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Life Sciences

2012

Kansas State University Libraries

Articles 1 - 19 of 19

Full-Text Articles in Physical Sciences and Mathematics

Variation Analysis For Fiber Quality Traits Among Different Positionsin Eight Upland Cotton Cultivars, Yi Xu, Johnie N. Jenkins, Jack C. Mccarty, Jixiang Wu Apr 2012

Variation Analysis For Fiber Quality Traits Among Different Positionsin Eight Upland Cotton Cultivars, Yi Xu, Johnie N. Jenkins, Jack C. Mccarty, Jixiang Wu

Conference on Applied Statistics in Agriculture

Equivalencyof fiber quality within a plant of upland cotton, Gossypium hirsutum L., is very important. There are several traits within a plant that can be used to measure fiber quality and five of those traits will be investigated. Eight representative upland cultivars were grown at the Plant Science Research Farm at Mississippi State University in 1986 and five fiber traits: micronaire, fiber elongation, 2.5% and 50% span length, and fiber strength, were measured at different plant locations. The analysis of the study was modeled after a crop stability analysis with plant locations being treated as environments in the analysis. Three …

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Towards Better Fdr Procedures For Discrete Test Statistics, Xiongzhi Chen, R. W. Doerge Apr 2012

Towards Better Fdr Procedures For Discrete Test Statistics, Xiongzhi Chen, R. W. Doerge

Conference on Applied Statistics in Agriculture

The false discovery rate (FDR) has been a widely used error measure in situations where a large number of tests are conducted simultaneously. Most methods that control the FDR at a prespeci…ed level, or estimate the FDR of a multiple testing procedure (FDR procedures), were essentially developed for continuous test statistics. As such, their performances need to be carefully assessed when applied to discrete test statistics. We review some popular FDR procedures, point out a key reason for their excessive conservativeness when applied to discrete p-values, and suggest an improvement for these methods for such p-values.

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Statistical Considerations When Using Hysteresis To Estimate Internal Heat Load In Dairy Cows, S. Maynes, A. M. Parkhurst Apr 2012

Statistical Considerations When Using Hysteresis To Estimate Internal Heat Load In Dairy Cows, S. Maynes, A. M. Parkhurst

Conference on Applied Statistics in Agriculture

Water is often used to manage heat stress in dairy cattle. Sprinklers are often placed over the feed bunk or used while cattle are waiting to be milked, however in this experiment cattle were given control over water with a cow-activated shower. Previous studies have focused on how wetting can lower body emperature or reduce respiration rates. An alternative way to investigate this management practice is to examine internal heat loads. Internal heat load can be quantified by fitting a hysteresis loop to daily field data. The hysteresis loop is formed by a phase diagram of body temperature versus an …

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The Nuances Of Statistically Analyzing Next-Generation Sequencing Data, Sanvesh Srivastava, R. W. Doerge Apr 2012

The Nuances Of Statistically Analyzing Next-Generation Sequencing Data, Sanvesh Srivastava, R. W. Doerge

Conference on Applied Statistics in Agriculture

High-throughput sequencing technologies, in particular next-generation sequencing (NGS) technologies, have emerged as the preferred approach for exploring both gene function and pathway organization. Data from NGS technologies pose new computational and statistical challenges because of their massive size, limited replicate information, large number of genes (high-dimensionality), and discrete form. They are more complex than data from previous high-throughput technologies such as microarrays. In this work we focus on the statistical issues in analyzing and modeling NGS data for selecting genes suitable for further exploration and present a brief review of the relevant statistical methods. We discuss visualization methods to assess …

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Treatment Heterogeneity And Potential Outcomes In Linear Mixed Effects Models, Troy E. Richardson, Gary L. Gadbury Apr 2012

Treatment Heterogeneity And Potential Outcomes In Linear Mixed Effects Models, Troy E. Richardson, Gary L. Gadbury

Conference on Applied Statistics in Agriculture

Studies commonly focus on estimating a mean treatment effect in a population. However, in some applications the variability of treatment effects across individual units may help to characterize the overall effect of a treatment across the population. Consider a set of treatments, {T,C}, where T denotes some treatment that might be applied to an experimental unit and C denotes a control. For each of N experimental units, the duplet {rTᵢ,rCᵢ}, i = 1,2, … , N, represents the potential response of the i th experimental unit if treatment were applied and the response …

