Physical Sciences and Mathematics Commons^™

Separation Of Single Gene Effects From Additive-Dominance Genetic Models, Jixiang Wu, Johnie N. Jenkins, Jack Mccarty Jr, Chris Cheatham

Conference on Applied Statistics in Agriculture

Separation of single gene and polygenic effects would be useful in crop improvement. In this study, additive-dominance model with a single qualitative gene based on diallel crosses of parents and progeny F₁s (or F₂s) was examined. The mixed linear model approach, minimum norm quadratic unbiased estimation (MINQUE), was used to estimate the variance and covariance components and single gene effects. Monte Carlo simulation was used to evaluate the efficiency of each parameter estimated from the MINQUE approach for this genetic model. The results of 200 simulations indicated that estimates of variance components and single gene effects …

Performance Of The Exact And Chi-Square Tests On Sparse Contingency Tables, D. G. Renter, J. J. Higgins, J. M. Sargeant

Conference on Applied Statistics in Agriculture

A cross-sectional observational study design was used to determine the prevalence of Escherichia coli 0157:H7 in wild deer feces. Samples were voluntarily submitted at a number of different locations. In order to determine if the proportions of E. coli 0157: H7 positive samples submitted were equal for each of the 26 locations, a 26 by 2 contingency table was analyzed. There were only four E. coli 0157:H7 positive samples, which resulted in a sparse table. It is possible to obtain statistically significant results in sparse tables using Fisher's exact test, whereas the chi-square test is generally unreliable in such situations. …

An Autoregression Model For A Paired Watershed Comparison, D. Meek, D. Dinnes, D. Jaynes, C. Cambardella, T. Colvin, J. Hatfield, D. Karlen

Conference on Applied Statistics in Agriculture

Analysis of water quality data from a paired watershed design is needed to determine if a best fertilizer management practice reduces a specific water quality variable compared to a conventional fertilizer management practice. This study examines an existing recommended method of analysis for paired watershed designs, simple analysis of covariance (ANCOVA) on time aggregated data, then offers two autoregression analyses (AR) as alternatives. The first approach models the sequence of paired differences and estimates its 95% confidence band. The second approach develops individual watershed AR models then examines the joint 95% confidence interval about the predicted difference. A reliability analysis …

Optimum Design For Exponential Model Using An Exponential Loss Function And Its Applications In Agriculture, Imad H. Khamis

Conference on Applied Statistics in Agriculture

Accelerated life testing has been used for years in engineering. Test units are run at high stress and fail sooner than at design stress. The lifetime at design stress is estimated by extrapolation using a regression model. This paper considers the optimum design of accelerated life tests in which two levels of stresses, high and low are constantly applied. For the exponential model the expected value of an exponential loss function of the arameter is to be used. The initial sample proportion allocated to the high stress which minimizes the expected loss function is determined. In the agriculture context, plants …

Uncertainty Analysis Of A Pipe Model Based On Correlated Distributions, Shoufan Fang, George Z. Gertner

Conference on Applied Statistics in Agriculture

Traditionally, uncertainty analysis of complex simulation models has been conducted based on the assumption of that the components of the model are independent. In practice, correlation is universal in ecosystems. This study applied Bayesian estimation and rejection sampling to generate correlated random samples for an uncertainty analysis of a process based forest growth model, a pipe model. Comparison of error budgets built using independent and correlated distributions shows that correlated distributions are very important to provide reasonable and realistic simulation and uncertainty analysis.

A Simulation Study To Evaluate Proc Mixed Analysis Of Repeated Measures Data, Leanna Guerin, Walter W. Stroup

Conference on Applied Statistics in Agriculture

Experiments with repeated measurements are common in pharmaceutical trials, agricultural research, and other biological disciplines. Many aspects of the analysis of such experiments remain controversial. With increasingly sophisticated software becoming available, e.g. PROC MIXED, data analysts have more options from which to choose, and hence more questions about the value and impact of these options. These dilemmas include the following. MIXED offers a number of different correlated error models and several criteria for choosing among competing models. How do the model selection criteria behave? How is inference affected if the correlated error model is misspecified? Some texts use random between …

Some Strategies For Selecting And Fitting Covariance Structures For Repeated Measures, Raul E. Macchiavelli

