Graduate Thesis Or Dissertation
 

The use of remote sensing in an integrated approach for stress detection on the cultivated cranberry

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  • Remote sensing is an attractive method for the detection and monitoring of crop stress. The feasibility of using remote sensing for the detection and monitoring of fungal diseases, insects, weeds, and non-infectious diseases affecting the cultivated cranberry (Vaccinium macrocarpon Ait.) is evaluated. A study on the fungal disease twig blight (Lophodermium spp.) was undertaken to illustrate the potential of using remote sensing. The important symptoms for remote sensing detection include leaf discoloration, reduced vigor, and biomass loss. Biomass loss and reduced vigor are the most important symptoms for cranberry stress detection, while leaf discolorations are usually inconspicuous and not widespread. Weeds, areas of dehydration, and general bog conditions can be easily detected at image scales of 1:12,000 and smaller. Fungus and insect damage can be monitored at smaller scales (1:6,000 and smaller); however, this information is more useful for regional or higher levels of management rather than for the individual grower. This is due to the likelihood of damage symptoms being the result of inefficient control practices rather than from the early establishment of stress. Many of the stresses have similar symptoms, making the identification of the stress agents difficult. Thus the timing of imagery acquisition is important and additional sources of information are necessary. Currently, remote sensing is best suited for inclusion in an integrated approach for a working stress detection and monitoring system. Study plots for the fungal disease twig blight (Lophodermium spp.) were selected in Long Beach, Washington. Aerial missions were conducted using color and color IR film with a 9" x 9" format (1:12000) and a 70mm format (1:3800). The progression of twig blight was monitored in study plots located in a commercial cranberry bog with ground photography employing 35mm color and color IR film. Comparisons of 11 different filters were made (5 IR filters, 3 red filters, and one green, yellow, and blue filter) with the best film/filter combination being a Wratten no. 12 (yellow) and color IR film. Aerial photograph interpretations were made from differences in image tone rather than leaf color changes. However, color differences are useful for identifying certain stress agents. Darker image tones had a positive correlation to Lophodermium spp. incidence, were independent of upright density, and had a negative correlation to upright density-revised. Upright density-revised is the total number of uprights minus the number of infected uprights. Healthy uprights grow above and cast a shadow over damaged uprights; therefore, upright density-revised is a better predictor of ground conditions important for remote sensing. Interpretation differences between filters could be attributed more to exposure differences than to anything else.
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