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Identifying Spectra Important For Prediction Of Senescent Grassland Canopy Structure, Rebecca Phillips, Nicanor Saliendra, Mark West Apr 2012

Identifying Spectra Important For Prediction Of Senescent Grassland Canopy Structure, Rebecca Phillips, Nicanor Saliendra, Mark West

Conference on Applied Statistics in Agriculture

Managers of the nearly 0.5 million ha of public lands in North and South Dakota, USA rely heavily on manual measurements of vegetation properties to ensure conservation of grassland structure for wildlife and forage for livestock. Spectral imaging data may be useful in assessment of large (>100,000 ha) landscapes, as in the Grand River National Grassland (GRNG), South Dakota. Here, we examined the predictive potential for the Advanced High Resolution Spectrometer (AVIRIS) to estimate mixed-grass prairie canopy structural attributes (photosynthetically active vegetation (kg PV ha-1), non-photosynthetically active vegetation (kg NPV ha-1), total standing crop (kg …

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Exploration Of Reactant-Product Lipid Pairs In Mutant-Wild Type Lipidomics Experiments, Lianqing Zheng, Gary L. Gadbury, Jyoti Shah, Ruth Welti Apr 2012

Exploration Of Reactant-Product Lipid Pairs In Mutant-Wild Type Lipidomics Experiments, Lianqing Zheng, Gary L. Gadbury, Jyoti Shah, Ruth Welti

Conference on Applied Statistics in Agriculture

High-throughput metabolite analysis is very important for biologists to identify the functions of genes. A mutation in a gene encoding an enzyme is expected to alter the level of the metabolites which serve as the enzyme’s reactant(s) (also known as substrate) and product(s). To find the function of a mutated gene, metabolite data from a wild-type organism and a mutant are compared and candidate reactants and products are identified. The screening principle is that the concentration of reactants will be higher and the concentration of products will be lower in the mutant than in wild type. This is because the …

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Variance Inflation Factors In Regression Models With Dummy Variables, Leigh Murray, Hien Nguyen, Yu-Feng Lee, Marta D. Remmenga, David W. Smith Apr 2012

Variance Inflation Factors In Regression Models With Dummy Variables, Leigh Murray, Hien Nguyen, Yu-Feng Lee, Marta D. Remmenga, David W. Smith

Conference on Applied Statistics in Agriculture

Variance Inflation Factors (VIFs) are used to detect collinearity among predictors in regression models. Textbook explanation of collinearity and diagnostics such as VIFs have focused on numeric predictors as being "co-linear" or "co-planar", with little attention paid to VIFs when a dummy variable is included in the model. This work was motivated by two regression models with high VIFs, where "standard' interpretations of causes of collinearity made no sense. The first was an alfalfa-breeding model with two numeric predictors and two dummy variables. The second was an economic model with one numeric predictor, one dummy and the numeric x dummy …

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Stability Analysis For Yield And Seed Quality Of Soybean [Glycine Max (L.) Merril] Across Different Environments In Eastern South Dakota, Kaushal Raj Chaudhary, Jixiang Wu Apr 2012

Stability Analysis For Yield And Seed Quality Of Soybean [Glycine Max (L.) Merril] Across Different Environments In Eastern South Dakota, Kaushal Raj Chaudhary, Jixiang Wu

Conference on Applied Statistics in Agriculture

Genotype-environment interaction has always been an important and challenging issue for plant breeders in developing desirable varieties. Determination of genotype and environment is common in breeding program as it helps to find out the genotypes that have wide or specific adaptability across various environmental conditions. In this study, fifteen varieties of soybean were evaluated for stability of grain yield (ton/ha), protein content (%), and oil content (%) at six different locations of Eastern South Dakota in 2011. Mixed linear model and Additive main effects and multiplicative interactions (AMMI) were applied to detect genotype-by-environment (G*E) interactions and stability of each variety …

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Gene Set Testing To Characterize Multivariately Differentially Expressed Genes, John R. Stevens, S. Clay Isom Apr 2012

Gene Set Testing To Characterize Multivariately Differentially Expressed Genes, John R. Stevens, S. Clay Isom

