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Articles 15871 - 15900 of 16621
Full-Text Articles in Physical Sciences and Mathematics
Foreword And Kfgc Award Winners [2004], Garry D. Lacefield, Christi L. Forsythe
Foreword And Kfgc Award Winners [2004], Garry D. Lacefield, Christi L. Forsythe
Kentucky Grazing Conference
No abstract provided.
A Comparison Of Geostatistical And Spatial Autoregressive Approaches For Dealing With Spatially Correlated Residuals In Regression Analysis For Precision Agriculture Applications, Ignacio Colonna, Matías Ruffo, Germán Bollero, Don Bullock
A Comparison Of Geostatistical And Spatial Autoregressive Approaches For Dealing With Spatially Correlated Residuals In Regression Analysis For Precision Agriculture Applications, Ignacio Colonna, Matías Ruffo, Germán Bollero, Don Bullock
Conference on Applied Statistics in Agriculture
Regressions such as Grain yield=f(soil,landscape) are frequently reported in precision agriculture research, and are typically computed using conventional OLS methods, implicitly ignoring spatial correlation of the residuals. This oversight can have a marked effect on the final conclusions derived from these regressions. A further issue is, which approach should be used to account for this problem? We investigated this question using a 2 year data set that includes sitespecific soil and topographic information and soybean yields and compare regression results from direct covariance representation and spatial autoregressive approaches. Our results show that the coefficients from both spatial approaches are in …
Distribution Of Boll Number And Lint Yield By Time And Position In Upland Cotton Cultivators, Jixiang Wu, Johnie N. Jenkins, Jack C. Mccarty Jr.
Distribution Of Boll Number And Lint Yield By Time And Position In Upland Cotton Cultivators, Jixiang Wu, Johnie N. Jenkins, Jack C. Mccarty Jr.
Conference on Applied Statistics in Agriculture
The time period and position which make the major contribution to total yield and to its variation is important for the field management and breeding for upland cotton, Gossypium hirsutum, L. Two-year end-of-season plant mapping data from 11 upland cotton cultivars were analyzed by position and by week. The data showed that the first position in the second and third weeks made the largest contribution to the total boll number and lint yield. The eleven cultivars differed with respect to the earliness but they had similar lint yield at harvest. The early season cultivars produce more yield and more …
Identification Of Errors In Cotton Fiber Data Sets Using Bayesian Networks, G F. Sassenrath, J. E. Boggess, Xintong Bi, H. C. Pringle
Identification Of Errors In Cotton Fiber Data Sets Using Bayesian Networks, G F. Sassenrath, J. E. Boggess, Xintong Bi, H. C. Pringle
Conference on Applied Statistics in Agriculture
Cotton fiber is graded on a series of parameters based on physiological factors (strength, length, and thickness), lint color, and presence of non-lint matter such as leaves, stems or other foreign materials. Cotton lint is graded by the USDA-AMS after harvest and ginning, and the grade determines the price of the lint. Given the importance of cotton fiber quality to the value of the crop, the spatial variability of cotton fiber properties is of particular interest to researchers and producers in developing management scenarios for optimal profitability. Previous research studies have relied on hand-harvesting the cotton at intervals throughout the …
Conditioning Plots And Designed Experiments, Jeffrey S. Pontius, John W. Slocombe, John E. Boyer, Jr.
Conditioning Plots And Designed Experiments, Jeffrey S. Pontius, John W. Slocombe, John E. Boyer, Jr.
Conference on Applied Statistics in Agriculture
Conditioning plots (coplots) are useful graphics for displaying values of response variables conditional on the values of given (conditioning) variables. We present a principles guide for construction of coplots when the data or statistics come from studies based on designed experiments, and illustrate the usefulness of these coplots in interpreting results. We have found coplots to be useful in our statistical consulting work, and illustrate our approach so that others may find them useful. Coplots in traditional and in trellis displays are provided.
