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Articles 1 - 15 of 15
Full-Text Articles in Agriculture
Estimating Area And Lag Associated With Thermal Hysteresis In Cattle, F. Yang, A. M. Parkhurst
Estimating Area And Lag Associated With Thermal Hysteresis In Cattle, F. Yang, A. M. Parkhurst
Conference on Applied Statistics in Agriculture
Thermal hysteresis in cattle becomes visible when the phase diagram of body temperature (Tb) vs ambient temperature (Ta) exhibits a loop. The hysteresis loop shows a rotated elliptical pattern which depends on the lag between Tb and Ta. The area of the loop can be used to quantify the amount of heat stress during thermal challenge. Three methods to estimate the area and lag of the elliptical hysteresis loop are: linear least squares method, ellipse-specific nonlinear least squares method, and Lapshin’s analytical method. Linear least squares method uses residual least squares to estimate the coefficients of the ellipse for which …
Comparison Of Linear Mixed Models For Multiple Environment Plant Breeding Trials, Carl A. Walker, Fabiano Pita, Kimberly Garland Campbell
Comparison Of Linear Mixed Models For Multiple Environment Plant Breeding Trials, Carl A. Walker, Fabiano Pita, Kimberly Garland Campbell
Conference on Applied Statistics in Agriculture
Evaluations of multiple environment trials (MET) often reveal substantial genotype by environment interactions, and the effects of genotypes within environments are often estimated using cell means, i.e. the simple mean of the observations of each genotype in each environment. However, these estimates are inaccurate, especially for unreplicated or partially replicated trials, so alternative methods of analysis are necessary. One possible approach utilizes information, often from pedigree data, about relationships among the tested genotypes through the use of a genetic relationship matrix (GRM). Predictive accuracy may also be improved by the use of factor analytic (FA) structures for environmental covariances. In …
A Hierarchical Bayesian Approach For Detecting Differential Gene Expression In Unreplicated Rna-Sequencing Data, Sanvesh Srivastava, R. W. Doerge
A Hierarchical Bayesian Approach For Detecting Differential Gene Expression In Unreplicated Rna-Sequencing Data, Sanvesh Srivastava, R. W. Doerge
Conference on Applied Statistics in Agriculture
Next-generation sequencing technologies have emerged as a promising technology in a variety of fields, including genomics, epigenomics, and transcriptomics. These technologies play an important role in understanding cell organization and functionality. Unlike data from earlier technologies (e.g., microarrays), data from next-generation sequencing technologies are highly replicable with little technical variation. One application of next-generation sequencing technologies is RNA-Sequencing (RNA-Seq). It is used for detecting differential gene expression between different biological conditions. While statistical methods for detecting differential expression in RNA-Seq data exist, one serious limitation to these methods is the absence of biological replication. At present, the high cost of …
Bootstrap Estimation And Comparison Of An Index Of Phylogenetic Correlation, William J. Price, Bahman Shafii, Carole B. Rapo, Sanford D. Eigenbrode, John Gaskin
Bootstrap Estimation And Comparison Of An Index Of Phylogenetic Correlation, William J. Price, Bahman Shafii, Carole B. Rapo, Sanford D. Eigenbrode, John Gaskin
Conference on Applied Statistics in Agriculture
A common objective of bioinformatic analyses is to assess the similarity of species, given a biological trait or characteristic. Phylogenetic correlation is one means to achieve this objective. Such measures provide a means to evaluate evolutionary models and history as well as having potential application to ecological relationships including host preference selection. Typically, these measurements are based on the deviation of an observed phylogeny from a Brownian evolutionary model. Statistical inference for this difference is assessed through likelihood ratio tests. These tests, in turn, rely on the assumption of a Normal likelihood within the phylogenetic trait. In addition, statistical comparison …
Modeling The Root-Knot Nematode/Nutsedge Pest Complex: Perspectives From Weed Science, Nematology And Statistics, Leigh Murray, Stephen H. Thomas, Jill Schroeder, Scott Kreider, Zhining Ou, J. M. Trojan, C. Fiore
Modeling The Root-Knot Nematode/Nutsedge Pest Complex: Perspectives From Weed Science, Nematology And Statistics, Leigh Murray, Stephen H. Thomas, Jill Schroeder, Scott Kreider, Zhining Ou, J. M. Trojan, C. Fiore
