Physical Sciences and Mathematics Commons^™

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?"

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.

Package Options For Alfalfa, Michael Collins

Kentucky Alfalfa and Stored Forage Conference

Most of the hay crop in Kentucky is harvested as dry hay and stored in round bales of various sizes for feeding on the farm. Most of the round-baled hay in Kentucky is used on-farm in feeding beef and dairy cattle. When alfalfa hay in round bales is left outside without protection from the weather, large losses in DM yield and in forage quality usually result. We routinely measure DM losses in the range of 20- 35% for a normal length hay storage season. Our research has shown that several economical storage options exist for protecting this hay from weathering. …

Marketing Kentucky Hay, Billy Ray Smith

Kentucky Alfalfa and Stored Forage Conference

The production of hay and pasture crops is essential to a profitable future for Kentucky agriculture. The Commonwealth ranked seventh in the nation in hay production in the year 2000 with 6.2 million tons. These forages provide the bulk of the feed supply for our livestock industry. In addition, a significant portion of our hay crop is marketed, both to in-state and out-of-state buyers.

Innovative Loading And Stacking Systems For Custom Hay Sales, Tom Keene

Kentucky Alfalfa and Stored Forage Conference

As the face of agriculture continues to change, so does the hay industry. What was standard operating procedure twenty years ago is now no longer economically feasible in the cash hay industry. This is especially true in the loading and stacking end of the business.

The business has changed because new technology along with the dramatic decrease in the availability of "hand labor" has helped to drive the need for new loading and stacking systems for the hay industry. These two phenomenon will continue to drive us toward total mechanization in the hay industry in fact many hay producers are …

Designing A Grazing System For Alfalfa, Ken Johnson

Kentucky Alfalfa and Stored Forage Conference

As we think about grazing alfalfa, we should decide why we are considering alfalfa and where it fits. I want to address some of these issues from my prospective as a grazer with several years experience and as an agriculture employee working with many grazers over the years. Alfalfa is the most productive, high quality grazing forage we can grow in Kentucky; we need to be using it more.

Grazing Alfalfa At The Western Kentucky University Farm, Byron Sleugh, Raquel Stiles, David K. Stiles, Amanda Canty, Curtis Mitchell

Kentucky Alfalfa and Stored Forage Conference

Alfalfa has been around for centuries. In all this time, it was used in many different ways to provide high quality forage to livestock. In fact, in the area where alfalfa originated, the word actually means "horse power". We have come a long way since then and alfalfa is used for a wide range of animals, from rabbits to rhinos.

In order to maximize the efficiency of utilization of alfalfa, it has become necessary to graze it. Grazing is preferred over harvesting and storage for several reasons: less equipment and thus lower cost, less harvest loss, and greater quality forage …

Managing Alfalfa For Yield-Quality-Persistence, Garry D. Lacefield

Kentucky Alfalfa and Stored Forage Conference

Alfalfa is a premier forage legume that has played an important role in Kentucky's forage-livestock program for many years. It's role at present is increasing and it's most significant role is yet to come.

Advances In Alfalfa Breeding — What Will The Alfalfa Variety Of The Future Smell, Taste, Look And Act Like?, Jimmy C. Henning

Kentucky Alfalfa and Stored Forage Conference

Alfalfa is the highest quality, highest yielding and arguably the highest value forage crop in Kentucky and in the US. It is useful as hay, haylage or pasture for a variety of species of livestock. It is well adapted to Kentucky and is an important part of the forage/livestock system.

Alfalfa breeders are actively working to develop varieties that will meet and exceed farmer expectations for yield and persistence. In addition, other traits are sought after to make the variety meet a special need or to have better marketability or attraction to the customer.

So what will the alfalfa of …

Foreword [2002], Garry D. Lacefield

Kentucky Alfalfa and Stored Forage Conference

This is the front matter of the proceedings.

Student Survey Of Information Technology, Wku Information Technology, Richard Kirchmeyer

Board of Regents Documents

Survey of 400 WKU students about information technology used in strategic operations planning for Information Technology. The survey attempted to determine the depth and breadth of student computer use and knowledge of a variety of hardware and software. The report was presented to the WKU Board of Regents at the August 17, 2001 meeting.

