Title page for ETD etd-12172002-123317


Type of Document Master's Thesis
Author Holden, Erin
URN etd-12172002-123317
Title Spatial Ecology and Remote Sensing in the Precision Management of Tetranychus urticae (Acari: Tetranychidae)in Peanut
Degree Master of Science
Department Entomology
Advisory Committee
Advisor Name Title
Brewster, Carlyle C. Committee Chair
Herbert, David Ames Jr. Committee Member
Lewis, Edwin E. Committee Member
Youngman, Roger R. Committee Member
Keywords
  • UAV
  • spatial distribution
  • Tetranychus urticae
  • remote sensing
Date of Defense 2002-12-12
Availability unrestricted
Abstract

The twospotted spider mite (TSSM), Tetranychus urticae Koch, is a common polyphagous pest in peanut agroecosystems. The mite has caused serious economic losses to peanut farmers in the Virginia-Carolina area, where approximately 20% of the peanuts are produced annually in the United States. Peanut farmers depend on pesticides to control mite populations. Because TSSM has developed resistance to many acaricides and there are restrictions on the use of pesticides, an alternative approach, such as precision pest management, is needed that would reduce the amount of pesticides that must be applied. This study was initiated to determine whether precision pest management is a feasible management strategy for use against TSSM populations in peanut. Two requirements of the precision management approach are that maps of the spatial distribution of TSSM populations can be developed and the pattern of distribution changes little over time to allow management strategies to be implemented.

To this end, a study of four commercial peanut fields located in two counties of southeastern Virginia was conducted to characterize the spatial distribution of TSSM populations. Intensive sampling of TSSM populations was conducted within each of the fields. The results showed that there was a general increase in TSSM populations during the early phases of sampling. Fields with low densities of TSSM populations had a spatial distribution that was either uniform or random; in fields with relatively higher densities, TSSM populations usually were aggregated. Little or no change in the spatial distribution of TSSM occurred from week to week in all fields that were sampled. Where changes in the distribution were observed, these were apparently caused by the application of a pesticide by the grower.

The study also looked at remote sensing technology as an alternative to intensive sampling within peanut fields. Research was conducted under laboratory conditions to determine whether damage caused by feeding TSSM could be detected spectrally before symptoms become visible. The study showed that after eight days leaves of peanut plants subjected to low soil moisture levels had significantly lower reflectance ratios (mean = 9.4766; a = 0.05) than plants given medium (mean = 10.0186) or high (mean = 10.5413) soil moisture levels. After 10 days, there were significant differences (P < 0.05) in the mean reflectance ratios of peanut leaves exposed to four levels of spider mite densities (0, 5, 10, 20 mites/leaf) and the three levels of soil moisture. However, no significant interaction was observed between soil moisture and spider mite density (P = 0.8710). The mean reflectance ratio for 20 TSSM per leaf was found to be significantly lower than 0, 5, and 10 TSSM per leaf at all levels of moisture (low, medium, and high). The results suggested that remote sensing could be used to detect and map plant damage caused by feeding of spider mites before visual symptoms of damage are observed.

The study also attempted to develop a platform for using remote sensing technology in the field. An Unmanned Air Vehicle (UAV) was evaluated that carried a remote sensing system. The UAV remote sensing system was flown over peanut fields where it captured images, which were analyzed to show the spatial distribution of plant stress. Further studies are needed to relate the distribution of plant stress or damage observed by the UAV with the distribution of TSSM densities within peanut fields. Once this has been accomplished, low-altitude remote sensing could be used as an alternative to sampling for building maps of the spatial distribution of TSSM populations for precision pest management.

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