An Example Of Developing Covariates For Problems In Precision Agriculture, D. W. Meek, J. W. Singer
An Example Of Developing Covariates For Problems In Precision Agriculture, D. W. Meek, J. W. Singer
Conference on Applied Statistics in Agriculture
Methodology for precision agriculture is, perhaps, too focused on methods that allow for spatial correlation in the ANOVA error term. While sound inference about differences between local yields can be computed, no understanding of what is driving these differences is achieved. A completely general form for a spatial model can include suitable covariates. Most research in precision agriculture includes gathering a variety of site-specific information. Through the presentation of the analysis of data from a published soybean [Glycine max (L.) Merr.] study, one specific type of covariate is developed - a duration index for soybean canopy light interception over …
Nonlinear Models With Repeated Measures For Analyzing Disease Progress In Plant Epidemiology, R. Macchiavelli, W. Robles, E. Abreu, A. Pantoja
Nonlinear Models With Repeated Measures For Analyzing Disease Progress In Plant Epidemiology, R. Macchiavelli, W. Robles, E. Abreu, A. Pantoja
Conference on Applied Statistics in Agriculture
Nonlinear models are commonly used in plant disease epidemiology to model temporal changes in the proportion of diseased plants (disease index). Most of the times they are fit using linearizing transformations or nonlinear least squares. These approaches assume that the disease index has a normal distribution, that they are independent and that they have constant variance. None of these assumptions can be justified in disease indices. In this paper we apply different strategies to model the progress of papaya ring spot virus in papaya. Using the logistic model we compare different strategies using the SAS® System. Marginal (population average) and …
Hotelling’S T2 Approximation For Bivariate Mixed (Dichotomous & Continuous) Data, Imad Khamis, Pradeep Singh, James Higgins
Hotelling’S T2 Approximation For Bivariate Mixed (Dichotomous & Continuous) Data, Imad Khamis, Pradeep Singh, James Higgins
Conference on Applied Statistics in Agriculture
The comparison of the means of two treatments or populations when more than one variable is measured may be done using Hotelling’s T2 statistic. In many real world situations the data obtained are mixed, i.e. one variable is dichotomous and the other variable is continuous. The assumption of multivariate normality upon which Hotelling’s T2 is based is no longer valid. In this paper, an approximate Hotelling T2 test is proposed for bivariate mixed data and empirically evaluated in terms of Type I error rate. It is shown that the approximation does a good job of controlling the …
Analyzing Binomial Data In A Split-Plot Design: Classical Approaches Or Modern Techniques?, Liang Fang, Thomas M. Loughin
Analyzing Binomial Data In A Split-Plot Design: Classical Approaches Or Modern Techniques?, Liang Fang, Thomas M. Loughin
Conference on Applied Statistics in Agriculture
Binomial data are often generated in split-plot experimental designs in agricultural, biological, and environmental research. Modeling non-normality and random effects are the two major challenges in analyzing binomial data in split-plot designs. In this study, seven statistical methods for testing whole-plot and subplot treatment effects using mixed, generalized linear, or generalized linear mixed models are compared for the size and power of the tests. This study shows that analyzing random effects properly is more important than adjusting the analysis for non-normality. Methods based on mixed and generalized linear mixed models hold Type I error rates better than generalized linear models. …
Comparing Analyses Of Unbalanced Split-Plot Experiments, Christina D. Smith, Dallas E. Johnson
Comparing Analyses Of Unbalanced Split-Plot Experiments, Christina D. Smith, Dallas E. Johnson
Conference on Applied Statistics in Agriculture
Several procedures for constructing confidence intervals and testing hypotheses about fixed effects in unbalanced split-plot experiments have previously been presented and discussed by Remmenga and Johnson. They recommended a few of the procedures they considered as useful and reliable procedures. Since the advent of the SAS® MIXED procedure, mixed model analyses with REML estimates of the variance components are easily accessible to researchers. This paper compares the analysis of unbalanced split-plot experiments using mixed model procedures with REML estimates of the variance components to the previously established procedures by means of additional simulation studies.
Estimating Rheological Properties Of Yogurt Using Different Versions Of The Freundlich Model And Design Matrices, M. Zhou, A. M. Parkhurst, H. K. Voss, C. L. Weller
Estimating Rheological Properties Of Yogurt Using Different Versions Of The Freundlich Model And Design Matrices, M. Zhou, A. M. Parkhurst, H. K. Voss, C. L. Weller
Conference on Applied Statistics in Agriculture
The rheological properties described by the consistency coefficient and flow behavior index can be estimated from the relationship between shear stress and shear strain rate following a Freundlich model. An additional rheological property of concern to food scientists studying yogurt is yield stress. They extend the Freundlich model to include a three-parameter model called the Herschel-Bulkley model. In addition, the Herschel-Bulkley model is often linearized by taking logarithms of both sides. An additional complication is the viscometer limits the range of shear strain rates. The objectives of this study are to compare parameter estimates from the three models and to …
Statistical Analysis Of 70-Mer Oligonucleotide Microarray Data From Polyploid Experiments Using Repeated Dye-Swaps, Hongmei Jiang, Jianlin Wang, Lu Tian, Z. Je Rey Chen, R. W. Doerge
Statistical Analysis Of 70-Mer Oligonucleotide Microarray Data From Polyploid Experiments Using Repeated Dye-Swaps, Hongmei Jiang, Jianlin Wang, Lu Tian, Z. Je Rey Chen, R. W. Doerge
Conference on Applied Statistics in Agriculture
Polyploidy plays an important role in plant evolution. A series of Arabidopsis autopolyploids and allopolyploids have been developed, and their transcript abundance compared using a 70-mer oligonucleotide microarray consisting of 26,090 annotated genes in Arabidopsis thaliana. The experimental design included repeated dye-swaps, and analysis of variance (ANOVA) was employed to detect significant gene expression changes among and between the diploid, autopolyploid, and allopolyploid populations. Here, we discuss the statistical issues (replication, normalization, transformation, per-gene variance estimate, and the pooled estimate of variation) involved in analyzing these data, as well as the statistical findings of these analyses.