Another Look At Clark's Adit-Silver Series, David W. Meek

Conference on Applied Statistics in Agriculture

The empirical semivariogram for Clark's adit-silver series has been the subject of several publications. Its use in the literature along with some other discussed considerations makes this series a suitable selection for a classroom or workshop semivariogram modeling exercise. My emphasis in this exercise is on estimating the scale of fluctuation (8). Alternative unbounded, bounded asymptotic, and bounded transitional models are developed via weighted least-squares estimation for both regular and integral semivariogram parameterizations (ISV). Results are compared with Clark's recommendation along with some other traditional models, nonparametric models, and ad hoc numerical methods. When a given model fits well using …

An Uncertainty Analysis Procedure For Spatially Joint Simulations Of Multiple Attributes, Shoufan Fang, Guangxing Wang, George Z. Gertner, Alan Anderson

Conference on Applied Statistics in Agriculture

In this study, an uncertainty analysis procedure for joint sequential simulation of multiple attributes of spatially explicit models was developed based on regression analysis. This procedure utilizes information obtained from joint sequential simulation to establish the relationship between model uncertainty and variation of model inputs. Using this procedure, model variance can be partitioned by model input parameters on a pixel by pixel basis. In the partitioning, the correlation of neighboring pixels is accounted for. With traditional uncertainty analysis methods, this is not possible. In a case study, spatial variation of soil erodibility from a joint sequential simulation of soil properties …

Comparison Of Sas Proc Nlin And Nlmixed For Parameter Estimation In Pet Model, Y. Xie, A. M. Parkhurst, T. L. Mader, J. B. Gaughan

Conference on Applied Statistics in Agriculture

Cattle body temperatures were measured under semi-controlled hot cyclic chamber temperatures. The four-parameter nonlinear PET model, is used to estimate body temperature in cattle challenged by heat stress. For each steer, the parameters can be estimated by the Nlin procedure and the sensitivity of each animal can be studied. It is also desirable to generalize the results by using the Nlmixed procedure to combine both the fixed and random effects. When comparing the results from the two procedures, we found heterogeneity among animals and/or days caused convergence problems for proc Nlmixed. Simulation studies were used to study how deviations from …

Developing System For Auditing The Database Of Agricultural Trial, Olga Susana Filippini De Delfino, Ana Aguua, Hugo Delfino

Conference on Applied Statistics in Agriculture

Many steps are involved in getting data from an experimental unit of an agricultural trial into a final report. Each step may introduce a great variety of errors. Building quality into systems is much more productive than building checks onto the end. Poor quality database have effects on final study results in terms of estimation, significance testing and power; but auditing agricultural trial is a complex process designed to ensure that it will provide a reliable answer to the question being posed. By introducing digit errors into database in a tomato assay, with small sample size, we demonstrate that simple …

Assessing Refinements In Modeling Sinusoidal Conditions Used To Drive Cattle Body Temperatures, Sheng Feng, Anne Parkhurst, Kent Eskridge, Daryl Travnicek, Donald Spiers, G. L. Hahn, Terry Mader

Conference on Applied Statistics in Agriculture

A model, termed the PET model, is used to estimate body temperature in cattle challenged by hot cyclic chamber temperatures. The model is based on Newton's law of cooling, driven by an estimated sinusoidal function. In practice, it is often difficult to maintain hot sinusoidal fluctuations in chamber temperatures. However, it is possible to model cyclic chamber temperatures using a discrete Fourier series. By increasing the precision in estimating the cyclic temperature driving function, we can more precisely estimate the parameters in the PET model. Simulation studies were performed to investigate the effect of under- and over-parameterization on accuracy of …

Predicting Soybean Weight Per Pod, Timothy P. Keller, Michael Schmidt, Catherine Schmidt

Conference on Applied Statistics in Agriculture

The National Agricultural Statistics Service (NASS) makes predictions of soybean yield at both the state and national level. Experience indicates that the key to improving yield predictions is improving the prediction of soybean weight pod. Towards this end, NASS has entered into a three year cooperative agreement with the Department of Plant, Soil and General Agriculture at Southern lllinois University at Carbondale (SID-C) to investigate predictive models for soybean weight per pod based on a measurement of pod width and a count of the number of seeds per pod. Aside from the scientific issues involved in this effort, the practical …

Development Of Experiments For The Harvesting And Storing Of Vidalia Sweet Onions, Ben G. Mullinix, Bryan W. Maw, Reid L. Torrance