Conference on Applied Statistics in Agriculture

In a gene expression experiment (using oligo array, RNA-Seq, or other platform), researchers typically seek to characterize di erentially expressed genes based on common gene function or pathway involve-ment. The eld of gene set testing provides numerous characterization methods, some of which have proven to be more valid and powerful than others. These existing gene set testing methods focus on experimental designs where there is a single null hypothesis (usually involving association with a continuous or categorical phenotype) for each gene. Increasingly common experimental designs lead to multiple null hypotheses for each gene, and the characterization of these multivariately di …

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Determining The Effectivesness Of Including Spatial Information Into A Nematode/Nutsedge Pest Complex Model, Joel Vetter, Zhining Ou, Leigh Murray, Stephen H. Thomas, Jill Schroeder Apr 2012

Determining The Effectivesness Of Including Spatial Information Into A Nematode/Nutsedge Pest Complex Model, Joel Vetter, Zhining Ou, Leigh Murray, Stephen H. Thomas, Jill Schroeder

Conference on Applied Statistics in Agriculture

An experiment was performed in 2005-2006 to determine if a nematode-resistant variety of alfalfa (Medicago sativa L.) can effectively reduce the pest complex consisting of yellow and purple nutsedge (YNS, Cyperus esculentus L. and PNS, C. rotundus L.) and the southern rootknot nematode (SRKN, Meloidogyne incognita (Kofoid & White) Chitwood). The alfalfa field, which had a history of severe infestation from both species of nutsedge and SRKN, was divided into 1m x 2m quadrats. In May, July and September of each year, eighty quadrats were randomly selected and counts of PNS, YNS and a soil sample (analyzed for the count …

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Statistical Tests For Stability Analysis With Resampling Techniques, Jixiang Wu, Karl Glover, William Berzonsky Apr 2012

Statistical Tests For Stability Analysis With Resampling Techniques, Jixiang Wu, Karl Glover, William Berzonsky

Conference on Applied Statistics in Agriculture

Crop trials or crop performance trials (CPT), which are among the most important activities associated with plant breeding programs, are commonly used to measure the performance stability of genotypes. Several methods which include variation, regression, and cluster analyses for determination of crop stability have been proposed and are commonly used. However, many of these approaches require the use of normally distributed data. Thus, commonly used statistical tests, like the t- or F-test may not be appropriate when the assumptions of data are violated. In this study, two resampling techniques (jackknife and bootstrapping) were integrated into several crop stability analyses. An …

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Bayesian Mcmc Analyses For Regulatory Assessments Of Food Composition, Jay M. Harrison, Derek Culp, George G. Harrigan Apr 2012

Bayesian Mcmc Analyses For Regulatory Assessments Of Food Composition, Jay M. Harrison, Derek Culp, George G. Harrigan

Conference on Applied Statistics in Agriculture

In order to gain regulatory approval to market a new seed product derived with biotechnology, grain and forage composition data must be collected from field trials, and summaries must be reported to various government agencies. Currently, both tests of differences in composition between a genetically modified organism (GMO) and its control and tests of equivalence of the GMO to conventional genotypes are required by regulatory agencies. Bayesian analyses offer an attractive option for regulatory assessments by expressing results that can be interpreted more easily by a wide audience and by providing more ways to examine various hypotheses of interest. In …

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A Comparison Of Analytic And Bayesian Approaches For Characterizing Thermal Hysteresis In Cattle Using Algebraic And Geometric Distances, F. Yang, A. M. Parkhurst, S. Zhang, C. N. Lee, T. M. Brown-Brandl, K. G. Gebremedhin, P. E. Hillman Apr 2012

A Comparison Of Analytic And Bayesian Approaches For Characterizing Thermal Hysteresis In Cattle Using Algebraic And Geometric Distances, F. Yang, A. M. Parkhurst, S. Zhang, C. N. Lee, T. M. Brown-Brandl, K. G. Gebremedhin, P. E. Hillman

Conference on Applied Statistics in Agriculture

A high ambient temperature poses a serious threat to cattle. Above a certain threshold, an animal’s body temperature (Tb) appears to be driven by the hot cyclic air temperature (Ta) and hysteresis occurs. Elliptical hysteresis describes the output of a process in response to a simple harmonic input, and the trajectory forms a closed loop. The hysteresis loop shows a rotated elliptical pattern which depends on the lag between Tb and Ta. The objectives of this study are 1) to characterize hysteresis using bootstrapped ellipse specific nonlinear least squares 2) to reformulate models using the Bayesian method, and 3) to …

