The 1967 Iowa corn yield test

The results of the Iowa Corn Yield Test are published to aid Iowa farmers in selecting corn varieties adapted to their farms. This is the forty-eighth consecutive year for the Iowa Corn Yield Test since it began in 1920. A picker-sheller has been used to harvest a majority of fields since 1960 and on all fields since 1965. Individual-year yield data are presented for corn varieties entered two or more consecutive years in a district. One-, 2- and 3-year yield averages are presented in tables 1 through 6 for both high and moderate plant populations for each district. Information concerning other attributes of the entries tested also are listed in tables 1 through 6. This is the fifth year of the district arrangement shown in fig. 1 and the fifth year in which all entries are compared at both high and moderate plant populations at each location. The presentation of data for the varieties tested does not imply approval or endorsement by the authors or by the agencies sponsoring or conducting the test. The entry names listed in the tables are their brand and variety designations

Preferences of children in grades two through eight in social studies subject areas

Thesis (Ed.M.)--Boston Universit

The 1965 Iowa corn yield test

The results of the Iowa Corn Yield Test are published to aid Iowa farmers in selecting corn varieties adapted to their farms. This is the forty-sixth consecutive year for the Iowa Corn Yield Test- since its beginning in 1920 and the sixth consecutive year in which a picker-sheller has been used to harvest a majority of the test fields. Individual year yield data are presented for corn varieties entered two or more consecutive years in a district. One-, two- and three-year yield averages are presented in tables 1 to 6 for both high and normal plant populations for each district. Information concerning other attributes of the entries tested are listed in tables 1 to 6. This is the third year of the district arrangement shown in fig. 1 and the third year in which all entries are compared at both high and normal plant populations at each location. The presentation of data for the varieties tested does not imply approval or endorsement by the authors or by the agencies sponsoring or conducting the test. The entry names listed in the tables are their brand and variety designations

Choosing project risk management techniques. A theoretical framework

The pressure for increasing quality while reducing time and costs places particular emphasis on managing risk in projects. To this end, several models and techniques have been developed in literature and applied in practice, so that there is a strong need for clarifying when and how each of them should be used. At the same time, knowledge about risk management is becoming of paramount importance to effectively deal with the complexity of projects. However, communication and knowledge creation are not easy tasks, especially when dealing with uncertainty, because decision-making is often fragmented and a comprehensive perspective on the goals, opportunities, and threats of a project is missing. With the purpose of providing guidelines for the selection of risk techniques taking into account the most relevant aspects characterising the managerial and operational scenario of a project, a theoretical framework to classify these techniques is proposed. Based on a literature review of the criteria to categorise risk techniques, three dimensions are defined: the phase of the risk management process, the phase of the project life cycle, and the corporate maturity towards risk. The taxonomy is then applied to a wide selection of risk techniques according to their documented applications. This work helps to integrate the risk management and the knowledge management processes. Future research efforts will be directed towards refining the framework and testing it in multiple industrie

Barcode sequencing and a high-throughput assay for chronological lifespan uncover ageing-associated genes in fission yeast

Ageing-related processes are largely conserved, with simple organisms remaining the main platform to discover and dissect new ageing-associated genes. Yeasts provide potent model systems to study cellular ageing owing their amenability to systematic functional assays under controlled conditions. Even with yeast cells, however, ageing assays can be laborious and resource-intensive. Here we present improved experimental and computational methods to study chronological lifespan in Schizosaccharomyces pombe. We decoded the barcodes for 3206 mutants of the latest gene-deletion library, enabling the parallel profiling of ~700 additional mutants compared to previous screens. We then applied a refined method of barcode sequencing (Bar-seq), addressing technical and statistical issues raised by persisting DNA in dead cells and sampling bottlenecks in aged cultures, to screen for mutants showing altered lifespan during stationary phase. This screen identified 341 long-lived mutants and 1246 short-lived mutants which point to many previously unknown ageing-associated genes, including 46 conserved but entirely uncharacterized genes. The ageing-associated genes showed coherent enrichments in processes also associated with human ageing, particularly with respect to ageing in non-proliferative brain cells. We also developed an automated colony-forming unit assay to facilitate medium- to high-throughput chronological-lifespan studies by saving time and resources compared to the traditional assay. Results from the Bar-seq screen showed good agreement with this new assay. This study provides an effective methodological platform and identifies many new ageing-associated genes as a framework for analysing cellular ageing in yeast and beyond

An integrated approach to supply chain risk analysis

Despite the increasing attention that supply chain risk management is receiving by both researchers and practitioners, companies still lack a risk culture. Moreover, risk management approaches are either too general or require pieces of information not regularly recorded by organisations. This work develops a risk identification and analysis methodology that integrates widely adopted supply chain and risk management tools. In particular, process analysis is performed by means of the standard framework provided by the Supply Chain Operations Reference Model, the risk identification and analysis tasks are accomplished by applying the Risk Breakdown Structure and the Risk Breakdown Matrix, and the effects of risk occurrence on activities are assessed by indicators that are already measured by companies in order to monitor their performances. In such a way, the framework contributes to increase companies' awareness and communication about risk, which are essential components of the management of modern supply chains. A base case has been developed by applying the proposed approach to a hypothetical manufacturing supply chain. An in-depth validation will be carried out to improve the methodology and further demonstrate its benefits and limitations. Future research will extend the framework to include the understanding of the multiple effects of risky events on different processe