Conference on Applied Statistics in Agriculture

Sweet onions brought in nearly $70 million in 1998. Sweet onions have a soft bulb which makes them susceptible to injury if handled too roughly. Once injured, invasion by pathogens tends to render the bulbs unusable except for quick sale. They were harvested by hand until about ten years ago when efforts were begun to develop a mechanical harvester. Also, at that time, work was underway to develop a way of storing part of the crop so as to extend the market window beyond the traditional 6-8 weeks. Low temperature and low oxygen atmosphere conditions proved to be the most …

Are Spatial Models Needed With Adequately Blocked Field Trials?, Reid D. Landes, Kent M. Eskridge, P. Stephen Baenziger, David B. Marx

Conference on Applied Statistics in Agriculture

The use of nearest neighbors and spatial models (SPAT) to analyze field trial data has become commonplace in recent years. These two types of analyses improve precision compared to ANOVA when trials are poorly blocked, but results are less clear in well-blocked trials. We examined data from wheat trials containing 60 cultivars, conducted at five locations, where each location was set up as an alpha lattice design. We compared the relative efficiency of detecting cultivar differences for spatial models and nearest neighbors analyses (NNA) to ANOVA, fit of the models, and correlations of ranked cultivars. Though the SPAT and NNA …

An Analysis Of Daily Peak Stream Discharge Using A Non-Gaussian Time Series Model, S. Perera

Conference on Applied Statistics in Agriculture

Daily peak stream discharge data, collected over time, are typically characterized by a few large peaks separated by runs of small values, where peaks correspond to the occurrence of storms. Furthermore, the peak discharge on the first day of a storm has little or no relationship to the previous day's discharge. These characteristics are not present in standard Gaussian time series models in which a zig-zag behavior not conducive to runs of small values is observed and the present value always depends on the previous value. However, they can be successfully captured with non-Gaussian time series models.

Daily peak stream …

Using Proc Nlmixed To Analyze A Time Of Weed Removal Study, Erin E. Blankenship, Sean Evans, Walter W. Stroup, Stevan Z. Knezevic

Conference on Applied Statistics in Agriculture

Many studies in weed science involve fitting a nonlinear model to experimental data. Examples of such studies include dose-response experiments and studies to determine the critical period of weed control. The experiments typically use block designs and often have additional complexity such as split-plot features. However, nonlinear models are typically fit using software such as SAS PROC NLIN that are limited to a single error term and whose ability to account for blocking is either awkward or lacking entirely. For example, Seefeldt et al. (1995) only proceeded in fitting the nonlinear model after establishing that the block effect was negligible. …

Model Building In Multi-Factor Plant Nutrition Experiments, L. M. Olson, W. W. Stroup, E. T. Paparozzi, M. E. Conley

Conference on Applied Statistics in Agriculture

Often, the goal of plant science experiments is to model plant response as a function of quantitative treatment factors, such as the amount of nutrient applied. As the number of factors increases, modeling the response becomes increasingly challenging, especially since the resources available for such experiments are usually severely limited. Typical methods of analysis, notably second-order response surface regression, often fail to accurately explain the data. Alternatives such as non-linear models and segmented regression have been used successfully with two-factor experiments (Landes, et. aI, 1999). This paper extends previous work to three-and-more factor experiments. Models are assessed to explain the …

Designing Microarrays, B. A. Craig, O. Vitek, M. A. Black, M. Tanurdzic, R. W. Doerge

Conference on Applied Statistics in Agriculture

Microarrays allow the simultaneous assessment of expression levels for thousands of genes across various treatment conditions and time. It has been shown that in these experiments expression levels can also be affected by factors in the printing of the slide, in the hybridization process, and in the post-hybridization process. Recently, variations of the incomplete block design were proposed as a way to avoid confounding the expression levels of interest with several of these nuisance factors. In this paper, we propose additional design procedures to remove factors that contribute to the spatial variability on a slide. This approach requires the use …

Calculation Of The Minimum Number Of Replicate Spots Required For Detection Of Significant Gene Expression Fold Change In Microarra Y Experiments, Michael A. Black, R. W. Doerge