Introduction To Bayesian Quantitative Trait Locus Analysis For Polyploids, Dachuang Cao, Bruce A. Craig, R. W. Doerge
Introduction To Bayesian Quantitative Trait Locus Analysis For Polyploids, Dachuang Cao, Bruce A. Craig, R. W. Doerge
Conference on Applied Statistics in Agriculture
Quantitative Trait Locus (QTL) mapping in polyploids is complicated by the un-observable parental QTL con guration, especially the number of copies (dosage) of the QTL. Existing techniques estimate the parental QTL con guration using a profile likelihood approach and do not address the uncertainty in the estimates. In this paper, a Bayesian method is proposed to jointly model the parameters including the parental QTL configuration, QTL location, and QTL effects. Inference for parameters is obtained by integrating the posterior distribution of the parameters via a Markov chain Monte Carlo (MCMC) sampler, which is a hybrid of the Metropolis-Hastings, Gibbs, and …
Some Results On The Design Of Experiments For Comparing Unreplicated Treatments, R. J. Martin, J. A. Eccleston, N. Chauhan, B. S. P. Chan
Some Results On The Design Of Experiments For Comparing Unreplicated Treatments, R. J. Martin, J. A. Eccleston, N. Chauhan, B. S. P. Chan
Conference on Applied Statistics in Agriculture
In early generation variety trials, large numbers of new varieties may be compared, and little seed is usually available for each variety. A so-called unreplicated trial has each new variety on just one plot at a site, but includes several (often around 5) replicated check or control (or standard) varieties. The total proportion of check plots is usually between 10% and 20%. The aim of the trial is to choose some (around 1/3) good performing varieties to go on for further testing, rather than precise estimation of their mean yield.
Now that spatial analyses of data from field experiments are …
Statistical Analysis Software For Multiplicative Interaction Models, Eun-Joo Lee, Dallas E. Johnson
Statistical Analysis Software For Multiplicative Interaction Models, Eun-Joo Lee, Dallas E. Johnson
Conference on Applied Statistics in Agriculture
In a two-way cross-classified experiment, one is almost always interested in whether the two factors interact or not. When there are no independent replications, there are no traditional tests for interaction. This research considers the problem of analyzing a two-way cross-classified experiment using multiplicative interaction models when there are no independent replications and interaction between the two factors may exist. The purpose of this research is to develop SAS® macros to provide user-friendly statistical software for the analysis of interaction in two-way experiments. The macros also provide many useful graphical displays including displays to help one determine the pattern of …
Automatic Model Selection In The Mixed Models Framework, Matthew Kramer
Automatic Model Selection In The Mixed Models Framework, Matthew Kramer
Conference on Applied Statistics in Agriculture
Stepwise model selection is a commonly used technique in regression when there are many candidate independent variables and limited time to develop a model. This approach was adapted to the mixed models framework and gives good results, established by simulation with a known model and by application to real world data. Model selection is done using an information criterion (selected by the user). The application is primarily written in Perl. The Perl code tracks which variables are in or out of the model, calculates the information criterion, and writes and submits SAS code. Proc Mixed in SAS is used to …
The Onset, Cessation, And Rate Of Growth Of Loblolly Pines In The Face Experiment, Susanne Aref, David J. Moore, Evan H. Delucia
The Onset, Cessation, And Rate Of Growth Of Loblolly Pines In The Face Experiment, Susanne Aref, David J. Moore, Evan H. Delucia
Conference on Applied Statistics in Agriculture
The Duke Forest FACE experiment was set up to investigate the impact of elevated CO2 levels on a larger eco system. One of the studies dealt with the impact of elevated CO2 levels on the onset and cessation of growth of loblolly pine trees (Pinus taeda L.). In this study the times of these events were determined for each year, 1996 - 2002. The rate of growth, the growth duration, and actual growth were determined from the models of onset and cessation of growth. Adjusted for initial basal area, the rate of growth, the actual growth, …
Genetic Mapping Of Gene Expression Levels: Expression Level Polymorphism Analysis For Dissecting Regulatory Networks Of Plant Disease Resistance, Kyunga Kim, Marilyn A. L. West, Richard W. Michelmore, Dina A. St. Clair, R. W. Doerge
Genetic Mapping Of Gene Expression Levels: Expression Level Polymorphism Analysis For Dissecting Regulatory Networks Of Plant Disease Resistance, Kyunga Kim, Marilyn A. L. West, Richard W. Michelmore, Dina A. St. Clair, R. W. Doerge
Conference on Applied Statistics in Agriculture
The genetic basis of inherited traits has been studied through di erent approaches in many areas of science. Examples include quantitative trait locus (QTL) analysis and mutant analysis in genetics, genome sequencing and gene expression analysis in genomics. Each of these approaches is used for the investigation of complex traits, such as disease resistance, but also provides knowledge on components of complex biological systems. We introduce a novel functional genomics approach that integrates two areas, genetics and genomics, by applying QTL analysis to quantitative di erences in the mRNA abundance of trait-related genes. This approach allows comprehensive dissection of regulatory …
