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Screening Experiments (screening + experiment)
Selected AbstractsEfficacy of Beauveria bassiana (Bals.) Vuill. against the tarnished plant bug, Lygus lineolaris L., in strawberriesJOURNAL OF APPLIED ENTOMOLOGY, Issue 2 2008R. Sabbahi Abstract Beauveria bassiana has a high insecticidal potential to control the tarnished plant bug, Lygus lineolaris, a significant pest of strawberries. Screening experiments showed that L. lineolaris adults were susceptible to several B. bassiana isolates. Another screening test with Coleomegilla maculata, a natural enemy found in strawberries, was also performed in order to select the isolate having lower entomopathogenic impact on this insect. Based on data obtained from both insect species and on the ecozone origin of the B. bassiana isolates, INRS-IP and INRS-CFL isolates were selected for further experiments. The LC50 values of these two isolates against L. lineolaris adults were 7.8 × 105 and 5.3 × 105 conidia/ml, and average survival time (AST) values were 4.46 and 4.37 days at a concentration of 1 × 108 conidia/ml respectively. Results also indicated that L. lineolaris nymphs are susceptible to the selected isolates. During field experiments, using a randomized block design with four replicates, INRS-IP and INRS-CFL isolates were applied at two rates (1 × 1011 and 1 × 1013 conidia/ha) weekly during a period of 4 weeks. These multiple applications triggered a significant reduction of L. lineolaris nymphal populations in strawberries. Twenty-four days after the first application, a significant difference was observed between the mean population densities of surviving nymphs in all B. bassiana -treated plots (less than one insect per five plants) compared with those in control plots (four insects per five plants). During the field experiment, persistence of insecticidal activity and viability of B. bassiana conidia were also monitored. The results showed the presence of viable and infective conidia up to 6 days after each application on strawberry foliage. Moreover, the multiple applications of B. bassiana at the rate of 1 × 1013 conidia/ha triggered a significant reduction in strawberry fruit injuries induced by L. lineolaris feeding behaviour compared with the control plots. [source] Partial confounding and projective properties of Plackett,Burman designsQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 7 2007Murat Kulahci Abstract Screening experiments are typically used when attempting to identify a few active factors in a larger pool of potentially significant factors. In general, two-level regular factorial designs are used, but Plackett,Burman (PB) designs provide a useful alternative. Although PB designs are run-efficient, they confound the main effects with fractions of strings of two-factor interactions, making the analysis difficult. However, recent discoveries regarding the projective properties of PB designs suggest that if only a few factors are active, the original design can be reduced to a full factorial, with additional trials frequently forming attractive patterns. In this paper, we show that there is a close relationship between the partial confounding in certain PB designs and their projective properties. With the aid of examples, we demonstrate how this relationship may help experimenters better appreciate the use of PB designs. Copyright © 2006 John Wiley & Sons, Ltd. [source] Forty-nine new host plant species for Bemisia tabaci (Hemiptera: Aleyrodidae)ENTOMOLOGICAL SCIENCE, Issue 4 2008Alvin M. SIMMONS Abstract The sweetpotato whitefly, Bemisia tabaci (Gennadius), is a worldwide pest of numerous agricultural and ornamental crops. In addition to directly feeding on plants, it also acts as a vector of plant viruses of cultivated and uncultivated host plant species. Moreover, host plants can affect the population dynamics of whiteflies. An open-choice screening experiment was conducted with B-biotype B. tabaci on a diverse collection of crops, weeds, and other indigenous plant species. Five of the plant species were further evaluated in choice or no-choice tests in the laboratory. The results reveal 49 new reproductive host plant species for B. tabaci. This includes 11 new genera of host plants (Arenaria, Avena, Carduus, Dichondra, Glechoma, Gnaphalium, Molugo, Panicum, Parthenocissus, Trianthema, and Triticum) for this whitefly. All species that served as hosts were acceptable for feeding, oviposition, and development to the adult stage by B. tabaci. The new hosts include three cultivated crops [oats (Avena sativa L.), proso millet (Panicum miliaceum L.), and winter wheat (Triticum aestivum L.)], weeds and other wild species, including 32 Ipomoea species, which are relatives of sweetpotato [I. batatas (L.) Lam.)]