Conference on Applied Statistics in Agriculture

Since in longitudinal studies the covariance structure is often regarded as a nuisance parameter, the strategy has been to use a parsimonious covariance model that describes adequately the observed data and permits better inference on the parameters of interest. In this paper we present some diagnostic tools to choose an appropriate covariance structure and discuss some strategies for fitting it. The main diagnostic tool is the "residual", computed as the standardized difference between the elements of the fitted covariance (concentration or correlation) matrix and the corresponding unstructured matrix. SAS Proc Calis is a very efficient procedure that fits many covariance …

Bias In Principal Components Analysis Due To Correlated Observations, Hong Jiang, Kent M. Eskridge

Conference on Applied Statistics in Agriculture

A common practice in many scientific disciplines is to take measurements on several different variables on each unit from a designed experiment. This practice is cost efficient and results in data that may be analyzed using multivariate statistical methods. Usually, principal components analysis (PCA) is conducted by decomposing the covariance matrix of the several dependent variables using eigenanalysis without accounting for possible correlations among the observations. To evaluate how correlated observations bias PCA results, we used algebraic derivation and simulation for several different types of correlation structures. Our results indicated that sampling error generally had a much larger impact on …

Development Of Wild Oat Seed Dispersal Distributions Using An Individual-Plant Growth Simulation Model, William J. Price, Bahman Shafii, Donald C. Thill

Conference on Applied Statistics in Agriculture

An individual-plant growth simulation model for quantifying competition between spring barley and wild oat has been previously described (price, Shafii, and Thill, 1994). Individual plants within a population were modeled independently and competition between plants was determined by resource demand within plant specific areas-of-influence. Calibration of the model to spring barley and wild oat biomass data was performed and shown to have a high degree of accuracy under mono culture conditions. The work presented here applies the specified model to a larger scale simulation for the purpose of demonstrating seed dispersal in wild oat. This is accomplished by breaking the …

Application Of Computer Intensive Methods To Evaluate The Performance Of A Sampling Design For Use In Cotton Insect Pest Management, J. L. Willers, W. L. Ladner, J. M. Mckinion, W. H. Cooke

Conference on Applied Statistics in Agriculture

A scouting protocol for cotton insect pests was developed which combines high resolution, multispectral remotely sensed imagery with a belt transect that crosses rows of cotton. Imagery was used to determine sample site selection while estimating plant bug abundance in a more than 200 ac. cotton field in 1997. Tarnished plant bug (Lygus lineolaris) counts were acquired using a standard drop cloth for each of eight rows along a transect. The sample data indicated that plant bug population densities spatially vary as a function of different spectral (color) classes present on the imagery. We postulate that such classified …

Using Nonlinear Growth Curves To Estimate Heat Stress In Processing Feedlot Cattle, A. M. Parkhurst, T. L. Mader

Conference on Applied Statistics in Agriculture

Summertime heat waves cause excessive discomfort and, in extreme cases, death of feedlot cattle. During such emergencies, extension specialists are called upon for recommendations of management practices to minimize heat stress. Since moving cattle is believed to raise body temperature 1 degree, one recommendation is to move cattle before mid-day or reschedule to another day. More knowledge of body temperature dynamics could lead to more specific recommendations of how far cattle can be moved without stress. Several models are investigated - especially those involving exponential growth(challenge) and decay (recovery) such as the bi-exponential, single compartment and other models in pharmacokinetics. …

Point Estimators Of Heritability Based On Confidence Intervals: A Closed-Form Approximation To The Reml Estimator, Brent D. Burch, Ian R. Harris

Conference on Applied Statistics in Agriculture

Estimating heritability, the proportion of variation in phenotypic values due to (additive) genetic effects, is an important subject matter to plant and animal breeders alike. In most applications there is not an analytic expression for the restricted maximum likelihood (REML) estimator of heritability since it is obtained via an iterative procedure. The focus of this paper is to find a closed-form approximation to the REML estimator of heritability for those scenarios in which mixed linear models having two variance components are appropriate. This procedure is equivalent to constructing approximate pivotal quantities and thus confidence intervals for heritability. See Burch and …

Establishing Population And Individual Bioequivalence Confidence Intervals, Feng Yu, Linda J. Young, Gary R. Stevens

Conference on Applied Statistics in Agriculture

Average bioequivalence is used to assess pharmacokinetic properties of proposed generic drug before they are marketed. The limitations of average bioequivalence have led the U.S. Food and Drug Administration to propose the use of popUlation bioequivalence and individual bioequivalence. In this study, bootstrap confidence intervals were used to evaluate population bioequivalence and individual bioequivalence in the context of a 2 x 4 crossover experimental design. Two bioequivalence criteria were compared: the mean-squared difference criterion and a probability-based criterion. Simulations were conducted to study the properties of the bootstrap confidence intervals under each criterion in establishing population bioequivalence or individual bioequivalence. …

