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Mohsen Mohseni-Moghadam, Christopher S. Cramer, Robert L. Steiner and Rebecca Creamer

. The Proc General Linear Models (GLM) procedure in SAS (SAS 9.0; SAS Institute Inc., Cary, NC) was used to determine if there were differences among entries in different years, sample methods, and their interactions for disease severity and incidence

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Jianguo Li, Hong Zhu and Rongcai Yuan

analyses. Statistical analyses were for a randomized complete block design and included analysis of variance and Duncan's multiple range test. General linear model (GLM) procedure of SAS (Version 9.1 for Windows; SAS Institute, Cary, NC) was applied to

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Elizabeth A. Baldwin, John W. Scott and Jinhe Bai

the CIE L*, a*, b* system including chroma and hue ( Baldwin et al., 1991 ). Statistical analyses. SAS (version 9.3; SAS Institute, Cary, NC) was used for data analysis. Analysis of variance (ANOVA) was performed by using the general linear model (GLM

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Sudeep S. Sidhu, Qingguo Huang, Robert N. Carrow and Paul L. Raymer

to evaluate the main effects of treatment duration, treatments, and interaction effects of duration × treatment using a general linear model (GLM) ( SAS Institute Inc., 1994 ). Treatments were combined into five groups and analyzed as repeated

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James A. Poss, Walter B. Russell, Stacy A. Bonos and Catherine M. Grieve

the 0- to 30-cm sand depths. Roots were washed in tap water and collected in a series of screens ending with a 150-μm mesh, then dried at 60 °C, and weighed. Analysis of variance was performed with the general linear models (GLM procedure) and

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Zhengli Zhai, David L. Ehret, Tom Forge, Tom Helmer, Wei Lin, Martine Dorais and Athanasios P. Papadopoulos

capacities in the bacterial community. The time integral of average absorbance per positive substrate and the number of substrates used were the parameters that were analyzed statistically. Statistical analysis. The data were analyzed using the General Linear