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2002

Agriculture

Conference on Applied Statistics in Agriculture

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Full-Text Articles in Physical Sciences and Mathematics

Spatial Modeling Of Biomass In Nebraska Windbreaks, Qingjiang Hou, Linda J. Young, James R. Brandle, Michele M. Schoeneberger Apr 2002

Spatial Modeling Of Biomass In Nebraska Windbreaks, Qingjiang Hou, Linda J. Young, James R. Brandle, Michele M. Schoeneberger

Conference on Applied Statistics in Agriculture

Field windbreaks have the potential of sequestering large amounts of carbon. Predicting how much carbon would be sequestered in a newly planted windbreak after ten or more years is of interest. The amount of carbon in a tree depends on its biomass. In a pilot study of Nebraska windbreaks, a Markov random field was used to predict the biomass of green ash in windbreaks as a function of soil and climate conditions. The spatial dependence parameter was significantly different from zero, indicating the presence of small scale variation. In addition to age, the 30 year average summer precipitation and the …

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Effect On Boll Weight Of Cotton Plants Planted At Various Densities, B. G. Mullinix, C. W. Bednarz Apr 2002

Effect On Boll Weight Of Cotton Plants Planted At Various Densities, B. G. Mullinix, C. W. Bednarz

Conference on Applied Statistics in Agriculture

Previous research has shown that yield of cotton increases with plant density until density reaches 16 to 20 plants m-2. In 1997 and 1998 cotton was planted at various densities ranging from 2.5 to 22.5 plants m-2 in a RCB design. Ten row feet (3.048 m) of cotton were cut at ground level in each plot and placed into separate bags. Plant density for each plot was found by counting the number of plants in the bag representing that plot. For each plant, a boll found was placed in a small bag representing the fruiting branch and …

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Simulation And Response Surface Methodology To Optimize Winter Wheat Response To Global Climate Change, P. Dhungana, K. M. Eskridge, A. Weiss, P. S. Baenziger Apr 2002

Simulation And Response Surface Methodology To Optimize Winter Wheat Response To Global Climate Change, P. Dhungana, K. M. Eskridge, A. Weiss, P. S. Baenziger

Conference on Applied Statistics in Agriculture

Future climate changes can have a major impact on crop production. But, whatever the climatic changes, crop production can be adapted to climate change by implementing alternative management practices and developing new genotypes that will take full advantage of the future climatic conditions. Since the classical agronomic research approach is not possible in identifying these new agronomic technologies for the future climatic conditions, we used response surface methodology (RSM) in connection with the CERES-Wheat crop model and the HADCM2 climate simulation model to identify optimal configuration of plant traits and management practices that maximize yield of winter wheat under high …

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Using Nonlinear Fixed And Mixed Models To Study Acclimation To Heat Stress In Cattle, L. Lan, A. M. Parkhurst, D. A. Spiers, K. M. Eskridge, G. L. Hahn Apr 2002

Using Nonlinear Fixed And Mixed Models To Study Acclimation To Heat Stress In Cattle, L. Lan, A. M. Parkhurst, D. A. Spiers, K. M. Eskridge, G. L. Hahn

Conference on Applied Statistics in Agriculture

Researchers studying acclimation of cattle to heat stress want to know if exposure to heat stress in controlled chambers will help cattle adjust to climatic conditions in the field. The four parameter nonlinear PET model is used to study the relationship between core body temperature and ambient temperature. This model works well when cattle are challenged by heat stress but the model is less useful for thermoneutral conditions. Both proc Nlin and Nlmixed are used to compare and contrast the field parameters between the controlled and the potentially acclimated group. Simulation studies were used to compare the effectiveness of proc …

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Spline Models For Estimating Heat Stress Thresholds In Cattle, A. M. Parkhurst, D. A. Spiers, G. L. Hahn Apr 2002

Spline Models For Estimating Heat Stress Thresholds In Cattle, A. M. Parkhurst, D. A. Spiers, G. L. Hahn

Conference on Applied Statistics in Agriculture

Studies of the relationship between animal body temperature and air temperature suggest body temperature is essentially unresponsive until a threshold is reached, then it responds dramatically to increasing air temperature. The goal is to estimate the threshold between the thermoneutral plateau and the beginning of the heat stress challenge. One approach is to fit a polynomial to estimate the knot position and use spline functions to perform linear least squares piecewise polynomial fitting. Another alternative is to use nonlinear regression to estimate the knot or an inflection point of a nonlinear function. In both approaches the cyclic nature of body …