. Yellow nutsedge, Cyperus esculentus L., did not serve as a host for B. tabaci in either open-choice or no-choice tests. The results presented herein have implications for whitefly ecology and the numerous viruses that B. tabaci spreads to and among cultivated plants. [source] A novel approach for screening discrete variations in organic synthesisJOURNAL OF CHEMOMETRICS, Issue 5 2001Rolf Carlson Abstract In this paper we present a general strategy for screening discrete variations in organic synthesis. The strategy is based upon principal properties, i.e. principal component characterization of the constituents defining the reaction system. The first step is to select subsets of test items from each class of constituents defining the reaction space, i.e. substrates, reagents, solvents, catalysts, etc., so that the selected items from each class cover the properties considered. The second step is to construct a candidate matrix which contains all possible combinations of the items in the subsets. This matrix is a full multilevel factorial design. The third step is to assign a tentative model for the screening experiment and to construct the corresponding candidate model matrix. The fourth step is to select experiments to yield an experimental design that spans the variable space efficiently and that also gives good estimates of the model parameters. We present an algorithm that uses singular value decomposition to select experiments. The proposed strategy is then illustrated with an example of the Fischer indole synthesis. Copyright © 2001 John Wiley & Sons, Ltd. [source] Use of software to facilitate pharmaceutical formulation,experiences from a tablet formulationJOURNAL OF CHEMOMETRICS, Issue 3-4 2004Nils-Olof Lindberg Abstract This paper exemplifies the benefits of using experimental design together with software to facilitate the formulation of a tablet for specific purposes, from screening to robustness testing. By applying a multivariate design for the screening experiments, many excipients were evaluated in comparatively few experiments. The formulation work was generally based on designed experiments. Most of the experiments were fractional or full factorial designs, generated and evaluated in Modde with the centre point replicated. The robustness of the formulation was evaluated with experimental designs on two different occasions. Tested flavours were found to have limited influence on the important responses, which was key information in order to proceed with that particular composition. The formulation was also robust towards normal batch-to-batch variation of the excipients and the active pharmaceutical ingredient. A process step was investigated and, by applying experimental design and keeping in mind previous findings, important information could be gained from the study. The different studies yielded good and very useful models. Established relationships between design factors and responses provided information that was vital for the project. In cases of poor models, essential information regarding robustness was obtained. Copyright © 2004 John Wiley & Sons, Ltd. [source] Framework for the Rapid Optimization of Soluble Protein Expression in Escherichia coli Combining Microscale Experiments and Statistical Experimental DesignBIOTECHNOLOGY PROGRESS, Issue 4 2007R. S. Islam A major bottleneck in drug discovery is the production of soluble human recombinant protein in sufficient quantities for analysis. This problem is compounded by the complex relationship between protein yield and the large number of variables which affect it. Here, we describe a generic framework for the rapid identification and optimization of factors affecting soluble protein yield in microwell plate fermentations as a prelude to the predictive and reliable scaleup of optimized culture conditions. Recombinant expression of firefly luciferase in Escherichia coli was used as a model system. Two rounds of statistical design of experiments (DoE) were employed to first screen (D-optimal design) and then optimize (central composite face design) the yield of soluble protein. Biological variables from the initial screening experiments included medium type and growth and induction conditions. To provide insight into the impact of the engineering environment on cell growth and expression, plate geometry, shaking speed, and liquid fill volume were included as factors since these strongly influence oxygen transfer into the wells. Compared to standard reference conditions, both the screening and optimization designs gave up to 3-fold increases in the soluble protein yield, i.e., a 9-fold increase overall. In general the highest protein yields were obtained when cells were induced at a relatively low biomass concentration and then allowed to grow slowly up to a high final biomass concentration, >8 g·L,1. Consideration and analysis of the model results showed 6 of the original 10 variables to be important at the screening stage and 3 after optimization. The latter included the microwell plate shaking speeds pre- and postinduction, indicating the importance of oxygen transfer into the microwells and identifying this as a critical parameter for subsequent scale translation studies. The optimization process, also known as response surface methodology (RSM), predicted there to be a distinct optimum set of conditions for protein expression which could be verified experimentally. This work provides a generic approach to protein expression optimization in which both biological and engineering variables are investigated from the initial screening stage. The application of DoE reduces the total number of experiments needed to be performed, while experimentation at the microwell scale increases experimental throughput and reduces cost. [source] | ||||||||||