholarly literature that reinforce the importance of the trait EI construct by examining the reliability and validity of trait EI, discussing the benefits of trait EI, and presenting the paradigms of those scholars who believe that that individuals can enhance their current trait EI skills and techniques through training. Finally, this chapter will also discuss the principal contentions in the scholarly literature that oppose the trait EI construct by examining the unreliability and invalidity of trait EI, discussing the disadvantages of trait EI, and presenting arguments that individuals cannot enhance their current trait EI skills and techniques through training.
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Abstract Trait-based ecology is greatly informed by large datasets for the analyses of inter- and intraspecific trait variation (ITV) in plants. This is especially true in trait-based agricultural research where crop ITV is high, yet crop trait data remains limited. Based on farmer-led collections, we developed and evaluated the first citizen science plant trait initiative. Here we generated a dataset of eight leaf traits for a commercially important crop species ( Daucus carota ), sampled from two distinct regions in Canada, which is 25-fold larger than datasets available in existing trait databases. Citizen-collected trait data supported analyses addressing theoretical and applied questions related to (i) intraspecific trait dimensionality, (ii) the extent and drivers of ITV, and (iii) the sampling intensity needed to derive accurate trait values. Citizen science is a viable means to enhance functional trait data coverage across terrestrial ecosystems, and in doing so, can directly support theoretical and applied trait-based analyses of plants.
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Citizen Science
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