Prediction Of Yellow Starthistle Survival And Movement Over Time And Space, Fei Tian, Bahman Shafii, Christopher J. Williams, Timothy S. Prather, William J. Price, Lawrence W. Lass
Prediction Of Yellow Starthistle Survival And Movement Over Time And Space, Fei Tian, Bahman Shafii, Christopher J. Williams, Timothy S. Prather, William J. Price, Lawrence W. Lass
Conference on Applied Statistics in Agriculture
Yellow starthistle is a noxious weed that has become a serious plant pest with devastating impact on ranching operation and natural resources in western states. Early detection of yellow starthistle and predicting its spread has important managerial implications and greatly reduce the economic losses due to this weed. The dispersal of yellow starthistle consists of two main components, plant survival and seed movement. Resources and direct factors relating to these components are not typically available or are difficult to obtain. Alternatively, topographic factors, such as slope, aspect and elevation, are readily available and can be related to plant survival and …
Information Technologies And The Design And Analysis Of Site-Specific Experiments Within Commercial Cotton Fields, J. L. Willers, G. A. Milliken, C. G. O’Hara, J. N. Jenkins
Information Technologies And The Design And Analysis Of Site-Specific Experiments Within Commercial Cotton Fields, J. L. Willers, G. A. Milliken, C. G. O’Hara, J. N. Jenkins
Conference on Applied Statistics in Agriculture
Information products derived from multi-spectral remote sensing images, LIDAR elevations, or data products from other sensor systems (soil electrical conductivity measurements, yield monitors, etc.) characterize potential crop productivity by mapping biophysical aspects of cropland variability. These sensor systems provide spectral, spatial, and temporal measurements at resolutions and accuracies describing the variability of in-field, physical characteristic phenomena, including management practices from cropland preparation, selection of crop cultivars, and variable-rate applications of inputs. In addition, DGPS-equipped (differential, global positioning system) harvesters monitor yield response at closely spaced, georeferenced points. Geographic information system and image processing techniques fuse diverse information sources to spatially …
A Comparison Of Spatial Prediction Methods Using Intense Spatially-Acquired Water Quality Data, E. Barry Moser, Victor H. Rivera-Monroy, Ariel R. Alcantara-Eguren
A Comparison Of Spatial Prediction Methods Using Intense Spatially-Acquired Water Quality Data, E. Barry Moser, Victor H. Rivera-Monroy, Ariel R. Alcantara-Eguren
Conference on Applied Statistics in Agriculture
Water quality information obtained through intensive spatial sampling using automated devices provides opportunities to monitor and forecast the spatial distribution of nutrients and phytoplankton concentrations, and help establish water circulation patterns in estuarine and coastal waters. To be cost effective, efficient sampling designs and estimation methodologies must first be developed. As a starting basis, we applied an original transect sampling design that was used to estimate the spatial distribution of chlorophyll a, salinity, and temperature in the Cienaga Grande de Santa Marta, a coastal lagoon in Colombia. We superimposed the transects over satellite images of the lagoon obtained in the …
Random Models With Direct And Competition Genetic Effects, L. , D. Van Vleck, J. P. Cassady
Random Models With Direct And Competition Genetic Effects, L. , D. Van Vleck, J. P. Cassady
Conference on Applied Statistics in Agriculture
Livestock producers often select for animals which are genetically superior for yield. Competition among animals in the same pen may affect yield of pen mates. If competitiveness has a genetic component, selection should be for direct genetic effects for yield and for genetic effects of competitiveness on yield of penmates (Muir and Schinkel, 2002). This simulation study examined estimates of variance components from models which ignored competition effects. A population structure of 642 related animals was created. Random effects were residual and pen effects and direct and competition genetic values with genetic correlation. Conclusions, based on 400 replications for 16 …
Applications Of Statistical Data Mining Methods, George Fernandez
Applications Of Statistical Data Mining Methods, George Fernandez
Conference on Applied Statistics in Agriculture
Data mining is a collection of analytical techniques to uncover new trends and patterns in large databases. These data mining techniques stress visualization to thoroughly study the structure of data and to check the validity of statistical model fit to the data and lead to knowledge discovery. Data mining is an interdisciplinary research area spanning several disciplines such as database management, machine learning, statistical computing, and expert systems. Although data mining is a relatively new term, the technology is not. Data mining allows users to analyze data from many different dimensions or angles, explore and categorize it, and summarize the …
Editor's Preface And Table Of Contents, George A. Milliken
Editor's Preface And Table Of Contents, George A. Milliken
Conference on Applied Statistics in Agriculture
These proceedings contain papers presented in the sixteenth annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 25-27, 2004.
