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Accounting for Soil Spatial Autocorrelation in the Design of Experimental Trials

M. Fagrouda and M. Van Meirvenne*,b

a Ecole Nationale d'Agriculture de Meknès, BP S40, 50000 Meknès, Morocco
b Dep. of Soil Management and Soil Care, Ghent Univ., Coupure 653, 9000 Gent, Belgium



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Fig. 1. Location of the study area. Hatched area is the Sais plateau within Morocco.

 


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Fig. 2. Flow chart of the sequential gaussian simulation algorithm producing one realization l.

 


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Fig. 3. Normal score variogram of the available water capacity (AWC) within 1-m depth.

 


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Fig. 4. (a) Mean of 500 realizations of available water capacity (AWC), (b) means of aggregating AWC in plots of 4 x 8 m, (c) residual mean map from incomplete blocks of eight treatments and (d) corresponding residual variogram.

 


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Fig. 5. Some of the 24 plot configurations considered (see Table 2) for a 20 by 20 m subpart of the simulated areas (the top plot represents the original grid spacing (1 by 1 m) of the simulated maps before aggregation).

 


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Fig. 6. Average Nugget/Sill ratio as a function of plot width for AWC within 1 m. Bars indicate the empirical confidence intervals with a 95% confidence level.

 


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Fig. 7. Nugget/Sill Ratio as a function of plot length for two plot widths.

 


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Fig. 8. Configurations for one block with eight treatment plots as in an incomplete block design. Each block consist of one column (type I), one row (type III), two columns (Type II), or two rows (Type IV).

 


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Fig. 9. Nugget/Sill Ratio to Range ratio of variograms of the residuals versus number of blocks.

 


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Fig. 10. Average relative efficiency (Ei) of the incomplete block designs compared with the corresponding complete block design for a design with eight parcels per block. Design number refers to Table 4. Bars indicate the empirical 95% confidence intervals.

 





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