Protein folding mediated by solvation: water expelling and formation of the hydrophobic core occurs after the structure collapse

The interplay between structure-search of the native structure and desolvation in protein folding has been explored using a minimalist model. These results support a folding mechanism where most of the structural formation of the protein is achieved before water is expelled from the hydrophobic core. This view integrates water expulsion effects into the funnel energy landscape theory of protein folding. Comparisons to experimental results are shown for the SH3 protein. After the folding transition, a near-native intermediate with partially solvated hydrophobic core is found. This transition is followed by a final step that cooperatively squeezes out water molecules from the partially hydrated protein core.Comment: Proceedings of the National Academy of Science, 2002, Vol.99. 685-69

Mixing and matching siderophore clusters: structure and biosynthesis of serratiochelins from Serratia sp. v4

Studying the evolutionary history underlying the remarkable structures and biological activities of natural products has been complicated by not knowing the functions they have evolved to fulfill. Siderophores - soluble, low molecular weight compounds - have an easily understood and measured function: acquiring iron from the environment. Bacteria engage in a fierce competition for acquiring iron, which rewards the production of siderophores that bind iron tightly and cannot be used or pirated by competitors. The structures and biosyntheses of 'odd' siderophores can reveal the evolutionary strategy that led to their creation. Here, we here report a new Serratia strain that produces serratiochelin and an analog of serratiochelin. A genetic approach located the serratiochelin gene cluster, and targeted mutations in several genes implicated in serratiochelin biosynthesis were generated. Bioinformatic analyses and mutagenesis results demonstrate that genes from two well known siderophore clusters, the Escherichia coli enterobactin cluster and the Vibrio cholerae vibriobactin cluster, were shuffled to produce a new siderophore biosynthetic pathway. These results highlight how modular siderophore gene clusters can be mixed and matched during evolution to generate structural diversity in siderophores.This work was supported by the National Institutes of Health (Grants GM82137 to R.K., and AI057159 and GM086258 to J.C.). M.R.S. acknowledges support from the NIH Pathway to Independence Award (Grant 1K99 GM098299-01). S.C. and M.J.V. acknowledge support from the Portuguese Foundation for Science and Technology (PhD Grant SFRH/BD/38298/2007 to S.C.; Project PTDC/EBB-EBI/104263/2008 to M.J.V.)

The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization

Although recent advances in synthetic biology allow us to produce biological designs more efficiently than ever, our ability to predict the end result of these designs is still nascent. Predictive models require large amounts of high-quality data to be parametrized and tested, which are not generally available. Here, we present the Experiment Data Depot (EDD), an online tool designed as a repository of experimental data and metadata. EDD provides a convenient way to upload a variety of data types, visualize these data, and export them in a standardized fashion for use with predictive algorithms. In this paper, we describe EDD and showcase its utility for three different use cases: storage of characterized synthetic biology parts, leveraging proteomics data to improve biofuel yield, and the use of extracellular metabolite concentrations to predict intracellular metabolic fluxes

Lessons from Two Design–Build–Test–Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning

The Design–Build–Test–Learn (DBTL) cycle, facilitated by exponentially improving capabilities in synthetic biology, is an increasingly adopted metabolic engineering framework that represents a more systematic and efficient approach to strain development than historical efforts in biofuels and biobased products. Here, we report on implementation of two DBTL cycles to optimize 1-dodecanol production from glucose using 60 engineered Escherichia coli MG1655 strains. The first DBTL cycle employed a simple strategy to learn efficiently from a relatively small number of strains (36), wherein only the choice of ribosome-binding sites and an acyl-ACP/acyl-CoA reductase were modulated in a single pathway operon including genes encoding a thioesterase (UcFatB1), an acyl-ACP/acyl-CoA reductase (Maqu_2507, Maqu_2220, or Acr1), and an acyl-CoA synthetase (FadD). Measured variables included concentrations of dodecanol and all proteins in the engineered pathway. We used the data produced in the first DBTL cycle to train several machine-learning algorithms and to suggest protein profiles for the second DBTL cycle that would increase production. These strategies resulted in a 21% increase in dodecanol titer in Cycle 2 (up to 0.83 g/L, which is more than 6-fold greater than previously reported batch values for minimal medium). Beyond specific lessons learned about optimizing dodecanol titer in E. coli, this study had findings of broader relevance across synthetic biology applications, such as the importance of sequencing checks on plasmids in production strains as well as in cloning strains, and the critical need for more accurate protein expression predictive tools