Photos Of The 24th Kentucky Alfalfa Conference Award Winners, Kentucky Alfalfa Conference
Photos Of The 24th Kentucky Alfalfa Conference Award Winners, Kentucky Alfalfa Conference
Kentucky Alfalfa and Stored Forage Conference
No abstract provided.
Moisture--Temperature Management During Alfalfa Hay And Silage Making & Storing, Michael Collins
Moisture--Temperature Management During Alfalfa Hay And Silage Making & Storing, Michael Collins
Kentucky Alfalfa and Stored Forage Conference
In some areas of the country, producers store a substantial portion of their forage for winter feeding as silage or haylage. However, hay remains the most popular storage method for forage. Hay stores well for long periods and is better suited to cash sale and transportation than silage. Mechanical conditioning, which gained acceptance during the 1950's is probably still the greatest single change in hay harvesting and storage technology during this century. However, a number of other noteworthy changes and innovations have occurred in recent years which have helped to reduce the extent of losses during hay harvesting and storage.
Marketing Kentucky Alfalfa, Nicky Baker
Marketing Kentucky Alfalfa, Nicky Baker
Kentucky Alfalfa and Stored Forage Conference
The main key to marketing hay over the years is flexibility. Don’t gear up too heavy for the one specific market. Keep your options open and remember there aren’t any government payments.
Marketing Kentucky Alfalfa, Tom Keene
Marketing Kentucky Alfalfa, Tom Keene
Kentucky Alfalfa and Stored Forage Conference
In order to market Kentucky produced alfalfa, we need to go back and look at our operation to see if we can produce high quality alfalfa. We can start doing this by determining what the best land use is given the particular soils and typography that makes up your farm layout. There are other things we need to be aware of after we determine our ability to grow alfalfa; is the terrain suitable for harvesting alfalfa using different types of harvesting equipment? Also do we have the equipment necessary to produce alfalfa, either as a grazing tool, grass hay or …
Balancing Agronomics And Economics Of Alfalfa Hay Production, Brian Lacefield, Garry D. Lacefield
Balancing Agronomics And Economics Of Alfalfa Hay Production, Brian Lacefield, Garry D. Lacefield
Kentucky Alfalfa and Stored Forage Conference
Alfalfa has high-yielding, high-quality, persistent, and profitable potential if given adequate management and a balance of several agronomic and economic considerations. How can we account for the differences among producers who have the average alfalfa yields of 3.0 tons/A with the top hay producers who average approximately 5.0 tons/acre and the producer who has achieved the record yield of 10.13 tons/acre? Is the answer “luck”, better soils, moisture and growing conditions? The answer may certainly be yes, but. Yes, the factors above are important and can explain some differences; however, we believe the overall difference is the management of research-based …
Hybrid Alfalfa: Reality Or Pipe Dream? Dairyland Seed Company, Michael Velde
Hybrid Alfalfa: Reality Or Pipe Dream? Dairyland Seed Company, Michael Velde
Kentucky Alfalfa and Stored Forage Conference
Progress in increasing alfalfa forage yield has been minimal over the past 20 years. This is due primarily to lack of pollen control in open pollinated synthetic varieties. All alfalfa varieties to date have been open pollinated synthetic varieties. New alfalfa hybridization technology provides the tools to overcome the forage yield barriers that have been hindering alfalfa breeders from making progress