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Using Landscape Characteristics As Prior Information For Bayesian Classification Of Remotely Sensed Imagery, William J. Price, Bahman Shafii Apr 2002

Using Landscape Characteristics As Prior Information For Bayesian Classification Of Remotely Sensed Imagery, William J. Price, Bahman Shafii

Conference on Applied Statistics in Agriculture

Yellow starthistle is a dominant weed of north-central Idaho canyon grasslands. The distribution of yellow starthistle can be affected by general landscape characteristics, such as land use, as well as specific terrain related features such as elevation, slope, and aspect. Slope and aspect can be considered as indicators of plant community composition and distribution. Hence, these variables may be incorporated into prediction models to estimate the likelihood of yellow starthistle occurrence. An empirically derived nonlinear model based on landscape characteristics was developed to predict the likelihood of yellow starthistle occurrence in north central Idaho (Shafii, et al. 1999). While the …

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Estimating The Contribution Of Specific Wheat Varieties To State-Level Production, Bingxin Yu, Richard K. Perrin, David B. Marx Apr 2002

Estimating The Contribution Of Specific Wheat Varieties To State-Level Production, Bingxin Yu, Richard K. Perrin, David B. Marx

Conference on Applied Statistics in Agriculture

This paper addresses measurement issues involved in estimating the benefits from a university wheat breeding program. The conceptual foundation is to estimate the spatial distribution of farm-level yields for varieties in each year, based on Nebraska winter wheat variety test data from 1972 to 2001, with 9-20 locations per year. We can then estimate the state average yield difference that would occur between the portfolios of varieties that farmers actually grew, and the portfolio of varieties excluding those varieties from the university breeding program. This paper reports estimates of the statewide annual yields of individual varieties using a standard fixed …

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Impact Of Data Transformation On The Performance Of Different Clustering Methods And Cluster Number Determination Statistics For Analyzing Gene Expression Profile Data, Guoping Shu, Beiyan Zeng, Deanne Wright, Oscar Smith Apr 2002

Impact Of Data Transformation On The Performance Of Different Clustering Methods And Cluster Number Determination Statistics For Analyzing Gene Expression Profile Data, Guoping Shu, Beiyan Zeng, Deanne Wright, Oscar Smith

Conference on Applied Statistics in Agriculture

We have assessed the impact of 13 different data transformation methods on the performance of four types of clustering methods (partitioning (K-mean), hierarchical distance (Average Linkage), multivariate normal mixture, and non-parametric kernel density) and four cluster number determination statistics (CNDS) (Pseudo F, Pseudo t2, Cubic Clustering Criterion (CCC), and Bayesian Information Criterion (BIC), using both simulated and real gene expression profile data. We found that Square Root, Cubic Root, and Spacing transformations have mostly positive impacts on the performance of the four types of clustering methods whereas Tukey's Bisquare and Interquantile Range have mostly negative impacts. The impacts …

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Unreplicated Spatial Designs Compared Using Optimality Criteria, Tisha Maas, David Marx, Dr. Jeff Pedersen Apr 2002

Unreplicated Spatial Designs Compared Using Optimality Criteria, Tisha Maas, David Marx, Dr. Jeff Pedersen

Conference on Applied Statistics in Agriculture

In field trials including large numbers of varieties, it is often impossible or impractical to replicate each variety. In these situations, the researcher may choose to use only one replicate of each test variety and to include a "check" variety every so often so that the spatial variability of the field may be determined. Five different check patterns were purposefully designed, each possessing distinct characteristics. The purpose of this study is to determine which spatial patterns for the check variety are better able to identify the spatial structure in a field and to rank the experimental varieties accurately. The problem …

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Row-Colunin Designs At Pioneer Hi-Bred, Kevin Wright Apr 2002

Row-Colunin Designs At Pioneer Hi-Bred, Kevin Wright

Conference on Applied Statistics in Agriculture

Pioneer Hi-Bred annually tests more than one hundred thousand new varieties of corn hybrids. Experimental designs used for these tests include CRD, RCB, nested and split-plot. A Six Sigma project at Pioneer recommended testing the use of incomplete-block (IB) designs. In 2001 some experiments were structured as row-column IE designs. This talk will discuss the experience of implementing and analyzing the row-column designs, summaries of the results, and plans for future experiments.

