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Christopher J. Currey, Diane M. Camberato, Ariana P. Torres, and Roberto G. Lopez

comparisons between treatments using Tukey's honestly significant difference ( hsd ) test at P ≤ 0.05, and regression analysis were performed using SPSS (version 17.0; SPSS, Chicago). Table 2. The effect of substrate and plant growth retardant (PGR) drenches

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Omar A. Lopez, Danny L. Barney, Bahman Shafii, and William J. Price

light. Therefore, the objectives in conducting this research were to develop a regression model of the germination process for red huckleberry seeds and to use the regression model to assess the effects of temperature and GA concentration on cumulative

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Dana Sullivan, Jing Zhang, Alexander R. Kowalewski, Jason B. Peake, William F. Anderson, F. Clint Waltz Jr., and Brian M. Schwartz

the relationship between spectral reflectance and turfgrass cover and/or quality with regression, there is potential to reduce the number of visual ratings or photographic images needed in a large variety trial. Hybrid bermudagrasses have been widely

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Taun Beddes and Heidi A. Kratsch

-root transformation was used to achieve homogeneity of variance for nodule dry weight and nodule count before regression analyses. Analysis of NO 3 -N in the leachate from containers revealed that date of testing, treatment level, and their interaction were

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Qianni Dong, Xinwang Wang, David H. Byrne, and Kevin Ong

/ V P ( Hallauer et al., 2010 ). Narrow-sense heritability was also estimated by an offspring–midparent regression ( Connor et al., 2005 ), where h 2 = b = cov(O, MP)/cov(MP) ( Falconer and Mackay, 1996 ), i.e., the slope of the regression is then

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Timothy L. Grey, Keith Rucker, Lenny Wells, and Xuelin Luo

, data for each experiment were analyzed separately. All data were subjected to analysis of variance using the PROC MIXED procedure to test for interactions between treatments for leaf chlorosis, necrosis, and height measures. Linear regression analysis

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Keng Heng Chang, Kuan Ting Chang, Ren Shih Chung, Chun Tang Lu, and Ting Fang Hsieh

, dry weight, and length of all new roots were recorded. The data obtained were subjected to a linear regression analysis of grid number vs. each of the root growth parameters. The predictive equations were selected based on the combination of the

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Thomas E. Marler and Christopher A. Shaw

seeds without fully developed embryos. Gametophyte tissue was stored, processed, and analyzed as in Study 1. Statistical analysis. Study 1 data were subjected to a multiple linear regression model using a SAS macro application REGDIAG ( Fernandez, 2002

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Ibrahim Demir, B. Begüm Kenanoglu, Kazim Mavi, Tuba Celikkol, Fiona Hay, and Zeliha Sariyildiz

quantified using linear regression SPSS (9.05; SPSS Inc., Chicago, IL) of log σ versus log MC fitting the equation: K E was then calculated using the universal values for C H and C Q in the following equation: Validation of the constants. A separate

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Youbin Zheng and Mary Jane Clark

Dolime Spray Lime, Genoa, OH) was added at rates pre-determined by regression analysis following laboratory titrations (data not shown). To reduce experimental error in this study, rates of hydrated lime were separately incorporated into pre