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Mdomestica_196_v1.0.transcript.fa Mdomestica & - rsem-calculate-expression --phred33-quals--num-threads 50 --bowtie2 Sample.trimmed.fastq Mdomestica Sample. Data analysis. The “sample maximization” experimental set-up for multiplate qPCR studies is a

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The Louisiana Dept. of Agriculture and Forestry (LDAF) conducts sweetpotato weevil [SPW, Cylas formicarius (Fabricius)] monitoring in support of the statewide SPW quarantine program. The monitoring activity primarily involves a statewide pheromone-based trapping process that generates trap data for sweetpotato beds and production fields. We conducted GIS analysis of SPW trap data, collected over three years, to assess the potential use of GIS tools in managing and interpreting the data. The LDAF has already generated shapefiles for all beds and fields in each of three years, facilitating GIS analysis. However, trap data was manually collected and statewide data was compiled and stored in spreadsheet files. Trap data was mapped to specific beds and fields in each of three years, generating layers that clearly showed fields and parishes that reported high trap counts. GIS analysis showed potential SPW “hotspots” in each year, indicating that certain beds or fields are more prone to SPW infestation than others. This information can be useful in planning SPW management strategies by growers and other stakeholders. The GIS database also provides the foundation for the development of descriptive and predictive models of SPW occurence in Louisiana. Compiling the SPW trap data into a GIS database allows the data to be distributed over the Internet, facilitating real-time access by stakeholders.

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Breeders need powerful and simply understood statistical methods when analyzing disease reaction data. However, many disease reaction experiments result in data which do not adhere to the classical analysis of variance (ANOVA) assumptions of normality, homogeneity variance and a correctly specified model. Nonparametric statistical methods which require fewer assumptions than classical ANOVA, are applied to data from several disease reaction experiments. It is concluded that nonparametric methods are easily understood, can be productively applied to plant disease experiments and many times result in improved chances for detecting differences between treatments.

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Abstract

In the article “Analysis of Shear Force Data in Broccoli Transplant Studies”, by Joyce Griffin Latimer, Reuben B. Beverly, and Bill Blum [HortScience 23(3):627, June 1988], line 8 of the second paragraph should read “…amendment), organic (20 kg Pro-Mix BX,…”, not 10 kg.

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Polynomial, monomolecular, logistic, and Gompertz growth curves were evaluated for their suitability as mathematical models for germination data. Germination of hulled or leached creosote bush [Larrea tridentata (DC.) Cov.] mericarps were used in the evaluation. The Gompertz model gave the best fit. Germination curves and germination rate curves gave similar patterns of response to results obtained by other methods, which suggests the Gompertz model may have application in germination data analysis. Hulling improved germination over leaching intact mericarps. Nine hours was the optimum leaching duration for intact mericarps.

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A computerized system capable of controlling the freezing rate and collecting, storing, and analyzing data from multiple samples to determine their freezing point using low-temperature exotherm analysis is described. Details include electrical diagrams of modifications to the multiplexer/amplifier interface to provide additional signal amplification and permit control of the freezer's compressor. Computer software is described that permits variable temperature decline rates. Data analysis consists of a program in “C” that sequentially compares each data point in a low-temperature exotherm profile. Low-temperature exotherms are identified by a user-specified minimum differential between sequential data points. Examples of exotherm output and data analysis are given.

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The main objective of this study was to investigate the impact of an outdoor environmental program, Math and Science in the Outdoor Classroom, on elementary grade students' creative and critical thinking, and attitudes toward math and science. Math and Science in the Outdoor Classroom is an on-campus nature program in Santa Fe, N.M. Students participated in half-day programs focusing on topics such as water, insects, soil, and weather. Twenty-one teachers from five schools volunteered 175 second through sixth graders to participate in the program and research study. Surveys were administered to students, teachers, and volunteers after completion of the program. Interview data was analyzed using QSR NUD*IST (Nonnumerical Unstructured Data Indexing Searching and Theory-building) computer-assisted qualitative data analysis system to examine respondents' perceptions of the program using Bloom's taxonomy as a theoretical framework. Results indicated that students not only learned math and science at the lower levels of Bloom's taxonomy, but were also thinking at the higher levels of synthesis and evaluation within the framework.

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improve irrigation practices and implement site-specific cultivation; however, no research has been published evaluating its use on natural turfgrass sports fields. Mobile devices are ideal for intense data sampling for spatial analysis, but handheld

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Traffic stresses often cause a decline in turfgrass quality. Analysis of spectral reflectance is valuable for assessing turfgrass canopy status. The objectives of this study were to determine correlations of narrow band canopy reflectance and selected reflectance indices with canopy temperature and turf quality for seashore paspalum exposed to wear and wear plus soil compaction traffic stresses, and to evaluate the effects of the first derivative of reflectance and degree of data smoothing (spectral manipulations) on such correlations. `Sea Isle 1' seashore paspalum (Paspalum vaginatum Swartz) was established on a simulated sports field during 1999 and used for this study. Compared to original reflectance, the first derivative of reflectance increased the correlation coefficient (r) of certain wavelengths with canopy temperature and turf quality under both traffic stresses. Among 217 wavelengths tested between 400 and 1100 nm, the peak correlations of the first derivative of reflectance occurred at 661 nm and 664 nm for both canopy temperature and turf quality under wear stress, respectively, while the highest correlations were found at 667 nm and 820 to 869 nm for both variables under wear plus soil compaction. Collectively, the first derivative of reflectance at 667 nm was the optimum position to determine correlation with canopy temperature (r > 0.62) and turf quality (r < -0.72) under both traffic stresses. All correlations were not sensitive to degrees of smoothing of reflectance from 400 to 1100 nm. A ratio of R936/R661 (IR/R, Infrared/red) and R693/759 (stress index) had the strongest correlations with canopy temperature for wear (r = -0.63) and wear plus soil compaction (r = 0.66), respectively; and a ratio of R693/R759 had the strongest correlation with turf quality for both wear (r = -0.89) and wear plus soil compaction (r = -0.82). The results suggested that the first derivative of reflectance could be used to estimate any single wavelength simultaneously correlated with multiple turf canopy variables such as turf quality and canopy temperature, and that the stress index (R693/R759) was also a good indicator of canopy stress status.

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a LECO TruSpec Carbon and Nitrogen Analyzer (LECO Corporation, St. Joseph, MI). Data analysis. Collected data were analyzed using SAS software (SAS/Stat procedures, Release 9.02; SAS Institute, Inc., Cary, NC). Because the variances of the four N

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