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The Information-Theoretic Approach To Model Selection: Description And Case Study, Erin E. Blankenshipa, Micah W. Perkinsb, Ron J. Johnsonc Apr 2002

The Information-Theoretic Approach To Model Selection: Description And Case Study, Erin E. Blankenshipa, Micah W. Perkinsb, Ron J. Johnsonc

Conference on Applied Statistics in Agriculture

In the wildlife literature there has been some recent criticism of statistical significance testing. In the past few years, both the Journal of ·Wildlife Management and the Wildlife Society Bulletin have published articles criticizing the overuse and misuse of hypothesis tests. One alternative to using hypothesis tests for model selection is the information-theoretic approach, proposed by Burnham and Anderson (1998). This technique uses values such as the Akaike Information Criterion and others to choose a set of plausible models from a set of a prioTi candidate models. Inferences are based on the set of plausible models, rather than on a …

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Estimating Intraclass Correlation: Optimal Results Using Limited Resources, Brent D. Burch, Ian R. Harris Apr 2002

Estimating Intraclass Correlation: Optimal Results Using Limited Resources, Brent D. Burch, Ian R. Harris

Conference on Applied Statistics in Agriculture

From plant and animal breeding studies to industrial applications, the intraclass correlation coefficient (p) is used to measure the proportion of the total variation in the responses that may be attributed to a particular source. Confidence intervals for p are used to determine the optimal allocation of experimental material in one-way random effects models. Assuming the sample size is fixed, the authors investigate the number of groups and the number of observations per group required to minimize the expected length of confidence intervals. Examples are used to illustrate the selection of the best design. Both asymptotic and exact results suggest …

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Impact Of Variance Component Estimates On Fixed Effect Inference In Unbalanced Linear Mixed Models, Walt Stroup, Ramon Littell Apr 2002

Impact Of Variance Component Estimates On Fixed Effect Inference In Unbalanced Linear Mixed Models, Walt Stroup, Ramon Littell

Conference on Applied Statistics in Agriculture

Inference on fixed effects in mixed models depends on standard errors or test statistics which in turn depend on estimates of variance and covariance components. For unbalanced mixed models, even relatively simple models such as two-way cross-classification models with interaction where one factor is fixed and the other is random, dilemmas arise that have received inadequate attention to date. For example, if one uses SAS PROC MIXED, one can estimate variance components using expected means squares from Type I, II, or III sums of squares, or one can use likelihood-based algorithms such as the default restricted maximum likelihood. If there …

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Model Selection Techniques For Repeated Measures Covariance Structures, E. Barry Moser, Raul E. Macchiavelli Apr 2002

Model Selection Techniques For Repeated Measures Covariance Structures, E. Barry Moser, Raul E. Macchiavelli

Conference on Applied Statistics in Agriculture

A parsimonious covariance structure of repeated measures is often sought for purposes of increased power for testing hypotheses about the means, and for insight into the stochastic processes governing the repeated measures. For normal data, model selection is often based upon likelihood ratio tests or information criteria derived from the likelihood, sometimes supplemented with graphical plots of correlations and partial correlations. We exploit the ordered nature of repeated measures to decompose the likelihood ratio goodness-of-fit test statistic, and display graphical fingerprints associated with the covariance structures to help detect covariance structure misspecification, in order to provide guidance in choosing an …

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The Completely Sufficient Statistician (Css), Ralph G. O'Brien Apr 2002

The Completely Sufficient Statistician (Css), Ralph G. O'Brien

Conference on Applied Statistics in Agriculture

Today's ideal statistical scientist develops and maintains a broad range of technical skills and personal qualities in four domains: (1) numeracy, in mathematics and numerical computing; (2) articulacy and people skills; (3) literacy, in technical writing and in programm,ing; and (4) graphicacy. Yet, many of these components are given short shrift in university statistics programs. Can even the best statistician today really be "completely sufficient?"

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Editor's Preface And Table Of Contents, George A. Milliken Apr 2002

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

Conference on Applied Statistics in Agriculture

These proceedings contain papers presented in the fourteenth annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 28-30, 2002.

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