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Armedand Dangerous: The Consequences Of Not Randomizing The First Block, Edzard Van Santen, Mark West Apr 2012

Armedand Dangerous: The Consequences Of Not Randomizing The First Block, Edzard Van Santen, Mark West

Conference on Applied Statistics in Agriculture

Replication and randomization and are the keys for statistically valid experiments. Both are necessary components for statistically valid experimentation. Yet it is an industry wide practicein weed science research to assign treatment in the first block of a randomized complete block design in a systematic order for reasons of convenience. We investigated this practice by comparing four randomization/analysis scenarios: (i) complete randomization in all blocks, (ii) systematic assignment of treatmentsin block 1, where the best treatment was assigned to the best plot, (iii) systematic assignment of treatmentsin block 1, where the best treatment was assigned to the worst plot,and (iv) …

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Correcting For Amplification Bias In Next-Generation Sequencing Data, Douglas Baumann, R. W. Doerge Apr 2012

Correcting For Amplification Bias In Next-Generation Sequencing Data, Douglas Baumann, R. W. Doerge

Conference on Applied Statistics in Agriculture

Next-generation sequencing (NGS) technologies have opened the door to a wealth of knowledge and information about biological systems, particularly in genomics and epigenomics. These tools, although useful, carry with them additional technological and statistical challenges that need to be understood and addressed. One such issue is ampli cation bias. Specifically, the majority of NGS technologies effectively sample small amounts of DNA or RNA that are amplified (i.e., copied) prior to sequencing. The amplification process is not perfect, and thus sequenced read counts can be extremely biased. Unfortunately, current amplification bias controlling procedures introduce a dependence of gene expression on gene …

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Multivariate Statistical Analysis Of Avian Index Of Biotic Integrity, Bahman Shafii, William J. Price, Norm Merz, Dwight Bergeron Apr 2012

Multivariate Statistical Analysis Of Avian Index Of Biotic Integrity, Bahman Shafii, William J. Price, Norm Merz, Dwight Bergeron

Conference on Applied Statistics in Agriculture

The Index of Biotic Integrity (IBI) is a multi-metric index designed to measure the changes in ecological and environmental conditions as affected by human disturbances. Hence, IBI is used in practice to detect divergence from biological integrity attributable to human actions. The incorporation of biological attributes is often done at both the individual and higher level assemblages. The objective of this paper is to demonstrate the construction and statistical evaluation of a multi-metric Avian Index of Biotic Integrity (A-IBI). Canonical correlation analyses are utilized to select pertinent avian metrics as impacted by vegetation and hydrology variables. The resulting avian metrics …

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Evaluation Of Genotype By Environment Interactions From Unreplicated Multi-Environmental Trials Of Hybrid Maize, Ani A. Elias, Kelly R. Robbins, Dev Niyogi, James J. Camberato, R. W. Doerge, Mitchell R. Tuinstra Apr 2012

Evaluation Of Genotype By Environment Interactions From Unreplicated Multi-Environmental Trials Of Hybrid Maize, Ani A. Elias, Kelly R. Robbins, Dev Niyogi, James J. Camberato, R. W. Doerge, Mitchell R. Tuinstra

Conference on Applied Statistics in Agriculture

Diverse soils and varying weather conditions not only affect overall performance of hybrid maize in multi-environment field studies, but can also cause strong genotype by environment interactions (GEI). Modern maize breeding experiments utilize multilocation trials with augmented field designs to evaluate the performance of unreplicated test hybrids. Augmented designs are resource efficient; however, these designs do not efficiently quantify or test GEI variation in the test hybrids. New methods are being developed that use random regression models to incorporate multiple environmental effects into GEI models to increase their accuracy and predictive ability. Incorporation of varying weather and soil physical variables …

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Editor's Preface And Table Of Contents, Weixing Song Apr 2012

Editor's Preface And Table Of Contents, Weixing Song

Conference on Applied Statistics in Agriculture

These proceedings contain papers presented in the twenty-fourth annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 29 - May 1, 2012.

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