Conference on Applied Statistics in Agriculture
Previous research by the authors has established that southern root-knot nematode (SRKN, Meloidogyne incognita (Kofoid & White) Chitwood) and yellow and purple nutsedge (YNS, Cyperus esculentus L. and PNS, C. rotundus L.) form a pest-complex that adversely affects a wide variety of crops in the southern and western U.S. These pests appear to have co-evolved a mutually-beneficial relationship that promotes the survival of both nematodes and weeds to the detriment of crops. Traditional management has usually targeted one pest at a time, but managing this pest complex requires that all members of the complex be managed simultaneously. A series of …
Multi-Parental Mating Design Analysis: Model Evaluation And Application In Spring Wheat, M. Kadariya, K. D. Glover, J. Wu, J. L. Gonzalez
Multi-Parental Mating Design Analysis: Model Evaluation And Application In Spring Wheat, M. Kadariya, K. D. Glover, J. Wu, J. L. Gonzalez
Conference on Applied Statistics in Agriculture
Conventional quantitative genetics studies have mainly focused on bi-parental mating systems. However, genetic potential of selected individuals within a segregating population may be limited due to only two parents being used for each cross. Multiple-parental mating systems have been proposed that involve three or four diverse parents. This provides a higher potential of combining desirable genes. Due to complexity of the data structure of multi-parental mating systems, analysis of variance (ANOVA) methods are not applicable in analysis. The objective of this study is to validate and apply a mixed linear model approach, minimum norm quadratic unbiased estimation (MINQUE), to analyze …
Estimating The Subject By Treatment Interaction In Non-Replicated Crossover Diet Studies, Matthew Kramer, Shirley C. Chen, Sarah K. Gebauer, David J. Baer
Estimating The Subject By Treatment Interaction In Non-Replicated Crossover Diet Studies, Matthew Kramer, Shirley C. Chen, Sarah K. Gebauer, David J. Baer
Conference on Applied Statistics in Agriculture
Researchers in human nutrition commonly refer to the ‘consistent’ diet effect (i.e. the main effect of diet) and an ‘inconsistent’ diet effect (i.e. a subject by diet interaction). However, due to the non-replicated designs of most studies, one can only estimate the first part using ANOVA; the latter (interaction) is confounded with the residual noise. In many diet studies, it appears that subjects do respond differently to the same diet, so the subject by diet interaction may be large. In a search of over 40,000 published human nutrition studies, most using a crossover design, we found that in none was …
Probability Models To Study The Spatial Pattern, Abundance And Diversity Of Tree Species, D. M. Gowda
Probability Models To Study The Spatial Pattern, Abundance And Diversity Of Tree Species, D. M. Gowda
Conference on Applied Statistics in Agriculture
Ecological communities are composed of complex vegetation that differs from community to community and also within the community. The variability of tree species in the community in relation to their environments can be studied by using different statistical tools. The present study was conducted to describe and also to quantify the spatial pattern, abundance and diversity of tree species in the Western Ghats of Karnataka. The spatial pattern of tree species was studied by using Poisson and Negative binomial distributions. Results indicate that most of the selected tree species followed Negative binomial distribution having clumped pattern. The Species abundance distribution …
Spatio-Temporal Covariance Modeling With Some Arma Temporal Margins, Samuel Seth Demel, Juan Du
Spatio-Temporal Covariance Modeling With Some Arma Temporal Margins, Samuel Seth Demel, Juan Du
Conference on Applied Statistics in Agriculture
A valid covariance structure is needed to model spatio-temporal data in various disciplines, such as environmental science, climatology and agriculture. In this work we propose a collection of spatio-temporal functions whose discrete temporal margins are some autoregressive and moving average (ARMA) models, obtain a necessary and sufficient condition for them to be covariance functions. An asymmetric version of this model is also provided to account for space-time irreversibility property in practice. Finally, a spatio-temporal model with AR(2) discrete margin is fitted to wind data from Ireland for estimation and prediction, which are compared with some general existing parametric models in …