Conference on Applied Statistics in Agriculture

Calculations for the number of per gene replicate spots in microarray experiments are presented for the purpose of obtaining estimates of the sampling variability present in microarray data, and for determining the minimum number of replicate spots required to achieve a high probability of detecting a significant fold change in gene expression. Our approach is based on data from control microarrays, and employs standard statistical estimation techniques. We have demonstrated the usefulness of our framework by analyzing two experimental data sets containing control array data. The minimum number of replicate spots required on a treatment array were calculated to achieve …

Statistical Issues In The Analysis Of Microbial Communities In Soil, J. D. Wilbur, C. H. Nakatsu, S. M. Brouder, J. K. Ghosh, R. W. Doerge

Conference on Applied Statistics in Agriculture

Corn and soybean production dominates the agricultural systems of the mid-western United States. Studies have found that when a single crop species is grown continually, without the rotation of other crops, yield decline occurs. At present, this phenomenon, remains poorly understood, but there are possible links to microbial community dynamics in the associated rhizosphere soil. In this study, corn plants were grown in disturbed and undisturbed soils with a 24 year history of growth as a mono culture crop or two crops grown in annual rotation. Characteristic profiles of the microbial communities were obtained by denaturing gradient gel electrophoresis of …

Another Look At New Gma Orthogonal Arrays, Yingfu Li, Timothy Wittig

Conference on Applied Statistics in Agriculture

Non-regular factorial designs have not been advocated until last decade clue to their complex aliasing structure. However, some researchers recently found that the complex aliasing structure of non-regular factorial designs is a challenge as well as an opportunity. Li, Deng, and Tang (2000) studied nonl-regular designs and generated a collection of non-equivalent orthogonal arrays using a generalized miniumm aberration criterion, proposed by Deng and Tang (1999). Some new orthogonal arrays they found cannot be embedded into Hadamard matrices. In this paper, we study these orthogonal arrays from the angle of projection. We show that these new GMA orthogonal arrays are …

A Comparison Of Some Methods To Analyze Repeated Measures Ordinal Categorical Data, Yaobing Sui, Walter W. Stroup

Conference on Applied Statistics in Agriculture

Recent advances in statistical software made possible by the rapid development of computer technology in the past decade have made many new procedures available to data analysts. We focus in this paper on methods for ordinal categorical data with repeated measures that can be implemented using SAS. These procedures are illustrated using data from an animal health experiment. The responses, measured as severity of symptoms on an ordinal scale, are recorded for test animals over time. The experiment was designed to estimate treatment and time effects on the severity of symptoms. The data were analyzed with various approaches using PROC …

Assessing The Performance Of Closed-Form Approximations To The Reml Estimator Of Heritability, Brent D. Burch, Ian R. Harris

Conference on Applied Statistics in Agriculture

For many researchers the restricted maximum likelihood (REML) method of estimation is the procedure of choice for estimating heritability. In most applications the REML estimate can only be obtained via an iterative method. In some cases the algorithm used to compute the REML estimate may be slow or fail to converge. These predicaments have provided the motivation to develop closed-form approximations to the REML estimator of heritability in mixed linear models having two variance components. These estimators are compared to the REML estimator by considering their large and small sample properties. We provide guidance on how to select the closed-form …

Comparing Binomial Bootstrap And Bayesian Estimation Methods In Assessing The Agreement Between Classified Images And Ground Truth Data., Bahman Shafii, William J. Price

Conference on Applied Statistics in Agriculture

The degree of agreement between classification and ground truth in remotely sensed data is often quantified with an error matrix and summarized using agreement measures such as Cohen's kappa. In the case of ground truth however, the kappa statistic can be shown to be a transformation of the marginal proportions commonly referred to as omissional and commissional error rates. A more meaningful statistical interpretation of remote sensing results and less ambiguous conclusions can be obtained via direct utilization of these measures. Several estimation techniques have been suggested for these marginal proportions. In this study, we will develop the exact binomial, …

Papadakis Nearest Neighbor Analysis Of Yield In Agricultural Experiments, Radha G. Mohanty

Conference on Applied Statistics in Agriculture

Papadakis analysis, originally proposed by Papadakis in 1937 belongs to a larger class of methodologies called the nearest neighbor analysis which is primarily based on the fact that plots in close proximity ("neighbors") are exposed to similar environmental conditions and therefore, for a given plot, information from its neighboring plots could be used for adjustment of its response for spatial variability. The basic theory behind the application of Papadakis methodology to field trials is relatively simple. It is based on an analysis of covariance where the covariate is an index of fertility environment), and the response is some observable trait …