Date of Award
May 2020
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Division of Agriculture (SAFES)
Committee Member
Kendall R Kirk
Committee Member
John D Mueller
Committee Member
Kendall R Kirk
Committee Member
Jeremy K Greene
Abstract
Populations of plant-parasitic nematodes are difficult to manage due to their inherently sporadic nature and uneven distribution throughout a field. Soil sampling accompanied by laboratory extraction is the preferred method for estimating densities and locations of nematodes within a field. The uneven and sporadic nature of nematodes make them well suited for zone management in row crops, provided that effective zones can be defined. Effective zone definition for precision agriculture requires that differences in factors between zones are large and differences within zones are small.
This study compared methods of defining zones based on physical soil properties, soil SSURGO data, and grids of similar area to cost-effectively direct nematode sampling efforts. Twenty-six methods of zone definition were investigated based on soil electrical conductivity (EC), physical soil properties and relative nematode index predictions in various combinations. For each zone definition method, the fitness of models used to define zones was evaluated using the Davies-Bouldin Index (DBI) for measuring cluster separation where effectiveness of zone definitions decrease as the DBI increases. The DBI range for all zone methods investigated was 24.918, with a minimum of 5.086 and maximum of 30.004. The most effective zone was created by contouring relative weighted nematode index predictions, with predictions based on soil EC, with a delineation range of one standard deviation, which returned the lowest DBI.
Zones created based on a three equal range division of field silt levels returned the highest DBI indicating the least effective zone method. Using silt content in any range delineation showed to be inappropriate for zone definition. The two highest DBI values returned were when silt was used at a range delineation of 0.5 standard deviation, DBI of 29.0399, and a three equal division range, DBI of 30.004. Use of SSURGO soil data was also found to be significantly less effective for defining zones with a DBI of 27.155 compared with zones definitions based on soil EC. Zones defined using soil EC as a contributing factor demonstrated significantly effective zones. Of the nine zone definitions that were significantly effective, seven were defined using soil EC as some factor.
A second goal of this project was to asses multi-hybrid planting technology as a tool for the management of nematodes. Cotton varieties are now available that are resistant to Southern root-knot nematode, the most common and important species on cotton. For this study, a field was chosen based on the ability to grow two consecutive years of cotton within a two-year cotton to one-year peanut crop rotation and an unknown distribution of nematode density and species. This field did not return Southern root-knot nematode densities in adequate quantities for any solid conclusions to be made as to the use of resistant cotton varieties for determination of Southern root-knot nematode aggregations to be used as a basis for multi-hybrid planting or variable rate application for nematode control. The cost of this approach can be prohibitive as it can include higher seed costs, planter upgrades, and creation of planting prescriptions, which may be based on costly nematode sampling. If accurate nematode sampling zones can be determined, the overall cost of implementing this technology can be reduced.
Recommended Citation
Eubank, William Aubrey, "Development and Assessment of Nematode Management Zones in Cotton: Gossypium hirsutum" (2020). All Theses. 3290.
https://tigerprints.clemson.edu/all_theses/3290