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John M. Kauffman, John C. Sorochan, and Dean A. Kopsell

Thatch-mat and organic matter (OM) accumulation near the putting green soil surface impacts soil physical properties and turf performance. Excessive thatch and OM can encumber infiltration of water and oxygen into the soil profile and slow drainage of excess water away from the putting surface. Proper sampling of thatch-mat depths and OM contents is vital for management of putting green turf; therefore, a study was performed in Knoxville, TN, to derive proper sampling procedures of these important parameters using ‘TifEagle’ and ‘Champion’ bermudagrass (Cynodon dactylon × C. transvaalensis), ‘SeaDwarf’ seashore paspalum (Paspalum vaginatum), and ‘Diamond’ zoysiagrass (Zoysia matrella). ‘TifEagle’ and ‘Champion’ accumulated thatch-mat to a greater depth than ‘SeaDwarf’ and ‘Diamond’. However, ‘SeaDwarf’ had a higher OM content than ‘Diamond’ and both had higher OM contents than ‘TifEagle’ and ‘Champion’. Data generated from sampling procedures indicate that previous studies often undersampled plots for thatch-mat depth; however, previous sampling procedures have not traditionally undersampled plots for OM. Data in this study provide a range of confidence and minimum detectable difference levels which may allow future researchers to more accurately sample ‘TifEagle’, ‘Champion’, ‘SeaDwarf’, and ‘Diamond’ putting green plots for thatch-mat depth and OM content.

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Mark V. Yelanich and John A. Biernbaum

A model constructed to describe nitrogen dynamics in the root zone of subirrigated container-grown chrysanthemum was used to develop and test nitrogen fertilization strategies. The model predicts the nitrogen concentration in the root zone by numerical integration of the rates of nitrogen applied, plant nitrogen uptake, and nitrogen movement to the medium top layer. The three strategies tested were constant liquid N fertilization, proportional derivative control (PD) based upon weekly saturated medium extraction (SME) tests, or PD control based upon daily SME tests. The optimal concentration of N to apply using a single fertilization concentration was 14 mol·m–3, but resulted in greater quantities of N being applied than if PD controller strategies were used. The PD controllers were better able to maintain the predicted SME concentration within 7 to 14 mol·m–3 optimal range and reduce the overall sample variability over time. Applying 14 mol·m–3 N at every irrigation was found to be an adequate fertilization strategy over a wide range of environmental conditions because N was applied in excess of what was needed by the plant.

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Marivi Colle, Elizabeth N. Straley, Stephanie B. Makela, Sue A. Hammar, and Rebecca Grumet

plants, it is possible that a mixed disease response could result from variability within the PI sample. Variability within cucurbit PI accessions for disease resistance responses has been observed frequently (e.g., Davis et al., 2007 ; Donahoo et al

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Paraskevi A. Londra, Maria Psychoyou, and John D. Valiantzas

were applied through the saturated tension plate. Initially, the θ ( h ) were measured followed by the one-step outflow experiment in the same substrate sample in the same apparatus to avoid the effect of sample variability in the obtained results by

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Sharon J.B. Knewtson, Rhonda Janke, M.B. Kirkham, Kimberly A. Williams, and Edward E. Carey

Longnecker (2001) , we calculated that a sample size of 25 high tunnel and adjacent field pairs would be needed to measure a 5% mean difference in POM (α and β = 0.025). Because farm sample variability would potentially be higher than at the research stations

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Guillermo Padilla, María Elena Cartea, and Amando Ordás

sampling variability in maize accessions Maydica 41 307 316 Romesburg, H.C. 1984 Cluster analysis for researchers Wadsworth Belmont, Calif SAS Institute 2000 SAS Online Doc, ver. 8. SAS Institute, Inc

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Ariel Singerman, Stephen H. Futch, and Brandon Page

enough to matter. As pointed out by Kirk (1996) , “while statistical significance is concerned with whether a result is due to chance or sampling variability; practical significance is concerned with whether the result is useful in the real world” (p

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Riccardo Gucci, Giovanni Caruso, Angelo Canale, Augusto Loni, Alfio Raspi, Stefania Urbani, Agnese Taticchi, Sonia Esposto, and Maurizio Servili

on qualitative characteristics of oils were difficult to quantify because of the many sources of sample variability (cultivar, orchard location, cultural practices, processing technology in Gomez-Caravaca et al., 2008 ) or the low number (0, 100

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Rie Sadohara, James D. Kelly, and Karen A. Cichy

with the whiteness score of the five white genotypes ( Fig. 3B ). One possible reason for this is that L*, b*, C*, and L*/C* of sweetened paste had higher cv than those of unsweetened paste ( Table 2 ), indicating that within-sample variability

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Benedict C. Posadas, Patricia R. Knight, Christine E.H. Coker, Randal Y. Coker, and Scott A. Langlois

models were estimated by the robust variance procedure in Stata 12, as suggested by Rogers (1993) and Williams (2000) . Accurate assessments of the sample-to-sample variability of the parameter estimates are achieved with the use of the robust variance