b'Sulfur Mixed in Synthetic Fungicides: An Application to Suppress Sporulation after Fungal InfectionAlexander GomezSponsor: Dr. Emily G. CantonwineNothopassalora personata is a fungal pathogen that causes late leaf spot (LLS) in peanut plants. A recent study found that fungicides mixed with sulfur reduced LLS in the field more than expected. A lab experiment was conducted to evaluate the effect of sulfur on fungal growth and sporulation. Peanut leaves with LLS were collected from an untreated field plot and dipped into 1 of 6 fungicide treatments: water (control), sulfur, Tebuzol, Tebuzol with sulfur, Abound, and Abound with sulfur. They were then placed in a humidity chamber to induce sporulation. After 2 days, leaf spots were evaluated for sporulation using a 0-5 scale that estimated fungal spores density. Spores from the control and sulfur treatments were streaked onto a water agar plate to induce spore germination. After 3 days, percent germination, number of germ tubes, and germ tube branching were evaluated using a dissecting microscope. The Abound with sulfur treatment significantly reduced sporulation more than the control but did not differ from the other treatments. Compared to the control, sulfur affected branching and germ tube number but not percent germination. These results suggest that sulfur suppresses the fungus by reducing its ability to grow rather than its ability to sporulate. The Optimization of Facial Recognition Techniques for a Two-Year Mark-Recapture Study on Bahamian Lined Seahorses (Hippocampus erectus)Emily E. Craft and Darshi N. PatelSponsor: Dr. Emily RoseOur study aimed to determine the accuracy of the pattern recognition software, I3S, for seahorse individual identification using a subset of photographs from our two-year study. We used fluorescent elastomer tags placed under the seahorses skin and size comparisons to verify matches of 30 fish to measure the programs ability to detect known matches. Two digital fingerprints for each seahorses head were created in the I3S program to map facial patterns on both sides of the head and fishs body sizes were measured from photographs using ImageJ for identity confirmation. We tested the ability of the program to reliably identify matches within a database that contained all of the images and also created subsets of the images separating the data by either the fishs sex, side of the head, and a combination of face size and sex. By using photographs taken at different timepoints for the same fish we were able to assay the accuracy of the software for our population. Our results identified limitations presented by the software and the quality of our photographs, particularly nighttime images, and variation in patterning on either side of seahorses heads that will help to shape the future directions of our work.13'