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Geostatistical Analysis of Field Spatial Distribution Patterns of Soybean Cyst Nematode

Felicitas Avendañoa, Oliver Schabenbergerb, Francis J. Piercec and Haddish Melakeberhan*,a

a Dep. of Entomol., 243 Natural Science Bldg., Michigan State Univ., East Lansing, MI 48824
b SAS Inst., Cary, NC 27513
c Cent. for Precision Agric. Syst., Washington State Univ., 24106 North Bunn Rd., Prosser, WA 99350



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Fig. 1. Soil series maps and location of the soil samples collected from (a) Field A and (b) Field B in Shiawassee County, MI, in 1999 and 2000, and (c) nested sampling design with geometric progression–reduced distances. Distances between pairs of samples are indicated; the direction in which two consecutive samples were oriented was randomly selected. This design was applied within 50- by 50-m cells of a grid centered in each field. In Fig. 1a and 1b, black circles indicate sets of sample locations in selected cells for both 1999 and 2000, and the crosses indicate the locations of the additional samples collected in 2000 from alternate nodes of a 25- by 25-m grid. Soil series maps were digitized from Threlkeld and Feenstra (1974).

 


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Fig. 2. Frequency distribution and cumulative distribution function (cdf) of (a) cysts 100 cm-3 soil, (b) eggs per cyst, and (c) eggs 100 cm-3 soil from Field A and (d) cysts 100 cm-3 soil, (e) eggs per cyst, and (f) eggs 100 cm-3 soil from Field B. Samples were collected before planting in 1999 and 2000. The number of eggs per cyst was estimated as the average number of eggs found after crushing three randomly selected cysts in each sample.

 


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Fig. 3. Semivariograms of (a and b) cysts [log10(cysts 100 cm-3 soil + 1)], (c and d) eggs per cyst [log10(eggs per cyst + 1)], and (e and f) eggs [log10(eggs 100 cm-3 soil + 1)] from Field A in (a, c, and e) 1999 and (b, d, and f) 2000. Black circles indicate omnidirectional empirical semivariogram, the solid line indicates the theoretical model fitted by means of least squares, and the dashed line is the sample variance.

 


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Fig. 4. Semivariograms of (a and b) cysts [log10(cysts 100 cm-3 soil + 1)], (c and d) eggs per cyst [log10(eggs per cyst + 1)], and (e and f) eggs [log10(eggs 100 cm-3 soil + 1)] from Field B in (a, c, and e) 1999 and (b, d, and f) 2000. Black circles indicate omnidirectional empirical semivariogram, the solid line indicates the theoretical model fitted by means of least squares, and the dashed line is the sample variance.

 


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Fig. 5. Log-kriged maps represent the distribution of cysts in the area sampled within Field A in (a) 1999 and (b) 2000, the distribution of eggs per cyst in (c) 1999 and (d) 2000, and the distribution of eggs in (e) 1999. The shading scale indicates levels of cysts [log10(cysts 100 cm-3 soil + 1)], eggs per cyst [log10(eggs per cyst + 1)], and eggs [log10(eggs 100 cm-3 soil + 1)]. A solid line delineates the field boundaries.

 


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Fig. 6. Cross-correlograms between (a and d) cysts [log10(cysts 100 cm-3 soil + 1)], (b and e) eggs per cyst [log10(eggs per cyst + 1)], and (c and f) eggs [log10(eggs 100 cm-3 soil + 1)] in 1999 and 2000 in (a, b, and c) Field A and (d, e, and f) Field B. r = linear correlation coefficient.

 


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Fig. 7. Cross-correlograms between (a and c) eggs per cyst [log10(eggs per cyst + 1)] in 1999 and cysts [log10(cysts 100 cm-3 soil + 1)] in 2000 and (b and d) eggs [log10(eggs 100 cm-3 soil + 1)] in 1999 and cysts in 2000 in (a and b) Field A and (c and d) Field B. r = linear correlation coefficient.

 


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Fig. 8. Log-kriged maps represent the distribution of cysts in the area sampled within Field B in (a) 1999 and (b) 2000, the distribution of eggs per cyst in (c) 1999, and the distribution of eggs in (d) 1999 and (e) 2000. The shading scale indicates levels of cysts [log10(cysts 100 cm-3 soil + 1)], eggs per cyst [log10(eggs per cyst + 1)], and eggs [log10(eggs 100 cm-3 soil + 1)]. A solid line delineates the field boundaries.

 





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