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Kristen R. Hladun and Lynn S. Adler

) and subsequent univariate analyses of variance (ANOVA) using SAS (2003; SAS Institute, Cary, NC) were used to determine the effects of pollen composition, pollen amount, and their interaction on butternut squash fruit and seed production. All data were

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Matthew A. Cutulle, Howard F. Harrison Jr., Chandresakar S. Kousik, Phillip A. Wadl, and Amnon Levi

accessions with at least four plants were subjected to analysis of variance (ANOVA) and the lsd 0.05 was determined. Data for all visual ratings were converted to percentages and then subjected to arcsine transformation before ANOVA using Proc Mix in SAS

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A.W. Fleener, C.W. Robinson, J.D. Williams, and M. Kraska

posttests ( Tables 1 and 2 ), whereas one-way analyses of variance (ANOVA) tests were used to determine if there were any significant differences between the experimental and control groups before ( Table 3 ) and after ( Table 4 ) treatment. Additionally

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Peng Shi, Yong Wang, Dapeng Zhang, Yin Min Htwe, and Leonard Osayande Ihase

-related traits among these germplasms were observed and then analyzed using cluster, analysis of variance (ANOVA), correlation, path, and regression analysis, respectively. Furthermore, FOC prediction was constructed and validated for germplasm evaluation. The

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Lucia E. Villavicencio, James A. Bethke, and Lea Corkidi

number of flowers were assessed weekly for an additional 8 weeks. Fruit yield was also determined by harvesting, counting, and weighing all fruit produced per plant, 5 to 12 WAT. Data analysis A two-way analysis of variance (ANOVA) was used to analyze the

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Harbans L. Bhardwaj and Anwar A. Hamama

). Protein concentration was calculated as N × 6.25. These analyses were only conducted with seed produced during 2013. All data were analyzed using the analysis of variance (ANOVA) procedures in SAS (version 9.4; SAS Institute, Cary, NC). Means were

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Verónica De Luca, Diego Gómez de Barreda, Antonio Lidón, and Cristina Lull

interval period was subjected to a three-way repeated measures analysis of variance (ANOVA) to evaluate the effects of treatment, nutritional stress, and time on turf quality, color, growth, and clippings’ dry weight. When a significant three

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Michael J. Costello

variance (ANOVA) using year or date as the repeated-measures (“within-subjects”) variable using orthogonal contrasts for mean separation (PROC GLM; SAS Institute, 2003 ). Differences between means were considered significant with P < 0.05. Regression

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Drew C. Zwart and Soo-Hyung Kim

set at 0.05 for all treatment comparisons. Lesion size, biomass, and stem water potential were analyzed by one-way analysis of variance (ANOVA) with soil treatment (biochar amendment or chemical) as the main factor. When data failed the Shapiro

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Xiaoling He, Susan C. Miyasaka, Maureen M.M. Fitch, Sawsan Khuri, and Yun J. Zhu

complete block design. After inoculation, plantlets were observed daily for lesion initiation for 30 d. At 12 d, the lesion diameters were measured, averaged across three plantlets, and analyzed statistically by analysis of variance (ANOVA). The general