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Rangjian Qiu, Taisheng Du, Shaozhong Kang, Renqiang Chen, and Laosheng Wu

A ), but no significant differences were found for the slopes of the regression equations. The daily stem sap flow (SF) increased linearly with REW (SF = 2.56 REW –0.13; R 2 = 0.79). During the water deficit period, the ratio of daily stem sap flow

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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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Maksut Barış Eminoğlu, Uğur Yegül, and Kamil Sacilik

content, and M o = initial moisture content. Because the relative humidity is continuously fluctuating within the dryer, M R was reduced to M / M 0 ( Diamente and Munro, 1993 ). A nonlinear regression procedure was used to calculate rate constants

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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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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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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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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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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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Gitta Shurberg, Amy L. Shober, Christine Wiese, Geoffrey Denny, Gary W. Knox, Kimberly A. Moore, and Mihai C. Giurcanu

. Mean values were then used in regression analysis using PROC REG (SAS version 9.2; SAS Institute, Cary, NC) to determine the effect of annual fertilizer N rate on each plant response indicator. Linear and polynomial regression models were fitted by

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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