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Full-Text Articles in Agriculture
After Further Review: An Update On Modeling And Design Strategies For Agricultural Dose-Response Experiments, M. J. Frenzel, W. W. Stroup, E. T. Paparozzi
After Further Review: An Update On Modeling And Design Strategies For Agricultural Dose-Response Experiments, M. J. Frenzel, W. W. Stroup, E. T. Paparozzi
Conference on Applied Statistics in Agriculture
Research investigating dose-response relationships is common in agricultural science. This paper is an expansion on previous work by Guo, et al. (2006) motivated by plant nutrition research in horticulture. Plant response to level of nutrient applied is typically sigmoidal, i.e. no response at very low levels, observable response at mid-levels, point-of-diminishing returns and plateau at high levels. Plant scientists need accurate estimates of these response relationships for many reasons, including determining the lower threshold below which plants show deficiency symptoms and the point of diminishing returns, above which excessive doses are economically and environmentally costly. Guo et al. presented models …
Tridimensional Regression, Kendra Schmid, David Marx, Ashok Samal
Tridimensional Regression, Kendra Schmid, David Marx, Ashok Samal
Conference on Applied Statistics in Agriculture
Shape analysis is useful for a wide variety of disciplines and has many applications. There are many different approaches to shape analysis, one of which focuses on the analysis of shapes that are represented by the coordinates of predefined landmarks on the object. This paper introduces Tridimensional Regression, a technique that can be used for mapping images and shapes that are represented by sets of three-dimensional landmark coordinates. The degree of similarity between shapes can be quantified using the tridimensional coefficient of determination (R2). An experiment was conducted to evaluate the effectiveness of this technique to correctly match …
A Comparison Of Models And Designs For Experiments With Nonlinear Dose-Response Relationships, Shengjie Guo, W. W. Stroup, E. T. Paparozzi, M. E. Conley
A Comparison Of Models And Designs For Experiments With Nonlinear Dose-Response Relationships, Shengjie Guo, W. W. Stroup, E. T. Paparozzi, M. E. Conley
Conference on Applied Statistics in Agriculture
Research investigating dose-response relationship is common in agricultural science. Animal response to drug dose and plant response to amount of irrigation, pesticide, or fertilizer are familiar examples. This paper is motivated by plant nutrition research in horticulture. Plant response to level of nutrient applied is typically sigmoidal, i.e. no response at very low levels, observable response at mid-levels, point-of-diminishing returns and plateau at high levels. Plant scientists need accurate estimates of these response relationships 1) to determine lower threshold below which plants show deficiency symptoms and 2) to determine upper point-of-diminishing returns, above which excessive doses are economically and environmentally …
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 …
Spline Models For Estimating Heat Stress Thresholds In Cattle, A. M. Parkhurst, D. A. Spiers, G. L. Hahn
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 …
Model Building In Multi-Factor Plant Nutrition Experiments, L. M. Olson, W. W. Stroup, E. T. Paparozzi, M. E. Conley
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 …
Estimation Of Kinetic Parameters Associated With Nutrient Uptake By An Intact Plant Root System, Edward Gbur, Craig Beyrouty
Estimation Of Kinetic Parameters Associated With Nutrient Uptake By An Intact Plant Root System, Edward Gbur, Craig Beyrouty
Conference on Applied Statistics in Agriculture
Several mechanistic models have been developed for the prediction of nutrient uptake at low concentrations from the soil by a plant root system. Claassen and Barber (1974 Plant Physiology 54, 564-568; 1976 Agronomy Journal 68, 961-964) presented an experimental procedure to obtain data from intact plants to fit an ion depletion curve and used the data in a model which they developed to predict nutrient uptake. Their model assumed that nutrient absorption from the soil solution followed Michaelis-Menten kinetics. In this paper, we develop a stochastic version of the Claassen-Barber model and illustrate its application to the estimation of the …
Nonlinear Regression Functions For Forage Nutrient Disappearance From Bags Incubated In The Rumen, W. J. E. Potts, B. P. Glenn, J. B. Reeves, R. A. Erdman
Nonlinear Regression Functions For Forage Nutrient Disappearance From Bags Incubated In The Rumen, W. J. E. Potts, B. P. Glenn, J. B. Reeves, R. A. Erdman
Conference on Applied Statistics in Agriculture
Seven nonlinear regression functions are compared for fitting rumen in situ disappearance data. The standard function is based on a simple one-compartment model. In addition, we consider a time lag modification, a two-compartment model, and functions based on underlying probability models for degradation time. The empirical suitability of the seven regression functions are assessed using two in situ experiments involving forages fed to dairy cows. A function based on the loglogistic distribution is shown to have empirical and theoretical advantages.
Nonlinear Estimation Of Growth Curve Models For Germination Data Analysis, Bahman Shafii, William J. Price, Jerry B. Swensen, Glen A. Murray
Nonlinear Estimation Of Growth Curve Models For Germination Data Analysis, Bahman Shafii, William J. Price, Jerry B. Swensen, Glen A. Murray
Conference on Applied Statistics in Agriculture
Logistic, Gompertz, Richards and Weibull growth curves were evaluated for their suitability as mathematical and empirical models to represent cumulative germination. By avoiding the limitations associated with the method of moments and single-value germination indices, the fitted models provided superior description of the time course of germination. The four-parameter Weibull model gave the best fit across a relatively wide range of seed species and germination conditions, and the resulting parameter estimates reflected identifiable aspects of the germination process. The nonlinear estimation of the germination response included a parameter summary, together with their asymptotic standard errors and correlation matrix, along with …