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James F. Cahill and Eric G. Lamb

factors. In this article, we focus on competition and show how a wide range of complex interactions influence what was once thought to be a very straightforward process. Fig. 1. Plant performance (fitness, productivity, or yield) is affected by

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David B. Rubino

Suzy Flowers provided excellent technical support. Germplasm for this investigation was provided by J & L Plants, Amarillo, Texas; Earl J. Small Growers, Pinellas Park, Fla.; and Rosendals EX-PLANTS Aps., Assens, Denmark. I gratefully

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Ellen T. Paparozzi, Walter W. Stroup, and M. Elizabeth Conley

1 Dept. of Agronomy and Horticulture. For reprint requests, email address: etp1@unl.edu 2 Dept. of Statistics. Plant material was donated by Ecke's Poinsettias Inc. This article is submitted as Nebraska Agricultural Research Division journal series

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Cecil T. Pounders, Eugene K. Blythe, Donna C. Fare, Gary W. Knox, and Jeff L. Sibley

diverse environments produces an understanding of genotype × environment (G × E) interactions that affect performance of a particular clone. Such information is important to horticulturists and plant breeders for proper selection of the most appropriate

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Maria L. Burgos-Garay, Chuanxue Hong, and Gary W. Moorman

et al., 2010 ) and their interaction with plants. The coexistence of bacterial isolates that inhibit or enhance the growth of Pythium should be considered when investigating an ecosystem. Naturally occurring microorganisms have the ability to

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Virginia I. Lohr and Caroline H. Pearson-Mims

A nationwide phone survey of attitudes toward urban trees, participation in civic or educational activities, and memories of childhood experiences with gardening and nature was conducted with 2004 adults in large urban areas. We analyzed the influence of 11 childhood experiences and five adult demographic characteristics on three items: “Trees in cities help people feel calmer,” “Do trees have a particular personal, symbolic, or spiritual meaning to you?” and “During the past year, have you participated in a class or program about gardening?” Growing up next to natural elements such as flower beds, visiting parks, taking environmental classes, and gardening during childhood were associated with stronger adult attitudes and more actions. Growing up next to urban elements, such as large buildings, had a small, but opposite, influence. Demographics played a role in adult attitudes and actions. While both passive and active interactions with plants during childhood were associated with positive adult values about trees, the strongest influence came from active gardening, such as picking flowers or planting trees. These results indicate that horticultural programs for children raised in urban surroundings with few or no plants can be effective in fostering an appreciation for gardening in adults.

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Ellen T. Paparozzi, Walter W. Stroup, M. Elizabeth Conley, and Reid D. Landes

Horticulturists are often interested in evaluating the effect of several treatment factors on plant growth in order to determine optimal growing conditions. Factors could include three or more nutrient elements, or types and rates of irrigation, pesticides or growth regulators, possibly in combination with one another. Two problems with such experiments are how to characterize plant response to treatment combinations and how to design such experiments so that they are manageable. The standard statistical approach is to use linear and quadratic (a.k.a. response surface) regression to characterize treatment effects and to use response surface designs, e.g., central-composite designs. However, these often do a poor job characterizing plant response to treatments. Hence the need for more generally applicable methods. While our goal is to be able to analyze three and higher factor experiments, we started by tweaking two-factor nutrient analysis data. The result was a hybrid model which allows for a given factor to respond linearly or non-linearly. We will show how this was done and our current “in progress” model and analysis for analyzing three quantitative factors.

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M.P. Westcott, N.W. Callan, and M.L. Knox