Logistic Regression Analysis To Determine Factors Contributing To Summer Feedlot Deaths, J. Clausen, A. M. Parkhurst, T. L. Mader
Logistic Regression Analysis To Determine Factors Contributing To Summer Feedlot Deaths, J. Clausen, A. M. Parkhurst, T. L. Mader
Conference on Applied Statistics in Agriculture
Summer heat has already been identified as a major factor for cattle deaths in the feedlot. This study attempts to assess what other factors contribute to and/or influence cattle deaths. Identifying multiple factors that contribute to summer feedlot deaths could aid feedlot managers in implementation of mitigation strategies and minimize the loss of nearly finished cattle. Daily pen, cattle, and nutritional characteristics were recorded and included in this generalized linear mixed model analysis. Cattle data were obtained from cattle pens at a single location from July 1, 2010 to July 31, 2010. Hourly weather data were acquired from this feed …
Confidence Intervals For Variance Components Using Non-Normal Distributions, Brent D. Burch
Confidence Intervals For Variance Components Using Non-Normal Distributions, Brent D. Burch
Conference on Applied Statistics in Agriculture
Simulation studies are conducted to evaluate the performance of confidence intervals for variance components under non-normal distribution assumptions. Confidence intervals based on the pivotal quantity (PQ) method and the large-sample properties of the restricted maximum likelihood (REML) estimator are considered. Of particular interest is the actual coverage value of nominal 95% confidence intervals for a ratio of variance components. In the context of unbalanced one-way random effects models, simulation results and an empirical example involving arsenic concentrations in oyster tissue suggest that the REML-based confidence interval is preferred.
Ordinary Least Squares Regression Of Ordered Categorical Data: Inferential Implications For Practice, Beth Larrabee, H. Morgan Scott, Nora M. Bello
Ordinary Least Squares Regression Of Ordered Categorical Data: Inferential Implications For Practice, Beth Larrabee, H. Morgan Scott, Nora M. Bello
Conference on Applied Statistics in Agriculture
Ordered categorical responses (OCRs) are frequently encountered in many disciplines. Examples of interest in agriculture include quality assessments, such as for soil or food products, and evaluation of lesion severity, such as teat ends status in dairy cattle. OCRs are characterized by multiple categories recorded on a ranked scale that, while apprising relative order, is not informative of absolute magnitude of or proportionality between the categories. A number of statistically sound models for OCRs are available in the statistical literature, such as logistic regression and probit models, but these are commonly underutilized in practice. Instead, the ordinary least squares linear …
Issues In Testing Dna Methylation Using Next-Generation Sequencing, Douglas Baumann, R. W. Doerge
Issues In Testing Dna Methylation Using Next-Generation Sequencing, Douglas Baumann, R. W. Doerge
Conference on Applied Statistics in Agriculture
DNA methylation is an epigenetic modification known to affect gene expression, cellular differentiation, as well as phenotypes. Recent advancements in next-generation sequencing technologies have provided unparalleled insight into the location and function of DNA methylation in a variety of organisms. These data require vastly different statistical procedures than data from previous genomic-based technologies. We outline the biological and chemical processes involved in several approaches for gaining DNA methylation data. The implications of the differences between the approaches are discussed relative to the statistical methodology, and the use of genome annotation is explored for the purpose of improving the statistical power …
Editor's Preface And Table Of Contents, Weixin Yao
Editor's Preface And Table Of Contents, Weixin Yao
Conference on Applied Statistics in Agriculture
These proceedings contain papers presented in the twenty-third annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, May 01 - May 03, 2011.
2011 Agricultural Research Southeast Agricultural Research Center, Kansas State University. Agricultural Experiment Station And Cooperative Extension Service
2011 Agricultural Research Southeast Agricultural Research Center, Kansas State University. Agricultural Experiment Station And Cooperative Extension Service
Kansas Agricultural Experiment Station Research Reports
No abstract provided.