Application And Comparison Of Three Spatial Statistical Methods For Mapping And Analyzing Soil Erodibility, George Gertner, Guangxing Wang, Pablo Parysow, Alan Anderson

Conference on Applied Statistics in Agriculture

The Revised Universal Soil Loss Equation (RUSLE) is a model to predict longtime average annual soil loss, related to rainfall-runoff, soil erodibility, slope length and steepness, cover management, and support practice. The soil erodibility factor K accounts for the influence of soil properties on soil loss during storm events in upland areas.

In this paper, ordinary kriging, sequential Gaussian and indicator simulation methods were used and compared for spatial prediction and uncertainty analysis of soil erodibility based on a data set from a very intensive soil survey (524 observations, 10 m by 10 m grid). Half the data was used …

Yield Prediction In 60ft2 Grids, S. Aref, D. G. Bullock

Conference on Applied Statistics in Agriculture

Large detailed yield databases incorporating GPS makes it possible to predict yield on a small scale. The objective of this study was to determine how closely yield could be predicted in grids of 60-ft² units. Com and soybean yields were averaged to the 60-ft² grid. The yields were modeled on previous yields, soil fertility, soil type, and terrain variables. Soil fertility variables were kriged from a I-acre grid to the 60-ft² grid. Terrain data and soil type data were available at the same scale. Multiple regression models and models with spatial correlation determined from yield semivariograms differed …

Exploring Factors Affecting Atrazine Concentration In The Big Blue River Basin, Steven R. Kirby, Linda J. Young

Conference on Applied Statistics in Agriculture

Atrazine is a herbicide commonly used on corn and sorghum. Consumption of atrazine adversely affects humans. Environmental factors are related to atrazine concentration in the surface waters of the Big Blue River Basin using regression techniques. The usefulness of environmental factors as predictors of surface water atrazine contamination appears to depend on the time period.

Analysis Of The Allelopathic Potential Of Rice Using K-Means Clustering Of Hplc Chromatograms, Edward E. Gbur, John D. Mattice, Robert H. Dilday

Conference on Applied Statistics in Agriculture

Allelopathy is the ability of an organism to affect the growth of another organism through the introduction of chemical compounds into the environment. Several researchers have reported rice inhibition of the growth of weed species such as barnyard grass and ducksalad. The objective of this study was to relate patterns found in HPLC chromatograms for leaf extracts of different rice accessions to their weed control activity. K-means cluster analysis was performed on 20 peak heights from chromatograms from 40 rice accessions. The resulting clusters corresponded to observed behavior of the accessions reported in other sources. Stepwise discriminant analysis was used …

An Introduction To Model Selection For Quantitative Trait Locus Analysis In Polyploids, R. W. Doerge, Bruce A. Craig

Conference on Applied Statistics in Agriculture

Substantial gains have been made in locating regions of agricultural genomes associated with characteristics, diseases, and agroeconomic traits. These gains have relied heavily on the ability to estimate the association between DNA markers and regions of a genome (quantitative trait loci or QTL) related to a particular trait. The majority of these advances have focused on diploid species (two homologous chromosomes per set), even though many important agricultural crops are, in fact, polyploid (more than two homologous chromosomes per set). The purpose of our work is to initiate an algorithmic approach for model selection and QTL detection in polyploid species. …

A Fertilizer-Rate Experiment Involving Young Citrus Trees: Does More Fertilizer Mean Higher Producing Trees?, John A. Cornell

Conference on Applied Statistics in Agriculture

Citrus growers are interested in making money. So, the most common practice among growers is to push young trees into early production by the application of high amounts (rates) of fertilizer. This practice can lead to disaster in terms of tree formation (canopy shape) and production stress. In contrast, when the applied fertilizer approaches both the optimum rate and the optimum N -P -K -Ca ratio for citrus, then the trees are more uniform in size and with compact canopies and the incidence of decline is less. Cordieropolis station in Sao Paula, Brazil, is the site of a large 3-component …

Editor's Preface, Table Of Contents, And List Of Attendees, George A. Milliken

Conference on Applied Statistics in Agriculture

These proceedings contain papers presented in the twelfth annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 30-May 2, 2000..